最新刊期
卷 57 ， 期 5 ， 2025
- “在气凝胶混凝土性能预测领域，研究人员利用BO‒XGBoost模型建立了性能预测模型，并通过335组数据进行训练与测试，验证了模型的有效性。”摘要：ObjectiveAccurately predicting the compressive strength and thermal conductivity of aerogel concrete with different mix ratios is essential. Conventional performance prediction methods involve repeatedly designing mix ratios and measuring performance in the laboratory, which requires substantial manpower and time. Alternatively, formula-based or statistical methods are employed to obtain optimal performance; however, the empirical formulas derived from these methods demonstrate low accuracy, remain highly dependent on specific experiments, and cannot be generalized or applied to other cases. This study proposes an aerogel concrete performance prediction model based on the Extreme Gradient Boosting (XGBoost) algorithm, which enables a clearer understanding of the nonlinear relationships between the components and the performance of aerogel concrete.MethodsFirst, relevant data were collected from research literature to construct a database containing 183 sets of compressive strength data and 152 sets of thermal conductivity data. The input features primarily consisted of mix ratios of materials such as cement, while the output features represented the performance of aerogel concrete, specifically compressive strength and thermal conductivity. Second, the XGBoost algorithm was employed for model training and performance prediction, and evaluation metrics such as the coefficient of determination (R2) and root mean square error (RMSE) were utilized to assess the model’s accuracy. The Bayesian optimization algorithm was applied to determine the optimal hyperparameters of the XGBoost model to enhance prediction reliability and reduce overfitting. Third, since the model contained two types of input methods, one approach used the amounts of materials such as aerogel, cement, silica fume, sand, and water as input variables, while the other used interpretable features such as the water-to-binder ratio, aggregate ratio, aerogel content, silica fume content, and curing age as input variables. The model also generated two output results, compressive strength and thermal conductivity. Three comparison schemes were designed, and their prediction accuracy and performance were assessed using the same database to compare the two input methods and to evaluate the strategies of "building one model to predict both performances" versus "building two models to predict the performances separately". Fourth, to demonstrate the advantages of the BO‒XGBoost algorithm in predicting aerogel concrete performance, comparisons were conducted with multiple classical machine learning algorithms, including Random Forest (RF) and Artificial Neural Networks (ANN). For objectivity, all algorithms used the same unified database and underwent Bayesian optimization for hyperparameter tuning. Fifth, to investigate the generalization capability of the BO‒XGBoost model, it was applied to predict the performance of 12 new sets of aerogel concrete data, and the prediction accuracy of the model was observed. Finally, since machine learning models were inherently "black boxes," making it challenging to characterize complex nonlinear relationships between input and output variables, the Shapley Additive Explanations (SHAP) model was employed for feature interpretability analysis, calculating the contribution of each feature to the model’s predictions and explaining the relationships between input features and output results.Results and Discussions1) The analysis of the prediction accuracy of models established under the three schemes revealed that all three schemes achieved high accuracy in predicting the performance of aerogel concrete, with R2 values greater than 0.92 for the test set. The model under Scheme 1 yielded the best results, with R2 values of 0.977 and 0.978 for compressive strength and thermal conductivity, respectively, and RMSE values of 2.366 MPa and 0.104 0.128 W/(m·K). 2) When compared to four other traditional machine learning algorithms, the XGBoost model was shown to be more suitable for predicting the performance of aerogel concrete. The compressive strength and thermal conductivity models based on the XGBoost algorithm achieved R2 values of 1.000 and 0.992 for the training set, and R2 values of 0.977 and 0.978 for the test set. In contrast, the R2 values of the test set for RF, ANN, and other classical algorithms were all below 0.963, indicating poor fitting accuracy and significant overfitting, which rendered them unsuitable for predicting aerogel concrete performance. 3) The generalization ability of the model was verified using 12 new sets of aerogel concrete mix ratio data. The R2 values for compressive strength and thermal conductivity prediction were 0.986 and 0.895, respectively, with RMSE values of 1.539 MPa and 0.128 W/(m·K), demonstrating the model’s strong generalization capability. 4) The SHAP model analysis revealed that the primary factors influencing the compressive strength of aerogel concrete are aerogel content and water-to-binder ratio. As the aerogel content and water-to-binder ratio increase, the compressive strength decreases. The primary factors influencing the thermal conductivity of aerogel concrete are also aerogel content and water-to-binder ratio, with higher values leading to reduced thermal conductivity. The results obtained from SHAP analysis are consistent with conclusions drawn from laboratory experiments.ConclusionsThis study proposes an XGBoost-based performance prediction model for aerogel concrete, designed to predict both the compressive strength and the thermal conductivity of ordinary aerogel concrete. Compared to conventional empirical fitting formulas, the prediction model exhibited higher accuracy and stronger generalization capacity, presenting a novel approach for predicting performance and designing mix ratios of aerogel concrete.关键词：aerogel concrete;performance prediction;bayesian optimization;XGBoost algorithm;SHAP interpretability analysis281|408|0更新时间：2026-01-25
- “在建筑结构领域，研究者通过侧向冲击试验，揭示了新型装配式格构柱的抗冲击性能和破坏机理，为提升结构安全提供科学依据。”摘要：ObjectiveThis study designs a new layered prefabricated lattice column as a protective support structure, which presents unique advantages in preventing and controlling rockfall disasters. Two groups of nine specimens are designed and fabricated for impact testing to investigate the impact resistance and failure mechanisms of the proposed layered fabricated lattice column under low-velocity and high-mass impacts. The influence of impact mass, impact height, and impact position on the dynamic response of the structure is analyzed by comparing the test results. A linear relationship between residual deformation and impact energy is established through curve fitting, providing empirical support for engineering applications.MethodsThe dynamic response of a newly developed layered prefabricated lattice column under impact was systematically investigated through experimental testing. The test setup consisted of a track rod, a steel pipe fixed to a reaction wall, and an impact apparatus. A total of 9 specimens were examined under varying impact masses (60, 80, and 100 kg), impact heights (3, 4, and 5 m), and impact positions (near and far from the fixed end). The deformation characteristics and failure modes of the specimens were observed, and the impact time history curve, strain time history curve, and displacement time history curve were recorded using a high-speed camera, dynamic acquisition instrument, and quartz sensor. The influence of different test parameters on the failure mode, impact peak value, impact platform value, impact duration, strain peak value, plastic strain, maximum lateral displacement, and residual displacement was identified through comparative analysis of the experimental results. Finally, a linear relationship between the impact energy and the residual deformation in the range of 2 400 to 5 000 J was established through curve fitting.Results and discussionsThe primary residual deformation of the new layered prefabricated columns after impact was local denting. When the specimen failed, the web member bent, and the bolts at both ends of the web member underwent a shear failure. Under identical impact energy conditions, the impact position has a significant effect on the dynamic response. Specimens impacted farther from the fixed end exhibited lower resistance, greater damage severity, and a more dispersed impact plateau value. With the increase in impact mass or impact height, both the impact peak value and impact duration increase. The mass has a more significant effect on the duration of the impact, while the impact velocity has a greater influence on the peak value of the impact. The residual deformation of the specimen increases with a rise in the impact energy. Specimens impacted near the fixed end exhibit larger residual displacements (up to 5.27 mm), whereas impacts away from the fixed end result in greater lateral displacements (up to 6.21 mm), as more energy is dissipated through vibration. The relationship between residual deformation and impact energy was established, with a deviation of less than 6% as determined by further regression analysis.ConclusionsWhen the impact energy reached 5 000 J, the bolts of the web members undergo shear failure due to insufficient shear strength. Impact point farther from the fixed end reduce impact resistance of structure. Impact mass mainly affects the impact duration, while impact velocity primarily affects the peak impact force. Impacted near the fixed end exhibit larger residual displacements, while impacted farther from the fixed end exhibit larger lateral displacements. The linear relationship between residual deformation and impact energy provides a quantifiable means to assess structural damage, with an error
- “在建筑领域，研究者开发了轻型装配式重组竹墙板，通过实验分析了其抗震性能，为绿色低碳建筑提供新方案。”摘要：This study introduces a lightweight prefabricated wall panel made from reconstituted bamboo, which leverages the material's high strength-to-weight ratio along with its sustainability, low carbon footprint, and energy efficiency. The panel features a convenient and reliable connection system, making it well-suited for prefabricated construction. Six wall panel configurations were designed and fabricated to evaluate their seismic performance. The investigation examines the influence of several variables (including vertical joint configuration, the number of bolts in vertical joints, presence of holes, and surface panel thickness) on failure modes, shear strength, ultimate and yield displacements, yield load, and energy dissipation capacity. Experimental results reveal that using two bolts in the vertical joints reduces unit shear strength by approximately 10% compared to configurations with four bolts. Increasing the number of bolts effectively limits inter-panel slip, reduces local stress concentrations, enhances structural stiffness and shear capacity, and improves connection strength. Panels with 20 mm thick surface layers show 18.8% greater unit energy dissipation than those with 10 mm thickness, demonstrating superior plastic deformation capacity. This increased deformability allows the panels to absorb more energy without failure and delays self-tapping screw failure, thereby enhancing the panel's overall energy dissipation performance. Digital image correlation (DIC) technology was employed to analyze surface damage progression, offering valuable insights into the damage evolution of the surface panel. Results indicate that increasing surface panel thickness markedly improves damage resistance, restricts crack propagation, and enhances the structural stability and safety of the panel system. Additionally, a parametric study using ABAQUS was conducted to assess the effects of edge nail spacing and the number of cross braces on seismic behavior. Finite element analysis shows that edge nail spacing significantly influences the load-bearing capacity, while the number of cross braces primarily affects displacement behavior.关键词：bamboo scrimber wall panel;seismic performance;DIC;finite element analysis210|717|0更新时间：2026-01-25
- “在建筑工业化领域，专家对全装配混凝土模块结构连接节点进行试验研究，揭示了节点破坏模式和力学性能影响因素，为提高结构安全性提供依据。”摘要：ObjectiveConcrete modular buildings provide advantages such as strong structural integrity, high living comfort, and reduced construction and maintenance costs. In modular concrete structures, the connections between modules play a decisive role in the overall structural performance. The fully assembled modular construction reinforced concrete (FAMC‒RC) system is composed of prefabricated concrete modules joined through bolted connections, in which horizontal joints are primarily formed using high-strength bolts, steel spacers, and threaded sleeves. Current investigations on the performance of horizontal connections in this system remain limited, particularly concerning load-transfer mechanisms, joint configurations, and mechanical behavior. This study conducts tensile tests on 13 FAMC‒RC horizontal bolted connection specimens with different parameters to evaluate their tensile load-bearing capacity and deformation characteristics.MethodsThirteen horizontal connection joint specimens were designed with key parameters that included concealed beam height, edge distance width, bolt-hole diameter, and bolt-hole geometry. Each specimen contained a pre-embedded hand-hole bolted joint. Monotonic tensile loading and forward cyclic loading tests were conducted on the specimens using a vertical actuator. A rectangular steel plate was pre-embedded at the base of each specimen and anchored to a rigid ground surface through foundation bolts to provide vertical constraints to better simulate real engineering conditions. A box-section loading beam was attached to the vertical actuator and connected to the specimen using high-strength bolts for vertical load application. Monotonic tensile loading was controlled through a force-displacement hybrid method, whereas forward cyclic loading was displacement-controlled. The tests were terminated when the tensile load-bearing capacity of the specimens declined to 85% of the peak load or when significant failure phenomena were recorded.Results and DiscussionsFive distinct failure modes were identified in the thirteen horizontal connection joint specimens under tensile loading: Mode Ⅰ, thread stripping or fracture of Grade 8.8 bolts; Mode Ⅱ, conical punching shear failure of the concrete above the operating hand-hole; Mode Ⅲ, concrete crushing followed by conical punching shear failure above the operating hand-hole; Mode Ⅳ, net-section tensile failure at the cross-section above the operating hand-hole; and Mode Ⅴ, anchorage failure between embedded steel plates and vertical reinforcement. In ModeⅠ, when the load reached 180 kN, the growth rate of the tensile load-bearing capacity significantly decreased, accompanied by a distinct plateau segment in the load-displacement curve, which indicated the yielding-strengthening behavior of Grade 8.8 bolts. The thread stripping failure occurred at 200 kN. Modes Ⅱ and Ⅲ were both categorized as punching shear failures, differentiated by the presence of a 100 mm concrete crushing zone prior to punching shear in Mode Ⅲ. Mode Ⅱ was characterized by the sudden widening of progressively extending diagonal cracks above the operating hand-hole that developed into dominant failure cracks, corresponding to the maximum peak load-bearing capacity. Mode Ⅲ displayed pronounced concrete crushing and spalling above the operating hand-hole before punching shear failure occurred. Under sustained loading, diagonal cracks rapidly propagated along both edges of the crushing zone, ultimately producing punching shear failure with a relatively lower peak load-bearing capacity. Based on the calculation theory of punching shear capacity, the reduced peak load-bearing capacity in Mode Ⅲ compared to Mode Ⅱ was attributed to the reduction in the effective height of the punching shear cone caused by the crushing zone, which resulted in diminished anti-punching shear capacity. In Mode Ⅳ, when the load increased to 134.2 kN, abrupt fracture failure of the concrete at the cross-section above the operating hand-hole of the specimen was recorded, with minimal cracking. This failure mechanism was attributed to the reduced edge distance width of the specimen, which lowered the net-section bearing capacity. Mode Ⅴ, caused by poor welding quality between vertical steel bars and embedded steel plates, was regarded as non-representative of actual structural performance. Load-displacement curves revealed four consistent stages across all failure modes: prestress loss, elastic loading, crack development, and brittle failure. No alteration in failure modes was recorded in specimens subjected to forward cyclic loading, and identical mechanical behavior was demonstrated relative to specimens tested under monotonic loading. The experimental results indicated that the tensile mechanical performance of the horizontal connection joints was governed by several parameters, including edge distance width (B), concealed beam height (H), bolt-hole diameter (D), and bolt-hole geometry. When H equaled 250 mm, increasing B from 160 mm to 325 mm enhanced the peak load-bearing capacity by 117% and the initial stiffness by 61%, whereas for H = 200 mm, the same variation in B improved the capacity by 20% and the stiffness by 72%. Both parameters reached stable states with negligible increments when B exceeded 325 mm. This phenomenon indicated that an edge distance width greater than 325 mm was sufficient to ensure full utilization of the joint’s tensile performance. For H increments from 200 mm to 250 mm in 25 mm intervals, the peak load-bearing capacity exhibited quasi-linear increases of 23% and 24%, while the initial stiffness demonstrated limited improvements of only 7% and 4%. This disparity confirmed the significantly higher sensitivity of load-bearing capacity to H compared to stiffness, making H augmentation an inefficient approach for stiffness enhancement. Increasing D from 25 mm to 32 mm and then to 40 mm resulted in peak load-bearing capacity reductions of approximately 3% and 22%, respectively, with stiffness variations confined to ±5%, demonstrating that D
- “在建筑领域，研究者通过拟静力试验，分析了套筒灌浆缺陷对装配式混凝土剪力墙抗震性能的影响，为提高建筑抗震性能提供参考。”摘要：ObjectivePrecast concrete structure has obvious advantages such as improving production efficiency, saving energy and green environmental protection. Precast concrete shear wall is widely used in high-rise residential buildings, which plays an important role in promoting the industrialization of housing. The reliability of the vertical connection of precast concrete shear walls is very important to ensure the mechanical performance of the structural system. The seismic behavior of precast concrete shear wall with grout defects were analyzed. This paper study the effect of sleeve grouting defects on the seismic performance of precast concrete shear wall, and provides a reference for the performance evaluation and subsequent treatment of sleeve grouting defects.MethodsSeven prefabricated concrete shear walls (six test specimens with grouting defects and one test specimen with full grouting) connected by reinforcement sleeve grouting were designed for low cycle repeated loading tests. The main designed parameters of the specimens in the tests were the number of sleeves with grouting defects and the length of grouting defects that reduced the anchorage lengths between upper reinforcements and grout. The design anchorage length of reinforcement bar and grout material was 8D (D is the nominal diameter of reinforcement bar). By setting rubber plugs of different lengths outside the upper reinforcement bar, the grout defects in the sleeve were accurately simulated. The anchorage length of upper reinforcement bar and grout material in the sleeve of specimens was 4D and 5D. The grouting defect was set in the sleeve of the edge members of shear wall. The number of sleeve joints with grouting defect is 4, 8 and 12 in three cases. The design axial compression ratio of the specimens was 0.35. First, vertical pressure was applied to the top of the wall to a predetermined value, keeping the vertical pressure unchanged, and then horizontal reciprocating force was applied to the top of the wall. The vertical pressure was provided by hydraulic jack at the top of loading beam, and horizontal force was applied by the electro-hydraulic servo actuator. The loading system of displacement control was adopted in the test. The failure process and final failure mode were observed. The hysteretic curves of horizontal force-displacement were obtained. The hysteresis loops, bearing capacity, deformation, stiffness degradation, ductility and energy dissipation capacity of specimens were analyzed.Results and DiscussionsThe test results indicated that the failure mode of precast concrete shear wall with grouting defects was the same as that of the specimen with no defects. The final failure modes of walls could be characterized as the outside longitudinal reinforcements of edge members yielded even broke because of inclined sleeve, and concrete cover outside the sleeve crushed and peeled in the corner of wall. Compared with full grouting specimen, the horizontal crack of grouting defect specimen appeared slightly earlier. As the number of grouting defect sleeves in the wall increased, crushing height of concrete outside corner sleeve decreased gradually. The hysteretic curves of load-displacement of specimens with grouting defects look like bow or reversed S-shape, and the pinching effect of curves showed more obvious with the increase of the number of defective grout sleeves. The load-displacement skeleton curve of precast concrete shear wall with sleeve grouting defects was divided into three stages: elastic section, elastoplastic section and falling section. At the initial stage of loading, the curves of the specimens had good coincidence, and the grouting defects had little influence on the mechanical performance of the precast shear wall in elastic stage. When the skeleton curve entered the nonlinear stage, the slope of the upward section of the skeleton curve of different grouting defect specimens was different. Compared with full grouting specimen, the peak bearing capacity of grouting defect specimens decreased, the slope of the upward section of the skeleton curve became smaller, and tended to be flat with the increase of grouting defect sleeves. With the increase of number of sleeve grouting defects, the bearing capacity of specimens gradually decreased. The bearing capacity of specimen with all grouting defect sleeves of edge member decreased obviously, and the peak bearing capacity decreased by about 40% of full grouting specimen. The influence of different grouting defect lengths on the peak bearing capacity was not significant. Compared with full grouting specimen, the displacement at crack point, yield point and peak point of grouting defect specimens decreased more, but the displacements at failure point decreased less. With the increase of sleeve grouting defects, the displacement of feature points gradually decreased, and the more grouting defects, the worse the overall deformation performance of specimen. The ductility coefficient of all specimens was less than 3, and the ductility coefficient of grouting defect specimen was larger than that of grouting full specimen. The stiffness of specimen decreased gradually with the increase of loading displacement. When the displacement was small, the grouting defect has little influence on the stiffness. With the increase of displacement, the stiffness degradation of the grouting defect specimen accelerates. The stiffness degradation of specimen with grouting defects in all the sleeves of edge members was significantly faster than that of other specimens. Compared with grouting specimen, the energy dissipation of grouting defect specimen reduced. Before the yield displacement of specimen, the energy dissipation coefficient changed little. With the increase sleeve grouting defects, the energy dissipation of specimen decreased.ConclusionsThe failure mode of precast concrete shear wall with grouting defects was the same as that of specimen with no defects. The hysteretic curves of load-displacement with grouting defects look like bow or reversed S-shape, and the pinching effect of curves showed more obvious with the increase of the number of defective grout sleeves. The bearing capacity, deformation and energy dissipation capacity reduced with the effects of grout defects, while the effect of grout defects on initial stiffness was slight. The bearing capacity, peak deformation and energy dissipation capacity reduced with the increase of the number of defective grout sleeves. The stiffness reduced with the increase of the number of defective grout sleeves and the length of grouting defects.关键词：precast shear wall;grout sleeve splicing;grout defects;seismic behavior;quasi-static tests166|214|0更新时间：2026-01-25
- “在人工智能领域，专家建立了深度学习体系，为智能技术发展提供新方向。”
PRECAST RURAL RESIDENCES
- “最新研究揭示干热岩地热井套管-胶结面-水泥环-地层组合体热流固耦合模型，为保护井筒完整性提供指导。”摘要：ObjectiveThe development and utilization of dry hot rock resources help China achieve its dual carbon goals. The reliability of the wellbore system is crucial for the development of dry hot rock resources. However, the casing cement sheath bonding surface in wellbore system components is a relatively weak structure, and when the wellbore is subjected to thermal‒hydraulic‒mechanical (THM) coupling, the casing-cement sheath interface (CCSI) is prone to breakage, reducing the reliability of the wellbore system. This study aims to understand the fracture mechanism of the casing cement sheath bonding surface.MethodsThe research method of this study was theoretical research and numerical calculation. Using the superposition principle, the boundary conditions of the model were decomposed into axisymmetric and non-axisymmetric boundary conditions. The model under non-axisymmetric boundary conditions obtained displacement and stress field expressions through the elastic thick-wall theory. Under axisymmetric boundary conditions, the model considered the coupling effect of the temperature field, mechanical field, and fluid flow field, and the expressions of each field were functions of position and time. Using the Laplace transform and inverse transform, the solution of the model was obtained. The inverse Laplace transform employed the Stehfest algorithm, and MATLAB software was used for numerical analysis.Results and DiscussionsThe undetermined coefficients of all fields were time functions. Except for λE1 = 0, the temperature field coefficients of casing, CCSI, cement sheath, and formation all changed logarithmically with time. The coefficients λC1, λC2, and λD2 increased with time, whereas the coefficients λD1 and λE2 decreased with time. The coefficients of the mechanical field and fluid flow field of casing, CCSI, cement sheath, and formation followed a logarithmic change law, except for λC3 and λD3, which followed a linear change law. λF1, λF2, λD3, λD4, λD5, λD6, λE3, λE4, λE5, and λE6 increased with time. The coefficients λC3, λC4, λC5, and λC6 decreased with time. Published temperature curves were selected to verify the temperature field of the THM coupling model in this study. The results were found to be consistent by comparing the temperature curves at three moments. Published radial stress and radial displacement curves were also selected to verify the mechanical field of the THM coupling model, and the results were similarly consistent. Therefore, the establishment and solution process of the combinatorial THM coupling model proposed in this study was accurate. Based on the engineering background of a dry hot rock well in the Chabcha area, Gonghe Basin, Qinghai Province, the temperature curve and radial stress curve of all surfaces in the wellbore system over time were studied. Due to the thin thickness of CCSI, the transformation law of the bonding surface between the casing and CCSI was essentially the same as that of the bonding surface between CCSI and the cement sheath. The temperature at CCSI decreased to the temperature of the casing inner wall in 2.3 days; however, the cement-formation interface reached the temperature of the casing inner wall in 6.9 days. The radial stress at CCSI decreases briefly at first and then increases, with the minimum value of 6.31 MPa occurring at 0.2 days. The curve exhibits an exponential change, while the radial stress curve of the cement sheath-formation interface shows a linear change. The curve of radial stress versus radius shows that the radial stress increases rapidly in the casing, and the growth rate slows after reaching CCSI. The radial stress at CCSI is larger, while the failure strength of CCSI is relatively low, making CCSI more prone to failure than other locations. Further analysis was conducted on the influence of CCSI THM coupling parameters on the radial stress at the bonding surface between casing and CCSI. The radial stress decreased initially and then increased with the increase of the ratio of elastic modulus between CCSI and cement sheath. When the ratio was 0.33 and 1.67, the radial stress was maximum, and when the ratio was 1.11, the radial stress was minimum. Changes in CCSI Poisson's ratio had little influence on radial stress during the initial period; however, after approximately 4.6 days, the influence became greater. With an increase in Poisson's ratio, the radial stress of CCSI first decreased and then increased. When the Poisson's ratio was 0.30, the radial stress was minimum, and when the Poisson's ratio was 0.34, the radial stress was maximum. With the increase in porosity, the growth rate of radial stress gradually increased. When the porosity was in the range of 0.1~0.3, the growth rate of radial stress was small, while for porosity greater than 0.4, the growth rate of radial stress was large. With the increase in the T‒O coefficient, the radial stress first decreased and then increased. When the T‒O coefficient was 1.0, the radial stress was minimum, and when the T‒O coefficient was 2.0, the radial stress was maximum. After a certain period, the growth rate of the radial stress remained unchanged. The radial stress increased with the increase in temperature difference. The greater the temperature difference, the greater the growth rate of radial stress. When the temperature difference exceeded 200 ℃, the growth rate of radial stress was significantly higher than when the temperature difference was below 200 ℃. The maximum tensile stress criterion was chosen for tension, and the M‒C criterion was selected for compression to assess CCSI damage.ConclusionsWhen the elastic modulus, Poisson's ratio, and T‒O coefficient of CCSI are similar to the corresponding properties of the cement sheath, they are more effective in reducing the radial stress at the interface between the casing and CCSI and in protecting the integrity of the casing-interface-cement-formation system. Lower formation temperatures and lower interface porosity have the same effect in reducing CCSI damage. This study holds great significance for ensuring the integrity of wellbore protection in dry hot rock geothermal wells.关键词：dry hot rock geothermal wells;thermal‒hydraulic‒mechanical coupling;casing-cement sheath interface;stress field;analytical solution281|359|0更新时间：2026-01-25
- “在负碳技术领域，专家运用随机森林算法建立吸附剂特征与CO2吸附容量预测模型，为DAC技术产业化提供关键参数。”摘要：ObjectiveDirect air capture (DAC) emerges as a promising negative emission technology to mitigate global warming. The performance of direct air capture adsorbents, particularly amine-based solid porous adsorbents, plays a critical role in the industrial deployment of DAC. Extensive experimental studies are conducted worldwide to investigate the CO2 capture capabilities of these adsorbents, generating a substantial volume of data. However, the CO2 capture performance is influenced by multiple parameters, requiring a systematic and comprehensive analysis to clarify the relationship between the structural and conditional parameters of amine-based adsorbents and their CO2 capture capabilities.MethodsThis study systematically compiled experimental data on amine-based solid DAC adsorbents from peer-reviewed scientific articles. Four different types of machine learning algorithms (random forest, artificial neural network, support vector machine, and ridge regression) were employed to construct a predictive model that correlated the features of amine-based solid adsorbents with their CO2 adsorption capacity values. In addition, the study utilized shapley additive explanations (SHAP) analysis to deconstruct the machine learning model’s predictive process, quantitatively revealing key parameters that determined the CO2 adsorption capacity of the adsorbents.Results and DiscussionsThis study collected 629 valid data entries from 32 scientific publications, covering a wide range of CO2 capture capacities from 0 mmol/g to 5.0 mmol/g, to guide the design of new DAC adsorbents with enhanced CO2 capture performance. Each data entry was characterized by 24 descriptors, which encompassed information on the porous substrate components, textural properties, amine properties, and experimental conditions. An individual-variable analysis using the Pearson method revealed little linear correlation between the descriptors and CO2 capture capability, except for the amine loading in the adsorbents, with a Pearson correlation coefficient R = 0.543. Machine learning models were employed to uncover potential nonlinear and multivariable relationships. Four algorithms with good fitting capabilities and robustness against information noise were selected to build predictive models for the CO2 capacity of amine-based adsorbents, namely artificial neural network (ANN), support vector machine (SVM), ridge regression (Ridge), and random forest (RF). The dataset was split into training and test sets in a 4:1 ratio, and hyperparameters were optimized using grid search and validated with 5-fold cross-validation. After the optimization of hyperparameters, the RF model showed superior performance compared to the other selected models. The optimal RF model demonstrated the best performance in predicting CO2 adsorption capacity, with R2 = 0.823, MAE = 0.270, and RMSE = 0.372 in the test set. The performance of the RF model indicated that the 24 descriptors effectively covered the key factors that determined the CO2 capacity of amine-based adsorbents within the current experimental design space. A quantitative structure-property relationship (QSPR) analysis was conducted using the SHAP analysis method based on the mentioned reliable RF model. In this case, the SHAP method quantified the contribution of each descriptor of the DAC data entry to the output (predicted CO2 adsorption capacity) of the RF model, providing interpretability and insights into the model's decision-making process. The SHAP analysis results identified the most important descriptor influencing CO2 capacity, the amine loading, which exhibited a strong positive correlation. Other significant descriptors included the molecular weight of the incorporated amines (negative correlation), CO2 concentration (positive), porosity of the adsorbent (positive), and elemental contents in the substrate material, such as O (negative), C (positive), and F (positive). Accordingly, three experimental design strategies were proposed for further exploration of amine-based DAC adsorbents: 1) utilize substrates with high porosity, 2) avoid using amine-based polymers with excessively high molecular weight (> 10 000), and 3) select substrates containing C or F elements. These strategies contributed to the further enhancement of the CO2 adsorption performance of amine-based solid porous adsorbents and accelerated the development and deployment of DAC as a key negative emission technology. At the same time, the current limitations of chemical diversity and experimental space highlighted several areas and directions that required further research. For example, additional experimental studies were needed to investigate the CO2 capacity of amine-based adsorbents in humid and low-temperature environments, as well as the impacts of gas flow rate and gas mixture composition on the adsorbents’ CO2 capacities. In addition, an ideal DAC adsorbent should have met multiple criteria beyond CO2 capacity, such as efficient mass transfer and high stability in adsorption-desorption cycles. Currently available experimental data are still insufficient to address these aspects using machine learning strategies.ConclusionsThis research highlights the potential of machine learning in analyzing large-scale datasets to identify factors that influence the CO2 capture performance of DAC adsorbents. Critical factors were identified, including amine loading and adsorbent porosity. The findings provide insights that can guide the design of more effective DAC adsorbents and highlight areas requiring additional experimental research, particularly regarding the effects of environmental conditions and gas composition on adsorbent performance. This study contributes to the progress of DAC technologies as a feasible solution to achieving China's carbon dioxide peaking and carbon neutrality objectives by advancing the understanding of amine-based adsorbents.关键词：CO2;direct air capture;amine-based solid adsorbent;machine learning;carbon capture511|569|0更新时间：2026-01-25
- “在CO2地质封存领域，专家建立了两相渗流流固耦合模型，分析了CO2注入对井筒完整性的影响，为降低井筒失效风险提供解决方案。”摘要：ObjectiveWellbores can be damaged due to multiphysical coupling during geological CO2 storage in deep saline aquifers, which compromises wellbore integrity and creates potential leakage pathways for CO2. This study proposes a fully coupled hydromechanical model to simulate the two-phase flow of brine and CO2 near the wellbore and to investigate the mechanical responses of the reservoir rock and cement sheath.MethodsThe wellbore structure in the model consisted of casing, a cement sheath, and the surrounding reservoir rock. The reservoir was considered a saturated, homogeneous, isotropic elastic medium, with deformation characterized as small, linear elastic deformation. Pore pressure diffusion was governed by the Biot storage model, while the two-phase flow for brine and CO2 was described by Darcy’s law and the Brooks‒Corey model. Since pore pressure increase led to wellbore damage during CO2 injection, the indirect variation in reservoir porosity and permeability was also considered, showing a correlation with changes in average effective stress. The mechanical response and pore pressure variation were fully coupled, and the Coulomb failure criterion was utilized to evaluate the damage risk of both the reservoir rock and the cement sheath. It was found that damage to the cement sheath depended on its inherent properties, the surrounding stress state, and changes in pore pressure. Therefore, the effects of initial porosity, permeability, and elastic modulus of the reservoir rock, as well as the stress ratio and injection rate, on CO2 migration and damage to the wellbore and reservoir rock were analyzed. The initial porosity and permeability of the reservoir rock were described using the Weibull distribution.Results and DiscussionsThe influence of various factors on CO2 migration and damage to the wellbore and reservoir rock was examined. Analyses of the benchmark model showed that CO2 saturation and average pressure distributions were closely related, with the highest pore pressure occurring near the injection well. Pore pressure changed significantly from 0.5 to 4.0 days, with maximum average pressure changes initially reaching 5 MPa and increasing up to 15 MPa as the pore pressure diffused. This increase reflected the influence of boundary conditions on the migration of CO2. Heterogeneity in reservoir porosity and permeability significantly affected distributions of both pore pressure and CO2. Initial CO2 saturation exhibited a distinctly nonuniform pattern. As CO2 migrated, its distribution became more uniform but still depended on variations in porosity and permeability. Previous field simulations indicated that reservoir heterogeneity and the presence of fractures can significantly alter CO2 migration patterns. For the wellbore model, despite boundary constraints limiting further pressure diffusion, heterogeneity impacted CO2 migration and pore pressure distribution, influencing potential damage to the wellbore and surrounding areas. It was found that the injection rate, reservoir porosity, and permeability controlled CO2 migration, with the stress ratio and elastic modulus being largely negligible, as indicated by analyzing CO2 saturation and pore pressure at 4 days. In cases of low porosity and permeability, a higher injection pressure was required, resulting in greater CO2 saturation and extended migration distances, though excessive pressure posed a risk of fracturing. Since CO2 migration was linked to pore pressure diffusion, pressure-induced damage was mainly influenced by injection rate and changes in reservoir characteristics. Damage to the reservoir rock was attributed to increased porosity and permeability resulting from CO2 injection, as well as mechanical damage at the cement sheath interface. Analysis showed that porosity changes induced by effective stress variation ranged between 0 and 0.001. Permeability changes reached up to 0.03 mD and were even higher locally, with local increments reaching up to 0.06 mD. The Coulomb failure criterion indicated varying degrees of damage under different conditions. Scenarios such as low injection rate and high permeability delayed damage onset beyond 1 day, while low permeability or high injection rates accelerated damage, potentially fracturing the rocks. Damage initially appeared as point damage, potentially evolving into surface damage with continuous injection, occurring at the reservoir-cement sheath interface. The integrity of the cement sheath depended on its properties, the surrounding stress conditions, and variations in pore pressure. For high CO2 injection volumes, increasing the reservoir's porosity and permeability reduced pressure buildup. Visual analysis revealed damage at the interface between the cement sheath and the casing. Nonuniform changes in the Coulomb failure criterion at these interfaces, influenced by heterogeneity in reservoir rock properties, can result in radial cracks within the cement sheath.ConclusionsThis study employs a two-phase hydromechanical coupling model to assess the impact of multiple factors on wellbore and surrounding rock damage caused by CO2 injection. The findings indicate that CO2 migration is aligned with pore pressure diffusion, resulting in both compression and expansion of internal pores. Although reservoir heterogeneity influences CO2 migration, the injection rate and initial permeability play a more critical role in determining CO2 flow and pore pressure distribution. Damage typically occurs at the reservoir-cement sheath interface and the cement-casing interface. Reducing injection rates and increasing reservoir permeability can help mitigate damage to reservoir rocks and the cement sheath. The elastic modulus and stress ratio have limited influence on damage. As the damage evolves from point to surface, enhancing permeability in low-permeability reservoirs is recommended to sustain high CO2 injection rates and reduce the risk of cement sheath failure.关键词：hydromechanical coupling;two-phase flow;wellbore damage;CO2 injection;cement sheath failure;heterogeneity159|339|0更新时间：2026-01-25
- “在绿氨生产领域，专家提出了基于动力学和热力学原理的随机规划建模框架，设计了间接冷却反应器，提升了反应单程转化率，降低了能耗，为绿氨生产过程节能降耗提供了解决方案。”摘要：ObjectiveRenewable energy sources, such as wind and solar power, are intermittent and fluctuating, and they require efficient storage solutions to ensure a stable and continuous energy supply. Ammonia, with its advantages of convenient storage and transportation, versatility, and high energy density, serves as a long-term storage medium for renewable energy. It mitigates energy wastage caused by intermittencies, such as unused wind and solar power, and reduces carbon emissions associated with traditional ammonia production processes in alignment with the goal of “Carbon Peak and Carbon Neutral”. This process is referred to as renewable power to ammonia (RePtA).RePtA involves producing hydrogen from renewable energy through the electrolysis of water. The hydrogen is then compressed and mixed with nitrogen obtained by air separation based on stoichiometric ratios. The mixture is heated to the catalyst start-up temperature and introduced into a reactor to undergo ammonia synthesis. After synthesis, the reaction gas undergoes cooling and separation to obtain industrial-grade liquid ammonia, while the unreacted synthesis gas is recycled back into the reactor to sustain the reaction. However, the intermittent instability of renewable energy sources, such as wind power, causes fluctuations in the flow of hydrogen produced through electrolysis, which leads to instability in the feed flow to the green ammonia reactor. This condition disrupts the thermal and kinetic equilibrium of the ammonia synthesis reaction and prevents the reaction from proceeding under optimal conditions. Hence, adapting the conventional ammonia synthesis reactor to meet the requirements of the green ammonia production process for smooth operation presents challenges. At present, the ammonia synthesis process mainly relies on the Haber‒Bosch method.Mathematical models developed in previous studies are often scenario-specific and assume constant feed flow rates and system process parameters. However, in actual production, the availability of renewable resources such as wind continuously changes, causing fluctuations in hydrogen flow due to electrolysis. These fluctuations lead to variations in ammonia yield and heat release during the synthesis reaction and can ultimately reduce product yield or even cause complete cessation of the reaction, resulting in serious consequences.MethodsA two-stage stochastic planning modeling framework rooted in the principles of kinetics and thermodynamics was proposed to enhance the robustness of green ammonia production and reduce the impact of uncertainty factors on the production process, which integrated key processes such as hydrogen production from electrolytic water, ammonia synthesis reaction, and ammonia cooling and separation.The first stage in the stochastic planning model determined the reactor topology, including the heat transfer area configuration of the heat exchangers, the volume of each reactor bed, and the connection of the piping, whereas the second stage focused on optimizing the production process by considering the uncertainty parameters. It determined key process parameters such as the circulating flow streams, the tail gas emissions, and the flow rate of the flow streams into each heat exchanger under each scenario.The ammonia synthesis reactor system was first simulated and analyzed using a physicochemical model, which subdivided the reactor system into three subsystems, namely, the heat exchanger, the catalyst bed, and the mixer. The processes occurring within the boundaries of each subsystem were physically and/or chemically distinct. Combining these subsystems allowed for the quantification of the overall behavior of the synthesis system.Results and DiscussionsThe first stage in the stochastic planning model compared the adiabatic quench cooling reactor (AQCR) and the adiabatic indirect cooling reactor (AICR), which were commonly in use, and the difference in the effectiveness of the two reactors was mainly due to the variation in the residence time of the reactant gas within the catalyst bed, which resulted in a difference in ammonia yield. This determination included the volume of each bed, the heat transfer area, and the connection of the pipelines. The optimized reactor configuration was illustrated in this study. Regarding the bed volumes, the catalyst bed volumes increased sequentially from Bed 1 to Bed 3. The main reason was that the ammonia reaction is reversible. As the reaction progresses to the later stage, the forward reaction rate slows down, the reverse reaction rate accelerates, the resistance to the forward direction increases, and the overall reaction rate decreases. It was necessary to increase the bed volume under specific air velocity conditions without altering the internal structure and pressure of the reactor to ensure thorough gas reaction.ConclusionsThe obtained reactor configuration in the second stage was employed as the foundation for optimizing the production process. The robustness of the RePtA production process was further strengthened through adjustments of operational parameters, including the flow rate of each reactor stream under various feeding conditions, by applying the multi-scenario stochastic planning model. The results indicated that the designed indirectly cooled reactor can effectively accommodate variations in operating scenarios caused by fluctuations in feed flow rate, ensuring stable performance under multiple operating conditions.The total cost of the designed reactor increased by approximately 410 000 RMB, representing a 10% rise compared to the original reactor. At the same time, the AICR improved the one-way conversion of the reaction, leading to an 18% increase in ammonia production compared to the original, with an annual production growth of about 8 000 t. Therefore, the cost per tonne of ammonia was reduced by 4.5% with only a minor increase in the annual cost. In addition, due to greater heat release from the AICR, the energy consumption of the RePtA process was reduced, resulting in an annual energy saving of 3.8×106 MJ. Accordingly, the optimized design provides advantages in four essential areas: coping with variable load conditions, increasing ammonia production, reducing process energy consumption, and lowering production costs.关键词：stochastic programming;chemical reactors;optimization design;power-to-ammonia;renewable energy;process system246|454|0更新时间：2026-01-25
CARBON NEUTRALITY AND CLEAN ENERGY
- “在能源网络与信息网络深度耦合背景下，移动目标防御技术在提升新型电力系统安全性方面具有重要作用，为智能电网和多能互联场景下的MTD技术发展提供了参考框架。”摘要：Significance With the integration of energy systems and information networks, power systems now rely on large-scale data acquisition, state monitoring, and dynamic scheduling. Although these advancements improve real-time sensing and control, they also introduce new security risks. The impact of information-level attacks gradually extends to the physical system, posing a significant threat to the security of the power system. The false data injection attack (FDIA) is a common and destructive network attack. FDIA interferes with state estimation, causing system operation to deviate from the normal operational range by tampering with or injecting forged data. Therefore, serious power supply failures can occur. At present, defending against FDIA has become a key area of power system security research. Moving target defense (MTD) is an emerging active defense method that provides significant advantages in countering FDIA. MTD dynamically changes the state of the system, disrupting the attacker's control over system information. This approach makes it difficult for attackers to obtain the real state information of the system. MTD effectively increases the difficulty and cost of attacks by continuously perturbing key parameters of the power system. With the continuous evolution of network threats, the importance of MTD strategies in new power systems is steadily increasing. Their application not only enhances the overall security of the system but also provides an active defense against complex and dynamic cyber threats.ProgressMTD technology originated in the field of network security defense, and its concepts were later introduced into power systems by scholars. The initial MTD strategy for power systems adopted a random perturbation approach, which was insufficient for stable and effective defense. As research advanced, scholars successively optimized the performance of MTD with the primary objective of maximizing the rank of the measurement matrix. This optimization aimed to reduce defense blind spots and improve overall system security. One approach, known as hidden MTD, minimized the impact of MTD on power flow while ensuring the normal operation of the system to maintain stability. The hidden MTD strategy emphasized the stealth of defense actions, making it more difficult for attackers to detect defensive behaviors. In addition, the AC current model-based MTD adapted defenses to the actual characteristics of the power system through a more realistic modeling approach. Perturbation sensor gain-based MTD further reduced the impact on the power system by adjusting sensor gains to induce state perturbations.Conclusions and ProspectsMTD, as an active defense method, demonstrates significant potential for application in new power systems. With the growing complexity and intelligence of power systems, the design of MTD strategies presents both challenges and opportunities. On one hand, the diversified characteristics of new power systems expand the implementation scenarios and methods of MTD strategies; on the other hand, the complex multi-energy interconnection structure imposes higher requirements on their implementation effectiveness. The systematic framework for the application and development of MTD in new power systems is presented in this study with the objective of continuously strengthening the defense capability of power systems. This goal will be achieved within future complex energy environments, ultimately ensuring the safe and stable operation of power systems. Current research primarily focuses on traditional transmission networks, which are difficult to adapt to the requirements of new power systems. This study analyzes the application potential of MTD in new power systems and proposes the corresponding key technologies. In addition, based on the characteristics of new power systems in power generation, transmission, distribution, and consumption, this study discusses the specific implementation strategy of MTD in detail. Future MTD technology should not be limited to an independent application but should operate in interaction within a multi-layer defense system, acting as a link across the detection, identification, and response stages. Through the coordinated application of multi-layer defense measures, the resilience of power systems against attacks such as FDIA can be significantly enhanced.关键词：new power systems;false data injection attack;moving target defense;cyber-physical systems;multi-energy interconnection178|813|0更新时间：2026-01-25
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Non-intrusive Load Monitoring Based on Colored V-I Trajectory Features and Edge Machine Learning AI导读
“在非侵入式负荷识别领域，提出了基于彩色V-I轨迹特征和轻量级孪生网络的新方法，有效提高了负荷识别准确率，并实现了模型的动态实时在线更新。”摘要：ObjectiveA large amount of data is generated during the process of power consumption, which serves as the basis for informed user decisions and helps realize home energy efficiency monitoring, safety protection, and demand-side management. Therefore, obtaining real-time electricity consumption information through load identification has significant research value. Non-intrusive load monitoring (NILM) refers to a method that does not require the installation of a monitoring device for each individual load. Instead, it analyzes only the voltage and current data on the bus to obtain information about various factors, such as load type, operating status, and power consumption. Studies have shown that non-intrusive load recognition helps users reduce their energy consumption by up to 15%. As a primary tool for analyzing users’consumption behavior, non-intrusive load identification is crucial for both energy-use monitoring and electrical safety assessment. Methods based on the V-I trajectory have indicated promise, but several limitations remain. First, V-I trajectories often overlap: many appliances produce very similar shapes, especially after normalization, so using the trajectory alone makes it challenging to separate look-alike loads. This calls for integrating auxiliary cues, power and power-factor statistics, harmonic features, or other spectral or temporal descriptors. Second, many approaches are closed-set. They frame recognition as multiclass classification and identify only classes seen during training, while unknown loads are mishandled. The associated neural classifiers are also relatively complex. Third, training pipelines typically depend on server-class compute. When ported to embedded edge devices, limited resources prevent timely model updating or retraining. As the number of unseen loads grows, accuracy degrades without on-device or real-time adaptation, making it challenging to guarantee effectiveness and latency in practice and revealing a gap between lightweight AI and deployable systems.MethodsThis study proposed a NILM method that combined colored voltage-current (V-I) trajectory features with a lightweight Siamese network. The aim is to address the overlapping features caused by different loads. The method has two main objectives: to enhance the information conveyed by V-I images and to maintain a compact inference pipeline suitable for embedded, real-time NILM applications. This study introduced a simple and effective method for constructing colored V-I trajectory images. The approach involved creating colored V-I trajectory images that incorporated directional information using load voltage and current data, while employing the RGB color channels of the images. Compared to traditional V-I trajectories, this new method captured more load characteristics and clearly reflected the distinct features of each load. The improved colored V-I trajectory enabled a more detailed depiction of load characteristics, enhancing the accuracy of load identification. Given that the load V-I trajectory images were not overly complex and that NILM must operate online on embedded devices, a highly complex neural network structure was unnecessary. This study employed a Siamese network to calculate the similarity between the V-I trajectory image of the load to be identified and the V-I trajectory images in the load feature database, which enabled preliminary identification. The Siamese network model consisted of two components: the convolutional neural network (CNN) model and the backpropagation (BP) model. The CNN model extracted feature vectors from the colored V-I trajectory images, while the BP model computed the similarity between these feature vectors. The CNN model referenced was the classical lightweight neural network structure known as LeNet-5, which produced a 32-dimensional feature vector. LeNet-5 has a simple architecture and low complexity, which makes it suitable for real-time operation. The BP model took as input a 64-dimensional vector derived from merging two 32-dimensional feature vectors obtained by the CNN model, and its output was a continuous value between 0 and 1. An evaluation was made on whether the input vectors belonged to the same class by comparing the output results of the Siamese network with a predetermined threshold. The second stage incorporated harmonic features for identification after the initial recognition using the Siamese network to prevent misidentification of different loads with similar V-I trajectories. Specifically, the cosine distance between the harmonic features of the current was calculated and compared against a threshold to complete the load identification process. Initially, loads in the harmonic feature database corresponding to the V-I trajectory image that has matching harmonic features (including the 1st, 3rd, 5th, and 7th harmonics) were identified, and the similarity between these harmonic features was assessed using cosine distance. A greater cosine distance indicated higher similarity between the two loads. If the similarity exceeded the threshold, the load to be identified was classified as a known load in the database. In contrast, if the similarity fell below the threshold, the load was considered a new load, and its feature vector was added to the feature database. Through this dynamic updating of the feature database, the load was recognized as known if it appeared again. The method effectively avoided misidentifications that could have arisen from the similarities in V-I trajectories of different loads by integrating the features of V-I trajectories with harmonic features.Results and DiscussionsThe Siamese network model was trained using V-I trajectories from the WHITED dataset and was deployed on an embedded Linux system powered by an STM32MP1 microprocessor. It was then validated using laboratory electrical loads. The results indicated that the colored V-I trajectory provided a more detailed representation of load characteristics, which enhanced the accuracy of load identification. In addition, the improved artificial intelligence model was lightweight, which significantly reduced computational requirements. The on-device feature database was updated online in real time, and local retraining or incremental updates were supported. Unlike server-dependent pipelines, this deployment eliminated the requirement for a round-trip to a PC or server for retraining and subsequent redeployment to the edge device.ConclusionsThe method employs the embedded terminal to accurately identify unknown loads, preventing a reduction in recognition accuracy as the number of unknown loads increases and ensuring effective load recognition. The system's runtime for identifying a single load is approximately 0.2 seconds, which satisfies real-time requirements and demonstrates substantial research value and practicality. The colored V-I trajectory combined with a lightweight Siamese network model provides a robust and deployable approach for real-time NILM on resource-constrained embedded hardware.关键词：Non-intrusive load monitoring;edge machine learning;Siamese network;embedded Linux system510|714|0更新时间：2026-01-25 - “新能源接入和储能技术进步推动云储能模式成为用户侧储能管理新方式。专家提出配电网-云储能系统双层优化运行方法，有效降低配电网运行成本，减小负荷峰谷差，实现三方共赢。”摘要：ObjectiveWith the increasing proportion of renewable energy integrated into the distribution network, along with advancements in energy storage technology, cloud energy storage (CES) provides a new approach for the future management of customer-side energy storage. Many decentralized energy storage resources exist on the consumer side of the distribution network, which exhibit high inactivity and present management challenges. The effective utilization of decentralized energy storage resources not only raises the consumption of renewable energy but also reduces the operating cost of the distribution network and enhances the utilization of inactive decentralized energy storage resources. Therefore, this study proposes a bi-level optimization scheduling method for the distribution network-cloud energy storage system while considering renewable energy uncertainties.MethodsA multi-agent interaction structure of the distribution network with the CES system was established to analyze the characteristics of decentralized energy storage resources on the customer side of the distribution network. Specifically, a bi-level optimal scheduling model of the distribution network-cloud energy storage system was proposed by considering wind and solar uncertainties. With the objective of minimizing the operation cost of the distribution network, the upper-level model determined the optimal dispatching strategy of different generating units and the charging/discharging strategy of the CES system. Accordingly, the lower-level model aimed to maximize the benefit of the CES system by determining the detailed charging and discharging strategy of its customers while considering the operation constraints of the distribution network.Results and DiscussionsThe validity of the proposed bi-level optimization scheduling method of the distribution network-cloud energy storage system under renewable energy uncertainties was verified through four numerical cases. The comparative analysis was conducted in terms of the load profile of the distribution network, the charging and discharging strategy of the CES system, and the operation cost of the distribution network. In Case 1, the optimal scheduling strategy of the distribution network-cloud energy storage system was obtained. The charging hours of the CES system were mainly from 01:00—05:00 and at 24:00, while the discharging hours were mainly from 12:00—14:00 and 18:00—20:00. The peak-to-valley load difference of the distribution network was 2.7 p.u., together with the total operating cost of ￥93 401.2. For the distribution network, the electricity purchasing cost from the upper-level grid was ￥46 542.6, the operation cost of the gas unit was ￥45 382.1, the charging/discharging cost paid to the CES operator was ￥3 187.5 , and the charging revenue from the CES operator was ￥1 711.0. From the perspective of the CES system, the charging/discharging cost paid to EV customers was ￥399.1, the charging/discharging cost paid to UPS customers was ￥611.6,the compensation cost paid to load interruption customers was ￥562.2, and the charging revenue from EV customers was ￥2 037.0. As a result, the total revenue of the CES operator was ￥1 940.6. In Case 2, the CES system was not considered, and EV users performed uncontrolled charging. The UPS and load interruption customers were also not included. Compared to Case 1, the peak-to-valley load difference of the distribution grid increased to 3.4 p.u., with an increase of 25.9%. In addition, the total operating cost of Case 2 increased by 8.0%, and the electricity purchasing cost from the upper-level grid increased by 19.2%. Specifically, the charging cost of EV customers increased by 245.7%. Case 3 examined the influence of CES capacity by changing the number and capacity of CES customers. The CES capacity participating in the distribution network scheduling was adjusted to 75%, 50%, and 25% of its capacity in Case 1, respectively. It was concluded that the total operating cost of the distribution network decreased as the CES capacity increased. However, the peak-to-valley load difference of the distribution network appeared to increase inversely when the CES capacity reached 100%, because the charging loads of EV customers were shifted to the low valley hours. Hence, the charging of the CES system at 01:00 increased abruptly from 0.2 p.u. to 0.7 p.u. at the capacity of 75%, while the CES system did not charge at 06:00—07:00, which increased the peak-to-valley load difference. Therefore, it was concluded that the appropriate capacity of the CES system can smooth the peak-to-valley difference of the load profile when participating in the distribution network scheduling. In Case 4, the uncertainty of wind and solar power was considered. Taking the wind and solar power prediction curve of Case 1 as the base scenario, 5 typical wind and solar power output scenarios were generated by Monte Carlo sampling and simultaneous backward reduction. For Scenario 3, the wind power output increased from 21:00 to 23:00, and the excess wind power was consumed by the CES system through charging. For Scenario 5, the wind power output decreased at 02:00, and the CES system discharged power to meet the load demand of the distribution network, with the discharging power increasing from 0 to 0.5 p.u. Therefore, the CES system managed the fluctuation of wind and solar power by adjusting its charging and discharging power under the premise of satisfying the charging demand of CES customers, improving the flexibility and stability of system operation. The proposed bi-level optimization scheduling model of the distribution network-cloud energy storage system under renewable energy uncertainties effectively reduced the operation cost of the distribution network and the peak-to-valley difference of the load curve, while improving the economy and stability of the distribution network operation. In addition, by adjusting the charging and discharging strategies of the CES system, the distribution network maintained stable operation under the fluctuation of wind and solar power.ConclusionsNumerical results demonstrate that the proposed cloud energy storage operation strategy effectively reduces the operational cost of the distribution network, mitigates peak-load differentials, and fosters a mutually beneficial relationship among the distribution network, cloud energy storage operators, and cloud energy storage users. In addition, using the flexible regulation capability of the cloud energy storage system, the stable operation of the distribution network can be maintained even under fluctuating renewable energy outputs such as wind and solar power.关键词：cloud energy storage;renewable energy consumption;day-ahead scheduling;bi-level optimization model;uncertainty274|351|0更新时间：2026-01-25
- “在孤岛微电网领域，专家提出了一种无功均分控制策略，有效解决了系统等效阻抗变化导致的无功均分难题，为改善母线电压质量提供了新方案。”摘要：ObjectiveIn the microgrid under islanding mode, factors such as local load shedding or variations in line impedance cause differences in system equivalent impedance, which makes it challenging for parallel inverters using droop control to achieve accurate reactive power sharing. A reactive power sharing control strategy for islanded microgrids with both frequency and amplitude compensation functions is proposed to address this issue.MethodsFirst, analyzing the power transmission characteristics of the droop-controlled parallel inverter indicated that the active power output of the inverter was not affected by the line impedance. When the active power droop coefficient was inversely proportional to the inverter capacity, active power sharing was achieved. However, the reactive power output of the inverter was not only related to the reactive power droop coefficient but also affected by the line impedance. Due to the low voltage level of the microgrid and the non-negligible line resistance, there was a power coupling problem when using inductive droop control for parallel inverters. Therefore, a virtual impedance was introduced in the dual-loop control to make the system equivalent impedance inductive, thus realizing the decoupled control of active/reactive power in low-voltage microgrids. Secondly, the analysis of the reactive power sharing condition exhibited that the accuracy of reactive power equalization was closely related to the line impedance and the output voltage of the inverter. When the impedance of the line did not match the capacity of the inverter, it was difficult to evenly distribute the reactive power output of the inverter based on the capacity. Although introducing appropriate virtual impedance matched the line impedance with reactive power capacity and improved the accuracy of reactive power sharing, the accuracy was affected by the variation of equivalent impedance and caused additional bus voltage drop. Therefore, this study introduced an integral correction term in the reactive power control loop and adopted the method of regulating the output voltage of the inverter to achieve reactive power sharing. Based on the three-dimensional schematic diagram of the effect of power sharing on the amplitude of the inverter output voltage, it was observed that by introducing a reactive power correction term to adjust the amplitude of the inverter output voltage, it was distributed on the line where power sharing occurred, thus achieving reactive power sharing. The reactive power correction term was set to an adaptive form, driven by reactive power deviation, to adjust the inverter output voltage and achieve reactive power sharing to adapt to changes in line impedance and local load switching scenarios. The accuracy of reactive power sharing was not affected by changes in line impedance. However, introducing reactive power correction caused changes in the inverter output voltage, which in turn affected the amplitude of the bus voltage. Therefore, it was necessary to consider measures for compensating the bus voltage. In addition, droop control simulated the droop characteristics of synchronous generators. When there were large-scale load changes, the inverter output voltage frequency and amplitude deviated significantly from the rated values, which also affected the quality of the bus voltage. Frequency and amplitude compensation terms were introduced in the active and reactive control loops, respectively, to suppress the voltage frequency and amplitude deviation caused by large-scale load shedding. The selection principles of frequency and amplitude compensation coefficients were analyzed from the perspective of the dynamic response of the power control loop. Introducing frequency compensation suppressed frequency offset; however, the analysis of the active power transmission characteristics after the introduction of frequency compensation indicated that a substantial frequency compensation coefficient reduced the accuracy of active power sharing. An active power correction term was introduced into the active control loop to suppress frequency deviation while ensuring the accuracy of active power sharing. The power transmission characteristics indicated that the introduction of an active power correction term eliminated the active power deviation caused by frequency compensation.Results and DiscussionsThe proposed strategy was compared to traditional droop control and virtual impedance-based droop control. Simulation results showed that the proposed control achieved adaptive reactive power sharing in the scenario of system equivalent impedance variation, and the accuracy of reactive power sharing was not affected by the variation of system equivalent impedance. In the scenario of plug-and-play for inverters, the proposed strategy allocated power reasonably based on the status of the inverters. The proposed strategy in both scenarios reduced the magnitude of bus voltage and frequency deviation while achieving active and reactive power sharing, improving the quality of bus voltage.ConclusionsA self-adaptive reactive power-sharing control strategy is proposed to address the challenges posed by system equivalent impedance variation and bus voltage amplitude and frequency deviation caused by large-scale load switching on the reactive power-sharing performance of droop-controlled parallel inverters. This strategy integrates voltage frequency and amplitude compensation functions. The proposed strategy has reference value for research on improving the power equalization accuracy of isolated microgrids while suppressing voltage frequency and amplitude deviations.关键词：parallel inverter;droop control;reactive power sharing;frequency compensation;voltage compensation216|490|0更新时间：2026-01-25
NEW TYPE POWER SYSTEM
- “西北干旱地区夯土遗址消亡研究取得新进展，揭示了夯土崩解特征与基质吸力的关联性，为遗址保护提供科学依据。”摘要：ObjectiveSoil erosion at earthen sites in northwest China remains one of the primary factors compromising site stability. Simultaneously, soil disintegration and matric suction are considered key indicators influencing the degree of soil‒water interaction. However, for rammed earth exhibiting temporal and spatial properties, the characteristics of disintegration and the variation in matric suction during the disintegration process remain unclear. This study investigates the correlation between disintegration behavior and matric suction to identify the fundamental factors influencing the disintegration of rammed earth.MethodsThe fine disintegration process of rammed earth was examined using a custom-built disintegration apparatus. This apparatus primarily consisted of an electronic balance, a data acquisition system, an automatic flow rate controller, a disintegration tank, a sample basket, a support frame, and sensors. The test specimen was an undisturbed cubic soil sample with a side length of approximately 3 cm. First, the sample basket was suspended from the lower interface of the electronic balance. Its position within the disintegration tank was adjusted to the appropriate height, the balance was zeroed, and the specimen was placed horizontally within the basket. Water was then injected into the disintegration tank at a constant rate via the flow control device until the water level exceeded the top surface of the soil, at which point the water injection was stopped. Test phenomena were promptly observed and recorded. Once the data collected by the acquisition system stabilized over a defined period, data collection was terminated, marking the end of the soil disintegration process. The disintegration process was then categorized into distinct stages based on variations in the disintegration data, and characteristic values for each stage were calculated. The soil‒water characteristic curve (SWCC) was determined using both the pressure plate method and the filter paper method. The pressure plate method employed axis translation technology to measure the low suction range, whereas the filter paper method relied on a calibration curve to assess the high suction range. The filter paper used was No. 203 slow‒filter paper with an ash content of 0.01%. Relevant data points were obtained through staged pressure application and the calibration curve. Then, the complete soil-water characteristic curve was fitted using the Van Genuchten (VG) model.Results and DiscussionsThe results of the refined disintegration process tests demonstrated that rammed earth disintegration exhibited classification characteristics and distinct spatiotemporal regularity. The disintegration process for the 11 easily disintegrated rammed earth samples consisted of a hygroscopic softening stage, a disintegration stage, and a stabilization stage. In contrast, the difficult-to-disintegrate rammed earth displayed only the hygroscopic softening stage and the stabilization stage. During the disintegration stage, the primary soil behaviors involved breaking and separation. Simultaneously, spatiotemporal regularity was more pronounced in the easily disintegrated rammed earth. In the hygroscopic softening stage, the hygroscopic rate followed the sequence: extreme arid area > arid area > semi-arid area. During the disintegration stage, the disintegration rate followed the sequence: semi-arid area > extreme arid area > arid area, and Ming Dynasty > Han Dynasty > Qing Dynasty > Tang Dynasty > Song Dynasty. In addition, the VG model was found suitable for characterizing the soil‒water characteristic curve of rammed earth, with a fitting coefficient exceeding 0.99. Only the initial suction values for the two types of rammed earth exhibited distinct classification characteristics, while their spatiotemporal regularity remained insignificant. This outcome resulted from the fact that the calculation of suction indices in the SWCC test was independent of the soil disintegration process. Therefore, an index termed the suction-time change rate was proposed, which integrated the disintegration process and suction changes within the same temporal dimension for comprehensive characterization. The results revealed a one-to-one correspondence between the suction‒time change rate and the disintegration characteristics, both in classification and spatiotemporal regularity. In addition, a suction-time change rate of 2 000 kPa/s during the hygroscopic softening stage can serve as a threshold condition for distinguishing the type of disintegration. A strong quantitative relationship was observed, fitting exponential growth functions with correlation coefficients greater than 0.8. Analysis of the gradient changes in matrix potential energy during the disintegration process also indicated a specific correlation between these factors. These findings provided theoretical support for subsequent studies on the erosion mechanisms of site gullies. Finally, the spatiotemporal factors influencing rammed earth disintegration were recognized as complex. For the Tang and Song Dynasty sites, the rammed earth was more resistant to disintegration. Whether this was related to the economic development and tamping technology of the dynasty, or geopolitical and military strategies, or the different structural functions arising from variations in building types, or to the differences in the quantity of aggregates and the spatial arrangement characteristics between particles and pores under the spatiotemporal conditions caused by the variation in building materials, these issues required further research and ongoing enhancement of the related archaeological literature and excavation efforts.ConclusionsThe results revealed a correlation between matrix suction and the disintegration of rammed earth, indicating that the rate of change in suction over time is the decisive factor influencing the degree of disintegration. This conclusion is supported by an analysis of the gradient changes in matrix potential and pressure potential during the disintegration process. These findings provide significant reference value for research on the erosion development mechanisms of gullies at the site.关键词：rammed earth;disintegration characteristic;classification;spatiotemporal regularity;matric suction;matrix potential energy;suction-time change rate217|323|0更新时间：2026-01-25
- “在建筑结构减隔震技术领域，专家提出了点振型埋地超材料，拓宽低频带隙，为地震超材料结构设计提供参考。”摘要：ObjectiveEarthquakes generate seismic waves that cause significant damage to buildings on the ground. At present, the metamaterial isolation barrier represents an emerging seismic reduction technology for building structures. However, existing research frequently encounters challenges such as excessive ground space requirements and limited band gaps in metamaterial isolation barriers. Therefore, this study proposes a buried point-vibration-type metamaterial encased in steel plates, with an internal structure composed of alternating steel blocks and rubber columns. The fundamental principle of seismic metamaterial isolation is to dissipate the energy of incoming seismic waves through local resonance, providing effective protection to buildings located within the barrier.MethodsThe fundamental principle for calculating the dispersion relationship of periodic structures was derived from the theory of elastic waves. The band structure of the metamaterial and the mode shapes at specific points were calculated using the finite element method. The accuracy of the dispersion curve calculation method was validated by the simulation results of previous studies. A frequency-domain analysis model was developed, and displacement excitations in the frequency range of 0.1 to 20.0 Hz were applied at the excitation points. The frequency response curve was plotted using the transfer spectrum, and the filtering effect of the metamaterial barrier under 6.0 Hz excitation was analyzed based on the mode and displacement distribution. The filtering characteristics of multi-layer barriers on oblique incident waves were then calculated. Then, the optimal material parameters and number of buried layers were determined through parameter analysis by filling various layers of soil and rubber with different densities and elastic moduli inside the metamaterial structure. A model consisting of 6 layers of soil and metamaterials with different parameters was constructed to calculate the band gap and frequency response curve of metamaterials under layered soil conditions, considering the gradual variation of soil parameters with depth in real scenarios. In addition, the arrangement of the metamaterial structure in a 4×5 array was examined to enhance the attenuation effect of elastic waves. Finally, artificial sine waves with a wave period of 10 and center frequencies of 0.7, 5.0, and 8.0 Hz were constructed using the Heaviside step function. The 0.7 Hz sine wave was outside the band gap, while the 5.0 and 8.0 Hz sine waves were inside the band gap. Representative seismic waves were selected from the Peer ground motion database to simulate the filtering effect of metamaterials when encountering actual seismic waves.Results and DiscussionsThe results demonstrated that metamaterials generated a wide low-frequency band gap, with a band gap range of 0.87～12.57 Hz and a band gap width of 11.70 Hz. The mechanism behind the formation and closure of the gap was analyzed using the mode theory of specific points on the band structure, revealing that the gap was formed through the local resonance of the structure. The displacements at the response points were computed under three conditions: no super barrier, a 10-element structure, and a 20-element structure, and the frequency response curves were plotted based on the transfer spectrum. The results showed that the attenuation range of the frequency response curve was consistent with the gap, verifying the accuracy of deriving the gap from the dispersion curve. The displacement field and displacement distribution diagrams under 6.0 Hz excitation indicated that the displacement minimally decreases after the elastic wave passes through without the metamaterial barrier. However, the displacement significantly decreases with the addition of the metamaterial barrier, confirming the filtering effect of the metamaterial barrier. The metamaterial barrier also provided strong attenuation for oblique incident waves. As the number of soil layers increases, the midpoint frequency (fm) gradually increases, and the relative band gap width (fw) reduces, shifting the gap toward higher frequencies with a smaller bandwidth. Similarly, an increase in rubber density led to a gradual decrease in fm and a gradual increase in fw, resulting in lower frequencies with a larger bandwidth in the gap. In addition, an increase in rubber elastic modulus causes a gradual increase in fm and a gradual decrease in fw, shifting the gap toward higher frequencies with a smaller bandwidth. Under stratified soil conditions, the structure generated a gap with a range of 0.87～17.61 Hz and a width of 16.74 Hz, which was 5.04 Hz wider than the gap width of uniform soil layers. The frequency response curve showed a significantly enhanced attenuation effect of the metamaterial barrier with a 4×5 array structure. When an artificial sine wave with a frequency outside the gap range of 0.7 Hz was input, the average attenuation effect reached about 13%. Even when the main frequency of the signal wave was outside the gap range, the metamaterial barrier still produced a smaller acceleration at the response point compared to the structure without the super barrier, indicating that the metamaterial did not amplify the signal wave outside the gap. In addition, when 5.0 and 8.0 Hz artificial sine waves were input, the average attenuation effect reached about 65% and exceeded 96%, respectively. The accelerations of two seismic waves (Imperial Valley and El‒Centro) were attenuated by about 46% and 74% in the Z direction.ConclusionsThe structure with a metamaterial barrier possesses a broad low-frequency band gap generated through local resonance. The metamaterial demonstrates effective attenuation of elastic waves within the gap range, and the barriers retain strong attenuation capability even for oblique incident waves. It is recommended to utilize metamaterial barriers with one, two, or three layers of buried soil to ensure structural stability. Employing rubber with a higher friction coefficient helps minimize the impact on the gap while maintaining other parameters constant, whereas the use of rubber with a higher elastic modulus still preserves a favorable gap range. The gap width in stratified soil conditions increases, making the metamaterial barrier more suitable for practical applications. A 4×5 array or similar arrangement structures are recommended to enhance the attenuation effect. The metamaterial barrier effectively attenuates sine waves with frequencies within the gap without producing adverse effects on sine waves with frequencies outside the gap. It also demonstrates effective attenuation of recorded seismic waves and verifies the capacity to absorb low-frequency seismic wave energy. The findings presented in this study can provide valuable references for the practical application of seismic metamaterials and the design of vibration isolation structures with broader band gaps, stronger feasibility, and improved stability.关键词：seismic waves;metamaterials;band gap;local resonance231|341|0更新时间：2026-01-25
- “在工程地质领域，专家建立了冻结钙质黏土剪切模型，为解决冻结法施工难题提供解决方案。”摘要：Calcareous clay strata present significant engineering geological challenges, including low freezing temperatures, substantial post-freezing expansion, high susceptibility to disintegration in water, and low strength. These properties readily cause excessive deformation or fracture of freezing pipes during construction, representing a major obstacle in artificial ground freezing (AGF) projects. Establishing an accurate constitutive model for calcareous clay freezing walls is therefore a critical element of their design. A series of triaxial shear tests is performed on calcareous clay retrieved from a mining area in Huainan. Field samples are prepared into standard cylindrical specimens (50 mm diameter, 100 mm height). Specimens are first consolidated within a triaxial pressure chamber and subjected to 24 h freezing curing. Testing is conducted using the W3Z‒200 frozen soil triaxial apparatus at Anhui University of Science and Technology's frozen soil laboratory. Test parameters include a strain rate of 1%/min, temperatures of ‒5, ‒10, and ‒15 ℃, and confining pressures of 0, 1, 3, and 5 MPa. Experimental stress‒strain relationships for the frozen soil are obtained. The Duncan‒Chang hyperbolic model is enhanced by incorporating fractional calculus, resulting in a fractional hyperbolic model specifically for frozen calcareous clay. The parameters of this model are determined, and its performance is compared against the original Duncan‒Chang model. Triaxial shear tests on frozen calcareous clay reveal that, under constant confining pressure, its peak strength increases significantly with decreasing temperature. In contrast, at constant temperature, peak strength increases approximately linearly with increasing confining pressure. The stress‒strain curves exhibit distinct strain-hardening behavior. The fractional hyperbolic model accurately captures this hardening characteristic. This model demonstrates broad applicability, effectively accounting for the simultaneous influence of both temperature and confining pressure. Validation confirms its good-fitting performance, while its relatively few parameters facilitate simple determination. This study utilizes natural soil samples and does not consider variations in water content as an experimental parameter. If moisture content differs significantly in specific engineering applications, the model parameters can be re-determined using the methodology proposed herein. Future research focuses on incorporating moisture content parameters directly into the model for further refinement.关键词：calcareous clay;hyperbolic model;stress‒strain curve;fractional-order calculus156|290|0更新时间：2026-01-25
- “在冰川力学特性研究领域，专家基于多晶冰试样三轴试验数据，建立了二元介质本构模型，为理解冰川灾害发生提供理论支撑。”摘要：The Bishop stress variable method and the Fredlund stress variable method are applied to the triple-shear strength criterion to derive two triple-shear failure stress ratios and the related triple-shear yield surface equations for unsaturated clays under the two stress variable methods. The unified hardening parameter is then introduced into the original yield surface equations to obtain the over-consolidated yield surface equations for unsaturated soil. The subloading surface theory is applied to establish two triple-shear subloading surface hardening models (TSSH) for over-consolidated unsaturated clays to reflect the soil deformation characteristics under dynamic and static loads. These two proposed models reflect strain softening, dilatancy, as well as plastic strain accumulation and hysteresis under cyclic loading. Taking the remolded red clay in the Nanchang area of Jiangxi Province as the research object, the basic soil parameters required for the calculation of the TSSH are obtained by laboratory geotechnical tests. The unsaturated static triaxial CD (consolidated drained) tests and the saturated cyclic triaxial CD tests for the over-consolidated unsaturated clays are conducted. The stress‒strain relationship curves for the over-consolidated clays under static and cyclic loads are obtained, and the constitutive model results are compared to the static and cyclic triaxial CD tests. The results showed that the constitutive model outcomes are consistent with the experimental data, which better reflect the mechanical properties such as strain softening, dilatancy, and the ratchet and Masing effects of the over-consolidated clays under cyclic loads. The applicability of the proposed constitutive models in reflecting the basic stress‒strain properties of the over-consolidated clays is verified. The numerical simulations of the true triaxial show that when the influence coefficient of the intermediate principal stress, the matrix suction, and the over-consolidation ratio are larger, the peak stress of conventional static triaxial becomes larger, and the cumulative plastic strain of the cyclic triaxial decreases as the clays reach the end of deformation. The constitutive model effectively reflects the mechanical properties of over-consolidated soil under true triaxial consolidation and drainage.关键词：over-consolidated unsaturated clays;subloading surface hardening model;triple-shear strength criterion;unified hardening parameters;Jiangxi red clay148|468|0更新时间：2026-01-25
- “在冰川力学特性研究领域，专家基于多晶冰试样三轴试验数据，建立了二元介质本构模型，为理解冰川灾害发生提供理论支撑。”摘要：ObjectiveGlaciers are distributed widely in nature. Under the disturbance of external environmental factors, glacier ice becomes unstable, which triggers the occurrence of glacier disasters. Therefore, studying the mechanical properties and constitutive models for polycrystalline ice has important theoretical value for understanding the triggering mechanism of glacier disasters.MethodsFor preparing the polycrystalline ice samples, ice particles with a diameter of less than 2 mm were selected and layered in the mold for compaction. The samples were then degassed and saturated using the bottom-in water saturation method. On the mesoscopic level, based on the preparation method, the samples consist of both skeleton ice and pore ice. The confining pressures at -2 and -6 ℃ in the triaxial tests were 0.5, 1.0, 3.0, and 4.0 MPa, respectively. The instrument used for the tests was an MTS triaxial testing machine. Based on the framework of breakage mechanics and homogenization, a Binary Medium Constitutive Model was established to describe the mechanical properties of polycrystalline ice samples. This model adopted a mesoscopic approach to describe the failure process of polycrystalline ice. The samples in the model consist of two parts: bonded elements and frictional elements. At the beginning of the tests, the samples were intact and composed entirely of bonded elements, which exhibited elastic-brittle mechanical behavior. With the increase in external load, the local pore ice in the samples is destroyed, and the skeleton ice near the pore ice slips and crushes, showing the characteristics of loose ice particles. The frictional elements are composed of the broken parts of the samples, exhibiting elastic-plastic mechanical behavior. In the RVE (representative volume element), during loading, the bonded elements gradually fracture and transform into frictional elements, both of which jointly bear external loads. Finally, the polycrystalline ice becomes entirely composed of frictional elements. The breakage ratio and the strain concentration factor were introduced using homogenization theory to describe the evolution of the internal structure and the non-uniform strain distribution under external load in the RVE. The linear elastic constitutive relation in the model was applied to the bonded elements. For the frictional elements, the ideal elastoplastic constitutive relation was adopted, in which the material was linear elastic before failure and ideally plastic at failure. The yield criterion of the frictional elements follows the Mohr-Coulomb yield criterion, assuming a non-associated flow rule. The breakage ratio is expressed as a function of strain, describing the transformation from bonded to frictional elements in the RVE. The breakage ratio function adopted an empirical formula. The strain concentration factor is also expressed as a function of strain, representing the relationship between the strain of the bonded elements and that of the RVE. The parameters of the model include two types: material parameters and structural parameters. The material parameters were obtained from test results and previous research, whereas the structural parameters were derived from macro analysis of test data or trial-and-error methods.Results and DiscussionsThe deviatoric stress-axial strain curves of the polycrystalline ice samples showed a strain-softening trend, which can be divided into the elastic-brittle stage, plastic yield stage, softening stage, and plastic flow stage. During the plastic flow stage, the curves stabilized after reaching the residual strength. Under different test conditions, the samples reached peak stress when the axial strain approached 1%, indicating that polycrystalline ice exhibited brittle material. As the confining pressure increases, the peak stress of polycrystalline ice rises, but when the confining pressure exceeds a specific value, the peak stress decreases. The results confirmed that a threshold exists when the confining pressure is less than 4 MPa. Before and after this threshold, the response of peak stress to confining pressure was opposite. At low confining pressures, the volumetric strain-axial strain curves of polycrystalline ice samples showed slight compression at first, followed by significant dilatancy. As the confining pressure increases, the curves display complete compression under high confining pressures. The tested curves at -2 °C under different confining pressures were compared to the simulated curves, and both exhibited similar variation trends. In addition, the evolution law of parameter values with confining pressure was established. The tested curves at -6 °C under low and high confining pressures were compared to the simulated curves.ConclusionsThe effect of confining pressure on the samples is manifested in two ways. On one hand, the confining pressure exerts a compacting effect and lateral restraint on the samples, which reduces the pores, strengthens the connection between the ice particles, and constrains the radial displacement of the samples, resulting in an increase in peak stress and volume compression of the polycrystalline ice. On the other hand, the confining pressure produces melting and crushing effects on the ice particles, weakening the bonding between them and causing fracturing and sliding of the particles, which decreases the peak stress of the samples. These two effects coexist and together determine the peak stress and the volumetric strain pattern of the samples. A decrease in temperature reduces the amount of unfrozen water in the samples and intensifies the bonding between ice particles, which increases peak stress and decreases the tendency for volumetric contraction. The rationality of the constitutive model is verified by comparing the curves at different temperatures. In addition, a sensitivity analysis of structural parameters is conducted. The universality of the model is verified by comparing the curves under different parameters.关键词：Polycrystalline ice;binary medium;breakage ratio;strain concentration factor171|947|0更新时间：2026-01-25
- “最新研究显示，风积沙粉替代水泥可显著提升风积沙混凝土微观力学性能，为固废材料在混凝土中大掺量使用提供新思路。”摘要：In response to the issue of decreased mechanical properties of concrete caused by replacing river sand with windblown sand in large quantities, this study adopts the concept of waste treatment. Windblown sand is finely ground to prepare windblown sand powder, and then 10%, 20%, and 30% replace cement in windblown sand concrete. The influence and improvement mechanism of windblown sand powder on the micro mechanical properties of windblown sand concrete are examined through a nanoindentation test and a mercury intrusion test (MIP). The results show that after adding aeolian sand powder, the indentation modulus and hardness of aeolian sand concrete significantly improve. Compared to other additives, 20% aeolian sand powder produces the most significant improvement in the indentation modulus and hardness of aeolian sand concrete, resulting in an average increase of 19.9% and 25.9%, respectively. In addition, based on the indentation modulus, hardness, and volume fraction of the hydrate phase, 20% aeolian sand powder greatly improves the modulus and hardness of the hydrated phase in aeolian sand concrete, reduces the low-density C‒S‒H gel and void content, and increases the high-density C‒S‒H gel and CH content. This further reduces the void volume fraction in aeolian sand concrete of > 100 nm, increases the void volume fraction of < 100 nm, optimizes the pore structure of low-carbon concrete, and causes the interface transition zone to shrink, reducing its thickness by 10% μm, resulting in an improvement in micro mechanical properties. This study provides new ideas and insights for using large amounts of solid waste in concrete and for treating waste with waste.关键词：aeolian sand;Aeolian sand powder;Micro mechanical properties;interface transition zone294|610|0更新时间：2026-01-25
- “厦门第二东通道翔安大桥振动台试验揭示，不同地震波下大直径变截面单桩动力响应特性差异显著，为抗震设计提供参考。”摘要：This study relies on the Xiamen Second East Corridor Xiang'an Bridge to explore the dynamic response of a large-diameter variable-section monopile in a liquefied site under the action of different types of seismic waves. The pore-pressure ratio response of the saturated sand layer, the acceleration of the pile body, and the horizontal displacement of the pile top in the large-diameter variable-section monopile are analyzed through shaking table tests with a strength of 0.15g in the 5010 wave, the 1004 wave, the Kobe wave, and the El‒Centro wave. The bending moment of the pile body and other dynamic response characteristics are also examined. The results show that the liquefaction of the saturated sand soil layer has an amplification effect on seismic waves, and the acceleration response of the pile top demonstrates an evident hysteresis phenomenon relative to the variable section and pile bottom. The pile top exhibits permanent lateral displacement under the action of the four types of seismic waves. The bending moment of the pile body shows a tendency to increase and then decrease from the pile bottom to the pile top, with a steep increase at the position of the variable section. The acceleration of the pile body and the peak bending moment under the action of the 1004 wave reach the maximum, while the peak horizontal displacement of the pile top under the Kobe wave reaches the maximum. These results indicate that there are significant differences in the sensitivity of the dynamic response characteristics of large-diameter variable-section pile foundations to different types of seismic waves. Therefore, for the seismic design of large-diameter variable-section pile foundations, different types of seismic waves should be selected to evaluate the dynamic response characteristics of the pile foundation.关键词：liquefaction sites;large diameter pile with variable cross-section;saturated sand;dynamic response;earthquake design202|355|0更新时间：2026-01-25
- “在建筑工程领域，柱锤冲扩桩地基处理技术因其高效经济被广泛应用。专家通过模型试验和数值模拟，揭示了成桩机理，为现场施工提供理论支持和实用指导。”摘要：ObjectiveAn accurate understanding of the pile formation mechanism of downhole dynamic compaction (DDC) piles is critical for optimizing their application in foundation reinforcement. Traditional foundation strengthening methods suffer from extended construction periods and high costs, while DDC piles have gained popularity due to their advantages in efficiency, cost-effectiveness, and environmental sustainability. However, their pile formation mechanism remains insufficiently documented, particularly at the micro-level. In addition, sand and pebble soil, widely distributed in the Chengdu region, is often discarded as construction waste, which causes environmental issues. This study aims to explore the pile formation mechanism of DDC pile foundation treatment technology using sand and pebble soil as fill material, addressing both technical gaps and environmental concerns.MethodsLaboratory model tests and Flac3D‒PFC coupled numerical simulations were employed to analyze the working principle and effect of DDC piles at both macro- and micro-levels. The model tests focused on measuring soil acceleration and deformation. The numerical simulations investigated changes in skeleton force chains and soil stress responses at different depths and radial distances during the impact process, providing intuitive and quantitative evidence for understanding the pile formation mechanism.Results and DiscussionsThe results indicated that the column hammer impact process can be divided into three distinct stages: soil deformation increase, rebound, and stability. This process primarily utilizes stress waves for energy transfer, with energy decaying rapidly from the downhole bottom to the surrounding foundation soil, facilitating the compaction of ground soil, especially around fill materials. For the studied ground and hammer conditions, when the distance from the downhole bottom exceeded 3d (where d is the downhole diameter), the dynamic response of foundation soil became negligible, indicating a minimal reinforcement effect beyond this range. Dynamic monitoring of force chain skeleton structures in fill materials (sand and pebble soils) revealed that the fill material skeleton underwent breakage and reconstruction during impact. As inter-particle voids decrease, the number of force chains in fill materials increases, significantly enhancing their stability and supporting capacity. Based on foundation soil dynamic responses, an effective reinforcement zone was identified: vertically, it ranged from ‒0.5d to 3.0d (with negative distances indicating positions above the initial downhole bottom); horizontally, its diameter was approximately 1.5d from the downhole centerline. Within this range, foundation soil experienced significant dynamic responses, consumed most impact energy, and underwent substantial deformation, achieving the desired compaction and strength.ConclusionsThe results demonstrate that DDC pile technology effectively modifies soil structure and enhances soil compactness and load-bearing capacity. Dynamic responses of foundation soil during impact reveal the complexity of the pile formation mechanism, particularly the evolution of foundation soil acceleration, deformation, and force chain skeletons in fill materials. This perspective provides valuable insights for optimizing and understanding DDC piles. The findings provide theoretical support and practical guidance for engineering applications of DDC piles using construction wastes (sand and pebble soil, waste concrete) as fill materials.关键词：downhole dynamic compacted pile;reinforcement mechanism;soil displacement;dynamic response;skeleton force chains213|511|0更新时间：2026-01-25
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Experimental Study on the Bond Performance Between Corroded Steel Bar and Fiber-reinforced Concrete AI导读
“最新研究揭示了锈蚀钢筋与玄武岩-聚丙烯纤维增强混凝土黏结滑移机理，为BF-PF增强混凝土性能评估提供数据支持。”摘要：ObjectiveReinforced concrete structures remain highly vulnerable to chloride ion corrosion during prolonged service life. Fiber-reinforced concrete (FRC) demonstrates enhanced durability, making it well-suited for complex environments and rigorous engineering demands. This study seeks to clarify the influence of fiber incorporation on the concrete matrix and to examine the variation in bond performance between different types of FRC and corroded steel reinforcement.MethodsA total of 36 specimens were designed for basic mechanical performance testing, and eccentric pull-out tests were conducted on 48 prism specimens subjected to varying corrosion rates (0, 2%, 5%, and 10%). The corrosion of the steel reinforcement was accelerated using electrochemical methods. Stirrups were incorporated into the specimens without insulation or oxygen isolation treatment to simulate actual engineering conditions. A corrosion current density of 200 μA/cm² was maintained. The relationship between the applied time and the theoretical corrosion rate was determined based on Faraday's law. After reaching the predetermined corrosion time, the specimens were dried and then subjected to pull-out tests. The pull-out force was measured using sensors on the testing machine, while two Linear Variable Differential Transformers (LVDTs) recorded slip values. Tests were performed using a displacement-controlled loading method at a rate of 0.5 mm/min, and the pull-out process was terminated when the pull-out force stabilized or the specimen failed. Surface changes and failure modes were documented. The bonded steel was extracted, rust was removed through acid washing, and the actual corrosion rate of the steel reinforcement was calculated using the mass loss method. Scanning electron microscopy (SEM) was then employed for microscopic analysis of the bonded interface after failure. SEM observations revealed the microstructure of the basalt-polypropylene fiber-cement interfacial transition zone, as well as the distribution and post-failure morphology of the fibers, which further clarified the fiber action mechanisms. Based on the experimental results and incorporating the corrosion damage factor, semi-empirical and semi-theoretical bond strength prediction formulas, together with a three-segment bond-slip constitutive model, were developed for different fiber incorporations. These models generally maintained errors within 20%, which confirmed their effectiveness and accuracy.Results and DiscussionsIn terms of mechanical properties, fiber bridging effectively inhibited crack development and dispersed the applied loads. The incorporation of basalt fibers (BF) and polypropylene fibers (PF) into the concrete resulted in a more pronounced improvement in splitting tensile strength, with splitting tensile strength and flexural strength increasing by 12.43%～18.65% and 5.36%～9.64%, respectively. BF restricted the initiation and propagation of microcracks, while PF primarily limited the expansion of macrocracks after their formation, demonstrating a positive synergistic effect of PF+BF. An analysis of the specimens' appearance after corrosion indicated that corrosion products accumulated between the steel reinforcement and the concrete. As corrosion advanced, rust-induced swelling cracks formed on the concrete surface, accompanied by the overflow of reddish-brown rust products. The incorporation of fibers modified the concrete's porosity and permeability, and factors such as corrosion discretization caused actual corrosion rates to be lower than theoretical values. Due to the bridging effect of fibers and the lateral confinement provided by stirrups, all specimens failed in splitting pull-out. FRC specimens exhibited finer and fewer cracks than normal concrete (NC) specimens. Primary cracks extended toward the concrete side and, as the load increased, developed into longitudinal through-cracks parallel to the steel reinforcement, ultimately leading to the ductile failure of the specimens. Bond strength degraded significantly with increasing corrosion rates in terms of bond performance. When the corrosion rate reached approximately 5%, the bond strength of BPFRC decreased to 87% of that of the non-corroded specimens. When steel mass loss ranged between 6% and 7%, the bond strength of NC decreased by an average of 18.1%. Under corrosive conditions, the bond strength of FRC increased by 11.1%～27.6% compared to NC, with BPFRC exhibiting improvements of 19.9%～27.6%, which was 5.2%～11.8% higher than that of specimens with single PF or BF additions, indicating a positive synergistic effect. In addition, FRC demonstrated higher initial and secant bond stiffness. At an average corrosion rate of 1.65%, the accumulation of corrosion products increased the friction between the steel reinforcement and the concrete, which resulted in an increase in the initial bond stiffness of BPFRC, PFRC, and BFRC by 4.2%, 5.2%, and 8.0%, respectively. However, as corrosion progressed, cracking of the protective layer significantly reduced concrete confinement and interface friction. At a corrosion rate of 6.56%, the secant bond stiffness of BPFRC and NC decreased by 43.3% and 39.0%, respectively, while the initial bond stiffness was less affected, decreasing by 5.0%～11.8%. Under the same lateral confinement conditions, FRC exhibited a more gradual decline and higher residual bond strength compared to NC. Fiber incorporation effectively delayed specimen failure, absorbed part of the energy, and provided additional structural support. No consistent patterns were identified in the changes of slip amounts among different FRCs and NC under identical corrosion conditions, where an initial increase was followed by a decrease. This behavior was partly influenced by concrete cracking but remained relatively stable.ConclusionsThe experimental results confirm that corrosion damage is a critical factor influencing the bond performance between steel reinforcement and concrete. As the corrosion rate increases, bond degradation becomes more severe. Fiber-reinforced concrete, compared to normal concrete, demonstrates improvements in both fundamental mechanical properties and bond performance after corrosion damage. Appropriate fiber additions mitigate initial defects in the concrete and effectively suppress crack propagation. A bond strength prediction formula and a constitutive relationship for fiber-reinforced concrete under corrosion influence were established. This research provides data support for evaluating the performance of BF-PF reinforced concrete and provides a theoretical basis for practical engineering applications.关键词：fiber reinforced concrete;corrosion;mechanical properties;bond‒slip;constitutive model141|238|0更新时间：2026-01-25 -
Experimental Study and Parameter Analysis on the Mechanical Performance of Flush End-plate Joints AI导读
“在建筑结构领域，研究了端板厚度小于规范构造要求的钢框架平齐端板节点力学性能，通过拟静力试验和有限元分析，揭示了端板厚度、柱翼缘厚度和螺栓直径对节点性能的影响，为提高钢框架节点性能提供参考。”摘要：ObjectiveMany numerical simulations and tests were performed to study and investigate the failure modes, ultimate flexural capacity, hysteretic performance, energy dissipation capacity, ductility coefficient, and neutral axis position of beam sections in flush end-plate connections under quasi-static loading. However, there is no unified minimum thickness requirement for end-plates in the design of flush end-plate connections. Only the GB51022 and CECS260 codes explicitly state that the end-plate thickness must not be less than 16 mm or 0.8 times the bolt diameter. Although these end-plates satisfy the design requirements for the flexural capacity of the connection, the absence of standardization results in the design of some connections with thicker end-plates, causing a certain degree of resource waste. Therefore, it is necessary to investigate the minimum thickness of end-plates.MethodsThis study examined the failure modes, ultimate flexural capacity, hysteretic performance, energy dissipation capacity, ductility coefficient, and neutral axis position of beam sections of flush end-plates through numerical simulation and experimental testing to investigate the mechanical properties of flush end-plate joints in steel frames when the end-plate thickness was less than the design requirements specified by codes. In the first stage, six flush end-plate connection specimens were designed and fabricated. These specimens were subjected to quasi-static loading. In the second stage, numerical simulations of the quasi-static tests on the six specimens were conducted, and the results were compared to the test data to validate the accuracy of the developed numerical model. Based on the validated model, a parametric element analysis was conducted to assess the effects of varying end-plate thickness, column flange thickness, and bolt diameter on the flexural capacity, initial rotational stiffness, and ductility coefficient of the connections. Therefore, a design recommendation was proposed, stating that the minimum thickness of end-plates must not be less than 12 mm.Results and DiscussionsThe failure modes of the flush end-plate connection specimens primarily included end-plate warping, column flange buckling, and bolt failure. Specifically, specimens JD‒1 and JD‒2 failed due to end-plate warping at both ends, JD‒3 exhibited end-plate yielding accompanied by bolt bending, JD‒4 showed column flange buckling, while JD‒5 and JD‒6 experienced bolt failure. The hysteresis curves of the connections demonstrated a pronounced pinching effect. Connections that utilized six high-strength bolts (M14 or M16) with proper arrangement achieved greater ultimate flexural capacity, initial rotational stiffness, and energy dissipation capacity compared to connections that utilized four M20 high-strength bolts. However, the rotational capacity and ductility of the connections with six smaller bolts were lower than those with four M20 bolts. Based on the European EC3 code, all tested joints were classified as semi-rigid connections. A comparison between the experimentally determined ultimate flexural capacity of the connections and the values calculated using the CECS260 and EC3 codes revealed that, except for the forward loading test of JD‒6, which closely matched the EC3 calculated value, all other specimens exhibited ultimate flexural capacities that exceeded the calculated values, indicating a safety margin in both codes. The values calculated using the CECS260 code were 0.68 to 0.98 times those of the EC3 code, indicating that the CECS260 code provided a higher safety margin. Strain measurements of the beam sections showed that the neutral axis positions did not align with those predicted by the CECS260 and EC3 codes but instead lay between the compression flange and the nearest bolt. Hence, the actual lever arm of the connection was smaller than the design lever arm. Strain measurements of the end-plates and bolts indicated that increasing the thickness of the end-plates and column flanges or using six smaller-diameter bolts generated greater prying forces on the bolts under the same lateral displacement loading, which prevented deformation of the connection components. When the bolt diameter was small, the tensile forces caused by end-plate deformation exceeded the prying forces generated by the bolts, leading to bolt failure. Finite element analysis using ABAQUS was conducted to simulate the quasi-static tests on the six flush end-plate connection specimens. The numerical simulation results showed strong agreement with the experimental results, confirming that numerical simulation was a reliable method for conducting parametric analysis of flush end-plate connections. The initial rotational stiffness and ultimate flexural capacity of the connections increase with the thickness of the end-plates, while ductility first increases and then decreases, reaching its maximum at an end-plate thickness of 12 mm. These findings indicated that increasing end-plate thickness improves the flexural capacity of the connection but adversely affects its rotational capacity and ductility. Based on both experimental and numerical results, it is recommended that the minimum thickness of flush end-plates must not be less than 12 mm. The initial rotational stiffness, ultimate flexural capacity, and ductility coefficient of the connections also increase with the thickness of the column flanges. When the column flange thickness is small, the flexural capacity of the connection is governed by the column flange. As the column flange thickness increases, the governing component of the flexural capacity shifts to the end-plate, which allows other connection components to undergo full deformation, enhancing the initial rotational stiffness, ultimate flexural capacity, and ductility coefficient of the connections. When the bolt diameter was small, the initial rotational stiffness, ultimate flexural capacity, and ductility coefficient increased with the bolt diameter. However, once the bolt diameter reached a specific size (M24 in this study), the rotational stiffness and ultimate flexural capacity were no longer influenced by bolt diameter, and the ductility coefficient showed a decreasing trend.ConclusionsThe results indicate that when the end-plate thickness is less than the design requirements specified by the GB51022 and CECS260 codes, the ultimate flexural capacity of the joint increases by 3.71% for every 2 mm increase in thickness. When the bolt diameter is smaller than M24, the ductility coefficient of the joint increases by 36.66% for every 2 mm increase in diameter, and the ductility coefficient reaches its maximum value when the diameter is M24.关键词：flush end-plate joint;mechanical property;quasi-static test;finite element method;end-plate thickness141|603|0更新时间：2026-01-25 - “在结构健康监测领域，专家提出了复刻FBG型七芯光纤多参量同步监测系统，实现了多种参量同步采集，为多芯光纤应用提供新思路。”摘要：ObjectiveOptical fiber sensing systems have gradually became important components of structural health monitoring systems (SHM). A multi-parameter synchronous monitoring technology based on engraved FBG seven-core fiber is proposed, which effectively integrates Raman optical time-domain reflectometry (ROTDR), fiber Bragg grating (FBG), and Brillouin optical time-domain analysis (BOTDA) into one seven-core fiber to address the difficulty of achieving multi-parameter synchronous acquisition with a single-core sensing fiber. The ROTDR sensing core monitors distributed temperature, the FBG sensing core measures point strain, temperature, and vibration frequency simultaneously, and the BOTDA sensing cores perform distributed strain data acquisition.MethodsFirstly, the space division multiplexing mechanism of multi-core fiber was thoroughly analyzed. The cross-sectional layout of the seven-core fiber and the composition of the seven-core fiber multi-parameter monitoring system were introduced, and the cores were numbered. The strain, temperature, and natural frequency of the structure were synchronously collected using four cores of the seven-core fiber, considering the symmetry of the cores and the sensitivity of the sensing technology to temperature and strain. Among them, core 7 in the central position was employed to sense the point strain and temperature through FBG sensing technology, while cores 1 and 4 in symmetrical positions were utilized to monitor distributed strain through BOTDA sensing technology. At the same time, core 2 was utilized to measure distributed temperature through ROTDR sensing technology. In addition, the strain measurements of BOTDA and FBG were susceptible to fluctuations in ambient temperature and the shear lag effect of strain transfer layers. The influence of the shear lag effect of strain transfer layers on BOTDA and FBG strain was investigated by finite element analysis and strain transfer experiments. Theoretical analysis and sensitivity coefficient calibration experiments were conducted to analyze the influence of ambient temperature fluctuations on strain measurement values. The strain correction formula that considered temperature compensation and strain transfer rate was established. Finally, the multi-parameter synchronous monitoring experiment of a full-scale steel beam was conducted to test the multi-parameter synchronous sensing performance of the engraved FBG seven-core fiber and the effectiveness of the strain correction formula. The multi-parameter monitoring experiment included two parts: a static graded loading experiment and a free attenuation vibration experiment, which were conducted to verify the static and dynamic working performance of the engraved FBG seven-core fiber, respectively. Before the experiment, the ABAQUS finite element model was established to guide the procedure. The length of the steel beam specimen was 12 m, which met the requirements of BOTDA spatial resolution. During the test, the strain values were collected by strain flower, FBG, and BOTDA. At the same time, the temperature values were monitored by a high-precision thermometer, FBG, and ROTDR. In addition, the natural frequency of the specimen was collected by the accelerometer and FBG. All the measured values of the optical fiber sensing technologies were compared to the measured values of the traditional sensors.Results and DiscussionsThe results showed that the shear deformation hysteresis effect of the strain transfer layers and the fluctuation of ambient temperature led to errors in strain measurement. The strain sensitivity coefficients of FBG and BOTDA were 1.2 pm/10-6 and 0.044 MHz/10-6, respectively. The temperature sensitivity coefficients of FBG and BOTDA were 19 pm/°C and 1 MHz/°C, respectively. Therefore, a temperature fluctuation of 1 °C caused strain errors of 23×10-6 in BOTDA and 16×10-6 in FBG. The stable strain transfer rates of finite element analysis and experiments were 85% and 89%, respectively, which were independent of strain magnitude. The shear deformation hysteresis effect caused the strain measurement values to decrease by 11% to 15%. The shear deformation hysteresis effect of the strain transfer layers and the fluctuation of ambient temperature have a significant influence on the strain measurement results, which cannot be ignored. It was necessary to establish a strain correction formula to improve the accuracy of strain measurement. In addition, the monitoring values of the multi-parameter synchronous monitoring system based on the engraved FBG seven-core fiber were consistent with those of the traditional sensors. The temperature measurement errors of ROTDR and FBG were 0.36 °C and -0.04 °C, respectively. After correction by the strain correction formula using FBG temperature measurement values, the BOTDA strain measurement error was -15×10-6, while the FBG strain measurement error was -0.4×10-6. Compared to the pre-strain correction, the strain accuracy was improved by 12% and 98%, respectively. It was important to note that when the ROTDR temperature measurement values were utilized to correct the strain, the strain error was not reduced, because the ROTDR strain measurement accuracy was poor, and excessive temperature compensation was introduced. The natural frequency of the specimen measured by FBG was 2.18 Hz, which was consistent with 2.19 Hz measured by the accelerometer.ConclusionsThe multi-parameter monitoring technology based on engraved FBG seven-core fiber achieved the synchronous acquisition of multiple parameters. This technology combined the advantages of point strain, distributed strain, and temperature compensation, without affecting the performance of each sensing technology. In addition, the strain correction formula effectively improved the accuracy of strain measurement. Finally, reasonable suggestions were proposed for the application of engraved FBG seven-core fiber in practical engineering, and future research directions were identified to further optimize the multi-parameter synchronous monitoring system based on engraved FBG seven-core fiber. The study provides new insights into the application of multi-core fiber in structural health monitoring.关键词：multi-core fiber;fiber bragg grating;temperature compensation;strain transmission;space division multiplexing144|377|0更新时间：2026-01-25
CIVIL ENGINEERING
- “在机器人自主抓取领域，研究人员提出了一种新的6D位姿检测方法，有效提高了识别效率和精度，为机器人精准抓取提供了有力保障。”摘要：Objective6D pose detection is a key technology for enabling autonomous grasping in robots. Currently, traditional point‒pair feature (PPF) methods face three major challenges: 1) excessive sensitivity to sensor noise, severe occlusions, and background clutter; 2) reduced matching performance when the workpiece has numerous repetitive features; 3) slow recognition speed due to the need to search many point pairs and compute transformation relationships. This study proposes a point-pair feature-based 6D pose detection method designed for robotic sorting system grasping tasks.MethodsFirstly, multi-plane feature workpieces were screened based on distributions of model plane points, and their boundary features were extracted for 6D pose detection. Model point pairs were extracted from multi-view points to remove redundant point pairs and improve the recognition speed of algorithms. Secondly, to further enhance recognition speed, a method was employed to extract model point pairs from multiple viewpoints, which helped in eliminating redundant point pairs that did not contribute to the detection process. Thirdly, the point-to-point characteristics between scenes and models were matched, and a fast voting scheme was employed to obtain pose hypothesis sets for targets in a disordered scene. Then, a pose verification and screening method was introduced to eliminate duplicate and mismatched poses, which was essential for realizing a rough estimation of multi-instance poses for the targeted workpieces. Finally, an algorithm called Iterative Closest Points (ICPs) was utilized to refine the rough estimates and achieve a more accurate estimation of the targeted poses.Results and DiscussionsExperimental results showed that in the context of disordered simulation scenes, the proposed method demonstrated a single recognition time of
- “在机械设计领域，专家利用几何综合方法，建立了空间曲柄摇杆机构极限位置综合的几何流程，为解决机构尺度确定问题提供解决方案。”摘要：ObjectiveThis study presents a geometric synthesis method to address the dimensional synthesis problems of spatial crank-rocker mechanisms (Revolute-Sphere-Sphere-Revolute mechanisms, i.e., RSSR mechanisms) based on the limit position angle and the limit position of the rocker. It improves the intuitiveness and transparency of the synthesis process.MethodsThe research started from the spatial kinematic geometry rules of a line with two positions. The movement form of a fixed point on a line was investigated.
- “在大型铸锻件表面打磨领域，专家提出了一种新型机器人系统平台，有效解决了传统打磨机器人占地面积大、灵活性差等问题，为大型铸锻件表面打磨提供了新方案。”摘要：ObjectiveThe demand for automated surface grinding of large castings and forgings continues to increase with production scale and quality requirements. Conventional grinding robot systems, while functional, present significant limitations: large spatial footprint, poor adaptability to diverse workpiece sizes and shapes, and high investment and maintenance costs. These constraints hinder their application in space- and cost-sensitive manufacturing. Therefore, this research introduces a truss-based hybrid grinding robot system that combines a wide operational reach with a compact layout, ensures high stiffness at the grinding head for precision, and adapts to varied workpiece sizes and complex geometries. The study presents an innovative structural configuration, a complete theoretical framework, and simulation-based validation, making contributions to industrial robotic grinding.MethodsThe design process started with functional decomposition, including omnidirectional mobility, an extendable and retractable structure for large workpieces, a high-reach manipulator for complex positioning, and a grinding end-effector that maintained constant contact force over varying surfaces. The system integrated: 1) an omnidirectional mobile platform that allowed free movement without reorientation constraints; 2) a truss-type folding structure that provided a deployable framework expanding the workspace while minimizing the idle footprint; 3) a serial robotic arm that offered large reach and positioning flexibility; and 4) a parallel adaptive grinding head, a passive parallel mechanism with pneumatic damping that ensured constant-force compliance and high stiffness. The serial arm and parallel head were modeled as an equivalent eight-DOF hybrid mechanism, combining the stiffness and load capacity of parallel kinematics with the reach of serial designs. Forward and inverse kinematics were developed using the Denavit‒Hartenberg (D‒H) method to map joint space to Cartesian space. The workspace of the system and the single-arm grinding range were analyzed to define operational limits and optimal deployment. The passive parallel head was modeled separately using the vector method to assess the workspace under fixed arm postures, which enabled optimization of adaptability without affecting positioning. For constant-force grinding, mechanical and pneumatic conditions for adaptive drive joint adjustment under varying end-loads were examined. Pneumatic damping was optimized so that variations on the constant-pressure side yielded stable trends on the floating side, ensuring surface-contact stability. For energy efficiency, the hybrid arm's kinematic model derived joint velocities and accelerations during grinding tasks. An energy consumption function was formulated with total arm power as the optimization objective. Case studies of linear grinding evaluated power patterns. Finally, the design and models were validated through an ADAMS virtual prototype that simulated realistic motions to verify kinematics, workspace, constant-force behavior, and energy use.Results and DiscussionsWorkspace analysis confirmed that the truss-folding structure greatly extended the operational range without a proportional increase in footprint, enabling grinding of large and irregular workpieces. For single-arm operation, the reachable range was quantified, supporting task allocation in dual-arm setups. The passive parallel head maintained stable floating-end pressure under constant-force control, validating pneumatic optimization and ensuring consistent surface contact for uniform removal and finish. Simulations confirmed the kinematic accuracy of the serial and parallel subsystems, with minimal deviation between theoretical and simulated outcomes. The hybrid model achieved the intended stiffness and reach. Energy analysis demonstrated that spiral grinding trajectories consumed more power than serpentine paths in straight-line grinding, which highlighted the impact of trajectory on energy usage and provided guidance for task planning. The omnidirectional base enabled rapid repositioning between zones, reducing idle time and improving coverage. The truss-folding design enhanced adaptability when shifting between large flats and contoured areas without requiring full disassembly or repositioning.ConclusionsThe truss-based hybrid grinding robot integrates the advantages of parallel and serial configurations, delivering high stiffness and wide coverage. The folding truss design accommodates large workpieces while maintaining a compact footprint when not in operation. Complete kinematic, workspace, energy, and pneumatic control models were validated through simulation. The system adapts to varying sizes and shapes while ensuring precision and surface quality. In addition, the modeling framework is transferable to other hybrid robotic designs. In practice, this approach enhances productivity, reduces labor demands, and improves quality consistency in large-scale surface finishing. Key innovations include the following: eight-DOF hybrid mechanism modeling of a passive parallel head and serial arm as a unified analytical framework; pneumatic damping optimization for stable floating-end pressure under varying inputs, advancing constant-force compliance in grinding; integration of truss-folding structures into mobile robots to achieve large workspaces with minimal idle footprint; and trajectory-dependent energy consumption analysis that informs energy-efficient path planning. The research contributes both a practical robotic design and analytical tools applicable to various automated manufacturing processes involving large and complex workpieces.关键词：Large castings and forgings;Polishing robot;kinematic analysis;adaptive control;trajectory optimization294|957|0更新时间：2026-01-25
MECHANICAL ENGINEERING
- “在无线传感器网络节点定位领域，专家提出了融合测距修正和蜘蛛蜂优化的DV-Hop算法，有效降低了定位误差，提高了算法精度。”摘要：ObjectiveIn the context of node localization in wireless sensor networks (WSNs), the non-range-based DV‒Hop algorithm exhibits significant localization errors due to inaccuracies in hop count estimation and the neglect of actual node distances. This study proposes a modified DV‒Hop algorithm that incorporates distance correction and a spider wasp optimization (SWO) algorithm to address these limitations. The objective is to improve the accuracy of node localization and enhance the overall performance of the DV‒Hop algorithm, making it more reliable in practical deployment scenarios.MethodsThe proposed algorithm comprised two main components: distance correction and optimization using SWO. First, the traditional hop count calculation was improved by adopting the Jaccard coefficient as the metric to enhance the accuracy of hop count estimation. The Jaccard coefficient, a well-established similarity measure, ensured that the hop count reflected a more accurate estimate of the network's topology. After acquiring the hop count information, a credibility calculation was introduced to adjust the hop distances, enabling a more accurate representation of the actual distances between nodes.SWO was incorporated to refine the node position calculation and improve the precision of the DV‒Hop algorithm. The initialization of the SWO population was enhanced by a chaos mapping-based reverse learning strategy, which ensured that the population was more uniformly distributed across the search space. During the position update process, adaptive weighting was applied to optimize the convergence speed. Following the mating operation, Cauchy‒Gaussian mutation disturbance was introduced to the positions of the best individuals in the Spider Wasp swarm to prevent premature convergence to local optima.Results and DiscussionsThe proposed algorithm significantly outperformed the conventional DV‒Hop algorithm and other related methods in terms of localization accuracy and energy efficiency. The use of the Jaccard coefficient for hop count estimation improved the precision of distance calculation, while the credibility adjustment further enhanced the accuracy of node localization. The integration of SWO, with its improved population initialization and adaptive weighting mechanism, contributed to faster convergence and more precise localization results.In the simulation experiments, the proposed algorithm reduced the localization error by 30.0%, 33.0%, 37.2%, 38.9%, and 45.9%, respectively, compared to the traditional DV‒Hop localization algorithm under five different conditions: varying area size, region shape, number of anchor nodes, communication radius, and total number of nodes. At the same time, the algorithm's running time improved by 0.73 seconds. The incorporation of the chaos mapping strategy in the SWO initialization phase helped achieve a more evenly distributed population, reducing the risk of suboptimal solutions. The introduction of Cauchy‒Gaussian mutation after the mating operation prevented the algorithm from becoming trapped in local optima, ensuring better exploration of the solution space.ConclusionsThis study presents a novel hybrid localization algorithm that combines distance correction with spider SWO to enhance the DV‒Hop algorithm. The integration of the Jaccard coefficient to improve hop count accuracy, combined with the application of SWO using chaos mapping-based initialization, adaptive weighting, and Cauchy‒Gaussian mutation, significantly enhances localization precision and energy efficiency. The proposed algorithm exhibits robustness to environmental variations and network dynamics, establishing its effectiveness for real-world wireless sensor network localization tasks. The findings indicate that the algorithm provides a promising solution for increasing the accuracy and reliability of node localization in large-scale WSNs.关键词：wireless sensor network;DV‒Hop algorithm;Range Correction;localization accuracy;spider wasp optimization algorithm97|415|0更新时间：2026-01-25
- “在计算机视觉领域，研究者提出了一种新的端到端粗精网络场景图生成方法，有效提升了模型对视觉场景的理解与推理能力。”摘要：ObjectiveScene graph generation is a critical task in computer vision, enabling a comprehensive and deep understanding of visual scenes. It focuses on identifying entities and the relationships between them, ultimately requiring the model to output a series of triplets (subject-predicate-object) and a graph-structured scene representation. This places greater demands on the model's understanding and reasoning capabilities. Although existing scene graph generation methods have achieved substantial success, most models are hindered by either an excessive number of parameters or inaccurate predicate judgments. This study proposes an end-to-end rough-and-refine model (RRM) for scene graph generation to overcome these challenges.MethodsThe end-to-end rough-and-refine network model proposed in this study for scene graph generation consisted of two components: the rough part and the refine part, which were responsible for predicting and updating entities and their relationships, respectively. In the rough part, image features were initially extracted using convolutional neural networks and a Transformer encoder. These features were then input alongside entity queries into the entity decoder for self-attention computation, resulting in preliminary entity representations. In addition, a predicate decoder was designed to follow the entity decoder and generate predictions for predicates. Predicting relationships between entities requires considering both entity information and image feature information comprehensively. Therefore, the predicate decoder took image features, entity representations, and predicate queries as inputs. Specifically, entity representations were integrated into the predicate queries, followed by further attention computations in the predicate decoder to obtain predicate representations. Through the rough part, the system gained a preliminary perception and predictive capability regarding the scene. However, due to a lack of information interaction between entities, this stage struggled to excavate deeper semantic information. In addition, ambiguity remained in distinguishing between subjects and objects, necessitating the design of the refine part to enhance performance. In the refine part, a triplet query generation module was first established to support subsequent calculations for triplet prediction. Since a triplet required the prediction of three distinct types of information, subject, object, and predicate, three paths were designed: the subject path, object path, and predicate path. In each path, the model incorporated image features, entity representations, and relationship representations derived from the rough part, utilizing cross-attention computations to integrate different information. In addition, the predictions for subjects and objects were fused with the predicate information to enhance the representational capacity of the predicate component. This design allowed the model to more thoroughly consider the states of entity pairs during relationship prediction, fostering a deeper understanding of the interactions between subjects and objects. After the model completed the representation of triplets, it was required to produce specific prediction results. The subject and object needed to predict their categories along with location information represented by bounding boxes, which included normalized center coordinates (x, y) and the dimensions of the bounding boxes (length and width). In contrast, the predicate only required the prediction of its category. Predictions for the different paths of the triplet were independently executed using feedforward neural networks. Each feedforward neural network consisted of two perceptrons with ReLU activation functions and a linear projection layer, facilitating both category classification and bounding box regression.Results and DiscussionsSeveral commonly used metrics in this research domain were employed, including Recall@K (R@K) and Mean Recall@K (mR@K) to evaluate the performance of RRM in the scene graph generation task. R@K reflected the overall recall rate of the model on the dataset, measuring whether the top-k predicted triplets can be found among the true labeled triplets. In contrast, the mR@K metric calculated an R@K for each predicate category and then computed the average. This evaluation metric placed greater emphasis on the model's ability to learn low-frequency predicate categories within the dataset, ensuring that infrequent predicates received equal importance as frequent ones. This was particularly critical in addressing the long-tail distribution problem present in the dataset, as it demonstrated the model's learning capability across all predicate categories. The proposed method, RRM, achieved superior R@K results among single-stage methods, outperforming other single-stage approaches in the R@20, R@50, and R@100 metrics. Specifically, the RRM model achieved R@20 = 23.8, R@50 = 29.1, and R@100 = 32.5, which were higher than the optimal values of other single-stage methods by 2.6, 1.6, and 2.4, respectively. The mR@K metrics exceeded those of FCSGG, HOTR, RelTR, and most two-stage methods, reaching mR@20 = 7.7, mR@50 = 11.0, and mR@100 = 12.4. In a vertical comparison, the model significantly outperformed FCSGG and HOTR, and also demonstrated better performance across the six evaluation metrics, R@K and mR@K, compared to RelTR, although RelTR has a smaller parameter count. When comparing SGTR and SGTR+, the model performed better in terms of R@K, mR@20, and parameter count, while SGTR and SGTR+ exhibited better results in mR@50 and mR@100. In ablation experiments, the results indicated that each module made a positive contribution to the prediction of scene graphs, with the removal of any single module leading to a decline in the experimental results. The FMI and EMI modules have a significant impact on the model; removing either FMI or EMI resulted in an average decrease of 11.7% and 8.9%, respectively, as these modules introduced crucial scene information. The TQG and EPR modules also provided measurable improvement, with average decreases of 4.7% and 5.2% when removed. The model represented in the first row of the table, which excluded all four modules, was equivalent to the rough part, showing an average decrease of 24.9%.ConclusionsA scene graph generation method based on a rough-and-refine network is proposed to address the challenge of inadequate predicate representation. Experimental results demonstrate that the proposed network model achieves strong performance on public datasets, surpassing existing models across several key evaluation metrics and enabling the accurate extraction of information from images to scene graphs. Visualization experiments conducted in diverse scenarios confirm the model's capability in scene graph generation and highlight the performance improvements provided by the refine model over the rough model.关键词：scene graph generation;computer vision;artificial intelligence;visual relationship detection226|241|0更新时间：2026-01-25
- “工业控制协议操作字段识别技术取得新进展，专家提出基于稳态属性的识别方法，有效提高识别率和通用性。”摘要：The operation fields in industrial control protocols play a critical role in recognizing industrial control network behavior, understanding and monitoring network activities, and accurately identifying and extracting operation fields from industrial control network traffic. However, current methods for operation field recognition often rely on expert experience or manual analysis based on program execution, resulting in low efficiency, limited generalizability, and an inability to handle many undisclosed proprietary protocols or automatically recognize operation fields in complex network scenarios with unknown contexts and protocols. Therefore, this study uses the unique domain characteristics of industrial control networks and proposes an operational field recognition method based on the steady-state properties of industrial control protocols, overcoming the limitations imposed by protocols and programs. First, by preprocessing industrial control network session data, such as session reconstruction and fragmented packet reassembly, the value sequences of various fields at the application layer of the data packets are extracted. Then, through analysis of the stability, periodicity, and correlation of these value sequences, operation fields exhibit steady-state properties characterized by stability, high periodicity, and high correlation. These steady-state properties are quantified as features of operation fields. Next, an unsupervised clustering method is employed to effectively distinguish operation fields from other fields, ultimately achieving automatic recognition of operation fields. The proposed method demonstrates significant value in industrial control protocol security testing, regulating industrial control behavior, and anomaly detection in industrial control systems. For example, by utilizing the recognition results of operation fields, it becomes possible to construct and generate effective fuzzy testing data to enhance the security of industrial control systems. Through extensive validation in various industrial control system environments, including power grids, water treatment experimental platforms, and real industrial control traffic data, the method achieves a recognition rate of over 90% for operation fields, demonstrating its effectiveness and generalizability. In addition, in the experimental section, the influence of data size and quality on the method is discussed in detail. The proposed method accomplishes the recognition task with relatively small amounts of data but requires high-quality traffic data with minimal artificial operations or noise in the industrial control system traffic. Therefore, in practical applications, it is important to ensure the accuracy and purity of industrial control system traffic data. In conclusion, the operation field recognition method based on the steady-state properties of industrial control protocols rapidly and accurately identifies operation fields by analyzing features such as stability, periodicity, and correlation, without relying on specific protocol specifications or source code analysis. The method provides essential technical support for industrial control network security monitoring and behavior analysis, while also providing new possibilities for intelligent control and management of industrial control systems.关键词：industrial control protocols;operation fields;steady-state properties;field recognition159|295|0更新时间：2026-01-25
COMPUTER SCIENCE AND TECHNOLOGY
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