最新刊期
卷 56 ， 期 4 ， 2024
- “全球气候变暖导致山丘区极端降雨事件多发，中国山洪灾害研究取得显著成效。专家采用多学科知识，系统探究中国重灾省区重大山洪灾害事件的强降水时空演变规律，为山洪灾害防治提供解决方案。”摘要：Global warming has led to frequent extreme rainfall events in hilly areas, with rainfall intensity and magnitude constantly breaking regional historical records. Simultaneously, the fragile environment and intense human activities in these areas exacerbate the formation and evolution of flash floods, complicating the situation and increasing casualties and property losses. Flash flood disasters have significant natural and social attributes, resulting from the complex interaction of environmental factors in hilly areas. The local climate in the mountainous regions of our country is unique, characterized by diverse geological and geomorphic types, complex river systems, and prominent human activities. Numerous major flash flood events have demonstrated that the processes and characteristics of flash floods induced by extreme rainfall vary significantly, posing substantial challenges for prediction, warning, and defense. Research on flash floods remains a critical and difficult aspect of natural disaster prevention and control. Historically, flash flood research in China has focused on the spatiotemporal changes of rainfall and the inundation characteristics of water floods. This research has led to the calculation of critical rainfall/water level thresholds for flood disaster prevention and control, yielding significant practical results and reducing the overall number of casualties from water flood disasters. However, in mountainous areas, the formation and evolution of flash floods are influenced by multiple factors, including rainfall characteristics, surface composition, river morphology, and human activities. These floods often carry large amounts of sediment, manifesting as water floods, water-sediment floods, and debris floods. The causes and thresholds for local erosion, siltation, and inundation differ fundamentally between water-sediment and debris floods compared to water floods, contributing to the frequent occurrence of major flash flood disasters in China in recent years. To address the challenges of disaster prevention caused by extreme rainfall and human activities, a combination of field investigation, physical experiments, numerical simulation, and theoretical analysis is adopted. Utilizing interdisciplinary knowledge from meteorology, hydrology, and river dynamics, research has expanded from the traditional study of water floods to include all types of flash floods, such as water-sediment and debris floods. This research aims to understand the composite disasters caused by these floods, including erosion, sedimentation, and inundation. We will systematically explore the spatiotemporal evolution of heavy precipitation in major flash flood-prone provinces and regions of China, analyze the formation and evolution of multiple types of flash floods under extreme rainfall and strong human activities, and reveal the disaster mechanisms associated with meteorological, hydrological, and river responses. This involves establishing simulation methods for meteorological, hydrological, and sediment dynamic processes, identifying the risks of flash flood erosion, deposition, and inundation in mountainous areas, and developing methods to identify prone areas for different types of flash floods. Additionally, we aim to construct a multi-index early warning and defense method for zoning and grading water floods, water-sediment floods, and debris floods. This study is expected to enhance the theoretical and technical research on flash flood disasters in China and improve strategies for their prevention and control.关键词：mountainous watershed;Extreme rainfall;intense human activities;Flash flood disasters;disaster causes
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发布时间：2024-11-15
SCIENTIFIC FRONTIERS
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Research Progress in the Application of MOFs Coupled Wood Composites in Environmental Remediation AI导读
“在绿色发展理念推动下，研究人员探索了以纳米材料为核心的环境纳米技术，特别是金属有机骨架材料（MOFs）与木材的耦合策略，为环境修复领域提供了新视角。”摘要：In light of the national advocacy that “green waters and green mountains are golden mountains and silver mountains,” developing advanced, recyclable pollutant removal technologies that are efficient, cost-effective, and pollution-free has become crucial. Traditional technologies such as activated carbon adsorption, advanced oxidation, and membrane separation remain prevalent due to their low cost. However, these methods often suffer from low efficiency, high energy consumption, and secondary pollution issues. Environmental nanotechnology, centered on nanomaterials (including adsorption, catalysis, and membrane separation), has attracted significant attention for its high efficiency and functional diversity. Metal-organic frameworks (MOFs), multifunctional crystalline materials composed of metal ions and organic ligands, exhibit structures ranging from one-dimensional to three-dimensional. As an emerging class of porous materials, MOFs offer promising applications in environmental remediation due to their ordered pores, rich structures, and extensive surface area. However, the crystal structure of MOFs typically results in a powdered form that is inherently fragile, unsuitable for processing, and low compatibility. These limitations hinder their recycling, processing, and molding, severely restricting their practical application. Biomass materials have attracted great interest globally due to their diversity, low cost, and inherent high porosity. Wood, one of the most common and abundant biomass materials, features a natural multidimensional pore structure, abundant hydroxyl/carboxyl groups, and good processability, making it an ideal substrate for immobilizing powdered MOFs. In recent years, scholars have used its intrinsic structure and characteristics to introduce functional nanoparticles or heterogeneous catalysts and other active components to build a new structural system with MOFs as a novel carrier, which has emerged as a current research focus and is progressively being applied in the development of biomass and its derivatives-based composites such as wood, cellulose, gel, and in the catalytic conversion of biomass. The expanding foundational research demonstrates considerable potential for application. Accordingly, this study comprehensively introduces the coupling strategies between MOFs and wood, such as mixed immersion, vacuum immersion, solvothermal, and in situ growth methods. In addition, the mechanisms of MOFs loading onto wood to a couple of MOF/wood composite materials, such as physical adsorption, the wetting mechanism, capillary phenomenon, self-growth pressure, and nucleation sites, are revealed. The study also summarizes the representative achievements in the application research of MOF materials in biomass and its derived chemicals. Based on this, the current application status of these MOF/wood composites in environmental remediation fields such as gas phase adsorption, heavy metal ion removal, harmful particle filtration, and advanced oxidation is discussed, and the correlation between the microstructure design of MOFs and the macroscopic performance of the composite materials is clarified. Finally, the opportunities and challenges faced in developing MOF/wood composite materials are explored. This review provides a new perspective on the design and construction of MOF-based composite materials for practical environmental applications, which is anticipated to enhance their application in environmental remediation.关键词：Metal-organic frameworks (MOFs);Wood;Environmental remediation;Water treatment- 903
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发布时间：2024-11-15 - “最新研究利用太湖蓝藻制备生物炭，开发出高效电化学系统，成功去除水中抗生素SMX，为水处理技术提供新思路。”摘要：Following the concept of “treating waste using waste”, this study uses cyanobacteria in the Tai Lake after mechanical salvage as raw materials to prepare environmentally friendly cyanobacteria-based biochar through high temperature, oxygen-limited pyrolysis, and acid/alkali treatment. The obtained biochar is then utilized as particle electrodes in a three-dimensional electrochemical system (3DES) to remove the typical antibiotic sulfamethoxazole (SMX) from water. After pyrolysis and acid/alkali treatment, the biochar exhibits a larger specific surface area and a more abundant pore structure, which enhances the enrichment of SMX on the surface of particle electrodes. The original iron and nitrogen elements in cyanobacteria form a doping structure in the resulting biochar, significantly enhancing the generation of reactive oxygen species and improving the removal and mineralization efficiencies of SMX. The optimized biochar is prepared at a pyrolysis temperature of 700 ℃ and subsequently modified using alkali. The optimized operational conditions of 3DES involve a current of 600 mA, a pH of 6, a particle electrode dosage of 1.00 g/L, a water flow rate of 300 mL/min, and an electrolyte Na2SO4 concentration of 50 mm. The removal efficiency for SMX can exceed 96% within 120 min, and the total organic carbon (TOC) removal efficiency can reach 94% after 6 h. Mechanism studies indicated that indirect oxidation, accounting for 84.32% of SMX degradation, is more significant than direct oxidation, which accounts for 15.68%; both
${\mathrm{HO}}^{\;\cdot} $ ${\mathrm{SO}}_{4}^{\;\cdot - } $ $\mathrm{O}_2^{\,\cdot {-}} $ ${\mathrm{SO}}_{4}^{\;\cdot - } $ ${\mathrm{HO}}^{\;\cdot} $ 关键词：Cyanobacteria-derived particle electrode;3-dimensional electrochemical system;Antibiotic;degradation;Biochar- 781
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发布时间：2024-11-15 - “最新研究发现，硫化零价铁与过二硫酸盐结合，可高效降解水体中的四环素污染物。”摘要：Sulfidated zero-valent iron (S–nZVI) has been extensively utilized in wastewater treatment in recent years due to its superior electron transfer efficiency and selectivity. Integrating S–nZVI with advanced oxidation technology enhances the catalytic performance of the material, leading to efficient pollutant degradation. This study employs thiourea as the sulfur source to prepare highly active S–nZVI and constructs an S–nZVI-activated per-disulfide PDS oxidation system to achieve efficient tetracycline degradation. The composition and surface morphology of S–nZVI is characterized using scanning electron microscopy (SEM), X–ray diffraction (XRD), specific surface area (BET), and X–ray photoelectron spectroscopy (XPS). The effects of the molar ratio (S/Fe), vulcanization time, S–nZVI dosage, PDS concentration, initial pH of the solution, and coexisting ions on tetracycline (TC) degradation are examined. Active species quenching experiments and electron paramagnetic resonance (EPR) experiments explore TC degradation by both free radical and non-radical active species, while liquid chromatography-mass spectrometry (LC–MS) analyzes the potential pathways of tetracycline degradation. Test results indicated that vulcanization modification increases the specific surface area of nano-zero-valent iron (nZVI), and iron (Fe) and sulfur (S) are uniformly distributed on the surface of the material. The impact of S/Fe on TC degradation is minimal, and the degradation rate correlates positively with the dosage of S–nZVI and PDS concentration but shows a decreasing trend with prolonged vulcanization time. The S–nZVI/PDS system exhibits an enhanced TC degradation effect across a wide pH range (pH=5～9). The presence of different anions in the reaction solution variably inhibits the degradation rate of TC, with
$\mathrm{HCO}_3^- $ $\mathrm{SO}_4^{\cdot -} $ ${\mathrm{HO}}^{\;\cdot } $ 关键词：sulfidated nanoscale zero-valent iron;persulfate;tetracycline;influencing factors;degradation mechanism- 952
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发布时间：2024-11-15 - “最新研究突破：开发出高结晶度三维多孔Fru-ATO阳极，有效提升阿特拉津电化学降解效率，为环境治理提供新思路。”摘要：Objective Highly active and stable anodes are crucial for efficiently removing persistent organic pollutants such as atrazine (ATZ) using electro-oxidation technology. Sb–doped SnO2 (ATO) materials exhibit high oxygen evolution potential, but commonly prepared planar ATO electrodes face removal rate and stability limitations due to slow mass transfer and large charge transfer impedance. This study proposes a compression-sintering method using fructose as a pore-forming reagent to prepare self-supporting 3-dimensional porous ATO (Fru–ATO) anodes for highly efficient and stable ATZ removal.Methods The Fru–ATO anode is initially prepared using fructose particles as the pore-forming reagent through compression and sintering. The effect of sintering temperature on the anode’s structure and performance is investigated by characterizing the electrode morphology and crystallinity with scanning electron microscopy (SEM) and X–ray diffraction analyzer (XRD) and analyzing their electro-oxidation performance. Secondly, the optimization of initial solution pH, electrolyte concentration, and applied current density is conducted to achieve a better degradation rate of ATZ. Under optimized conditions, the performance of 1000–Fru–ATO in actual water and cycling tests is investigated. Finally, the reactive oxygen species generated on 1000–Fru–ATO are investigated through quenching experiments and in-situ electron paramagnetic resonance characterization. In addition, intermediate products in the degradation process of ATZ and possible degradation pathways are proposed based on liquid chromatography-triple quadrupole mass spectrometry (UPLC–MS/MS).Results and Discussions With the increase in sintering temperature, the size of particles in the anode increases, the XRD peak becomes sharper and higher, the potential for oxygen evolution reaction gradually shifts positively, and the performance in catalyzing ATZ degradation improves. Based on the 1000–Fru–ATO anode, acidic and neutral initial solutions showed higher ATZ degradation rates, with the corresponding k for pH = 6 reaching 0.071 min–1. The concentration of Na2SO4 electrolyte exerts a volcano-like influence on the ATZ degradation rate, with the highest k of 0.071 min–1 in 0.1 mol/L. The ATZ degradation rate increases monotonically as the applied current density rises, while the lowest energy consumption is observed at 10 mA/cm2. Under the optimized condition of 0.1 mol/L Na2SO4 electrolyte solution at the initial solution pH and an applied current density of 10 mA/cm2, the 1000–Fru–ATO anode degrades 90% of ATZ (20 mg/L) within 30 min and 99% within 60 min and maintains good cycling stability in a ten-cycle test. With actual water from Xinlin Bay, Xiamen, the 1000–Fru–ATO anode still degrades 90.2% of ATZ (20 mg/L) within 60 min. In addition, the quenching experiment and in-situ electron paramagnetic resonance showed that singlet oxygen is the dominant reactive oxygen species for the rapid ATZ degradation on the 1000–Fru–ATO anode. In addition, 17 intermediates of the ATZ degradation process are identified by UPLC–MS/MS, based on which three possible degradation pathways are proposed. Five reaction processes are mainly involved in ATZ degradation on the 1000–Fru–ATO anode, including dealkylation, dechlorohydroxylation, alkyl hydroxylation, alkyl oxidation, and hydroxylation. The electrode possesses a 3-dimensional porous structure that exposes more active sites and improves mass transfer efficiency. As a result, the simultaneous enhancement of mass transfer and charge transfer and the suppressed oxygen evolution promotes the generation of three reactive oxygen species, especially singlet oxygen, leading to the effective and rapid degradation of ATZ.Conclusions The results demonstrate the feasibility of the proposed method with fructose pore-forming reagent to prepare highly active and stable ATO anodes for efficiently and stably electro-oxidizing ATZ. This method can also be extended to other catalyst anode preparations and other persistent organic pollutant removals and would inspire more advances in preparing self-supported 3D porous electrodes with organic powder of small molecular weight as pore-forming reagents.关键词：SnO2–Sb;electrocatalysis;anodic oxidation;atrazine (ATZ);wastewater treatment
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发布时间：2024-11-15 - “煤化工废水处理领域取得新进展，专家提出Fe3+/H2O2体系，有效降低运行成本，为工程应用提供理论基础。”摘要：Coal chemical wastewater exhibits complex water quality, with a high concentration of difficult-to-degrade organic matter and ammonia nitrogen, posing significant challenges for wastewater treatment. Current technologies, including coagulation, adsorption, and membrane bioreactors, have limitations such as high costs, unstable operation, and suboptimal pretreatment effects, failing to meet the evolving needs of the coal chemical industry. This study introduces a novel method using the reducibility of phenolic organic compounds in coal chemical wastewater to enhance the Fe3+/Fe2+ cycle in the Fe3+/H2O2 Fenton-like system, thus efficiently treating the wastewater. Comparative experiments demonstrated that the Fe3+/H2O2 system achieves removal rates of COD, TOC, TN, and NH3–N at 74.63%, 52.62%, 10.46%, and 15.11%, respectively. This system significantly reduces coloration, shows the largest decline in the UV-Vis spectrum, and decreases the amount of iron sludge. Q-TOF analysis revealed that the primary eight organic compounds in the wastewater are phenolic or contain reducible functional groups such as aldehyde, carbonyl, carboxyl, carbon-carbon double bond, or ester. By monitoring changes in the COD removal rate and pH, Fe3+/Fe2+, H2O2, and others over time, the mechanism of organic matter removal in the Fe3+/H2O2 system is proposed: the reducible organic matter reduces Fe3+ to Fe2+, enhancing the Fe3+/Fe2+ cycle, and the generated Fe2+ reacts with H2O2 to remove organic pollutants via the Fenton reaction. Optimal operating conditions are identified as Fe2(SO4)3 dosage of 1.0 g/L, H2O2 dosage of 50 mol/L, reaction temperature of 30 °C, and initial pH of 6.8 using the controlled variable method. Under these conditions, after 60 minutes, the treatment shows significant COD, TOC, TN, and NH3–N removal efficiencies, a significant reduction in color, and an increase in biodegradability, with the B/C ratio rising from 0.17 to 0.47. This study confirms the viability of using a self-reduction Fe3+/H2O2 system for phenolic coal chemical wastewater, reducing operating costs and providing a theoretical foundation for further research and engineering applications.关键词：Fe3+;H2O2;fenton-like;coal chemical wastewater;phenolic compounds
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发布时间：2024-11-15
FUTURE OF ADVANCED OXIDATION PROCESSES IN THE TREATMENT OF EMERGING POLLUTANTS
- “在离群点检测领域，研究者提出了KLOD方法，有效改善K-means聚类效果，提高局部离群点检测精度和性能。”摘要：Objective Outliers are defined as data points generated for various special reasons. They are often regarded as noise points due to their deviation from normal data points and are considered points of research value, occupying a small proportion of the dataset. The task of outlier detection involves identifying these points and analyzing their potential abnormal information through the analysis of data attribute features. This process aims to uncover unusual patterns or behaviors within the dataset that can provide insights into unique phenomena or anomalies. Most clustering-based outlier detection methods primarily detect outliers in the dataset from a global perspective, with weaker performance in detecting local outliers. Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. A local outlier detection method, named KLOD (local outlier detection based on improved K-means and least squares methods), is developed to achieve precise detection of local outliers.Methods The K-means clustering algorithm is characterized by hard clustering, meaning that after clustering the dataset, each data point has a clear association with one cluster or another. This property makes it suitable for outlier detection, as outliers significantly affect the clustering process. However, selecting initial cluster centers and determining the number of clusters is crucial as they directly impact the clustering effectiveness. To select the accurate cluster center, clustering by fast search and finding density peaks is utilized to compute the local density and relative distance of data points, constructing a decision graph based on these metrics. The challenge lies in accurately determining the cutoff distance dc, making it difficult to precisely identify the number of cluster centers from the decision graph obtained using a single dc value. The elbow method is employed to determine the optimal number of clusters for an unknown dataset for the best clustering effectiveness to address the challenge of determining the number of clusters. When clustering data into different numbers of clusters, the cost function value changes accordingly. The number of clusters is depicted on the x-axis, and the cost function value is on the y-axis. The changes in the cost function value with the number of clusters are recorded and plotted as a line graph. When there is no significant decrease in the cost function value with an increase in the number of cluster centers, the position of the “elbow” is observed to determine the optimal number of clusters. After determining the initial cluster centers and the number of clusters k, the dataset is clustered using the K-means clustering algorithm to obtain k clusters and their corresponding cluster centers. The objective function value for each data point in each dimension within each cluster is then computed. Then, the objective function values for each dimension of the data points in each cluster are sorted in ascending order. The objective function values, sorted in ascending order, are fitted using the least squares approach to obtain a curve. The derivative of this fitted curve is then calculated to obtain the slope, providing insight into the rate of change of the objective function values within each cluster. Each dimension’s degree of dispersion and information content can vary in the dataset, so different weights are assigned to each dimension. Information entropy is employed to measure the dataset’s degree of dispersion, and higher weightage is given to dimensions with higher outlier degrees to represent their impact on the overall dataset. By incorporating information entropy, each dimension’s objective function value for each data point is weighted by the corresponding change rate. This process results in the final anomaly score, and the top-n data points with high anomaly scores are considered outliers.Results and Discussions The experimental results indicated that in the artificial dataset, KLOD, KNN, and LOF all detect sparse local outliers effectively. However, the LOF algorithm struggles to detect outliers within outlier clusters. Additionally, the KNN method cannot detect local outliers within densely distributed clusters when there is a considerable distance between normal data points. In contrast, the KLOD method analyzes each cluster individually, addressing the issue of uneven cluster densities. The KLOD method analyzes each dimension of the data points within each cluster separately, achieving accurate detection. In the UCI dataset, the KLOD method achieves optimal detection accuracy in 10 datasets, with detection accuracy on par with KNN and LOF in 2 datasets. Compared to the KNN and LOF algorithms, KLOD also demonstrates high accuracy in outlier detection. The fast search density peak method is applied to calculate the local density and relative distance of data points, and the γ value of each data point is determined based on these two metrics to improve the K-means clustering algorithm. However, the size of γ is influenced by the cutoff distance dc, making it difficult to intuitively choose k initial cluster centers. Hence, the elbow method selects the k data points with the largest γ values as initial cluster centers for the K-means clustering algorithm. Least squares fitting is employed to fit the objective function values for each dimension sorted in ascending order. This method highlights the degree of outlierness of outliers, incorporating more outlier information into the final anomaly score.Conclusions Experimental results on artificial and UCI real datasets demonstrated that the KLOD method can detect local outliers with moderate outliers. Compared to the KNN and LOF methods, it significantly improves detection accuracy. However, due to limitations of the K-means algorithm itself, its clustering performance is poor for datasets containing arbitrarily shaped clusters, affecting detection performance. Therefore, future studies can focus on enhancing the performance of outlier detection methods on datasets with arbitrary cluster shapes.关键词：outlier detection;K-means;least squares method;peak density;objective function
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发布时间：2024-11-15 - “在隧道缺陷检测领域，专家提出了受监督热图算法的隧道衬砌线关键点识别算法，有效提升了识别准确性和鲁棒性，为工程建设领域探地雷达无损检测数据解译工作提供技术支撑。”摘要：Objective As a critical step in tunnel defect detection and analysis, lining line identification has long faced challenges in analyzing detection data. This study proposes using supervised heatmap algorithms and anti-noise disturbance techniques to recognize keypoints of lining lines, based on the CenterNet algorithm, to overcome the limitations of traditional analysis methods and enhance the accuracy and robustness of the results. Methods The algorithm is divided into two stages: keypoint detection and curve fitting. It includes three improvement methods: grid classification task, peripheral point supervision, and anti-noise disturbance. Initially, during the two-stage training process, the keypoint detection phase aims to improve the CenterNet algorithm’s limited heatmap fitting capability for dense keypoints by incorporating a heatmap grid classification task. The grid sequence, aligned in the vertical (A–scan) direction, is divided equally into several segments. These segments are categorized based on the location of keypoints within the sequence. A transformer is employed to learn the mapping from grid sequences to classification labels through supervised training. This supervision of the heatmap fitting process is based on the classification results. Simultaneously, a certain number of outer-point heatmaps are produced in the initial training rounds, and the model’s learning process is constrained through the positional information between outer points and keypoints. In the fine-tuning stage of curve fitting, Gaussian noise is introduced to the curve, and anti-noise disturbance is applied to counteract image noise interference. Finally, the tunnel lining dataset, divided into training, validation, and test sets, is utilized. The training set contains 3 200 images with 753 562 keypoints and a data size of 12.35 GB. The validation set comprises 600 images with 188 635 keypoints and a data size of 2.88 GB. The test set consists of 999 images, including 236 742 keypoints, and a data size of 3.52 GB. This dataset is test data in the experimental stage to compare the CenterNet, CornerNet, and the proposed algorithm. The effects of the three specific improvement methods, grid classification task, peripheral point supervision, and noise resistance, on lining line recognition are initially verified. Through ablation experiments based on the CenterNet algorithm, the impacts of various improvement measures on the algorithm’s performance are further demonstrated. Results and Discussions The experimental results showed that different algorithms’ lining line recognition performance significantly improves after being supervised by the grid classification task. The curve spacing errors of the recognition results from the CenterNet algorithm, employing the backbone networks ResNet, DLA–34, and Hourglass–104, respectively, are reduced by 0.40, 0.40, and 0.28 pixels. The inference times are 11, 19, and 71 milliseconds, respectively. The CornerNet algorithm reduces errors by 0.34 pixels, with an inference time of 23 milliseconds. The grid classification task exists only during the training process, so it does not impact the inference time. Additionally, using outer points to supervise the heatmap fitting process also improves recognition accuracy. The more supervision training rounds, the better the recognition performance. After incorporating outer-point supervision in the first 10 rounds, the curve spacing errors recognized by different algorithms are 3.56, 3.20, and 2.65 pixels, showing improvement effects of 0.75, 0.75, and 0.73 pixels, respectively. Continuing the training beyond 10 rounds results in limited further improvements. By increasing the number of outer points, significant enhancements are initially observed. The optimal effect occurs when 8~10 outer points are used, with curve spacing errors of 3.48, 3.13, and 2.44 pixels, respectively, and improvement effects of 1.84, 1.88, and 2.08 pixels. As more outer points are added, the effect gradually diminishes. Therefore, using 8~10 outer points to supervise model learning in the first 10 rounds yields the most significant improvements. When noise is introduced early in the curve fitting input, recognition accuracy improves, with optimal noise disturbance intensity at approximately 0.08. The curve spacing errors recognized by different algorithms are 3.59, 3.20, and 2.49 pixels, respectively, with improvement effects of 1.73, 1.81, and 2.03 pixels. As noise intensity increases, the overall recognition effect deteriorates sharply. In the ablation experiment, the CenterNet algorithm with the Hourglass–104 backbone network is visually employed to verify the impact of different improvement measures on algorithm recognition performance. The results showed that the three measures of classification task supervision, outer-point supervised training, and anti-noise disturbance improve recognition accuracy by 0.09, 0.05, and 0.04 pixels, respectively, with memory consumption increases of 69, 19, and 6 MB. When classification task supervision and outer-point supervision training are employed simultaneously, the result is improved by 0.21 pixels, with a memory consumption increase of 88 MB. Similarly, when classification task supervision and noise disturbance are combined, the result improves by 0.16 pixels, and memory consumption increases by 77 MB. When outer-point supervised training and anti-noise disturbance are used together, the result improves by 0.11 pixels, and memory consumption rises by 32 MB. Implementing all three measures simultaneously effectively improves accuracy by 0.28 pixels and increases memory consumption by 95 MB. Conclusions The results showed that the grid classification task, outer-point supervision, and anti-noise disturbance proposed in this study can effectively enhance the effectiveness of tunnel lining line identification and mitigate the challenge of detecting dense keypoints. The proposed algorithm can provide technical support for interpreting ground-penetrating radar non-destructive testing data in engineering construction.关键词：ground penetrating radar;lining line detection;grid classification task;outer-points supervision;anti-noise disturbance
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发布时间：2024-11-15
ARTIFICIAL INTELLIGENCE
- “在建筑结构领域，专家通过混合连接方式，有效提升冷弯薄壁型钢组合墙体的抗破坏能力，为地震作用下的结构安全提供新方案。”摘要：This study proposes a hybrid connection of pull rivets and self-tapping screws to address the defects in components connected by self-tapping screws, which are susceptible to pulling and causing severe damage to the structure during seismic activity, and enhance the anti-destruction capability of cold-formed thin-walled steel composite walls activity. This connection aims to mitigate the failure modes of self-tapping screws by analyzing the force transmission mechanism at the interlayer connection of composite walls. In this regard, a total of 48 sets of joint shear performance tests are conducted to evaluate the shear resistance of the hybrid connection. These tests include five common thicknesses of connection sheets in cold-formed thin-walled steel structures and a range of lap sheet thickness ratios from 1.0 to 2.0. The methods of connection tested are self-tapping screw connections, pull rivet connections and hybrid connections. Observations from the tests showed that hybrid connections prevent the pulling and tearing failures typically seen with self-tapping screws. The failure modes observed are predominantly sheet bearing failure, combined screw tilt failure, rivet shear failure, and partial shear combined with sheet bearing failure. Compared to single connection methods, the hybrid connection’ load-displacement curve demonstrates a longer plastic phase. When the thickness ratio exceeds 1.5 and the combined sheet thickness is under 3 mm, the load-carrying capacity and ductility of the hybrid connection increase significantly in comparison to the single connections. The calculated bearing capacity of the hybrid connection, using existing calculation methods, was found to be conservative when compared to the actual test results. The findings suggest that the hybrid connection can effectively counteract the weaknesses of blind rivets and self-tapping screws under shear stress, improve the resistance to pulling and tearing of self-tapping screws, and thus enhance the bearing capacity and ductility of the connection. Thickness and thickness ratio are key factors that influence the failure mode and bearing capacity of the hybrid connection. Furthermore, as the thickness ratio increases, so does the bearing capacity. The method of arrangement has a minimal impact on the mechanical performance and failure mechanism of hybrid connections. Under the experimental conditions of this study, based on the observed failure mode of the hybrid connection, an improved calculation method is proposed. This new method is based on existing calculation methods but provides more accurate results.关键词：blind-rivet connections;screw-blind hybrid connection;cold-formed steel composite wall;shear behavior;calculation method of shear bearing capacity
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发布时间：2024-11-15 - “在桥梁工程领域，专家提出了一种新型装配式主梁连接方案，通过剪力键和横向预应力筋混合连接，有效提高了结构整体性和施工便利性，为飞机荷载桥梁的主梁拼装提供技术支撑。”摘要：Objective The hinge joint connection in traditional prefabricated beam transverse connections exhibits weak strength and poor stiffness, whereas the wet joint connection involves complex construction processes and lengthy durations. Research on the mechanical properties and enhancement measures of various connection schemes focuses primarily on highway and railway bridges. Aircraft loading bridges are characterized by large load sets, significant spatial stress, and continuous construction requirements, all demanding greater strength and construction efficiency in the transverse connections of main beams. However, research on the relevant transverse connections of prefabricated beams for aircraft loading bridges remains unaddressed.Methods A prefabricated beam transverse connection scheme is proposed to address these challenges, featuring a hybrid connection of shear keys and transverse prestressing tendons. This scheme considers the mechanical characteristics of aircraft loading bridges. Vertical shear keys are employed to connect adjacent beams at the joints, which are then bonded with epoxy resin adhesive. Transverse prestressing tendons, embedded within the top and bottom plates of the beams, apply compressive stress to the joint interface. This approach offers multiple advantages, including reliable connection performance, enhanced structural integrity, improved durability, and simplified construction processes. Material nonlinearities and contact nonlinear behaviors under load were considered based on a prefabricated beam’s straight shear test results. A reasonable solid model numerical simulation method is developed to analyze the mechanical performance of prefabricated beams using the ABAQUS platform. The results showed that the errors in bearing capacity and initial stiffness at the joint between numerical simulation and test results do not exceed 7% thus confirming the accuracy of the simulation method.Results and Discussions Taking the H1 taxiway bridge of an airport’s Phase Ⅲ expansion project as the research object, a nonlinear numerical model of the prefabricated beam with the proposed connection scheme is developed. Both static and dynamic analyses are conducted to validate the reliability of the proposed scheme. The results indicated that the proposed connection can meet the specification of beam deflection under static aircraft load with considerable safety reserves. The effects of parameters such as the positions, numbers, and heights of shear keys, as well as the initial prestress, on the structure’s mechanical behavior and seismic performance are examined. Under the impact of the aircraft’s static load, the beam’s mid-span deflection and bending moment are significantly reduced by the strategic placement of mid-span shear keys and an increase in their quantity. This adjustment enhances the collaborative deformation capacity among the beams and ensures uniform distribution of forces across the center and edge beams, effectively enhancing the structural integrity. Compared to the placement of shear keys only at the beam ends, incorporating three shear keys at the mid-span can lead to reductions in mid-span deflection and bending moment by 19.92% and 23.35%, respectively. The inclination and height of the shear keys had a minimal impact on the mechanical properties of the main beam but significantly influenced the local stress state of the shear keys. Decreasing the shear key inclination angle or increasing the shear key height enlarges the shear key force transfer area, reducing contact interface and key root shear stresses. The maximum shear and tensile stresses for each shear key in the proposed scheme do not exceed the design values for concrete shear and tensile strengths. Increasing the initial prestress of the transverse prestressed tendons enhances the pre-compression stress at the joint interface of the beam, preventing premature cracking of the structure. With the initial tension force rising from 135 to 195 kN, the compressive stress of the shear key directly bearing the aircraft load increased by 45.31%. The structural response variation under earthquake action, with differing shear key positions and initial prestress levels of prestressing tendons, reflected that observed under static load conditions. Incorporating three shear keys in the mid-span can reduce the beam’s deflection and bending moment by 17.29% and 40.12%, respectively. In addition, an increase in the initial prestress of the prestressing tendons can boost the compressive stress at the joint interface of the mid-span by 46.51%.Conclusions The research findings can provide essential technical support for the prefabricated beams used in aircraft loading bridges and can apply to heavy-load railway and highway bridges.关键词：aircraft loading bridge;prefabricated beams;shear key;transverse prestressed tendon;static analysis;seismic response
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发布时间：2024-11-15 - “在深部巷道围岩稳定性控制领域，专家研究了温度与压力耦合作用下锚杆杆体-树脂锚固剂界面变形破坏机理，为锚固支护参数设计提供理论依据。”摘要：In mining, the high temperatures and stresses in deep strata decrease the stability of the rock that surrounds the resin–anchor support structures of roadways, and so a solution is urgently required regarding how to exert effective control over the deformation of such rock. Therefore, it is necessary to study the mechanism for deformation and failure of the interface between the bolt body and the resin anchoring agent under the coupled effect of temperature and pressure. First, a description is given of the current situation regarding deep support engineering in the Lianghuai mining area, and combined with the results of pull–down tests in different indoor temperature environments, it is concluded that the deformation and damage of resin anchors are aggravated by high temperatures. Next, the axial and radial failure modes of the anchor body under pull–out load are analyzed, and the failure of the first anchorage interface is divided into three modes, i.e., elastic shear slip failure of the surrounding rock, non-penetration shear expansion slip failure, and penetration shear expansion slip failure. Based on elastic–plastic analysis of the stress state of the interface with different failure types of the anchoring interface under the stress of the surrounding rock, and considering the weakening of the mechanical strength of the resin anchoring layer under high temperatures, a calculation model is established for the failure mechanics of the first interface under the coupled effect of the temperature and stress of the surrounding rock. How changes in the surrounding-rock stress, ambient temperature, elastic modulus ratio, and other factors influence the anchorage performance of the first interface is analyzed, and it is concluded that the ultimate axial load of the first interface decreases with increasing temperature. When fissures are either developing in or penetrating the surrounding rock, the influence of its stress on the shear failure of the first anchorage interface is significantly higher than that when there are no fissures. Finally, the proposed calculation model is shown to be effective by comparing its predictions with the results of indoor drawing tests. The present research provides a theoretical basis for controlling the stability of surrounding rock and designing anchor-support parameters for deep roadways.关键词：temperature and pressure coupling;resin anchor;anchoring interface;failure mechanism;factor analysis
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发布时间：2024-11-15 - “在深覆土梯形拱明洞领域，专家采用模型试验和数值模拟方法，分析了其静力特性及卸荷效果，为设计和施工提供理论指导和技术支持。”摘要：Objective This study analyzes the static characteristics of trapezoidal arch openings and the unloading effect in deep overburden conditions to investigate the influence of the trapezoidal arch structure-fill interaction on surrounding soil pressure and unloading mechanisms. Additionally, it aims to clarify the advantages of trapezoidal arches over traditional rectangular arches.Methods This analysis combines indoor modeling tests and numerical simulations. In the experimental phase, organic glass plates serve as the test material. A numerical model and the specific thickness of the test material are deduced. Additionally, the preparation of a rubber granular soil mixture and its related compression and shear characteristic tests are conducted. In the numerical simulation phase, following verification with the indoor model test, the finite difference software FLAC3D and the discrete element software PFC2D are employed to establish the subway station model. Discrete elements primarily describe the fine contact between backfill particles, facilitating a better observation of the distribution of the contact force chain of the backfill around the openings. The static analysis of the deep overburden trapezoidal arch openings and their load unloading is also evaluated.Results and Discussions The study attributes the observed decrease in soil pressure to the gradual reduction of load shedding. The load reduction material enhanced the soil settlement at the top of the arch, creating a settlement difference within the soil column and forming a soil arch effect. This effect caused the soil pressure at the top of the arch to transfer to the sides, with the cross-section type exerting minimal influence on the settlement and distribution of the backfill above the opening. Before load reduction, the maximum axial force, the maximum positive bending moment, the minimum safety coefficient, and the maximum deformation of the lining in the trapezoidal arch roof slab opening all occurred at the central position of the roof slab. The maximum negative bending moment was observed at the interface between the straight roof slab of the trapezoidal arch and the sloping roof slab near the diaphragm wall. The maximum axial force, the maximum positive bending moment, and the maximum negative bending moment in the opening with trapezoidal arches were reduced by 17.5%, 34.1%, and 29.9%, respectively. The maximum deformations under working conditions T1, T2, J1, and J2 were 14.16, 9.50, 19.03, and 14.83 mm, respectively. Introducing a load-shedding layer did not alter the distribution of structural forces in deep overburden openings, but it significantly reduced the internal forces and deformation of metro stations, thereby enhancing the structural safety coefficient. The safety coefficients for various working conditions have been calculated according to the “Railway Tunnel Design Code”. The structural safety coefficients for trapezoidal arch caverns are in the following order: trapezoidal arch straight top plate < diaphragm wall < side wall < trapezoidal arch sloped top plate < bottom plate. For rectangular arch caverns, the order is rectangular arch top plate < diaphragm wall < side wall < bottom plate. The maximum and minimum safety factors for these two types of sections are found at the center of the top slab and the bottom slab of the unilateral cavern, respectively. Installing a load-shedding layer can increase the minimum safety coefficient of the trapezoidal arch and rectangular arch open caverns by 100.0% and 42.6%, respectively. Compared to trapezoidal arch roof subway stations, rectangular arch roof stations exhibit higher safety coefficients for the bottom plate and side wall but lower coefficients for the top plate, particularly at the center, which does not meet the specification requirements. The safety coefficients for trapezoidal arch roof subway stations increase significantly after installing a load-shedding layer, yielding a more pronounced effect. This study’s limitation lies in its sole focus on testing and numerical analysis to examine the internal force and deformation development in deep cover trapezoidal arch open holes under static force. However, it does not consider the substantial disturbances to the structure caused by backfill compaction during the open hole’s construction. Moreover, the study ignores the dynamic influences, especially seismic activities, and the development of solidification and settlement over time following the soil fill completion. These factors significantly affect the fill’s stress distribution and the structural force, posing a considerable impact on structural stability. Therefore, the dynamic effects, notably seismic actions, and the time-dependent consolidation and settlement after the completion require further investigation due to their substantial influence on the stress distribution of the fill and the structural stress, making them highly significant for research.Conclusions The results showed that in the absence of load shedding, the backfill settlement on both sides of the trapezoidal arch subway station exceeded the backfill settlement above the subway station, with the soil pressure on both sides of the subway station transferring to the top of the subway station. Furthermore, the soil pressure increased with the filling height, displaying a generally linear trend. During load shedding, the backfill settlement above the subway station was greater than on its sides, and the soil pressure gradually decreased with the increase of filling height.关键词：Deep overburden soil;ladder arch open-cut tunnel;Static characteristics;Unloading effect
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发布时间：2024-11-15 - “在工程领域，专家建立了碎石桩-排水板复合地基固结模型，有效提高固结速率，具有经济价值。”摘要：Composite foundations reinforced by stone columns and vertical drains are widely utilized in various projects due to their low cost, high consolidation rate, and effective reinforcement. Although the consolidation theory of a single vertical drain or stone column composite foundation is well-developed, reports on theories involving both types of drainage bodies are scarce. Previous models only accounted for unidirectional seepage of pore water in the radial direction, which diverges from the actual situation. Therefore, a theoretical model that accounts for bidirectional seepage of pore water under external loading in the radial direction is proposed. This model features a permeable top and an impermeable bottom, and the analytical solution is derived from the seepage continuity conditions of the stone columns, vertical drains, and surrounding soils. Under certain conditions, this solution may be simplified to the consolidation models for foundations with either a single stone column or a vertical drain, thereby demonstrating the universality and accuracy of the approach. Subsequently, the solution is applied to the settlement calculations of both an actual project and an indoor model test, with results aligning well with the measured data. The analytical solution is further employed to investigate the consolidation behavior of the composite foundation in detail. The results indicated that the consolidation rate significantly benefits from the installation of vertical drains between stone columns. Besides, the consolidation rate increases with the number of vertical drains, and the permeability coefficient of these drains greatly influences both the consolidation and settlement rates. Compared to reducing the column spacing in classical composite foundation technology, installing vertical drains between stone columns has higher economic value.关键词：stone column;vertical drains;combined composite foundation;consolidation;analytical solution;bidirectional seepage
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发布时间：2024-11-15 - “在高放废物地质处置领域，专家构建了裂隙花岗岩非线性蠕变本构模型，准确描述蠕变破坏全过程，为处置库长期稳定性提供解决方案。”摘要：The creep behavior of fractured granite is crucial for the long-term stability and safety of high-level radioactive waste disposal repositories. This study proposes a damaged elastic-visco-plastic model, considering the effect of stress-induced damage accumulation during the creep process. The model replaces the Newtonian element with a fractional derivative viscoelastic element and the classical viscoelastic body with a damaged elastic-visco-plastic body within the Burgers model framework. Consequently, a new nonlinear creep constitutive model and its corresponding 3D creep equation for fractured granite are established. The model parameters and their variations with stress levels are determined by fitting the experimental creep results of granite samples with fractures inclined at 30 and 45 degrees under varying stress conditions. Additionally, the suitability and rationality of the creep model are verified. A sensitivity study is conducted to examine the impacts of the fractional derivative order, damage factor, and stress level on the creep strain of fractured granite. The findings suggest that in specific cases, the nonlinear creep constitutive model can be simplified to the classical Burgers model. Importantly, the proposed model accurately describes the three stages of the creep failure process, particularly highlighting the nonlinear characteristics of creep strain in the accelerated stage.关键词：fractured granite;creep;nonlinear model;fractional derivative;parameter analysis
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发布时间：2024-11-15 -
Distribution Characteristics of Pea Gravel Behind Segment in Shield Tunnel Boring Machine Tunnels AI导读
“青岛地铁TBM隧道项目通过地质雷达测试和数值模拟，揭示了豆砾石分布特征及其对管片受力的影响，为TBM隧道施工提供指导。”摘要：Pea gravel plays a crucial role in segment stability as the connecting layer between the segment and the surrounding rock in TBM tunnels. Due to the influence of construction technology and geological conditions, the phenomena of dense filling and uneven distribution of pea gravel often occur, leading to various disasters such as dislocation, cracking, and water leakage. The distribution characteristics of pea gravel behind the segment ring form the basis for analyzing segment stress. Within the context of the Qingdao metro TBM tunnel project, geological radar is employed to examine the distribution characteristics of pea gravel behind the segment wall. Subsequently, a numerical simulation of single-ring pea gravel filling is conducted. This study analyzes the migration process of pea gravel behind the segment wall in both straight and curved sections of the tunnel and discusses the impact of geological conditions, filling pressure, collapses, and other factors on the quality of the filling. The results indicated that during TBM tunnel construction, the arch crown, tunnel bottom, and lower part of the outer side of the line’s turning section are the areas most prone to pea gravel empty tunnels. Moreover, the pea gravel empty of the arch crown and tunnel bottom exceeds 1 m, while those at the lower part of the outer side of the turning section are smaller and less dense. Poorer geological conditions increase the probability and scale of voids in the pea gravel behind the segment, with strongly weathered strata showing the most significant effects. Collapses impact pea gravel reclamation by obstructing migration paths and increasing energy demands, although their impact is limited to the collapse site. Enhancing the hydraulic fill pressure of the pea gravel can improve the fill quality at the vault and tunnel bottom; the improvement is more pronounced under better geological conditions, though it does not significantly enhance the filling quality in strongly weathered strata. Based on the causes of formation, the pea gravel cavities behind the segment ring are categorized into three types: collision energy dissipation, collapse block, and smaller clearance in the turning section. Additionally, the study presents the frequent parts, characteristics, and construction recommendations related to these activities.关键词：tunnel engineering;tunnel boring machine;segment ring;pea gravel;distribution characteristics- 146
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发布时间：2024-11-15 - “最新研究揭示了3维压剪应力下岩石剪切损伤破坏特征，为岩石工程稳定性分析和支护设计提供重要参考。”摘要：To study the shear damage deformation characteristics of intact rock in rock slopes under three-dimensional compressive–shear stress conditions, 16 sets of triaxial shear tests were conducted on saturated intact fine-grained quartz sandstone with simple composition and homogeneous structure under different confining pressures by using the Rock Top–50HT full-stress multi-field coupling triaxial test system. In the tests, the corresponding triaxial shear stress–strain curves and the shear–failure fracture surfaces containing original rock debris were obtained, the nonlinear variations of the strength characteristics of quartz sandstone under triaxial shear stress were analyzed, and the triaxial shear failure mode and the roughness characteristics of the fracture-surface morphology of quartz sandstone were explored. Also, based on the Delaunay point–cloud discretization algorithm, the failure fracture surface of quartz sandstone was reconstructed, and the variation characteristics of its potential contact part with the effective inclination threshold of the surface were analyzed. The results show that with increasing normal stress, the triaxial shear failure mode of quartz sandstone changes gradually from brittle failure to plastic failure and finally to plastic flow failure. The triaxial shear strength of quartz sandstone shows obvious nonlinear variation with increasing confining pressure. The Mohr–Coulomb criterion is used to fit the triaxial shear strength of quartz sandstone via piecewise linear fitting, and it is found that with increasing confining pressure, the cohesion increases while the internal friction angle decreases. The three-dimensional roughness characteristics of the shear–failure fracture surface are evaluated using the traditional Grasselli model, and its nonlinear fitting parameters
$\theta _{{\mathrm{max}}}^*$ 关键词：rock mechanics;triaxial shear test;failure mode;nonlinear shear strength;morphological characteristics of fracture surface- 176
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发布时间：2024-11-15 - “最新研究揭示深部煤炭开采顶板岩石拉伸破坏特性，为煤矿灾害防治提供指导。”摘要：Due to the complex environmental occurrences and resource exploitation in deep coal mines, the risk of disasters such as roof falls has sharply increased, with most being directly caused by roof tensile failure. Therefore, it is urgent to explore the mechanical characteristics and the laws governing the evolution of damage in roof rock under tensile failure. To study the mechanical properties and spatiotemporal evolution characteristics of acoustic emission (AE) in roof sandstone under direct tensile loading conditions, uniaxial direct tensile tests and synchronous AE tests were carried out. Simultaneously, the differential processes of direct tensile failure between roof sandstone and coal seams were studied, and a stress–strain damage constitutive model for coal and rock under tensile stress was developed and validated. The test results reveal that: 1) The average direct tensile strength of the roof sandstone is 5.01 MPa, which is approximately 7.6 times greater than that of coal. The direct tensile mechanical parameters of the roof sandstone exhibit strong variability, indicating that sandstone is prone to damage localization, leading to roof tensile failure. 2) The post-peak release rate of elastic energy from sandstone is significantly higher than that from coal, exhibiting brittle characteristics. 3) The analysis of AE spatial localization evolution revealed the mechanism of microcrack propagation and agglomeration nucleation process in roof sandstone at different tensile loading stages. Before the peak stress, only a small number of randomly distributed microcracks were generated, mainly resulting in the elastic deformation of the rock matrix. When the stress decreased by 20% after the peak, microcracks became localized, and then macroscopic cracks appeared and rapidly expanded until failure. 4) A constitutive model based on AE characteristic parameters for rock tensile damage was constructed. This model was validated using direct tensile and AE test data from sandstone and coal, demonstrating a good fit. The model effectively characterized the post-peak strain softening characteristics of rock under direct tensile action. These research findings hold considerable implications for optimizing tunnel support structure design and for preventing and controlling coal mine disasters.关键词：sandstone;coal;direct tensile;acoustic emission;damage constitutive model
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发布时间：2024-11-15 - “在山区泥石流灾害早期识别和监测预警领域，专家验证了深度全连接神经网络模型，为提高泥石流评价精度提供新思路。”摘要：More–accurate predictions of susceptibility to debris flows would help greatly in the early identification and large-scale monitoring of debris–flow disasters. Some existing models for doing so perform well during training and test but less well in practice, and this has adverse effects on engineering site selection and disaster prevention and mitigation. To find a method with high accuracy in training, prediction, and application, the present study considered four models—i.e., deep fully connected neural network, gradient boosting decision tree, random forest, and Bayesian network and assessed them for accuracy and out-of-distribution (OOD) generalization. Taking Ya’an City in China’s Sichuan Province as an example, small watershed units were used for regional meshing, and the data were divided randomly into a training set and a test set at the ratio of 7:3. During data cleansing, missing values were tackled using a K–means and IterativeImputer method, and excrescent data were rejected using the 3–sigma rule. After analyzing the collinearity, sensitivity, and predictive ability of various debris–flow susceptibility factors, 14 were selected for model operation. The four aforementioned models were then constructed for debris–flow susceptibility prediction and model comparison, and accuracy evaluation and OOD generalization verification showed that the deep fully connected neural network model was superior to the other three models in terms of AUC (0.027 higher), Acc (0.02 higher), Recall (0.02 higher), MAE (0.003 lower), and OOD generalization (0.056 higher). The results show that deep fully connected neural networks are good at predicting debris–flow susceptibility, thereby improving the accuracy and adaptability of debris–flow evaluation and providing a new way to evaluate debris–flow susceptibility.关键词：debris flow disaster;susceptibility evaluation;deep learning algorithm;OOD generalization verification;deep fully connected neural network
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发布时间：2024-11-15
CIVIL ENGINEERING
- “在景观水体设计领域，专家采用2维浅水数值模拟，探索了植被覆盖变化下的水流特性，为优化景观池塘、湖泊和湿地设计提供解决方案。”摘要：Objective Shallow basins, varying in natural and artificial forms, are prevalent in urban and rural areas. They play critical roles in ecology, water resource management, environmental protection, and enhancing landscape aesthetics. For instance, wetlands and ponds become hubs for fish, plants, and plankton; reservoirs store water for agricultural irrigation, drinking, and industrial uses; constructed wetlands and ponds facilitate the removal of pollutants and harmful chemicals; and landscape ponds and lakes, adorned with vegetation, increase the real estate value. Prior research has extensively debated shallow basins’ functions and influencing factors from these perspectives, employing methods such as field investigations, aerial remote sensing, physical experiments, large-scale modeling, and surveys. Despite achievements in addressing individual perspectives, a comprehensive, systematic study covering multiple aspects remains lacking. The hydrodynamics within a shallow basin dictate its efficiency in treatment, water exchange rate, and the ratio of stagnant water areas. Hence, numerous strategies have been employed to enhance the hydraulic performance of shallow basins. Altering the aspect ratio, for example, can adjust the stagnant water ratio, enhancing or impairing the basin’s hydraulic function. Elliptical basins are recognized for their superior hydraulic performance over rectangular ones. In addition, aquatic vegetation, whether emergent or submerged, is acknowledged to enhance the hydraulic performance of shallow basins by equalizing flow velocity as water spreads laterally upon entering the basin. From the landscape design perspective, strategically interspersing aquatic vegetation is believed to elevate the aesthetic appeal of the basin and its vegetation. However, a detailed quantitative analysis of the impact of vegetation’s spatial distribution remains unexplored, leaving room for optimizing vegetation layout for hydraulic efficiency and landscape beauty.Methods This study focuses on how various spatial arrangements of emergent aquatic vegetation affect the hydraulic performance of shallow basins, aiming to identify an optimal vegetation design. The basin shape is limited to a rectangle with a fixed width-to-length ratio (width: 4 m and length: 6 m), and the dimensions of inlet and outlet were standardized. The depth-averaged Reynolds Averaged Navier–Stokes equations with the k-ε turbulence model are applied to simulate water movement within the shallow basin. Experimental data from existing literature, specifically velocity distributions, are initially utilized for model validation. In addition, the study examines the independence of results from grid size to ensure modeling consistency.Based on the validation of the velocity profile from flume tests, the two-dimensional shallow water model can reliably simulate flow within shallow pools and successfully capture the flow patterns of circulations where the main stream adheres to one sidewall while developing asymmetrically on both sides. Incorporating a vegetation drag term into the momentum equations allows the simulation of flow dynamics influenced by emergent vegetation.Results and Discussions In order to examine the impact of vegetation’s spatial distribution on flow patterns within a shallow basin, five vegetation distribution scenarios are conceptualized: 1) complete coverage, 2) lateral full coverage with variable longitudinal partial coverage downstream of the inlet (LFVLPI), 3) lateral full coverage with variable longitudinal coverage downstream of the outlet (LFVLPO), 4) longitudinal full coverage with variable symmetrical lateral partial coverage (LFVSLP), and 5) localized vegetation coverage near the inlet. In the case of complete coverage, the influence of vegetation density is assessed to identify the threshold at which a plug flow pattern (or absence of dead water zones) emerges. The findings indicated a transition from bare to vegetated conditions, where an asymmetrical flow pattern featuring two distinct circulation sizes (or dead water zones) evolves into a symmetrical flow pattern with similar circulations. As vegetation density reaches a threshold of 5 m−1, circulations vanish, yielding a plug flow pattern. This density threshold surpasses those reported in previous studies. Upon reaching this critical vegetation density, the impact of various spatial distributions of vegetation, with constant density, on flow patterns is explored. For LFVLPI, reducing the vegetation coverage ratio from full coverage does not alter the plug pattern until the ratio diminishes to 1/8, at which point small circulations appear near the basin’s inlet. In contrast, with LFVLPO, circulations persist, characterized by a pair of large cells and a pair of small corner cells. For LFVSLP, only small corner circulations form. As lateral coverage lessens, these corner cells scarcely enlarge until vegetation is absent. The minimal local vegetation coverage necessary for establishing a plug flow pattern occurs when the lateral coverage ratio is 1/2 and the longitudinal ratio is 1/4. Further analysis of the center-axis longitudinal velocity and its gradient along the basin’s length is conducted to indicate the formation of the plug flow pattern in response to hydraulic adjustments due to the introduction of vegetation. The evolution of circulation zones is closely linked to the rate of longitudinal velocity adjustment upon water entering the basin. A rapid local decrease in velocity leads to a swift global homogenization, significantly reducing the velocity shear or adverse pressure gradient between the center and surrounding zones. Consequently, introducing vegetation can eliminate flow circulations or dead water zones if it causes a rapid velocity decrease in the area following the inlet. In addition, examining the relationship between the proportion of the circulating water body area Ar and the dimensionless mean velocity gradient
$(\Delta U U_{\mathrm{m}}^{-1}) /(L_{\mathrm{a}} L^{-1}) $ $(\Delta U U_{\mathrm{m}}^{-1}) /(L_{\mathrm{a}} L^{-1})$ 关键词：shallow basin flow pattern;emergent vegetation;shallow water simulation;flow circulation area;water connectivity efficiency- 664
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发布时间：2024-11-15 - “地震波入射方位和斜入射角度对沥青混凝土面板地震响应影响显著。专家基于波场叠加原理，推导了P波任意入射方位角和斜入射角空间斜入射下弹性半空间自由场计算公式，建立了P波空间斜入射波动输入模型。考虑16种不同入射方位角和斜入射角下的P波空间斜入射工况，分析了入射方位角和斜入射角对沥青混凝土面板地震响应特性的影响，并提出了考虑应变率效应的沥青混凝土面板破坏评价方法。”摘要：The seismic wave incidence azimuth and oblique incidence angle significantly impact the seismic response results of asphalt concrete-faced rockfill dams. This study derives the calculation formula for the free field in elastic half space under the oblique incidence of P waves from any azimuth and angle based on the propagation mechanism of ground motion and the superposition principle of wave fields. In addition, a model for oblique wave input in P-wave space is established. Utilizing the results from uniaxial dynamic tensile tests of asphalt concrete under different strain rates, this study proposes a failure evaluation method for asphalt concrete panels that accounts for the real-time variation of tensile strength with strain rates. Considering 16 different incident azimuths and oblique angles of P-wave spatial oblique incidence conditions, this research analyzes the influence of these factors on the seismic response characteristics of an actual asphalt concrete panel from the aspects of panel stress and acceleration. The evaluation of tensile failure in asphalt concrete panels is conducted, and the differences between static and dynamic evaluation methods are discussed. The results indicate that the established P-wave spatial oblique incidence wave input model can accurately simulate the free field in half space, and the numerical solution aligns well with the analytical solution. Compared to a vertical input beam, the peak acceleration of the panel increases by 135.9% along the water flow direction and 92.7% perpendicular to the water flow direction, while the peak vertical acceleration decreases by 68.3%. The spatial oblique input significantly increases the dynamic stress of the panel, with the maximum principal tensile stress and principal compressive stress increasing by 3.6 and 2.7 times, respectively. Neglecting the incident azimuth and oblique incidence angles may seriously underestimate the seismic response of the panel. The traditional method of estimating the tensile failure of asphalt concrete panels through increasing the static strength by 30% as the dynamic strength is overly stringent. The proposed evaluation method, considering the strain rate effect, aligns more closely with real-world conditions.关键词：Asphalt concrete faced rockfill dam;spatial oblique incidence;earthquake response;tension failure
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发布时间：2024-11-15 - “在深厚覆盖层上建造面板堆石坝领域，专家改进H-KS流变模型并建立流固耦合模型，分析坝基流变对大坝及防渗体系的影响，为大坝安全稳定体系建立提供理论支持。”摘要：In the construction of concrete face rockfill dams on deep overburden, it is important to consider the influence of dam-foundation rheology in addition to the fluid–solid coupling of water and soil. To better simulate the real stress of dam-foundation rheology on the dam and its seepage control system, the new rheological element model, H–KS, is refined based on the layered characteristics of deep overburden. Hence, a rheological and fluid–solid coupling model is established using Comsol. Mechanical indices for each stage of the Hekoucun concrete face dam are then calculated chronologically, analyzing the influence of dam-foundation rheology on the dam and seepage control system. Results indicated that for the layered dam foundation with noticeable anisotropy, the H–KS rheological model more accurately reflects the actual stress, deformation, and seepage conditions of the dam at each stage, with an error within 5%; Compared to the Duncan E–B model, which does not account for rheology, the stress and deformation have increased by more than 11.8%, and some of this increase affects the safety and stability of the dam structure. The total settlement and stress during the filling period account for more than 70% of the total, though the unit-time increases are minimal, e.g., the settlement increment is only 0.015 m/month. The rheology and fluid–solid coupling of the dam rock and soil during the impoundment period significantly impact the strength and stiffness of each part of the dam, with stress and settlement unit-time growth rates of 0.02 MPa/month and 0.038 m/month, respectively. The growth rate of each index during the operation period gradually slows and eventually stabilizes, but the increases in deformation and stress may cause the main structure to become unstable or damaged. The concrete panel-plinth-impervious wall forms a complete and effective seepage control system. The rheology of the dam foundation increases the horizontal displacement of the upper part of the impervious wall and reduces the overall strength; the plinth and the panel are prone to midsection bending damage. The rheology of layered rock and soil exhibits time sensitivity, with the rheology of the layered dam foundation largely completed within 2–3 years after water storage, and the corresponding indicators tend to stabilize. These results provide theoretical support for the establishment of the safety and stability system of the face dam on the layered overburden.关键词：deep overburden;rheology of dam foundation;rheological model;anti-seepage system
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发布时间：2024-11-15
HYDRAULIC ENGINEERING
- “在航空钣金机匣材料成形领域，专家基于GH3030材料，建立了冷态强旋仿真模型，探索了旋压参数对成形回弹与载荷的影响规律，为精确成形提供理论指导和技术支持。”摘要：It is difficult to form aviation sheet-metal casing materials, and the precision of the formed products is also difficult to control; considering these problems, in this work, the superalloy GH3030 was considered as a material. On the basis of clarifying the springback theory and the load mechanism of cold strong spinning forming of sheet-metal casings, the Simufact Forming finite-element software package was used to import the constitutive equation of GH3030 obtained prior to the laboratory experiments, and a simulation model of cold strong spinning of aviation-casing conical parts was established. The influences of spinning parameters such as the roller gap, roller feed ratio, and mandrel half-cone angle on the springback and load were analyzed. The primary and secondary rules of the influence of each process parameter on the springback angle were obtained by orthogonal testing, and an optimal combination of process parameters was obtained on this basis. The Box–Behnken design response surface test method was used to obtain a quantitative regression model for the maximum forming force and spinning parameters, and variance analysis of the regression equation was carried out to calculate its multivariate correlation coefficient, reliability, and accuracy. The final results show that the reliability and accuracy of the obtained model are high, and the error is less than 10% when the final experimental and simulation results are compared. Therefore, the regression model is very accurate. Finally, spinning experiments were carried out, and the springback angles of the simulation results and the measured results from these experiments were compared and analyzed. The average error was within 6.2%, and this verifies the reliability of the simulation results and the regression model. This work shows that the trend in the springback angle obtained from the simulation analysis is almost the same as that measured in experiments, and the error is controlled within 12%, indicating that the results of the simulation analysis can accurately represent the springback law of the spinning parts. As such, this paper provides theoretical guidance and technical support for the accurate forming of conical parts from cold strong rotation of high-temperature alloy sheet-metal casings.关键词：sheet metal casing;high temperature alloy GH3030;cold strong spin;springback;forming force
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发布时间：2024-11-15 - “在数控机床铣削稳定性领域，专家提出了基于Bagging与NSGA-II算法的预测与优化方法，为提高加工效率和质量提供解决方案。”摘要：The occurrence of chatter in the milling process is a key factor limiting the efficiency and quality of machining. The stability of milling depends mainly on the process parameters and the dynamic characteristics of the tool–workpiece system; however, the system dynamics vary with the machining position and tool properties. Considering these multiple influencing factors, herein, a method is proposed to predict the milling stability and determine optimal machining parameters based on a bootstrap aggregating (bagging) procedure and the non-dominated sorting genetic algorithm–Ⅱ (NSGA–Ⅱ). First, an orthogonal experimental design is used to divide the working space of the machine tool into different machining positions. Under each position, impact testing is then carried out at the tool tip for different tool-overhang lengths to obtain the corresponding frequency response functions (FRFs). Then, limiting axial cutting depth aplim values are theoretically predicted using the tool-tip FRFs and machining parameters. Using sample information, the bagging algorithm is applied to establish a model for predicting aplim, in which the inputs are the displacements of the moving parts (x, y, z), tool diameter (d), tool-overhang length (h), spindle speed (n), cutting width (ae), and feed rate per tooth (fz). Taking these process parameters (x, y, z, d, h, n, ap, ae, fz) as design variables, a multi-objective optimization model is constructed to balance machining efficiency and tool life. Additionally, the pre-established aplim prediction model is used to express the milling-stability constraint. The multi-objective optimization model is then solved using NSGA–Ⅱ, and the Pareto-optimal set is obtained. Finally, the entropy weight method and the technique for order preference by similarity to an ideal solution (TOPSIS) are combined to select a unique optimal solution from the Pareto-optimal set. A three-axis vertical machining center was used to carry out a case study. The prediction accuracy of the established bagging model for aplim was 2.99%, and no chatter was observed when performing a milling test with the determined optimal process parameters. These experimental results validate the feasibility of the proposed method for predicting milling stability and selecting optimal process parameters under multiple influencing factors.关键词：milling stability;process parameter optimization;multi–objective optimization model;tool overhang;bootstrap aggregating algorithm;NSGA–Ⅱ genetic algorithm
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发布时间：2024-11-15 - “在高速列车动力学参数匹配领域，专家引入基于距离相关系数的多输出灵敏度分析技术，建立了Kriging模型，并通过多峰优化算法优化超参数，为动力学参数匹配提供解决方案。”摘要：There are many parameters that affect the dynamic performance of high-speed trains, and there are many evaluation indexes that can be used to assess this performance. Comprehensive consideration of these dynamic indexes while conducting a sensitivity analysis of the parameters is a very significant approach for optimizing high-speed train performance. It is difficult to measure the sensitivity of vehicle dynamics to its parameters comprehensively and accurately using existing single-output sensitivity-analysis techniques. To avoid the limitations of existing methods, this paper introduces a multivariant sensitivity-analysis technique based on distance correlation. By solving the distance-correlation coefficient between a single input and multiple outputs, the proposed method achieves global sensitivity analysis for multiple outputs. To improve the efficiency of this sensitivity analysis, Kriging models between multiple dynamic indexes and input parameters are established. To improve the accuracy of the approximation model, a novel multimodal optimization algorithm is introduced to globally optimize the hyperparameters of these Kriging models. Contrasting with traditional single-objective intelligent optimization algorithms, the algorithm presented here transforms a single-objective optimization problem into a double-objective optimization problem by introducing the population-diversity index. As a result, the diversity of the offspring population is enhanced and the problem of getting stuck in local minima of the optimization space is avoided. Based on the proposed method, the CRH1 electric multiple unit is taken as an example to investigate the parameter sensitivity of multiple dynamic indexes. The results show that the proposed hyperparameter-optimization technique can significantly improve the accuracy and stability of the Kriging models because it enhances the population diversity. In addition, the described sensitivity-analysis method can more reasonably identify those parameters that have large and small impacts on the vehicle’s overall dynamic performance.关键词：Evolutionary multimodal optimization;Kriging model;multivariant sensitivity analysis;distance correlation
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发布时间：2024-11-15 - “在微细电火花微孔加工精度提升领域，专家提出集成正交试验与卷积神经网络的新方法，通过优化参数组合，显著提高了加工精度，为实际生产加工提供了指导。”摘要：Objective To improve the precision of the micro-electrical discharge machining (micro-EDM) of micro-holes, a pioneering approach is undertaken in this study. Deep learning is applied innovatively to micro-hole micro-EDM, weaving together orthogonal experiments and deep learning to present an intricate methodology, i.e., an integrated fusion of orthogonal experiments and convolutional neural networks (CNNs). This synthesis strives to secure a robust dataset for subsequent predictive analyses of experimental outcomes via a CNN while concurrently minimizing the number of experiments.Methods The initial phase involves a meticulous L27 (313) orthogonal experiment, featuring four factors and three levels. The intricate impact patterns and optimal processing parameters for feed rate, spindle speed, pulse duty cycle, and pulse frequency regarding entrance overcut (EnOV), exit overcut (ExOV), and taper angle (TA) in the micro-EDM of H62 brass micro-holes are investigated meticulously in this study. Rigorous range and variance analyses are conducted on the experimental results, complemented by the deployment of scanning electron microscopy (SEM) to scrutinize the machined morphology for result validation. Subsequently, to validate the precision and applicability of the model predictions, 81 groups of data from orthogonal experiments on entrance overcut, exit overcut, and taper angle serve as predictive data for a CNN based on the PyTorch framework. Eleven groups of data are chosen meticulously as prediction samples, leaving the remaining 70 groups for training samples to predict experimental results.Results and Discussions The results show that feed rate, spindle speed, pulse duty cycle, and pulse frequency wield significant influence over entrance overcut, exit overcut, and taper angle in the micro-EDM of H62 brass micro-holes. For the entrance overcut in micro-hole machining, the hierarchy of impact intensity from high to low is pulse duty cycle, pulse frequency, feed rate, and spindle speed, and the identified optimal combination of parameters is a feed rate of 0.08 mm/s, a spindle speed of 2 000 r/min, a pulse duty cycle of 60%, and a pulse frequency of 3 000 Hz. For the exit overcut in micro-hole machining, the determined order is feed rate, spindle speed, pulse duty cycle, and pulse frequency, and the optimal combination of parameters is a feed rate of 0.08 mm/s, a spindle speed of 1 000 r/min, a pulse duty cycle of 60%, and a pulse frequency of 3 000 Hz. For the taper angle in micro-hole machining, the hierarchy is feed rate, pulse duty cycle, spindle speed, and pulse frequency, and the optimal combination parameters is a feed rate of 0.05 mm/s, a spindle speed of 1 500 r/min, a pulse duty cycle of 60%, and a pulse frequency of 3 000 Hz. A holistic consideration and analysis of the relationships between various factors pinpoints the optimal combination of parameters for micro-hole machining precision through validation experiments, i.e., a feed rate of 0.02 mm/s, a spindle speed of 1 000 r/min, a pulse duty cycle of 60%, and a pulse frequency of 3 000 Hz. The PyTorch-based CNN demonstrates remarkable predictive accuracy while underscoring the resilience of its results. The predicted values of entrance overcut, exit overcut, and taper angle for micro-hole machining align closely with the true experimental values, exhibiting minimum and maximum relative errors of 1.60% and 10.89% for entrance overcut, 2.44% and 11.10% for exit overcut, and 2.75% and 11.82% for taper angle. All the predicted values have relative errors below 12%, affirming a resilient fit of the PyTorch-based CNN and demonstrating exceptional predictive performance. The model’s applicability extends impressively, showcasing the capability to utilize orthogonal-experiment data for predicting any parameter combination, thereby effectively meeting practical production and machining requirements. A novel and advanced method for predicting the precision of micro-EDM for micro-holes is introduced in this study. Additionally, it serves as a valuable guide for actual production and machining processes, providing insights and directions for future advancements in the field. As a result, the research contributes significantly to the ongoing efforts in enhancing micro-hole machining precision, providing a new methodology and serving as a foundational basis for guiding practical applications in the field of micro-electrical discharge machining. Expanding on the implications of these findings, it is evident that the integration of deep learning with traditional experimental approaches presents a paradigm shift in micro-EDM research.Conclusions The synergistic combination of orthogonal experiments and CNNs optimizes the utilization of experimental data while minimizing the resources required for conducting a vast number of experiments. The meticulous analysis of the impact patterns and optimal parameters for micro-EDM of H62 brass micro-holes offers a comprehensive understanding of the intricate relationships between various machining factors. The utilization of SEM further validates the experimental results by providing a detailed analysis of the machined morphology. The subsequent validation of the model predictions using a PyTorch-based CNN demonstrates the accuracy and applicability of the proposed approach. The model’s ability to predict entrance overcut, exit overcut, and taper angle with high precision, as evidenced by the minimal relative errors, establishes its reliability and effectiveness. The findings contribute to the theoretical understanding of micro-EDM processes while also providing practical insights for optimizing machining parameters in real-world applications. The recommended optimal combination of parameters provides a clear guide for achieving high precision in micro-hole machining, addressing a critical need in industries where micro-EDM is employed. The study’s emphasis on the applicability of the model to diverse parameter combinations ensures its relevance in various manufacturing scenarios. The high predictive accuracy of the CNN suggests its potential for broader applications beyond the specific parameters investigated in this study. In conclusion, this research advances the theoretical understanding of micro-EDM processes and introduces a practical and efficient methodology for optimizing machining parameters. The integration of deep learning with traditional experimental approaches opens new avenues for research in precision machining. The model’s applicability and accuracy position it as a valuable tool for industries relying on micro-EDM, offering a systematic and data-driven approach to enhance precision and efficiency in micro-hole machining. As industries continue to embrace advanced technologies, the findings of this study pave the way for the integration of deep learning in manufacturing processes, marking a significant contribution to the field of micro-electrical discharge machining.关键词：Micro-EDM;orthogonal experiments;convolutional neural network;H62 Brass;Micro-hole
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发布时间：2024-11-15 - “最新研究突破，提出了策略梯度Informer模型，有效提高了滚动轴承剩余寿命预测的精度和计算效率。”摘要：As a typical encoder–decoder, the transformer architecture has inherent limitations such as secondary time complexity, high memory usage, and a complex model structure; these issues can lead to lower prediction accuracy and decreased computational efficiency when applied to the prediction of the remaining useful life (RUL) of rolling bearings. For this reason, herein, a novel encoder–decoder, the Policy Gradient Informer (PG–Informer) model, is proposed and applied to the prediction of the RUL of rolling bearings for the first time. First, in the new encoder–decoder architecture of PG–Informer, a probabilistic sparse self-attention m echanism is used to replace the original self-attention mechanism of the transformer architecture to improve its nonlinear approximation ability and reduce its time and space complexity. Then, the self-attention distillation operation is used to reduce its number of parameters and their dimensions and enhance the prediction robustness of time series. Moreover, the generative decoder of PG–Informer only needs to decode the decoding input in one step to output the prediction results without dynamic multistep decoding, which improves the prediction speed of time series. Finally, a policy-gradient learning algorithm is constructed to improve the training speed of the PG–Informer parameters. These advantages enable the proposed rolling-bearing RUL-prediction method to obtain higher prediction accuracy, better robustness, and higher computational efficiency. Results for the No. 1 rolling bearing at the Center for Intelligent Maintenance Systems of the University of Cincinnati show that the proposed method was able to predict an RUL value of 963 min, representing a prediction error of only 6.50% when compared to the experimental result ; compared to the transformer-based RUL prediction method, this represents a higher prediction accuracy, a smaller prediction error, and greater robustness. The proposed method consumed only 132.37 s for RUL prediction, shorter than the time taken by the transformer-based RUL-prediction method. These results verify the effectiveness and advantages of the proposed method.关键词：informer model;probabilistic sparse self–attention mechanism;policy gradient;rolling bearing;remaining useful life prediction
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发布时间：2024-11-15
MECHANICAL ENGINEERING
- “在高速铁路信号设备领域，专家提出了一种雷击过电压损伤检测及判定方法，优化了通信接口雷击试验及检测技术，为信号设备安全运行提供了科学依据。”摘要：This article proposes a method for detecting and determining the lightning overvoltage damage in communication interfaces of high-speed railway signal equipment, which is an optimization and improvement of the current lightning test and detection methods for communication interfaces of high-speed railway signal equipment. Firstly, an analysis of the lightning wave spectrum is conducted to determine the lightning test waveform and detection circuit of the communication interface. Subsequently, the CAN communication interface device PCA82C250 of the ZPW–2000A track circuit system and the optocoupler TLP621–4 of the encoding reading circuit were selected as the test objects. The lightning impulse tests were conducted on the test objects with gradually increasing voltage amplitudes. The test results showed that the transverse lightning impulse damage voltage of PCA82C250 is about 88 V, and the longitudinal lightning impulse damage voltage is about 48 V. In the optocoupler acquisition circuit, when the lightning impulse is directly applied to the optocoupler, the voltage damaged by lightning impulse is about 140 V. By connecting a 4.7 kΩ resistor in series between the lightning impulse point and the optocoupler, the lightning impulse damage voltage is about 800 V. Therefore, increasing the input impedance of the device can improve the lightning impulse resistance level. Finally, the lightning overvoltage damage characteristics of signal equipment communication interface devices were discussed and analyzed. The analysis results showed that these characteristics can be divided into three stages, which are the normal stage, the critical damage stage, and the damage stage. There exists an accumulation effect of impact damage on these components. When the components are in the critical damage stage, data transmission can still be carried out, but the output signal is inconsistent with the normal stage. The detection of lightning overvoltage damage to communication interface devices of signal equipment should be carried out through lightning impulse testing with gradually increasing voltage amplitudes. The basic criteria for damage determination is the presence of the breakdown phenomenon during the impulse and the abnormal signal level on the communication line. Furthermore, scientific and accurate judgments should be made in conjunction with corresponding testing standards.关键词：high-speed railway;signal equipment;interface device;lightning overvoltage;damage
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发布时间：2024-11-15 - “在电机散热领域，专家提出了优化通风槽钢结构设计，有效降低电机内部温升，为电机散热研究提供新方向。”摘要：In order to reduce the ventilation and heat dissipation performance of the YJK450–6, 400 kW medium-sized high-voltage motors, the heat dissipation performance of different ventilation channel steel structures of these motors was studied in this paper. Firstly, on the basis of the linear standard ventilation structure of the existing motor, three axial–radial hybrid ventilation structure forms were proposed, those are the single-row scaling type, the double-row linear type and the double-row scaling type. The 3D numerical calculation model of the temperature field of the motor was established in the SpaceClaim software. The simulation parameters of the motor were calculated according to the basic assumptions, the boundary conditions and the internal heat transfer formula of the motor. The simulation was carried out by Fluent software. Notably, the heat source for calculating the temperature field was obtained by the motor loss value computed by the Ansoft Maxwell platform. Secondly, the 3D numerical calculation model of the temperature field established in this paper was validated through the grid independence and temperature rise tests. A comparative analysis was conducted through simulation to assess the impact of the three axial–radial hybrid ventilation structures and the linear standard structure. The orthogonal test method was used to optimize the parameters of the axial–radial mixed ventilation structure to obtain the optimal heat dissipation structure and parameter scheme. The effect of cooling air velocity on the heat transfer performance of the double-row scaled channel steel was further explored. Combined with the temperature rise of the stator windings and the uniformity coefficient of the overall temperature rise of the motor, the heat dissipation effect of the optimal heat dissipation structure and parameter scheme of the motor was evaluated. The simulation results showed that the calculation model established in this paper is effective. The double-row scaling ventilation channel steel structure exhibit the best heat dissipation performance indexes, making it the optimal ventilation channel steel structure. The double-row scaling ventilation channel steel structure with a radial air duct height of 6 mm and a quantity of 13 is identified as the optimal heat dissipation structure and parameter scheme. The average convective heat transfer coefficient on both sides of the double-row scaling ventilation channel steel structure increases with the cooling air velocity, and the average convective heat transfer coefficient on the windward side of the channel steel is significantly higher than that on the leeward side. Compared to that of the linear standard motor, the uniformity coefficient of temperature rise distribution of the inner/outer windings of the double-row scaling ventilation channel steel structure motor with a radial duct height of 6 mm and a quantity of 13 increase by 88.13% and 20.11% respectively. Therefore, the optimal design of the ventilation channel steel structure is conducive to the internal air flow and heat dissipation of the motor, which can effectively reduce the internal temperature rise of the motor.关键词：medium-sized high voltage motor;axial–radial hybrid ventilation structure;ventilation channel steel;radial air duct;temperature rise
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发布时间：2024-11-15
ELECTRICAL ENGINEERING
-
Reversible Data Hiding Algorithm in Encrypted Images with Difference Encoding and Block Compression AI导读
“在数字信息与云存储技术领域，专家提出了一种基于差分编码和块压缩的密文域可逆信息隐藏算法，有效提升了嵌入容量和安全性。”摘要：With the development of digital information and cloud-computing technology toward maturity, reversible hiding of data in encrypted images is gradually becoming an area of intensive research for protection of data privacy in communications. Nonetheless, notable challenges still exist regarding achieving greater compression of carriers to enhance embedding capacity by adaptive-recognition coding of pixels in local areas based on the distribution characteristics of pixels in different cover images. To address the problem of the low embedding capacity of reversible information hiding due to insufficient utilization of redundant space in carrier images, herein, a cipher-text domain-reversible data-hiding algorithm is proposed based on difference coding and block compression. First, the difference-image matrix is classified and adaptively coded according to the maximum difference value within the block based on the differences of strong-correlation neighbors in local areas of the natural image. At the same time, the original image is chunked, disrupting the order between blocks and diffusing pixels within blocks to ensure the security of the image information. Then, according to the result of the adaptive coding of the difference-pixel blocks, the redundant space is compressed on the corresponding encrypted image blocks, and the secret data is finally embedded by bit replacement. In contrast to previous algorithms , this approach rearranges the bits of the differential-encoded image, starting from the least-significant bit of the cipher-text image pixel, marking the sign bit of the differential pixel, and marking the least-significant differential bit in each of the remaining planes in turn. Due to the reversibility of the encryption operation and adaptive coding, a legitimate receiver can achieve lossless reconstruction of the original plain-text image and error-free extraction of the secret data. The experimental results show that the proposed algorithm has a greater embedding rate and better security than several existing algorithms. The average embedding rates were found to be 3.027 and 2.937 bpp for the BOSSbase and BOWS–2 datasets, respectively, and this was also improved by more than 0.57 bpp on classical test images.关键词：reversible data hiding;encrypted domain;privacy protection;difference encoding;block compression- 126
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发布时间：2024-11-15 - “在智慧用电领域，专家提出了基于SOINN的非侵入式负荷识别方法，有效识别单电器与多电器，具有实际应用可行性。”摘要：With the development of intelligent electronic technology, the accurate identification of electrical load usage will have extensive user demands in the field of smart electricity. In order to achieve the online real-time accurate monitoring of the electrical equipment, this paper proposed a non-intrusive load identification method based on the online self-organizing incremental neural network (SOINN). This method included two steps, which are the load feature extraction and the load feature classification with the equipment identification. In the process of load feature extraction, a 12-dimensional feature extraction scheme was proposed, which includes the odd harmonics, the mean value, the variance value, the third-order moment, the fourth-order moment, the root mean square current, the peak value of power spectrum, and the trough value of power spectrum. In the second step, a method combining SVM and SOINN for the load feature classification and the electrical equipment identification was proposed to overcome the limitation of the traditional SOINN algorithm in appliance type recognition. The functional algorithms in the proposed method are implemented as executable functional modules for the microprocessor system using C++ programming language. The functional modules were then ported and deployed on the HPS side of the SoC FPGA, achieving collaborative high-speed data communication between FPGA and HPS. Eight types of conventional household appliances were selected as the load identification objects. A hardware experimental platform based on SoC FPGA was built to select the optimal load characteristics. The proposed method was validated for identifying online loads of both single and multiple appliances. Experimental results showed that the above 12-dimensional features were selected as the optimal feature combination for the method proposed in this paper. The recognition rates of both single and multiple appliances using the proposed method were above 95%. The proposed load identification method can effectively and accurately identify both single and multiple electrical appliances. The system has strong implementability, high flexibility, the advantages of online learning, and practical feasibility for practical applications.关键词：incremental learning;load identification;12-dimensional sample characteristics;FPGA
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发布时间：2024-11-15
INFORMATION ENGINEERING
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