最新刊期
卷 57 ， 期 2 ， 2025
- “在社交网络链路预测领域，专家提出了基于增量学习的IL-SNLP方法，有效提升了预测性能和模型训练速度。”摘要：Objective Various types of relationships in social networks exist between nodes, and the number of nodes changes over time. The heterogeneity and dynamic topology pose significant challenges for link prediction. Specifically, this study addresses three key issues: (1) an incremental update strategy for random walk sequences, (2) the extraction of the correlation of causal relationships, and (3) the construction of the mutual perceptron.Methods Therefore, an incremental learning social network link prediction (IL−SNLP) method is proposed. IL−SNLP consists of two components: the node embedding model and the prediction model. The node embedding model structures the network in layers based on relationship types. An incremental update strategy is designed for each network layer to generate updated random walk sequences, employing a temporal random walk approach. The incremental skip-gram model is then utilized to extract the embedding vectors of nodes from the random walk sequences in each layer. A probabilistic model is employed to extract the correlation of causal relationships between relationship types, enhancing the representation of nodes across different layers. In the prediction model, a multilayer perceptron (MLP) is utilized to construct the mutual perceptron, which predicts links by processing the embedding vectors of node pairs. The specific process of the node embedding model consists of temporal random walks, an incremental update strategy for random walk sequences, an incremental skip-gram model, and extracting the correlation of causal relationships. In the process of generating random walk sequences based on temporal random walks, the next node is selected if its timestamp is greater than the current timestamp. This approach ensures that both local structural and temporal information are preserved within these sequences. An incremental update strategy is introduced to update the random walk sequences in scenarios involving data increments. This updated strategy considers three situations: completely outdated sequences, partially outdated sequences, and the emergence of new nodes. The incremental skip-gram model is employed to extract and update the embedding vectors of nodes from the revised random walk sequences. This model automatically updates the unigram table and the noise distribution of all nodes using the updated random walk sequences without requiring access to previous data. For each relationship type, a conditional probability model is employed to calculate the probability of other relationship types occurring following a given relationship type. This model extracts the correlation of causal relationships. The correlation of causal relationships is incorporated into the node embedding vectors to generate the final embedding vectors. The prediction model utilizes an MLP to construct the mutual perceptron. The contribution of a node to a link is determined using the inner product of vectors. The contribution of a node pair to a link is then obtained by summing the individual contributions of both nodes. The computed node pair contribution is passed through a sigmoid function to determine the probability of a link forming.Results and Discussions Experiments are conducted to evaluate the prediction performance of IL−SNLP on three real-world social networks with varying sizes and sparsity levels: Super User, Math Overflow, and Ask Ubuntu. These datasets contain three relationship types: answering questions, commenting on answers, and commenting on questions. The evaluation metrics include AUC and F1−score. The experiments encompass several aspects, including comparative analysis, validation of effectiveness, assessment of the impact of the temporal random walk strategy, and evaluation of the effect of different incremental granularities on IL−SNLP. The comparison experiment results shows that the IL−SNLP enhances prediction performance over the baseline methods by 10.08% to 67.60% in AUC and 1.76% to 64.67% in F1−score. This experiment demonstrates the superior prediction performance of IL−SNLP. In addition, the baseline models do not perform effectively on sparse networks. However, the prediction performance of IL−SNLP on Ask Ubuntu and Super User decreases by only 4.54% and 5.25%, respectively, compared to its performance on Math Overflow. IL−SNLP exhibits a more stable prediction performance than the baseline methods. The validation of effectiveness experiments includes the validation of the prediction performance effectiveness of the causal relationship and mutual perceptron, as well as the validation of the time performance effectiveness of IL−SNLP. These results showed 1) that IL−SNLP improves the AUC by 51.82% to 67.78% and the F1−score by 61.47% to 81.91% across the three datasets, validating the two modules’ effectiveness and demonstrates that the correlation of the causal relationship and the mutual perceptron enhances the model’s prediction performance; 2) after only 16 to 20 iterations of training with inherited parameters, the model achieves the same performance as a model trained with non-inherited parameters after 200 iterations; 3) IL−SNLP improves time efficiency by 30.78% to 257.58%. This experiment demonstrated that IL−SNLP significantly reduces the running time and validates training effectiveness with inherited parameters. In addtion, the effect of two temporal random walk strategies on IL−SNLP shows that the random walk with bias is more effective; the effect of different incremental granularity levels on IL−SNLP reveals that the prediction performance of IL−SNLP on larger-scale networks is more affected by incremental granularity.Conclusions Accordingly, IL−SNLP exhibits superior prediction performance and significantly enhances runtime efficiency. In practical application scenarios, IL−SNLP can support the discovery and prediction of anomalous relationships in social networks, ensuring their security and stability.关键词：social network;link prediction;incremental learning;temporal random walk;probabilistic model374|341|0更新时间：2025-03-21
- “在机会网络领域，专家提出了基于特征相似性的机会网络链路预测模型FS-ET，提升了预测性能，为机会网络研究开辟新方向。”摘要：Objective An opportunistic network is a self-organizing network in which communication arises from the chances of node movement encounters. It can be applied in various scenarios, such as wildlife tracking, underwater rescue expeditions, and network coverage in remote areas. Link prediction involves determining whether a link is missing between two nodes or predicting whether a link will exist in the future, and this study aims to predict future links. Unlike ordinary networks, an opportunistic network is characterized by sparse node connections, complex structures, and frequent topology changes, leading to challenges in link prediction. Most existing opportunistic network link prediction methods employ network embedding algorithms for link prediction, but these algorithms have poor prediction effectiveness in networks with short average paths, and they do not fully utilize the network’s local structure information. Therefore, this study proposes a link prediction model for opportunistic networks based on feature similarity. The similarity of nodes is defined by considering node embedding vectors and local node information to improve the link prediction effect in opportunistic networks. Methods The Graph2vec model was employed to extract features of each snapshot. The sample entropies of the network, varying with candidate slicing slots, were obtained based on the network sample entropy calculation method. The slicing slot was determined using TOPSIS (technique for order preference by similarity to an ideal solution), which scores the candidate slicing slots by considering sample entropies and the training time of the Graph2vec model. The opportunistic network was sliced to generate a sequence of discrete network snapshots. The node embedding model based on GraphSAGE was utilized to extract the latent features of nodes. Considering that the connection duration of the nodes in the current snapshot influences the latent feature similarity of the nodes, the latent feature similarity was calculated by combining the Pearson correlation coefficient and the connection duration. The potential feature of the nodes alone was insufficient for extracting the features of network evolution. Therefore, the local structure information of the nodes was also considered. The topological similarity between nodes was obtained by evaluating the degree of nodes, the distance between nodes, and the number of paths between nodes. The similarity of nodes in each snapshot was achieved by fusing the latent feature similarity and topological similarity using the L2 norm. The traditional trend-moving average method was enhanced by assigning a decayed factor to each snapshot, ensuring that the latest snapshot had the greatest weight. The possibility of a connection between nodes at the next step was obtained using the improved trend-moving average method.Results and Discussions Experiments were conducted on four real opportunistic network datasets, ITC, MIT, Infocom05, and Infocom06, where the dataset information included the number of nodes and the collection time of the datasets. AUC (area under the receiver operating characteristic curve) and F1-score were used as evaluation indicators of model performance. The experiments were divided into slicing slot, model complexity, model generalization, comparative experiment, and ablation experiment phases. Based on the experiments on network sample entropy, Graph2vec model training time, TOPSIS comprehensive score, and AUC value under different slicing slots, it was found that when the slicing slots are 8, 10, 3, and 6 minutes for datasets ITC, MIT, Infocom05, and Infocom06 respectively, the comprehensive evaluation score curve reaches a stable trend, and AUC achieves a good effect. Therefore, 8, 10, 3, and 6 minutes were selected as the slicing slots for the ITC, MIT, Infocom05, and Infocom06 datasets. The complexity of the model was compared and analyzed from the perspectives of model complexity, including the proposed model and baseline models, as well as the FLOPs and Params of the models. In addition, the prediction time of the models was compared. The accuracy of the proposed method was tested using ten-fold cross-validation. On the ITC, MIT, Infocom05, and Infocom06 datasets, the average AUC of the proposed method exceeded 0.92, with the average AUC on the Infocom05 dataset exceeding 0.95, demonstrating that the model has good generalization. After removing the node topological similarity module in the model for ablation experiments, the AUC of the proposed model decreased by 1.07% to 3.86%, and the F1-score reduced by 6.12% to 15.48%. This validates the effectiveness of the node topology similarity module. Compared to the baseline methods LSTM (long short-term memory), NESND (network embedding supplementing similarity information in the network domain), E–LSTM–D (encoder–LSTM–decoder), GCN–GAN (graph convolutional network–generative adversarial network), SE–GRU (structure embedded gated recurrent unit neural networks), and GC–LSTM (graph convolution embedded LSTM), the AUC improved by 0.5% to 24.8%, and the F1-score increased by 1.15% to 22.77%. Therefore, the proposed model achieves better performance.Conclusions This study proposes a slicing method based on network sample entropy and model training time, as well as an opportunistic network link prediction model, FS–ET, which is based on feature similarity. The experimental results on four real datasets show that, compared to baseline models, FS–ET achieves better performance.关键词：opportunistic network;link prediction;node embeddings;latent feature similarity;topological similarity207|293|0更新时间：2025-03-21
- “在无线传感器网络定位领域，IPLA算法通过改进PSA和混沌映射技术，有效降低了定位误差，提升了算法收敛性。”摘要：Objective This study proposes an improved 3D WSN localization algorithm with an enhanced particle swarm algorithm (PSA) to address the high positioning errors and instability encountered with the traditional 3D DV–Hop localization algorithm in locating wireless sensor network nodes. The proposed improved particle localization algorithm (IPLA) specifically targets and mitigates the error steps inherent in the traditional 3D DV–Hop localization process.Methods Firstly, in the traditional method, the nodes within the communication radius were considered as 1-hop, which caused the hop count calculation to be insufficiently refined and produced a significant error. In contrast, this study adopted a dual communication radius, broadcasted at R and R/2, respectively, to refine the hop count calculation and obtain the minimum hop count with a much smaller error. Secondly, the calculation of the average hopping distance in the traditional method was based on the topology of a linearly distributed wireless sensor network. The average hopping distance calculated by this method affected the accuracy of the localization. Therefore, a fitness function with a distance weighting factor was established. The improved PSA algorithm with meta-starting was used for the solution, and the introduction of chaotic mapping into the PSA algorithm enhanced the algorithm’s optimization capability and reduced the error in obtaining the average hopping distance.Finally, for the problem of large errors in obtaining node coordinates by the least squares method of the traditional method, an adaptation function with weights was established to reduce the error existing in the topology. The improved PSA algorithm was again employed in this paper instead of the least squares method, which was the traditional method, to further improve the accuracy of locating the nodes. Simulation experiments were conducted in different scenarios to compare the proposed IPLA algorithm with the traditional 3-dimensional DV–Hop algorithm, DBO algorithm, and WBOA algorithm in terms of localization performance. The results showed that the IPLA algorithm has good effects and a better convergence ability in improving the localization error of wireless sensors.Results and Discussions Comparative experiments on algorithm iteration performance and localization simulation were conducted using the IPLA algorithm, the traditional 3-dimensional DV–Hop algorithm, and other algorithms. The comparative analysis demonstrated the advantages of the IPLA algorithm. It achieved convergence in approximately five iterations, which is faster than the PSA, the adaptive weighted butterfly optimization algorithm (WBOA), and the dung beetle optimization algorithm (DBO). In addition, the IPLA algorithm exhibited lower fitness values at the convergence point, indicating a more efficient search for optimal solutions. In positioning simulation experiments, the IPLA algorithm was compared to the 3D DV–Hop algorithm optimized by the traditional 3D DV–Hop, DBO, and WBOA algorithms. It was found that with an anchor node ratio of 0.15 and a communication radius of 35 m, the IPLA algorithm performed better in reducing the positioning error as the total number of nodes increased. When the total number of nodes reached approximately 150, the localization errors of all algorithms stabilized, and the IPLA algorithm exhibited the lowest error value. With a further increase in the total number of nodes, the localization errors of the WBOA and DBO algorithms fluctuated, while those of the IPLA algorithm remained stable, demonstrating its superiority in complex topologies. In tests with different communication radii, when the anchor node ratio and the total number of nodes were set to 0.15 and 100, respectively, the normalized localization errors of all algorithms stabilized around 40 m with the increase in the communication radius. In contrast, the IPLA algorithm exhibited the lowest error, which could reach 0.17. This indicates that the IPLA algorithm can maintain stable localization performance despite increases in the communication radius and complexity of the topology. Finally, in the anchor node ratio test, when the total number of nodes and the communication radius were set to 100 and 35 meters, respectively, the IPLA algorithm outperformed the other three algorithms at different anchor node ratios. The performance of the IPLA algorithm started to stabilize at an anchor node ratio of about 0.2, and its normalized localization error was lower than that of the other algorithms. This demonstrated that the IPLA algorithm can maintain a low localization error across different anchor node ratios and maintain good performance even with changes in topology. Conclusions This study proposes the IPLA algorithm to solve the 3-dimensional DV–Hop algorithm based on non-ranging WSN positioning algorithms, which are characterized by significant errors and instability. This algorithm utilizes the dual communication radius, the distance weighting factor, and the improved PSA algorithm to optimize the positioning nodes and obtain coordinates with lower positioning errors. Simulation experiments demonstrated that the IPLA algorithm has superior convergence ability and provides better positioning accuracy and stability than the DV–Hop, DBO, and WBOA algorithms. The PSA algorithm is used twice, and although it increases energy consumption, it improves the positioning accuracy and will be the focus of future research.关键词：wireless sensor networks;3-dimensional WSN localization;chaotic mapping;dual communication radius183|180|0更新时间：2025-03-21
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Weak Speech Signal Detection in High Interference Environment Based on Distributed Acoustic Sensing AI导读
“在隧道塌陷事故搜救领域，专家提出了基于短期自相关特征的算法，有效提取低信噪比环境下的人声信号，为复杂场景下语音活动检测提供新方案。”摘要：Objective The distributed acoustic sensing (DAS) system can be applied to personnel search and rescue and voice signal localization in the event of tunnel collapse accidents. However, as the front end of the speech signal processing system, existing voice activity detection (VAD) algorithms do not yield satisfactory results in detecting human voices from DAS speech data. Conducting experiments in a real tunnel environment presents several challenges: (1) the inability to manually annotate extensive DAS speech data makes it difficult to obtain labeled data for supervised training, and (2) due to the noisy on-site environment and limited signal acquisition methods, DAS-collected speech signals are accompanied by substantial and complex high-energy noise, causing some VAD algorithms to lose robustness. Therefore, this study proposes a robust VAD algorithm (ST–ACF) based on short-term autocorrelation features.Methods The algorithm investigates the acoustic characteristics of DAS speech by combining pitch information and the autocorrelation function to detect relevant harmonic features of speech frames. This enables the VAD algorithm to extract all actual human voices, even in DAS system environments with an extremely low signal-to-noise ratio (SNR), less than −10 dB. Due to the significant interference caused by strong noise in DAS speech, the ST–ACF algorithm consists of denoising and speech detection channels. DAS noise primarily consists of continuous high-frequency noise and sudden high-energy noise. In the denoising channel, based on the study of the periodicity of pitch information in speech, a dual-channel time window is designed to denoise these two typical types of noise. Feature analysis of DAS speech data revealed that pitch periodicity and non-stationarity in speech and these two types of noise exhibit distinct patterns. Continuous high-frequency noise lacks harmonic properties, presenting stable non-pitched characteristics. Sudden high-energy noise has periodicity, and there is a traceable changing trend in pitch at the moment of eruption. Speech shares similarities with the latter, but due to the continuity of human speech, pitch period changes in speech are shorter. Therefore, ST–ACF uses spectral flatness (SFT) as an indicator to determine the presence of pitch in speech frames. A dual-channel time window is designed to capture short-term pitch changes. In a continuous time window, the SFT value change curve of DAS speech is fitted into a cosine function, revealing multiple “valleys” in speech segments, indicating the presence of multiple pitch frames, which is not a characteristic of noise. The incorporation of a time window in ST–ACF enables more accurate detection of different noise types, eliminating strong noise interference in VAD. ST–ACF improves the spectral local harmonicity feature (SLH) in the speech detection channel. Despite SLH’s stability in low SNR conditions, its overall performance is suboptimal. Given that SLH feature values in speech exhibit larger absolute values and variability than noise, the ST–ACF algorithm optimizes SLH by considering two dimensions of frame variation, SLH feature values and variability, by multiplying them to maximize the distinction between speech and noise. Considering the significant differences in variability scales between different sound types, normalization of all variability values is required before computation. The improved ST–ACF considers the magnitude of its values and accounts for their changing trends, enhancing the algorithm’s capability to process critical data and improving its accuracy in distinguishing noise from speech onset.Results and Discussions The performance of VAD was evaluated using the frame error rate (FER). The dataset employed for testing comprises two parts: (1) authentic speech signals collected by the DAS system in the Ya’an Shuikou Tunnel, with an average SNR of −10.3 dB, and (2) simulated data generated by combining noise from the NOISEX–92 dataset with human speech from the TIMIT database. The results indicate that ST–ACF exhibits minimal susceptibility to high-energy noise environments, demonstrating robustness even at –10 dB, with a FER of only 19.74%. Compared to the –5 dB environment, the FER fluctuates by approximately 2%. Following optimization, ST–ACF achieves a 5.91% performance improvement compared to SLH. This significant enhancement is also evident in the DAS dataset, where ST–ACF attains its best performance, showing a remarkable 21.11% improvement. ST–ACF maintains robust performance across different noise sets, proving its capability to handle complex environments. The comparison of ST–ACF performance under different noise sets demonstrates that the time window strategy, based on assessing the invariance of audio features over a period, effectively eliminates stationary noise. LTSV, which follows a similar concept, performs well in high-frequency stationary noise. Due to the uniqueness of the proposed time window, ST–ACF demonstrates the ability to handle non-stationary noise. Even when subjected to the most challenging gunshot noise, ST–ACF maintains an FER of less than 25%. The introduction of the time window is crucial to improving ST–ACF’s performance, contributing to a 5.07% enhancement in the DAS dataset, whereas optimizing the autocorrelation function results in a modest 1.89% improvement. This is primarily because the time window removes a significant portion of noise, preventing interference from complex noise in VAD, while optimizing the autocorrelation function preserves the integrity of speech extraction.Conclusions The maximum correlation between DAS noise and speech can be identified across multiple dimensions, facilitating targeted detection for each by integrating speech algorithm principles and analyzing DAS speech data. This research approach addresses certain shortcomings in VAD algorithms. ST–ACF successfully achieves its intended objectives, fully extracting effective speech from DAS data while preserving the integrity of the speech signal. ST–ACF exhibits remarkable performance in low SNR environments, highlighting its potential for application in diverse and complex scenarios. This fulfills its intended function and paves the way for future research in speech signal processing based on DAS.关键词：distributed acoustic sensing;voice activity detection;low signal-to-noise ratio;pitch information;autocorrelation function152|203|0更新时间：2025-03-21 - “在聚类算法领域，研究者提出了一种基于密度峰值的初始类中心决策值选择方法和密度调整谱聚类算法，有效解决了尺度参数设置和聚类结果不稳定的问题，为大规模数据集聚类分析提供了新方案。”摘要：Objective Clustering involves partitioning given data into multiple classification clusters without requiring knowledge of the true labels. In other words, clustering is an unsupervised learning process that ensures that samples within the same cluster are as similar as possible while those in different clusters are as dissimilar as possible. Traditional clustering algorithms can be categorized into five primary types: hierarchical, density-based, grid-based, model-based, and partition-based algorithms. However, these traditional models are sensitive to the cluster number K, outliers, and noise points. In addition, the selection of the initial cluster center is set artificially, and the cluster shape cannot extend arbitrarily. Spectral clustering, a clustering algorithm based on spectral graph theory, transforms the clustering problem into an optimal partition problem of the graph. This approach has emerged as one of the most widely adopted techniques in various domains, including data mining, face recognition, and image segmentation.Methods The spectral clustering algorithm provides simplicity in implementation, robustness to high-dimensional data, and flexibility in handling diverse sample space shapes. This enables global optimization and often results in superior performance compared to traditional clustering algorithms. However, existing spectral clustering methods encounter challenges, such as determining the scale parameter, suboptimal clustering results in multi-scale datasets, and instability in the obtained clusters. A density-adjusted spectral clustering algorithm based on neighborhood standard deviation is proposed to address the unstable clustering results caused by the random selection of initial cluster centers and the artificial setting of scale parameters in spectral clustering. This approach incorporates both global and local data information. The proposed algorithm treats the initial class center value and scale parameter as decision variables to achieve adaptive optimization and enhance spectral clustering. The neighborhood labeling difference is employed to determine the initial cluster center value, while the scale parameter is optimized to improve the expression of the Gaussian kernel function. The calculation methods for the scale parameter, sample local density, and initial cluster center of the density peak are redefined using the neighborhood standard deviation. Therefore, the proposed spectral clustering algorithm eliminates the need for neighborhood parameter input and produces stable clustering results. First, an initial class center decision value algorithm based on density peak (DP_KD) is designed to resolve the issue of unstable clustering results in density-adjusted spectral clustering. First, the initial cluster center value determination method replaces the artificial setting of scale parameters. In this process, K points are randomly selected from the dataset as initial clustering centers and different classes are assigned based on each selected point. Then, the reciprocal of the sample neighborhood standard deviation is used as a parameter to measure the local density of the sample, while the average distance between samples is utilized to calculate the corresponding neighborhood radius of each sample. Simultaneously, the neighborhood standard deviation inverse is defined as the local sample density, and the sample with the highest density is assigned the minimum Euclidean distance among the samples. Finally, the product of sample local density and sample distance is defined as the initial class center determination value λ. The samples with the largest λK are selected as the initial class centers for this algorithm, forming the center value Decision algorithm DP_KD.Results and Discussions The change of the scale parameter influences the construction of the similarity matrix, which affects the Laplacian matrix and the formation of the eigenvector space. In the spectral clustering algorithm, the similarity matrix is critical in determining the quality of the final clustering outcomes. Therefore, the Euclidean distance between a sample and its p-th nearest neighbor is introduced as the scale parameter for each sample, utilizing the neighbor information to enhance the similarity matrix and reduce the sensitivity of the spectral clustering algorithm to the scale parameter. In addition, based on the optimized initial class center decision value and the nearest neighbor parameter method, a density-adjusted spectral clustering algorithm based on neighborhood standard deviation (DSSD) is proposed to address the instability of clustering results caused by the random selection of initial cluster centers and the artificial setting of scale parameters. The proposed algorithm effectively fine-tunes the similarity between sample points in regions of varying density for multi-scale datasets.Conclusions Experimental results indicated that, compared to other spectral clustering algorithms, the proposed algorithm achieves improved clustering performance and yields more stable clustering results. When compared to IK_DM, IIEFA, OFMMK–means, classical clustering algorithms such as K–means and K–medoids, as well as the AP and SNN–MSC algorithms, the clustering performance of the DP_KD algorithm across seven UCI datasets is superior to that of the other algorithms. These findings demonstrate the feasibility and effectiveness of integrating the DP_KD algorithm into density-adjusted spectral clustering as a replacement for classical clustering algorithms. The experiments are conducted on seven UCI datasets: Iris, Wine, Seeds, Yeast, Glass, Ecoli, and Waveform. Four evaluation metrics, Accuracy (ACC), Purity, Rand Index (RI), and F–measure (F1), are employed to assess the clustering performance. A higher value for these evaluation indices signifies the superior performance of the proposed DP_KD algorithm. In general, the clustering effectiveness of the DP_KD algorithm across the seven UCI datasets surpasses that of the other algorithms. In addition, the DSSD algorithm is compared to four spectral clustering algorithms: ADSC, WDSC, SC, and PRSC. The experiments are conducted on seven UCI datasets: Sonar, Musk, Breast, Statlog, Madelon, Segmentation, and Waveform. The ACC index is utilized to evaluate the clustering effect of these spectral clustering algorithms. Experimental results demonstrated that the DSSD algorithm enhances the clustering effectiveness of density-adjusted spectral clustering and outperforms other advanced spectral clustering algorithms.关键词：spectral clustering;density adjustment;neighborhood standard deviation;adaptive;density peak159|329|0更新时间：2025-03-21
INTERNET OF THINGS
- “在航空航天高性能制造领域，针对局部点云缺失问题，提出了模型重构方法，显著提升了重构模型精度。”摘要：Objective With the increasing demand for improved assembly performance, conducting assembly performance analysis based on measured data has become increasingly important. At the present stage, assembly performance analysis requires model refactoring to predict assembly errors. The refactoring of a model of point cloud inverse reconstruction can reflect real physical information, which solves the deviation between simulation and actual results. However, large-sized and structurally complex parts face challenges such as blocks, which result in incomplete point cloud information. Therefore, the overall surface point cloud of the part cannot be fully obtained, preventing the refactored model from accurately representing real physical information. Therefore, research on model reconstruction methods without local point clouds is essential. This study proposes a Laplace mesh transformation method to deform the theoretical triangular mesh based on the scanned area. The corresponding region of the theoretical model is replaced with the scanned point cloud to obtain a complete point cloud of the part.Methods The theoretical model and the scanned area point cloud were used as data sources. The triangular mesh formed by the scanned region point cloud and the surface of the theoretical model constituted a two-dimensional manifold reference domain, ensuring that any point selected from the reference domain had a corresponding mapping in the triangular mesh. Then, the Laplacian mesh transformation was applied to achieve mesh mapping. This process utilized the Laplacian operator in the vertex differential equation of the discrete mesh model to express local features regarding the differential properties of the discrete scalar field on the surface. The reconstructed differential properties preserved the original meaning of the scalar fields, ensuring that the transformation process maintained the local feature details of the initial surface to the maximum extent. In other words, the mapped points of the triangular mesh on the reference domain could be projected onto the two-dimensional manifold triangular mesh without changing the mesh topology. Finally, the scanned point cloud carried on region partition, and the Interactive Closest Point (ICP) algorithm was utilized to match the scanned area with the theoretical model. The theoretical model, driven by the matching regions, was adjusted to obtain the surface points in the absence region of the point clouds of actual parts. These points replaced the corresponding region points, resulting in the parts’ complete surface point cloud. The primary difference between the proposed method and traditional local point cloud reconstruction approaches was that the point cloud fitting surface was no longer used for substitution. Instead, the original model was driven to adapt. Although the local model was efficiently reconstructed, the absence regions of the point cloud were ensured to transform in alignment with the actual model, improving the reconstructed model’s fidelity.Results and Discussions This study employed the outer cylinder of the landing gear as an experimental object to verify the proposed model reconstruction method. A comparative analysis between the traditional method and the proposed approach revealed that direct substitution in conventional methods resulted in misalignment at the junction of the scanned area and the absent point cloud region, leading to inconsistencies with the actual part. In contrast, the model reconstructed using the proposed method exhibited a smooth transition area, ensuring surface continuity. The deviation cloud map comparing the theoretical model with the complete point cloud indicated a maximum deviation of 0.802 mm, representing the largest error in 3D-printed part manufacturing in the middle of the outer cylinder. The model reconstructed using the traditional localized point cloud data approach exhibited a maximum deviation of 0.798 mm, whereas the model reconstructed using the proposed method had a maximum deviation of 0.719 mm, primarily in the middle region of the cylinder segment. The improvement in accuracy was not substantial due to the limited intermediate information in the scanned area. Additional control experiments were conducted by reducing the absent point cloud region. In these experiments, the maximum deviation for the model reconstructed using the traditional method remained at 0.798 mm, while the proposed method yielded a maximum deviation of 0.436 mm. The deviation in the outer cylinder was significantly reduced to 0.236 mm due to increased scanned data in the middle region of the outer cylinder, whereas the traditional method failed to reduce the deviation. When the point cloud coverage reached about 90%, another control experiment was conducted. The maximum deviation for the model reconstructed using the traditional method was 0.717 mm, while the proposed method reduced the maximum deviation to 0.145 mm. These findings indicated that increased scanned area decreases the reconstructed model’s overall deviation, validating the proposed approach’s rationality.Conclusions Compared to traditional direct replacement methods, the results showed that the proposed method effectively addresses surface misalignment issues and better preserves the reconstructed model’s surface continuity. In addition, the overall accuracy of the reconstructed model significantly improves as point cloud coverage increases. When the point cloud coverage reached about 90%, the maximum deviation of the reconstructed model was reduced to 0.145 mm, confirming the feasibility of the proposed method.关键词：local point cloud;loss of information;model reconstruction;Laplace mesh transformation338|255|0更新时间：2025-03-21
- “在水下构筑物健康诊断领域，专家提出了基于声光组合测量的3维可视化技术体系，提高了缺陷检测效率和精度，为水下构筑物表面缺陷的3维可视化及定量描述提供新方法。”摘要：Accurately grasping defect feature information on the surface of underwater structures provides a scientific basis for the health diagnosis and safety assessment of these structures. This study presents a three-dimensional visualization method for surface defects of underwater structures based on acousto-optic combination measurement, addressing the technical bottleneck of limited testing equipment size and the challenges of synchronized utilization and fusion of acousto-optic data in narrow underwater spaces. First, a quantitative characterization method that reflects typical feature parameters of defect targets is developed by capturing effective data using a combination of sound and light measurement technology. Then, a sound and light feature data matching method is proposed, comprehensively considering typical target features. Using defect features in a local single optical texture image as the search target enhances the matching degree of sound and light data, enriching the detail information in the global concatenated texture image. Finally, a three-dimensional visualization system for surface defects of underwater structures is developed by constructing a texture feature image enhancement algorithm, synchronously utilizing sound and light combination data. The results indicated that the combination of sound and light measurement technology improves the efficiency and accuracy of surface defect detection in underwater structures. The synchronous use of acoustic scanning data and optical texture information highlights the three-dimensional visualization features of surface defects in underwater structures. This study provides a novel technical method for the three-dimensional visualization and quantitative description of surface defects in underwater structures.关键词：Underwater structures;Sound and light combination measurement;Visualization of defects;acoustic scanning;Surface texture features324|98|0更新时间：2025-03-21
- “在结直肠癌预防和肠道疾病诊断领域，专家提出了深度感知的息肉分割网络DANet，显著提升了息肉边界和形状的识别能力，为息肉分割问题提供解决方案。”摘要：Objectives Polyp segmentation is crucial for preventing colorectal cancer and diagnosing intestinal diseases. However, existing polyp segmentation algorithms often fail to consider the three-dimensional structure of polyps, limiting their performance. This study proposes a Depth-Aware Network (DANet) for polyp segmentation, integrating depth information to enhance segmentation accuracy, particularly in identifying polyp boundaries and shapes. The method is designed to improve the model’s capability in capturing the spatial structure of polyps, enhancing overall segmentation accuracy.Methods The proposed DANet consists of three main components: a spatial branch, a depth branch, and a feature fusion module. Specifically, the spatial branch utilizes a Pyramid Vision Transformer (PVT)-based encoder, which captures multi-scale feature representations from endoscopic images. This encoder processes the input image through multiple stages, progressively reducing the spatial resolution while extracting detailed and hierarchical features. This approach enables the network to capture local and global spatial information, which is essential for accurately segmenting polyps of varying sizes and shapes. The depth branch is responsible for generating depth maps that provide critical insights into the three-dimensional structure of polyps. These depth maps are obtained using the Depth Anything Model, a robust pre-trained model capable of producing high-quality depth estimates from endoscopic images. The generated depth maps provide valuable information regarding polyp protrusions and shapes, which are often challenging to discern using conventional 2D imaging techniques. A depth attention module is incorporated to enhance features specifically related to polyp protrusions. This module dynamically refines focus on depth-based features, enabling the network to emphasize regions with significant structural variations and improving segmentation accuracy. The feature fusion module integrates spatial and depth features through an adaptive fusion process. This fusion occurs across multiple scales, ensuring that depth-related variations are effectively incorporated into the spatial feature maps at different resolutions. The model successfully recognizes polyp boundaries and shapes by combining spatial and depth features. The adaptive fusion mechanism allows the network to selectively prioritize the most informative features from both domains, leading to more precise and robust segmentation results.Results and Discussions Experiments were conducted on five public polyp segmentation datasets, and DANet’s performance was compared to several state-of-the-art methods. The results indicated that DANet substantially improved segmentation accuracy across multiple evaluation metrics, including mean Dice (mDice) and mean Intersection over Union (mIoU). For example, on the Kvasir–SEG dataset, DANet attained a mDice score of 0.911 and a mIoU of 0.855, outperforming other methods such as PraNet, SANet, and MSNet. Similarly, on the CVC–ClinicDB dataset, DANet achieved a mDice of 0.934 and a mIoU of 0.884, demonstrating its superior performance. The incorporation of depth information enhanced the model’s ability to capture the three-dimensional structure of polyps, which is crucial for accurately identifying polyp boundaries and shapes. In addition, DANet exhibited strong generalization capabilities when evaluated on datasets such as ETIS and EndoScene, yielding competitive results across all metrics. Ablation studies were conducted to assess the contributions of each module. The results showed that the entire model, which includes both the depth branch and the feature fusion module, achieved the best performance, confirming the effectiveness of integrating depth information. Regarding computational efficiency, DANet maintains a balance between accuracy and processing speed. The network was trained using the PyTorch framework on an NVIDIA TITAN RTX 3090 GPU, completing the training process in 100 epochs. The results indicate that DANet is well-suited for real-time medical applications due to its efficient architecture.Conclusions The proposed Depth–Aware Network (DANet) significantly improves polyp segmentation accuracy by incorporating depth information. The integration of spatial and depth features enables the model to capture the three-dimensional characteristics of polyps more accurately, improving the recognition of polyp boundaries and shapes across different datasets. The experimental results validate DANet’s generalizability, while ablation studies confirm the importance of the depth and feature fusion modules. This approach has potential applications beyond polyp segmentation, extending to other medical image segmentation tasks that require accurate three-dimensional structural recognition.关键词：Depth-aware;Polyp segmentation;deep learning;depth map269|172|0更新时间：2025-03-21
INTELLIGENCE INTERDISCIPLINARY SCIENCE AND ENGINEERING
- “在高水头泄洪放空洞弧形闸门出口领域，专家通过模型试验与数值模拟，揭示了空蚀破坏的水力学成因，并提出了掺气减蚀水力设计方案，为保障高水头泄洪建筑物安全运行提供科学依据。”摘要：Objective In high-head spillway tunnels, aeration devices are often installed at the outset of the radial gate to reduce cavitation erosion. Despite these precautions, cavitation erosion persists due to the complex flow pattern near the radial gate. Once the flow is discharged into an open channel, the pressure relief effect lead to the diffusion of high-speed flow and the flow quickly reaches the bottom and side walls of the channel, resulting clogging risk in aeration area. Up to the present, the hydraulic reason for weakening the aeration performance are still unknown, and there are little hydraulic designs to improve the aeration protection for the radial gate. Typically, the lateral and bottom aerators are installed at the pressurized outlet when the flow is directed into an open channel under high-head conditions. However, the lateral and vertical diffusions of flow complicates the flow pattern near the radial gate, influencing the effectiveness of the lateral and bottom aerators. It is significant to understand the aeration protection nullification mechanism and propose effective aerator designs for the sidewall and bottom protection. The present study focused on a given prototype hydraulic engineering featuring a radial gate in a high-head spillway tunnel , where the tunnel wall is damaged by cavitation erosion.Methods Focused on the cavitation erosion in the given prototype tunnel, the present study obtained the hydraulic characteristics based on experimental and numerical results, optimizing the lateral aerator. The physical model was designed based on Froude similarity criterion, and the numerical simulation model was established according to the prototype tunnel. The effects of aeration devices on the aeration protection efficiency were analyzed using aeration flow pattern, cavity length, flow velocity field and flow cavitation number. In the present study, the RNG k-ε turbulent model was used to simulate three-dimensional flow field of the radial gate, the VOF was used to simulate the aeration cavity, and the partial differential equations were discretized based on the control volume method, the SIMPLER model was employed for numerical simulation. The three dimensional structured grids were constructed for the spillway tunnel, and the high grid density in the radial gate, aeration cavity and wall boundary areas can enhance the accuracy of calculation.Results and Discussions The experimental results show that the three dimensional diffusion is significant when the flow is separated from the radial gate, featuring strong water-wing effect above the flow. The lateral aeration cavity is shorter than the bottom aeration cavity, resulting in weakened lateral aeration. The re-attachment flow cannot entrain enough air into the flow. Moreover, the lateral diffused flow may encroach upon the bottom cavity area, increasing the risk of cavity clogging. The numerical results show that the lateral impact and rebound motion of flow on the sidewall cause a low-pressure area when the high-speed flow discharges from the radial gate. The cavitation erosion observed in the prototype tunnel aligns with the low pressure and clear water area on the sidewall. For different gate opening tests, the above phenomenon persists due to the constrain of the radial gate on the flow diffusion. It is also the main reason for the side-wall cavitation erosion under high-speed flow and low flow cavitation coefficient. With the increase in gate opening, the restraining effect of radial gate decreases and the lateral cavity length increases. Especially under high-head and partial gate opening conditions, the adverse phenomenon is even worse. In order to prevent the cavitation erosion on sidewalls, the current study proposed two hydraulic design principles: increasing the sidewall pressure and flow cavitation coefficient and optimizing the design of shrinking side-wall aerator. Based on experimental and numerical results, the one-step and two-step sidewall aeration designs are proposed to improve the flow cavitation coefficient and eliminate the clear water area. The optimized aerators can make the flow cavitation number σ larger than 0.3 for all gate opening tests. However, for the one-step aerator, the lateral cavity length surpasses the bottom cavity for large gate opening (Fr < 6.0), leading to the weaken aeration. The ratio of lateral and bottom cavity length is smaller than 1.0 to avoid strong water-wing effects and cavity plugging. The process of lateral impact and rebound can reduce the clear water area of the sidewall, while the multi-step aeration process can improve the aeration level in the cavitation erosion dangerous area. It should be noted that the present study mainly focus on the macroscopic aeration properties, such as aeration cavity length and flow cavitation number, which can verify the availability of aeration protection. For the microscopic aeration properties, such as air concentration distribution, bubble quantity and size distributions, the effects of aerator factors on air–water flows need to be further explored.Conclusions The present study conducted a series of experiments and numerical simulations to investigate the reason of the cavitation erosion in high-head spillway tunnels, proposing effective lateral aerator designs to improve the aeration protection. The lateral flow causes the weakened aeration, resulting in a clear water area on the sidewall and low flow cavitation coefficient. For all gate opening tests, the combination of two-step lateral aerator and the bottom aerator can effectively eliminate the clear water area on the tunnel walls, and the three-dimensional aeration is sufficient with the steady air–water flow pattern. The excellent aeration performance of the two-step aerator is adaptable for all gate opening tests and can improve the safety of high-head spillway tunnels.关键词：high-speed flow;radial gate;cavitation erosion;aeration protection;bottom tunnel80|72|0更新时间：2025-03-21
- “在河流动力学领域，专家基于沙波地形水槽实验数据，建立了沙波迎流面流速和切应力垂向分布公式，揭示了沙波床面水流运动特征和空间变化规律。”摘要：Objective Dunes are shaped by the interaction between flow and sediment grains at the riverbed. The flow structures are influenced by bedforms and exhibit non-uniform characteristics due to changes in asymmetric features. Common formulas and predictors of flow structure are primarily based on the horizontal flow velocity over a flat bed and are described using length-averaged data of dunes. However, velocity over sand dunes continuously accelerates and decelerates along the stoss side, and the inherent relationship between the horizontal and vertical components is often neglected in velocity profile calculations. Experimental data and theoretical analysis are utilized to examine the variation characteristics of velocity and turbulent shear stress on the stoss side of dunes. Vertical distribution formulas for velocity and shear stress are derived, incorporating information on flow velocity's horizontal and vertical components. This study further reveals the effect of bedforms on flow characteristics and improves the calculation accuracy of velocity and turbulent shear stress over dunes.Methods The distributions of velocity and shear stress along the stoss side were quantitatively analyzed based on experimental data from flume studies with dunes. Statistical methods were employed to propose the concept of the flow velocity deviation angle. A sub-coordinate system near the riverbed was established based on dune geometry, and the relationship between the standard coordinate system and the sub-coordinate system was derived using coordinate rotation. Utilizing the vertical two-dimensional flow momentum equation and the Boussinesq hypothesis, theoretical derivations for the vertical distribution formulas of velocity and shear stress on the stoss side of dunes were developed. Experimental data from two published studies were utilized to validate the proposed formulas.Results and Discussions The variation characteristics of flow structure over dunes were influenced by both the stoss side angle and the horizontal distance along the stoss side. As the flow passed over the crest, velocity exhibited dynamic deceleration in the main flow area and acceleration near the bottom, causing a positive flow velocity deviation angle near the water surface. With decreasing relative water depth, the flow velocity deviation angle became negative, reaching its minimum at 0.1 times the relative water depth before returning to a positive value downstream along the stoss side. The distribution of the flow velocity deviation angle after the reattachment point followed an exponential function and was accurately described. The velocity vector variation with water depth was correlated with the velocity vector near the bottom of the stoss side through coordinate transformation. The probability distribution of fluctuating velocity, considering water particle interactions, aligned with a binormal distribution. The vertical distributions of velocity and turbulent shear stress on the stoss side of dunes were derived from the vertical two-dimensional dynamic flow equations, incorporating both horizontal and vertical flow velocity components. Validation results showed that the calculated values closely matched the measured flume data for both deep and shallow water depths, and the proposed velocity formula effectively captured velocity distribution characteristics influenced by velocity vector adjustments along the stoss side. The feedback effect of bedforms on flow structure was also evident in the distribution patterns of the momentum transfer coefficient and turbulent diffusion flux, which were well described by the established formulas and aligned with experimental observations. As flow progressed downstream along the stoss side, the vertical distribution of the momentum transfer coefficient exhibited a trend of monotonically increasing. The vertical velocity distribution over dunes continuously evolved from trough to crest, reflecting the complex characteristics of turbulent structure.Conclusions The results demonstrated that the established flow velocity deviation angle formula effectively captured the adjustment mechanisms of the flow velocity vector along the stoss side of dunes. Mathematical expressions describing the transformation relationships between standard and sub-coordinate systems were derived using coordinate rotation, and vertical distribution formulas for flow velocity and turbulent shear stress were derived, incorporating the dynamic characteristics of horizontal and vertical components of flow velocity. Comparison between experimental data and calculated values indicated that the proposed expressions effectively characterized the influence of sand dunes on the spatial distribution of flow velocity for both deep and shallow water depths. However, the influence of boundary layer separation over dunes was not fully considered when deriving the formulas for vertical velocity and turbulent shear stress distribution. Therefore, further research is necessary to investigate the adjustment mechanisms of turbulent structure and the spatial distribution characteristics of flow velocity resulting from boundary layer separation over dunes.关键词：Dunes;Velocity profile;Velocity deviation angle;Stoss side;Turbulent shear stress165|426|0更新时间：2025-03-21
- “在一维河网水动力学模拟领域，专家基于格子Boltzmann BGK模型提出了改进算法，有效提高了计算效率，为河网水动力模拟提供了新方案。”摘要：Objectives A refined approach is introduced to effectively simulate hydrodynamics in one-dimensional (1D) river networks, enhancing the computational efficiency of the traditional junction water stage iteration method.Methods This approach utilizes the lattice Boltzmann Bhatnagar-Gross-Krook (BGK) model, specifically designed for 1D unsteady open-channel flows. The 1D Saint-Venant equations are solved using the lattice Boltzmann BGK model, where discrete velocity vectors are represented by the D1Q3 model. Equilibrium distribution functions are established to recover the 1D Saint-Venant equations through Chapman-Enskog analysis. The method approximates the spatial derivative of the cross-sectional area in the equilibrium distribution functions using a second-order central difference scheme, achieving an overall second-order spatial accuracy. The coupling of the river network is facilitated through the junction water stage iteration method, initially segmenting the network into various sub-reaches. Water level boundary conditions are imposed at the upper and lower boundaries of each sub-reach. At each time step, the coupling water level is iteratively adjusted to maintain connectivity conditions at all junctions. Given that the lattice Boltzmann BGK model inherently employs an explicit algorithm, it eliminates the necessity for multiple iterations to compute the coupling water level.Results Standard verification scenarios, including steady flows in a looped channel network and unsteady flows in combined looped and treelike networks, were simulated to evaluate the accuracy of the refined method. The hydrodynamics of the middle and lower reaches of the Han River during the autumn flood of 2021 were simulated to validate its utility in real-world applications. The results are as follows:1) For the steady flow scenario in a looped channel network, the simulation outcomes were benchmarked against theoretical analyses, achieving a relative error of up to 7.43%.2) In scenarios involving unsteady flows in combined looped and treelike networks, the refined method precisely simulated the flooding process, with the flood hydrograph’s shape, peak discharge and flood rise and fall times aligning well with prior studies. Various metrics, including total simulation time, total iteration count, average iterations per time step, and average iteration time of the refined method, were compared to those obtained using the traditional junction water stage iteration method and the junctions group method. This comparison revealed that the total and per-step iteration counts of the refined method match those of the traditional method. However, the refined method’s average iteration time was significantly reduced due to eliminating multiple global evolutions per iteration.3) the simulated results were compared to measured data and calculations performed using MIKE software in a real-world case. A remarkable agreement was achieved, with the maximum global relative error of 10−2-10−3. A comparison of inflow and outflow discharges at a specific river network junction, obtained using the proposed method, the method of characteristics, the Lax diffusive scheme, and the original junction water stage iteration method, revealed that the internal boundary condition of river network junctions cannot be strictly met when employing either the method of characteristics or the Lax diffusive scheme. However, inflow and outflow discharges at river network junctions can be accurately balanced using the proposed method and its original counterpart.Conclusions These findings highlighted the importance, within the context of the junction water stage iteration method, of ensuring that the method utilized to solve the 1D Saint-Venant equations was consistent with that employed to iteratively solve the coupling water level at each river network junction. Although traditional explicit methods, such as the method of characteristics and the Lax diffusive scheme, enhanced computational efficiency by circumventing the global evolution within each iteration, computational accuracy cannot be guaranteed unless a uniform numerical method was employed for the global evolution. The proposed method improved computational efficiency without compromising computational accuracy and ensured that the connection conditions at each river network junction were rigorously maintained.关键词：computational hydraulics;unsteady flow in one-dimensional river networks;Lattice Boltzmann method;junction water stage iteration method;Han river233|575|0更新时间：2025-03-21
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Soil Erosion Characteristics at Small Watersheds Along Milin Region in the Yarlung Tsangpo River AI导读
“雅鲁藏布江流域土壤侵蚀特征研究取得新进展，揭示了地震前后侵蚀特征及驱动因子，为水电开发与水土保持提供科学依据。”摘要：Objective The Yarlung Tsangpo River, China’s longest highland river, possesses substantial water resources. Despite its significance, the river faces critical environmental challenges, including severe soil erosion, frequent landslides, and mudslides. These natural disturbances contribute to sediment siltation and riverbed blockages, undermining the river’s ecological integrity and hindering sustainable hydropower development in the basin. This study plays a critical role in analyzing soil erosion dynamics, which are essential for effective water resource management and strategic hydropower planning by emphasizing the urgency of addressing these environmental issues.Methods This research utilized the RUSLE model to quantify soil erosion processes in 12 representative sub-watersheds of the Yarlung Tsangpo River’s Milin section, specifically focusing on the changes in erosion patterns before and after a significant earthquake. It employed a geo-detector approach to identify the primary drivers of soil erosion within these sub-watersheds. Through a comprehensive analysis of multiple interacting factors, the research clarified the complex mechanisms driving soil erosion and determined high-risk areas, guiding targeted interventions to strengthen the ecological resilience of the region against ongoing and future environmental challenges.Results and Discussions The results showed that the LS factor distribution indicates the study area’s high altitude and significant topographic relief C factor values between 0.35 and 0.45 revealed poorer vegetation cover on high-altitude ridges and better cover at lower altitudes. K values ranged from 0 to 0.102 5, indicating lower soil erodibility at lower altitudes and higher erodibility at ridges. P values decreased from 2001 to 2016 and then increased after 2016. Rainfall erosivity showed a general downward trend, with fluctuations from 2008 to 2010. It was lower in high-altitude areas and stronger at lower elevations. From 2001 to 2020, the study area experienced an average soil erosion rate of 3 464.18 t·km–2·a–1, with over 60% of the area experiencing slight to mild erosion. The average soil erosion modulus in 2009 was the lowest, at 1 985.24 t·km–2·a–1, while the highest soil erosion occurred in 2008, with an average soil erosion modulus of 4 715.40 t·km–2·a–1. Among them, the average annual erosion in Dokongpu, Ruxiapuqu, and Dannianggou exceeded 300 000 t, which was related to the characteristics of a larger watershed area and higher elevation. The year 2016, which had the best vegetation cover, exhibited minimum erosion. The ecological environment was more stable, while the multi-year average erosion in the Menzupu, Benga, and Eadong (Qulu) sub-watersheds did not exceed 100 000 t. Before the earthquake, the explanatory power of factors influencing soil erosion ranked as follows: NDVI, soil condition, elevation, land use, temperature, rainfall, and slope. Post-earthquake, temperature’s explanatory power for soil erosion surpassed that of land use, while the ranking of the other factors remained the same. Vegetation cover was the main driving factor and its interaction with topography and climate predominantly controlled soil erosion. The interaction between slope and other factors enhanced erosion nonlinearly, increasing the q-value by 1.9 to 4.7 times. Earthquakes significantly impacted sediment transport and geomorphological evolution in the Yarlung Tsangpo River Basin. They caused ridge and slope fractures, reduced soil erosion resistance, and triggered landslides in high-elevation areas, destroying vegetation and generating many bare surfaces and loose material sources. The erosion modulus generally exhibited a fluctuating decreasing trend from 2001 to 2016. However, after the earthquake in 2017, the erosion modulus increased annually, with a tendency for strongly and very strongly eroded areas to transform into intensely eroded areas. Before the earthquake, highly erosive areas were primarily distributed at ridges with higher elevations. However, after the earthquake, erosion increased at the ridges and in the low-elevation areas, which showed an increasing trend. The pre-earthquake multi-year average soil erosion modulus was 3 415.77 t·km–2·a–1, and the average R factor was 878.22 (MJ·mm)/(hm2·h·a). In comparison, the post-earthquake multi-year average soil erosion modulus was 3 657.81 t·km–2·a–1 with an average R factor value of 855.33 (MJ·mm)/(hm2·h·a). Despite reduced rainfall erosivity post-earthquake, erosion volumes increased, indicating that the earthquake lowered the threshold for rainfall-triggered erosion in the watershed. Therefore, before the earthquake, the watershed’s soil erosion pattern was characterized by the interaction between climatic conditions and vegetation cover, resulting in an overall decreasing trend in soil erosion. In contrast, after the earthquake, rainfall erosion thresholds decreased, temperature influence increased, and the watershed became more sensitive to climate change. Areas with elevations of 3 875 to 5 138 m, annual rainfall of 609 to 670 mm, temperatures ranging from 2.08 to 6.11 ℃, land-use types including shrubs, grasslands, and bare ground, slopes greater than 17.8°, and NDVI values less than 0.41 had a higher risk of soil erosion. After the earthquake, the degree of soil erosion in each risk area increased to varying extents. Among them, the soil erosion modulus of bare land increased by 56.88 t·km–2·a–1, while the soil erosion modulus in areas with NDVI values ranging from 0.05 to 0.14 reached 103.46 t·km–2·a–1.Conclusions The research results significantly enhance our understanding of the dynamic soil erosion characteristics within the Yarlung Tsangpo River Basin, highlighting how vegetation cover, topography, and climatic conditions interact to influence erosion processes. These insights clarify the complex environmental challenges facing the region and provide a solid scientific basis for the strategic planning and optimization of hydropower development projects. In addition, the findings provide essential data to inform and refine soil and water conservation policies, reduce erosion risks, and enhance the ecological stability of this critical watershed. The research contributes to sustainable resource management and the protection of vital habitats in the basin by addressing these key aspects.关键词：Soil erosion;Geo-detector;Yarlung Tsangpo River;Spatial and temporal evolution101|353|0更新时间：2025-03-21 - “草鱼游泳特性研究取得新进展，揭示了草鱼在深潭变速水流中的运动行为和能耗评估，为鱼类游泳动力学研究提供新视角。”摘要：Objectives As one of the “four major Chinese carps” in the Yangtze River, unlike general mechanical movement, grass carp (Ctenopharyngodon idellus) is a kind of organism with locomotor vigor, which can control its movement process through its own muscle nerves, making it difficult to study the swimming dynamics of grass carp. In addition to guiding fishery production, the study of the swimming behavior of grass carp is also of great importance in the construction of ecological waterways.Methods Numerous studies have proved that the shallow ridge-deep pool riverbed topography created by damming and other engineering projects forms a slow-flowing area, which has been proven to be a suitable habitat for fish.The flow augmentation method was used to study the swimming locomotor characteristics of juvenile grass carp in a deep pool with variable velocity currents. The hydrodynamic environment of a continuous shallow deep pool was created by topographic design modifications.The flume test was carried out by Particle Image Velocimetry (PIV) to study the variation of flow structure in deep pools and to analyze the flow characteristics under different flow conditions in terms of two dimensions: flow velocity characteristics and flow structure.Behavioral characteristics of grass carp, including the active area and tail swing frequency of grass carp, were observed in the experiments to reveal the relationship between the movement process of grass carp and the response of the hydrodynamic environment under variable-speed currents in deep pools.The swimming movement of grass carp is essentially a process in which the state of movement of an object changes under the action of an external force. The grass carp will be subjected to the force exerted on it by the surrounding water body in the process of swimming, which will make the grass carp undergo a stress reaction and produce thrust through muscle contraction to counteract the water.Based on Newton’s second law, the concept of current-induced force (Fw) was proposed, and the force on the juvenile grass carp in the variable-speed current of a deep pool was analyzed by treating the grass carp as a general object that can generate its own motion thrust. The total energy dissipation coefficient (Cps) during the movement of the juvenile grass carp was calculated to evaluate the energy consumption of the juvenile grass carp during swimming movement.Results and Discussions 1) The flow velocity of the water in the deep pool is significantly smaller than the shallow flow velocity, and due to the hindering effect of the dam, the water flowing from upstream to downstream undergoes reflux, forming flat-axis vortex structures of different sizes. As the dam body is inundated by the water flow, the area of reflux is getting smaller and smaller, gradually moving in the downstream direction of the deep pool. When the flow rate is greater than 1.5 L/s, the vortex region starts to appear in the deep pool, and the area of the vortex region increases with the flow rate and extends downstream from the upstream of the deep pool gradually. 2) As the flow velocity increased, the grass carp showed an obvious clustering effect. The complex flow environment of the deep pool provided a good habitat and activity site for grass carp, which preferred to move in an area with a large water depth, low flow velocity, and turbulent flow pattern.There is a correlation between the area of grass carp larval activity and deep pools.The percentage of the activity area of grass carp decreased from 80.99% to 28.54% in the experiment, which not only reflected the clustering effect among fish groups but also reflected the suitable environmental preference of grass carp, and the suitable habitat area of grass carp in the deep pool gradually decreased with the increase of flow. 3) The turbulent water flow in the deep pool always caused the grass carp to exhibit intermittent and sudden tail wagging phenomena, and the overall fluctuation of tail wagging frequency was large. However, with the increase in flow velocity at the inlet, the frequency of tail wagging gradually increased, but the range of frequency fluctuations in the frequency of the grass carp tail swing gradually decreased. In the low-flow environment, the test fish were subjected to less flow coercion, and the movement of the fish was influenced by other subjective factors (e.g., hunger, fatigue, etc.), which resulted in different wagging frequencies and different degrees of activity for different test fish, and therefore the wagging frequency of grass carp fluctuated more at this time. When the flow rate increases, the fish usually increase the frequency of the tail swing to obtain power to maintain their own stability or upstream.4) As long as it is in motion, it is inevitable to produce energy dissipation. The main movement of fish organisms is swimming, and tail swinging is the main energy dissipation behavior during swimming. Based on Newton’s second law and force analysis on grass carp, the total energy dissipation coefficient of grass carp larvae in variable-speed deep pool currents was calculated.The total energy dissipation factor for grass carp movement was lowest when water flowed over the dam and at a flow rate of 1LB/s. When the flow rate was less than 1LB/s, the total energy dissipation coefficient of grass carp decreased with the increase in flow rate; when the flow rate was more than 1LB/s, the total energy dissipation coefficient of grass carp increased with the increase in flow rate.Conclusions The above study quantifies the movement process of grass carp larvae, fills a gap in the research on the movement characteristics of grass carp under variable-speed water flow, and provides guiding suggestions for fish habitat creation projects as well as the design of fishways.关键词：grass carp;deep pool;wagging frequency;current-induced force;energy dissipation coefficient67|104|0更新时间：2025-03-21
RIVER PROTECTION AND REGULATION
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Study on Impact Excitation and System Dynamic Characteristics of Shield Machine Planetary Gear Train AI导读
“在机械工程领域，专家建立了盾构机行星齿轮啮合冲击模型，揭示了内外啮合状态演变规律，为行星轮系统振动控制提供理论依据。”摘要：Objective This study aims to reveal the evolution law of the internal and external meshing state of the sun gear and planetary gear induced by the collision between the sun gear and planetary gear. Clear meshing impact causes changes in the rotational speed of the sun gear, planetary gear, and gear ring, resulting in internal impact between the meshing lines of each gear pair. An impact excitation analysis calculation model is established for the internal meshing of the shield machine planetary gear and external meshing gear sideline of the shield machine. The impact radius is solved through a reverse method, the position of the impact point C is determined, and the impact speed at impact point C and the synthesized flexibility between the gear pairs are obtained. This allows for determining the maximum impact force between the planetary wheel and gear ring. A solid model of the planetary wheel and gear ring structure is established using 3D modeling software. A shared node is applied between the solid unit and the rigid shell unit, with constraints imposed on the rigid body to restrict all freedoms other than the rotational freedom of the rigid shell unit on the inside of the two-gear wheels. The driving speed is applied to the rigid shell unit of the drive gear, load torque is applied to the rigid shell unit of the driven gear, and the corresponding initial speed is loaded on the drive gear.Methods Explicit dynamic simulation analysis was conducted using the contact automatic surface tosurface contact algorithm, which considered the effects of friction factors and damping. The contact force between a single pair of tooth surfaces was extracted, and the rationality of the analysis model was verified through comparison. In addition, a model of the impact mechanism of internal meshing impact induced by meshing impact on the planetary gear-gear ring and planetary gear-sun gear was built to study the influence of external meshing gear meshing impact. This model examined the meshing state of the planetary gear-gear ring and the outer engagement state of the sun gear-planetary gear. When the sun gear and planetary gear have an offline impact, the rotational speed changes of the sun gear, planetary gear, and gear ring are detected. The multi-point impact excitation of the gear ring exhibited regular changes. A centralized quality model for the planetary gear system of the shield machine was established, and internal excitations such as variable meshing stiffness, damping, and comprehensive transmission errors during loading were calculated. These calculations determined the meshing force between internal and external gear pairs under different impact excitations, clarifying the dynamic evolution between impact excitation and gear pair meshing force. Finally, a planetary wheel system dynamic model was built to extract the meshing force and contact force of the external and internal meshing gears, obtain the magnitude of the impact force of each gear, and identify the peak and valley values that cause fluctuations in meshing force. These results were compared to theoretical analysis to verify the rationality of the theoretical model.Results and Discussions The results indicated that the numerical values of the internal and external meshing impact forces fit well with the analytical solution, with a relative error of 4.09%. When the sun gear and planetary gear have an offline impact, the meshing line between the sun gear and planetary gear changes, causing changes in the planetary gear rotation speed and leading to an impact within the planetary gear and gear ring. The angular velocity of the sun gear fluctuated slightly due to the impact of kinetic energy transmission and frictional energy loss, causing tooth-side clearance between the sun gear and planetary gear. This resulted in a speed difference when the sun gear and planetary gear mesh again, inducing impacts within the sun gear and planetary gear (Ⅱ～Ⅳ) line. Planetary gear system impact incentives exhibited periodic changes, inducing a cyclic shift in the pulley to the galaxy.Conclusions The meshing force between the external meshing gear pairs changes, and the engagement impact excitation reduces the dynamic meshing force between the gear pairs. However, the induced inline impact excitation increases the dynamic meshing force of the gear system, leading to increased vibration of the planetary gear system. Compared to the planetary gear system's finite element simulation numerical solution and the theoretical analysis solution, the relative errors of external and internal meshing impacts were 3.21% and 6.4%, respectively, and the average meshing force errors were 6.93% and 3.8%, respectively. The peak error of the corresponding meshing force wave at the impact time was 17.17% and 13.19%, and the valley error was 11.19% and 13.22%, respectively, verifying the correctness of the theoretical model. In addition, this study uses DAMPING_GLOBAL to set different dampers and discusses the effects of damping on explicit dynamic simulation results. The size of the damping directly in the finite element model of dynamic gear contact affects the degree of convergence of the contact force between a single pair of teeth.关键词：meshing impact;analytical model;dynamic characteristics;planetary gears;shield machine175|283|0更新时间：2025-03-21 - “在航空领域，研究了U型铆接构件在不同载荷下的失效特性，建立了适用于坠撞仿真的铆钉数值模型，为飞机坠撞安全分析提供依据。”摘要：The failure of connecting components is one of the primary failure forms for transport aircraft under impact loads. For U-shaped riveted components, the failure characteristics under different loading angles (pure pull, 30°, 45°, 60°, and 90° pure shear) are studied using test and simulation methods, and the influence of varying thicknesses of U-shaped riveted components and loading angles on the failure characteristics is revealed. Bilinear element models (beam element, hexahedron element, 4–hexahedron cluster element, and 8–hexahedron cluster element) based on peak load failure are established. The SPR2 constraint element model is also developed, and a numerical model of rivets is obtained, which can be applied to aircraft crashworthy simulation. The results indicated that the rivet pull-out load transitions to the rivet shear load with increasing loading angles, and the rivet head pull-out failure changes to rivet rod shear failure. The out-of-plane tensile load of U-shaped riveted components changes to in-plane compressive load, and the failure displacement decreases. With increasing thickness of U-shaped components, the components become less susceptible to deformation, the failure load increases and the failure displacement decreases. Among the bilinear element models based on peak load failure, the failure loads and failure displacements obtained using the 8–hexahedron cluster element model exhibit the best agreement with test results. The deviation in failure load for the 8–hexahedron cluster element model and the SPR2 constraint element model is less than 10%; however, the deviation in failure load is smaller for the 8–hexahedron cluster element model. The deviation in failure displacement is slightly larger for the two models, but the deviation for the SPR2 constraint element model is within 15%. The 8–hexahedron cluster element model and the SPR2 constraint element model are suitable for aircraft crashworthy simulation applications.关键词：U-shaped riveted components;Failure characteristics;Bilinear element models;SPR2 constraint element model116|310|0更新时间：2025-03-21
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Meshing Characteristics Analysis of POM Gear Based on Thermoelastic-viscoplastic Constitutive Model AI导读
“在聚甲醛齿轮副啮合特性研究领域，专家建立了三维有限元接触模型，探索了温度、负载对啮合特性的影响，为塑料齿轮设计提供解决方案。”摘要：In order to reveal the influence of load, modification and temperature on the meshing characteristics of POM–POM gear pair, a three-dimensional finite element contact model of POM–POM gear pair based on thermoelastic-viscoplastic material constitutive model was established. At the same time, combined with the temperature-modulus effect of POM material, the steady-state thermal analysis of temperature-stress sequential coupling was carried out, and compared with the temperature service test results of POM–POM gear pair. Based on the steady-state thermal analysis, the fully coupled transient thermal contact analysis was carried out, and the transient temperature rise was compared with the Blok temperature results. Through the tooth root strain test, the validity of the tooth root strain calculation under different load conditions is verified. The results show that the steady-state temperature rise of the gear pair presents the distribution law of high tooth root, low tooth top and end face, and increases with the increase of load. Through the test comparison, the steady-state temperature rise of the gear calculated by the finite element method is consistent with the test results, and the transient temperature rise is consistent with the Blok formula. At the same time, the simulated tooth root strain of POM–POM gear pair is located in the strain error band of the experimental test, which shows that the thermoelastic-viscoplastic material constitutive considering the temperature-modulus effect can characterize the thermal and mechanical properties of POM plastic gear. In addition, the meshing line of POM–POM gear pair is extended and deviated from the theoretical position during the transmission process, and the temperature has little effect on the meshing line. The tooth surface modification can reduce the length of the meshing line, but can not improve the deflection degree. The meshing angle will change greatly when it is in and out of the meshing, and the temperature makes the meshing angle rise about in the double-tooth meshing area. The meshing stiffness is related to the load. As the load increases, the meshing stiffness decreases and the coincidence degree increases. Under the same conditions, the transmission error amplitude of POM–POM gear pair is about 10 times that of metal gear pair, and the temperature increases the transmission error amplitude by about 39%, and the tooth surface modification can reduce the transmission error amplitude by about 24%.关键词：visco-plasticity;POM Gears;meshing stiffness;Transmission error82|157|0更新时间：2025-03-21 - “在煤矿管道接拆管作业领域，专家基于人工操纵的液压机械臂，建立了运动学模型，实现了机器人自动搬运作业，提高了作业效率和安全性。”摘要：Connecting and disconnecting water and gas pipes is essential to coal mine site construction. With the increasing demands for installation quality, construction efficiency, and safety, traditional manual operation fails to meet construction requirements. This study analyzes the motion performance and automatic handling control of a manually operated hydraulic robotic arm to achieve automated handling during pipe connection and disconnection. First, the robot’s linkage coordinate system is established using the Denavit–Hartenberg (D–H) method. The forward and inverse kinematics of the robot’s manipulation and joint spaces are analyzed, and the mapping relationship between the robot’s joint space and drive space is determined using a geometrical method, providing the velocity Jacobi analysis of the robot. Based on this analysis, workspace images of the robot in common postures during actual operation scenarios are plotted in Matlab using the Monte Carlo method. The established mathematical model is implemented in Matlab, and the robotic arm is designed for path and trajectory planning. In addition, the robot’s mechanism model is simulated and analyzed in SolidWorks Motion to verify the accuracy of the mathematical model and enhance the safety of prototype experiments. The Matlab and SolidWorks Motion simulation results are consistent, confirming the validity of the correctness of the robot kinematic model and trajectory planning algorithm. The robot’s mechanism motion simulation process is continuous and smooth. Finally, a test platform for the robotic pipe assembly and disassembly prototype system is built, and an automatic pipe handling test is conducted. The test results indicated that the robot successfully performs automatic handling during pipe connection and disconnection. The handling operation cycle is 12 seconds, improving operational efficiency compared to traditional manual operation. The automated handling process is continuous and smooth, resolving the jitter problem caused by repeated manual adjustments of the robotic arm.关键词：hydraulic robotic arm;kinematics;work space;motion simulation;trajectory planning;robot104|165|0更新时间：2025-03-21
- “在机械密封领域，专家提出了基于压电陶瓷的可控机械密封结构，通过调节端面间隙分布，提升液膜承载力和稳定性，为设计提供理论指导。”摘要：A controllable mechanical seal structure based on piezoelectric ceramics is proposed to address the uncontrollable problem of liquid film instability during the operation of a mechanical seal. The mechanical seal adapts to variations in operating conditions and maintains a stable operating state by adjusting the end-face gap distribution of the seals. Firstly, the piezoelectric-mechanical multiphysics coupling model is established based on finite element software. The deformation law of the stator end face caused by voltage and the circumferential quantity of piezoelectric ceramics is analyzed. Then, a test device is developed to measure the end-face deformation of the stator. The deformation law of the stator end face is analyzed. Finally, based on the multiphysics coupling analysis model, the performance controllability of the mechanical seal under various sealing conditions is examined. The results show that the end face of the stator produces radial taper and circumferential waviness and that the deformation of the stator increases with increasing voltage, which facilitates the rapid formation of a convergent cone between the seal end faces. This enhances the hydrodynamic and hydrostatic effects of the fluid film and improves its load-bearing capacity. Increasing the number of piezoelectric ceramics on the back of the stator reduces circumferential waviness deformation and increases radial taper deformation, causing the end-face deformation of the stator to become more circumferentially uniform. This reduces the hydrodynamic effect and increases the hydrostatic impact of the fluid film, which enhances the stability of seal operation. The multiphysics coupling analysis results indicated that increasing the voltage of the piezoelectric ceramic enables the mechanical seal to transition from a contacting state to a non-contacting state. This reduces seal face wear and temperature rise while increasing the leakage rate. The results provide theoretical guidance for the design of controllable mechanical seals.关键词：controllable mechanical seal;piezoelectric ceramic;end face deformation;sealing performance54|161|0更新时间：2025-03-21
- “在高寒环境钢管约束混凝土结构力学行为研究领域，专家建立了考虑环境温度的钢管约束混凝土短柱承载力理论计算方法，为高寒地区钢管约束混凝土结构设计提供理论依据。”摘要：Objective Steel tube confined concrete (STCC) members operate in external environments for extended periods. Ambient temperature variations alter the material properties of steel and core concrete. Due to the significant differences in their thermodynamic properties, interface debonding, and void formation in STCC are likely to occur, leading to substantial changes in bearing capacity. These changes have a considerable impact on the structural safety of STCC members. Investigating the influence of ambient temperature on STCC columns is crucial for understanding its effect on axial compression bearing capacity and developing a calculation method that accounts for ambient temperature.Methods This study independently designed and developed an axial compression test device for variable temperature steel tube confined concrete to address the significant influence of ambient temperature on the mechanical behavior of STCC structures. Using this test device, 26 axial compression tests of STCC short columns, including two types (M-type and S-type), were conducted under different ambient temperatures. The test phenomena and failure modes under various temperature conditions were analyzed, and the effects of ambient temperature on the axial compression mechanical properties of STCC columns were investigated. In addition, the mechanism of ambient temperature influencing the axial compression bearing capacity of STCC columns was identified. Given the limitations of existing theoretical calculation methods, which do not consider the effects of ambient temperature, a theoretical calculation method for the axial compression bearing capacity of STCC short columns was developed by integrating thermodynamic theory and limit equilibrium theory. The concept of "temperature-induced additional constraint effect" was introduced for the first time, and the accuracy of the proposed theoretical method was validated through experiments. This analytical approach systematically revealed the mechanism of influence of ambient temperature on the axial compression bearing capacity of STCC.Results and Discussions The external failure modes of the specimens under different temperature conditions were similar, all exhibiting typical shear failure. However, after cutting the outer steel tube, it was observed that the damage degree of core concrete under low-temperature conditions was significantly higher than that under normal and high-temperature conditions. The load-displacement curves of specimens under different temperature conditions were similar, consisting of the elastic, elastic-plastic, and descending stages. When the ambient temperature decreased from 40 ℃ to 20 ℃, 0 ℃, –20 ℃, and –40 ℃, the bearing capacity of M-type (S-type) specimens increased by 2.6% (12.0%), 7.8% (20.0%), 26.0% (22.7%), and 36.4% (43.2%), respectively. This result indicated a significant negative correlation between the axial compression bearing capacity and temperature of STCC short columns, and the larger the diameter-thickness ratio, the more pronounced the relationship. Under low-temperature conditions, the ambient temperature increased the specimen's bearing capacity and the brittleness of the core concrete and steel tube. Hence, the ductility of the specimen decreased significantly. The current calculation method of the axial compressive bearing capacity of STCC columns did not consider the influence of temperature, resulting in the maximum deviation between the calculated and experimental values ranging from 23% to 51%. However, the theoretical calculation method in this study accounted for the 'temperature-induced additional constraint effect' and the material variability of steel tube core concrete caused by temperature. The average deviation between the calculated and experimental values was only 2.0%, with a standard deviation of 0.06, demonstrating high accuracy and reliability. The bearing capacity of steel tube confined concrete columns under different ambient temperatures comprised three components: N1 (bearing capacity under normal temperature conditions), N2 (additional bearing capacity caused by material strength variation), and N3 (additional bearing capacity caused by the temperature-induced additional constraint effect). The temperature-induced additional constraint effect referred to the mechanical behavior in which the steel tube exhibited 'diameter shrinkage' due to ambient temperature changes. This resulted in applying circumferential temperature stress to the core concrete, which altered the confinement effect of the core concrete. The temperature-induced additional constraint effect had a significant impact on the mechanical properties of the specimen. When the ambient temperature was –40 ℃, the influence ratio on the bearing capacity reached 34.1% of the temperature-induced additional bearing capacity.Conclusions The temperature-induced additional constraint effect significantly influences the axial compression bearing capacity of STCC. This effect exhibits strong nonlinearity, and the influence amplitude of the bearing capacity of the specimen is affected by the temperature difference between the ambient temperature and the normal temperature, the temperature-dependent elastic modulus of the material, Poisson's ratio, the linear expansion coefficient, and the diameter-to-thickness ratio of the component. The theory proposed in this study considers the temperature-induced additional constraint effect and the material variability caused by temperature. The calculation results demonstrate high accuracy. Based on the theory presented in this study, a theoretical basis is provided for quantifying the influence of ambient temperature on the bearing capacity of steel tube-confined concrete. In the design of steel tube confined concrete structures in alpine regions, the effects of the temperature-induced additional constraint effect and temperature-induced material property variation on the mechanical behavior of structures should be comprehensively considered.关键词：steel-tube confined concrete (STCC);ambient temperature;Temperature-induced additional constraint effect;Bearing capacity;axial compression test220|254|0更新时间：2025-03-21
MECHANICAL ENGINEERING
- “在盾构隧道施工领域，专家提出了一种基于LSTM与SVR的堆叠集成预测模型，有效提高了盾构姿态预测精度，为盾构施工误差控制提供了新方法。”摘要：Objective A stacking ensemble prediction model based on long short-term memory (LSTM) and support vector regression (SVR) is proposed to address the issue of shield attitude deviation from the tunnel design axis.Methods The grey correlation analysis was employed to remove the rolling angle parameters with low grey correlation and then denoise them using discrete wavelet transform (DWT). The DWT–LSTM–SVR stacking ensemble prediction model was obtained by optimally weighting the processed data after prediction by two single models separately. The cutter horizontal displacement, shield tail horizontal displacement, cutter vertical displacement, and shield tail vertical displacement were used as the output variables of the prediction model. In addition, 22 tunneling parameters, such as jack pressure, cutterhead torque, cutterhead speed, tunneling speed, pitch angle, primary jack stroke, and soil chamber pressure, along with five stratigraphic parameters, including natural unit weight, dry density, and specific gravity, were used as input variables. The DWT–LSTM–SVR model was applied to the A3 bidding section of the water resources allocation project in the Pearl River Delta. A total of 410 datasets were collected from the A3 bidding section. These 410 sample datasets were divided into a training set and a test set in a 9:1 ratio. The data from rings 968～1 336 formed the training set for the combined model, while the data from rings 1 337～1 377 constituted the test set.Results and Discussions The results showed that the errors between the predicted and actual values of the cutter horizontal displacement, shield tail horizontal displacement, cutter vertical displacement, and shield tail vertical displacement shield attitude parameters of the DWT–LSTM–SVR model were smaller than those of the DWT–LSTM model, DWT–SVR model, and AWT–LSTM–SVR model. This finding indicated that the model effectively combined the single models and that eliminating parameters with low correlation to the cutter horizontal displacement, shield tail horizontal displacement, cutter vertical displacement, and shield tail vertical displacement shield attitude parameters improved the model’s prediction accuracy. In addition, the evaluation metrics of the DWT–LSTM–SVR model met the construction error requirements, with the best prediction achieved for the shield tail displacement values. The MAPE of the cutter horizontal displacement was 0.061, the MAPE of the cutter vertical displacement was 0.066, the MAPE of the shield tail horizontal displacement was 0.028, and the MAPE of the shield tail vertical displacement was 0.011. The R2 of the cutter horizontal displacement was 0.996, the R2 of the cutter vertical displacement was 0.960, the R2 of the shield tail horizontal displacement was 0.986, and the R2 of the shield tail vertical displacement was 0.985. These results indicated that the combined DWT–LSTM–SVR prediction model met the model design requirements. Finally, different datasets were established to analyze the sensitivity of data quantity to the prediction accuracy of the stacking ensemble model. It was found that the greater the data quantity, the higher the prediction accuracy of the stacking ensemble model. As the number of datasets decreased, the prediction results of the DWT–LSTM–SVR model began to show large deviations, especially in the last 10 rings.Conclusions The results indicated that the model’s prediction for the first 15 rings is less sensitive to changes in the dataset, whereas the prediction for the last 10 rings is more sensitive to dataset variations. The DWT–LSTM–SVR model can serve as a reference for the advance adjustment of other shield attitudes.关键词：shield attitude;gray correlation;deep learning;stacking ensemble prediction model;error prediction116|264|0更新时间：2025-03-21
- “在北方严寒及寒冷地区，研究纤维增强自密实轻骨料混凝土冻融后性能，为应用提供科学依据。”摘要：Objective Fiber-reinforced self-compacting lightweight aggregate concrete (FSLC) is characterized by its lightweight properties, thermal insulation, and excellent frost resistance, making it suitable for applications in buildings prone to freeze-thaw damage in the severe cold and cold regions of the north. Currently, most research focuses on qualitative predictions of the porous properties of the aggregate, highlighting the necessity of studying its frost resistance to promote its application in northern regions.Methods The rapid freeze-thaw test measures the frost resistance of FSLC but does not clarify the fiber reinforcement and toughening effects under freeze-thaw conditions. It remains uncertain whether the conclusions regarding fiber reinforcement and toughening at room temperature apply to the low-temperature freeze-thaw environment. Therefore, based on the rapid freeze-thaw test method, the study first determined the freezing resistance index of the specimens, followed by a bending toughness test after a specified number of freeze-thaw cycles. In an earlier stage, the bending toughness evaluation method proposed by the group was employed to assess the flexural toughness characteristics with a large peak spanwise deflection. This evaluation aimed to clarify the effect of fibers on the frost resistance of self-compacting lightweight aggregates under cold temperature freeze-thaw environments. The study focused on the influence of fibers on the flexural toughness characteristics of self-compacting lightweight aggregate concrete under low-temperature freeze-thaw conditions. A systematic analysis of the enhancement and toughening effects of fibers on different loading phases under various freeze-thaw cycles was conducted to provide theoretical support for applying FSLC in engineering.Results and Discussions Fibers improved their compressive strength to a certain extent when incorporated into SLC. The compressive strength increased and then decreased with the increase in fiber content. At 0.5% fiber content, the compressive strength reached a maximum value of 63.3 MPa, which was 16.8% higher than the compressive strength of the non-doped specimen SF0, measured at 54.2 MPa. However, when the fiber content exceeded 0.5%, the compressive strength of the specimens decreased as the fiber content increased. In addition, the dry apparent density of the concrete specimens showed a monotonically increasing trend with the increase in fiber admixture. The relative dynamic elastic modulus of fiber-reinforced recycled fine aggregate concrete decreased with the increase in freeze-thaw cycles. After 75 freeze-thaw cycles, the relative dynamic elastic modulus of SF0.25 and SF0.50 dropped below 60%, while SF0.75 and SF1.0 remained above 60%. Due to weak interfaces produced by fiber incorporation into concrete, the relative dynamic elastic modulus of SF0 was higher than that of SF0.25 and SF0.5 after 75 freeze-thaw cycles. Following 100 freeze-thaw cycles, the relative dynamic elastic modulus of the unreinforced specimen SF0 surpassed that of the fiber-reinforced specimens SF0.25, SF0.5, SF0.75, and SF1.0. Within the tested freeze-thaw cycles, the mass of each group of specimens increased to some extent. Under bending load, the peak load on the load-deflection curve decreased with the increase in freeze-thaw cycles, and the descending section of the load-deflection curve became more gradual. For the same freeze-thaw cycles, due to the bridging effect of fibers on cracks, the peak load on the load-deflection curve increased with the increase in fiber content, and the descending section of the load-deflection curve tended to flatten. Under different freeze-thaw cycles, the flexural strength of FSLC specimens first decreased and then increased with the increase in fiber content. The flexural strength of the specimen with 0.25% fiber content (SF0.25) was the lowest. Within the specified range of fine steel fiber content (0.25%～1.00%), the initial flexural strength ratio Re,p of FSLC specimens under different freeze-thaw cycles exhibited a "high-low fluctuation" trend with increasing fiber content. When the freeze-thaw cycles were fewer (less than 50), the residual flexural toughness Rrt,C, and the residual flexural strength ratio Rf,C increased with fiber content. However, when the freeze-thaw cycles exceeded 50, these two toughness indicators did not exhibit apparent regular trends. For FSLC specimens without freeze-thaw cycles, the fiber peak front contribution rate Ipre,C increased initially and then decreased with the increase in fiber content, while the fiber peak rear contribution rate Ipost,C exhibited a continuous increase. After freeze-thaw cycles, for specimens SF0.25 and SF0.50, the fiber peak front contribution rate Ipre,C was negative, while the fiber post-peak contribution index Ipost,C did not show a consistent trend with the increase in steel fiber content.Conclusions The research results indicated that increasing the freeze-thaw cycles shows a declining trend in the relative dynamic elastic modulus, while the mass loss rate remains negative, and the mass of the specimens exhibits an increasing trend. Micro-steel fibers enhanced the flexural strength of self-compacting lightweight aggregate concrete under freezing conditions. Within the selected number of freeze-thaw cycles, the initial flexural strength of fiber-reinforced self-compacting lightweight aggregate concrete with varying fiber contents changed irregularly with the increase in freeze-thaw cycles. When the freeze-thaw cycles were fewer than 50, the residual flexural toughness ratio and the residual flexural strength ratio increased with the rise in fiber content. However, when the freeze-thaw cycles exceeded 50, these two toughness indices no longer exhibited significant regularity. For the fiber-reinforced self-compacting lightweight aggregate concrete specimens without freeze-thaw cycles, the fiber pre-peak contribution rate increased first and then decreased with the increase in fiber content, while fiber post-peak contribution rate index showed an increasing trend. After freeze-thaw cycles, the fiber pre-peak contribution rate index and post-peak contribution rate index of fiber reinforced self-compacting lightweight aggregate concrete specimens had no obvious regular change trend with the increase of fiber content.关键词：self-compacting lightweight aggregate concrete;steel fiber;freeze-thaw cycle;flexural toughness;experimental study159|257|0更新时间：2025-03-21
- “在露天台阶爆破领域，专家通过基础理论方法和模型试验，系统研究了不耦合系数变化对破碎块体运动速度和能耗的影响，为岩体破碎和能耗分布研究提供理论指导和工程应用价值。”摘要：In open-pit bench blasting, the spatiotemporal movement law of broken blocks and energy consumption are crucial indicators of blasting effectiveness. This study adopts basic theoretical methods and constructs energy consumption calculation formulas based on the movement trajectory of broken blocks to address the issue of movement velocity and energy consumption of broken blocks under varying uncoupling coefficients. Then, combined with model experiments, it systematically examines the changes in movement velocity and energy consumption of blasting-induced broken blocks under different uncoupling coefficients. The research results indicate that after explosive initiation, cracks initially appear in the rock mass at approximately 2 ms and accelerate to completion within about 20 ms. The free surface of the rock mass exhibits a bulging shape, with lower elevations on the upper and lower sides and a higher elevation in the middle. The movement velocity of broken blocks follows a regular pattern over time and can be broadly divided into three phases: acceleration, dynamic uniform velocity, and throwing deceleration. The broken blocks reach their initial throwing velocity and kinetic energy at around 18 ms. After this point, they are largely unaffected by explosive products and move freely under the influence of gravity. Based on model test results and calculations, the kinetic energy of the throwing process under different uncoupling coefficients is determined, revealing that the proportion of total energy generated by the explosion ranges between 5% and 16%. The throwing kinetic energy and its proportion decrease as the uncoupling coefficient increases. When the uncoupling coefficient rises from 1.250 to 3.375, the throwing kinetic energy decreases from 3.06 to 1.12 kJ, while the throwing kinetic energy proportion declines from 15.26% to 5.58%. These findings provide theoretical guidance and engineering application value for rock fragmentation, the movement law of broken blocks, and energy consumption distribution under uncoupled charging conditions in open-pit bench blasting.关键词：uncoupling coefficient;bench blasting;movement velocity;throwing kinetic energy;high-speed camera126|335|0更新时间：2025-03-21
- “在水岩循环影响下，库岸岩体强度弱化对边坡嵌岩桩力学行为的影响研究取得进展。专家通过水岩循环弱化试验和数值模拟，揭示了岩石力学参数弱化规律及其对嵌岩桩力学行为的影响，为库岸边坡嵌岩桩设计施工提供参考。”摘要：Objective This study addresses the critical issue of mechanical property degradation in rock-socketed piles under cyclic wetting-drying conditions during reservoir operation. The research aims to quantitatively evaluate the weakening mechanisms of sandy shale and systematically reveal the evolution characteristics of pile bearing behavior under hydraulic cycling effects.Methods Cyclic wetting-drying tests were conducted on sandy shale specimens from the Luogu Bridge slope in Lianghekou reservoir. The generalized Hoek–Brown criterion was applied to characterize rock mass degradation, while finite difference numerical modeling incorporating Mohr-Coulomb constitutive relationships simulated pile behavior. Microstructural analysis using scanning electron microscopy (SEM) and X-ray diffraction (XRD) revealed mineralogical alterations. A computational model was established considering reservoir water level fluctuations between 2785 m (dead water level) and 2865 m (storage level), with 35 m-long rock-socketed piles (Pile 1-1 and 1-2) analyzed under 100 wetting and drying cycles.Results and Discussions The findings reveal that after 28 wetting-drying cycles, the uniaxial compressive strength, Young’s modulus, cohesion, and internal friction angle of the rock gradually decrease by 20.82%, 25.97%, 14.83%, and 28.67%, respectively. Simultaneously, Poisson’s ratio gradually increases, with a degree of deterioration of 44.13%. The mechanical parameters demonstrate strong correlations with the number of cycles through power and logarithmic functions. Microstructural analysis of the rocks indicates that after 28 cycles, hydration-prone minerals decrease, with mica content reducing from 35.1% to 27.5%, chlorite content from 11.4% to 8.4%, and anorthose content from 25.3% to 14.5%. Scanning electron microscope results highlight significant damage to the rock specimens’ microstructure after 28 cycles, including an increase in cracks and pores and an expansion of the dissolution area. The loss of hydration-prone minerals and the accumulation of microscopic cracks are the primary causes of the weakening of the rock’s mechanical indices during the wetting and drying cycles. The computational model for the Luogu Bridge slope rock-socketed pile is developed using finite difference methodology, incorporating the Mohr-Coulomb constitutive model for the numerical simulation of the rock mass. The design dead water level for the slope of the rock-socketed pile is established at 2785 m, with the storage water level set to 2865 m. The rock mass within this elevation range is identified as the zone affected by wetting and drying cycles. The rock-socketed pile, extending to a length of 35 m, includes one beneath the bearing platform of the bridge abutment, designated as Pile 1-1, and another near the river valley direction, named Pile 1-2. This study simulates the mechanical behavior of rock-socketed Piles 1-1 and 1-2 after 100 cycles of wetting and drying. The computational outcomes suggested that wetting and drying cycles significantly impact the mechanical behavior of rock-socketed piles. After a certain number of cycles, the axial force of Pile 1-1 initially increases with depth, then gradually decreases. In contrast, the axial force of Pile 1-2 first decreases with depth, then gradually increases, and finally trends downward again. As the number of wetting and drying cycles increases, the axial force at the same depth of the rock-socketed pile progressively rises, with a more noticeable increase in the central region of the pile. The increments at the top and bottom of the pile are comparatively modest. The variation curve of lateral frictional resistance with depth reveals distinct patterns for two piles. The curve for Pile 1-1 displays a “single peak” pattern, where the resistance stabilizes after reaching a burial depth of 25 m. In contrast, the curve for Pile 1-2 follows an “R” shape distribution, with the resistance peaking at a depth of 15 m, then continuously decreasing, and finally increasing towards the end of the pile. This phenomenon may be attributed to the bending moment exerted by the bearing platform above the pile. The attenuation of shear strength in the rock mass surrounding the rock-socketed pile during wetting and drying cycles significantly reduces friction between the pile and the rock material. As a result, the total lateral frictional resistance of the rock-socketed pile under bridge loading tends to decrease with an increasing number of wetting and drying cycles, leading to a similar decrease in the lateral frictional resistance of the pile foundation at the same depth. Deformation measurements after varying numbers of cycles indicate that the horizontal displacement at each depth and the settlement at the top and bottom of the pile exhibit an increasing trend with more cycles. For rock-socketed Pile 1-1, the horizontal displacement is larger after 100 wetting and drying cycles within the depth range of 5～25 m, with the maximum horizontal displacement increasing from 0.316 to 1.029 mm, whereas the horizontal displacements at the top and bottom of the pile are relatively smaller. For rock-socketed Piles 1-2, the horizontal displacements at the top and bottom change significantly under wetting and drying cycles, while changes in the middle are relatively minor. After 100 cycles, the displacement at the top of the piles is 0.656 mm, and at the bottom, it is 0.518 mm.Conclusions The study demonstrates that wetting and drying cycles significantly impact the mechanical behavior of rock-socketed piles, with both axial force and lateral frictional resistance decreasing over time. The accumulation of microcracks and loss of hydration-prone minerals in the surrounding rock are the primary causes of the observed weakening. These findings highlight the necessity of considering the effects of wetting and drying cycles when designing and constructing rock-socketed piles in reservoir embankments, in order to prevent potential reductions in load-bearing capacity.关键词：Reservoir bank rock;Wetting-drying cycles;strength weakening;rock-socketed pile;mechanical properties102|125|0更新时间：2025-03-21
- “最新研究突破了自感知水泥基导电填料分散难题，通过低温等离子体改性技术制备出羧基化碳纳米管，显著提高压敏稳定性，为智能结构监测提供新方案。”摘要：Self-sensing cementitious materials enable real-time, long-term, and intelligent digital monitoring of structures, providing a novel approach to structural monitoring. However, challenges such as the difficulty in dispersing conductive fillers, high costs, and the need for large amounts of admixtures hinder their practical application. In this study, a low-temperature plasma modification technique is utilized to enhance the hydrophilicity and dispersion of carbon nanotube (CNT) materials while minimizing surface damage. In addition, the study innovatively incorporates a pressure-sensitive material, silver nanoparticles (AgNPs), which have significant potential in smart wear applications, into the cement matrix. The pressure sensitivity of CNT and AgNPs, two conductive fillers in the cement matrix, is analyzed through three loading regimes: equal amplitude loading, variable amplitude loading, and frequency loading under long cycles. The polarization trends of both specimen groups remain consistent. As the cementitious material ages, the polarization end time increases gradually from 4～5 min at 14 d to about 1.0 h at 28 d, eventually stabilizing at about 1.5 h. Cyclic loading tests with equal amplitude revealed that AgNPs achieve significantly higher pressure-sensitive stability than P–CNT at a very low doping level of 0.004 8%, effectively reducing the required filler content. Experimental results from variable amplitude tests indicated that the stress sensitivity of AgNPs is more than three times higher than that of P–CNT under the same amplitude conditions. SEM analysis showed that excessive stress amplitude loading damages P–CNT fibers, negatively affecting their pressure-sensitive performance. The variable-speed cyclic loading test demonstrated that long-cycle cyclic loading or high-speed loading enhances the stability of the self-sensing cementitious pressure-sensitive curve.关键词：Self-sensing cement-based;Low temperature plasma modification treatment;carbon nanotubes;Nano-Silver;Stress sensitivity129|251|0更新时间：2025-03-21
CIVIL ENGINEERING
- “在级联功率变换器领域，专家通过动力学建模和稳定性分析，揭示了开关纹波交互对负载变换器稳定性的影响，为提高变换器稳定性提供解决方案。”摘要：In a cascaded power converter, the switching ripple interaction between the source converter and the load converter reshapes the voltage ripple at the common coupling point (CCP). When the equivalent series resistance (ESR) of the output capacitor is large, the output voltage ripple of the source converter significantly affects the stability of the load converter. This study examines the effect of the switching ripple interaction on the stability of the load converter using the cascaded valley voltage-ripple (VVR) controlled Buck converter as an example. The operation principle of the VVR-controlled Buck converter is detailed in its schematic diagram and steady-state operation waveforms. When the source converter possesses a large output capacitor ESR, the voltage ripple at the CCP is determined by the voltage across the output capacitor ESR of the source converter. The characteristics of the voltage ripple at CCP are analyzed when the input current ripple of the load converter is fed forward to the output capacitor of the source converter. Based on the relationship between the duty cycles of the source converter and the load converter, the voltage ripple at CCP has three types of waveforms. Typical circuit parameters of the cascaded VVR-controlled Buck converter are selected for circuit simulation to demonstrate the stability effect of the voltage ripple at CCP on the load converter. Based on the typical circuit parameters, two sets of circuit simulation results are obtained. When the load converter is supplied by a constant input voltage (in standalone operation), it operates in a stable period-1 state, whereas when the load converter is supplied by the output voltage of the source converter (in cascaded operation), it operates in an unstable period-2 state. Both the inductance of the source and load converters (L1 and L2) can affect the characteristics of voltage ripple at CCP and are selected as bifurcation parameters to analyze the bifurcation behaviors of the load converter. The bifurcation diagrams with variations of L1 and L2 are presented in this study. As L1 increases from 2 to 20 μH, the operation state of the load converter transitions from a chaotic state to an unstable period-2 state through a border-collision bifurcation at L1 = 6.6 μH and then to a stable period-1 state via inverse period-doubling bifurcation at L1 = 13.2 μH. As L2 increases from 40 to 100 μH, the operation state of the load converter shifts from a stable period-1 state to an unstable period-2 state via period-doubling bifurcation at L2 = 53 μH. The stability of the VVR-controlled Buck converter in standalone operation is independent of inductance; however, when the converter is in cascaded operation, its stability relates to the inductance of the source and load converters. When both the source and the load converters operate in continuous conduction mode (CCM), the cascaded VVR-controlled Buck converter has four switching states. A map between the state variables at the initial moment and the termination moment of the mth switch state is established by solving the state equation of the mth (m = 1, 2, 3, 4) switching state. Under the switching ripple interaction, the cascaded VVR-controlled Buck converter exhibits three switching state sequences in one switching cycle. With consideration of these three switching state sequences, an approximate discrete-time map model of the cascaded VVR-controlled Buck converter is developed. Based on this model, the corresponding Jacobian matrix around the fixed point and its eigenvalues are derived. The stability of the cascaded VVR-controlled Buck converter can be determined by monitoring the eigenvalues of the Jacobian matrix with variations in the chosen circuit parameters. As L1 decreases or L2 increases, the eigenvalue λ1 exits the unit circle via −1 at L1 = 13 μH or L2 = 52 μH, while the other three eigenvalues, λ2, λ3, and λ4, remain inside the unit circle, resulting in the occurrence of period-doubling bifurcation. Accordingly, typical eigenvalues for different L1 and L2 are listed in this study. The results of eigenvalue analysis are consistent with those of bifurcation analysis. The results showed that increasing the inductance of the source converter enhances the stability of the load converter, whereas increasing the inductance of the load converter diminishes its stability. Circuit simulation results for different L1 and L2 are presented to visually demonstrate the effects of L1 and L2 on the stability of the load converter. Finally, the experimental prototype of the cascaded VVR-controlled Buck converter is established. Based on the circuit simulation results, corresponding experimental results are provided. The experimental results confirm the accuracy of the simulation analysis and theoretical analysis. These results provide theoretical guidance for the parameter design of load converters in cascaded power converters. The research method can also be applied to load converters with other control methods, such as peak-current-mode control.关键词：Switching ripple interaction;cascaded power converter;load converter;stability mechanism;discrete-time map model336|529|0更新时间：2025-03-21
- “报道：永磁同步电机转子初始位置辨识新方法，无需滤波器，提高精度，适用于低速工况。”摘要：Objective Since the development of the permanent magnet synchronous motor, there have been position sensorless control algorithms for various operating conditions. Among these, identifying the initial position of the permanent magnet synchronous motor plays a crucial role in the motor’s starting performance. If the initial position cannot be accurately positioned, the motor can experience shaking, reversal, or even failure to start. At medium and high speeds, the back electromotive force information in the motor model is prominent, allowing the rotor position information to be indirectly obtained by extracting the back electromotive force data. However, at low speeds or even zero speed, the back electromotive force information is weak, and the rotor position can no longer be effectively identified. Therefore, studying the sensorless control algorithm of the motor at zero low speed is particularly important. Among all kinds of rotor position identification methods, the high-frequency injection method based on rotor salient pole characteristics is widely used and effective. It does not depend on the motor back electromotive force and has good control effects at zero low speed. The high-frequency pulse vibration injection method, in particular, is a widely used algorithm in the high-frequency injection approach. Traditionally, this method involves injecting a high-frequency sine wave voltage signal on the estimated rotor d-axis and using a filter to isolate the high-frequency response current of the motor under high-frequency excitation, obtaining the current information corresponding to the rotor position. However, the presence of the filter can introduce phase lag, which affects the accuracy of rotor position identification.Methods This study proposed an initial position identification method for permanent magnet synchronous motor rotors based on high-frequency square wave injection. Initially, the mathematical model of the system under high-frequency excitation was analyzed. When the motor operates at low speed or is stationary, and the injected high-frequency square wave signal’s frequency is significantly higher than that of the fundamental wave signal, the influence of back electromotive force and resistance voltage drop in the model can be disregarded, thus simplifying the motor model and the expression for response current. High-frequency square wave signals were then injected into the estimated rotor d-axis, and the response current separation method was utilized to differentiate between the high-frequency response current components and the fundamental wave current components of the response current. The fundamental wave current was used for current closed-loop control, while the high-frequency response current carried the rotor position information. The forms of the high-frequency square wave signal and the high-frequency response current are illustrated in Fig.1. Then, for the isolated high-frequency response current carrying rotor position information, a rotor position observer was designed without filters. The tangent function processed the high-frequency response current and decoupled the rotor position error information, which was then phase-locked to identify the rotor position. This method avoids the phase lag problem caused by the filter and uses the advantages of high frequency and large bandwidth utilizing square wave injection. After the preliminary positioning of the rotor’s initial position was completed, it was also necessary to identify the rotor polarity to determine whether the initial positioning of the rotor position and the actual rotor position were the same or opposite. This study, based on the magnetic saturation effect of the motor, applied current bias in different directions and equal amplitude to the reference d-axis in the identification of rotor polarity. The rotor polarity was determined by comparing the average value of the high-frequency response current amplitude of the d-axis during the operation time of the current bias. Therefore, the results of rotor polarity judgment are reliable and accurate.Results and DiscussionsThe entire permanent magnet synchronous motor (PMSM) position sensorless field-oriented control (FOC) system was designed, and a PMSM simulation and experimental platform was constructed to verify the feasibility of the proposed algorithm. The initial position identification of the permanent magnet synchronous motor in a static state and the motor’s performance in a running state were tested and verified. The algorithm accurately identified the rotor position in a static state and correctly determined the rotor’s polarity when the actual rotor position was 285°. The initially identified rotor position was compensated from 100.8° to 280.8°, which confirmed the accuracy of the position identification algorithm and the correctness of the polarity identification algorithm. In addition, the error in the initial position identification results of the proposed algorithm at various rotor angles was compared to that of the traditional high-frequency vibration injection. The proposed algorithm achieved more accurate identification results than the traditional method. After the initial positioning of the rotor was completed, the dynamic response performance of the motor was tested as it started and accelerated to the given speed, including when there was a sudden increase in speed. The steady-state performance of the motor at a constant speed and the response performance of the motor to abrupt forward and reverse rotation commands during the operation were also tested. Conclusions All experimental results demonstrated that this algorithm is suitable for permanent magnet synchronous motors at low speeds, and the dynamic control effect is good.关键词：Permanent magnet synchronous motor;high-frequency square wave injection;Initial position detection;Tangent function;Magnetic saturation effect678|870|0更新时间：2025-03-21
- “在天然气输气管网动态仿真领域，专家提出了一种离散化和线性化方法，有效提升了计算速度和求解精度，为动态仿真研究提供新方案。”摘要：This study proposes a discretization and linearization method for the dynamic PDE model of the gas transmission network to address the challenge of effectively balancing calculation speed and solution accuracy in current methods for solving the dynamic partial differential equations (PDEs) of the gas transmission network. Initially, it uses the finite volume method (FVM) and the finite difference method (FDM) to derive the discretized and linearized gas pipeline PDEs with high precision. Then, this research introduces a fast solution scheme based on the SIMPLE algorithm to address the complex problem of calculating large-scale discretized equations. For the equations at each discrete grid node, a solution equation format to reduce the variable scale is derived and is solved through the “assumption–correction” approach to enhance solution accuracy. Employing the results from the commercial software Pipeline Studio as a benchmark, the proposed method is applied to the dynamic simulation cases of a single pipeline and a simple pipeline network, respectively. The solution speed and accuracy are then compared to those of the FDM, characteristic method (CM), and energy circuit theory (ECT). In each case, the impact of different space steps on the accuracy and speed of the proposed method and other methods is explored. The results indicate that the average error of the proposed method was 0.194 3% when solving a single pipeline model, with a solution time of 1.169 seconds. The average error in the simulation of a simple pipeline network is 0.279 4%, and the time is 37.285 seconds. In addition, the proposed method ensures convergence with various space steps, maintaining an average error within 0.3%. This case demonstrates the stability of the proposed method, confirming that the speed and accuracy requirements can be fully met and effectively applied in the dynamic simulation research of natural gas transmission pipeline networks.关键词：natural gas pipeline network;partial differential equation;finite volume method;finite difference method;SIMPLE algorithm235|126|1更新时间：2025-03-21
ELECTRICAL ENGINEERING
- “河北保定涞水垃圾焚烧炉研究，揭示了结焦原因并提出优化方案，对提升焚烧效率具有指导意义。”摘要：In view of the characteristics of high ash content, low calorific value, and susceptibility to coking during the incineration power generation process, this study examines a mechanical grate waste incinerator with a daily treatment capacity of 500 t in Laishui, Baoding, Hebei Province, as the research object and explores the component characteristics of village and town domestic waste through sampling and analysis. The fly ash, bottom slag, throat wall coke, and ash soil components in the waste incinerator are sampled, and their ash melting points are measured. Based on the structural characteristics of the waste incinerator and the composition and calorific value of local domestic waste, FLIC and Ansys Fluent software are utilized to simulate the water evaporation, volatile release, volatile combustion, and coke incineration processes along the grate movement direction, as well as the distribution of the temperature field, velocity field, and concentration field in the furnace. The simulated results are compared and analyzed with the measured data. Considering the coking part, coke block shape, and coking degree in the furnace, the main factors affecting coking in the waste incinerator are analyzed. The risk and degree of coking in the equipment are reduced by adjusting the secondary air ratio between the front and rear arches. The ash melting point test results indicate that the hemispherical temperature and flow temperature of the ash samples in the furnace are slightly lower than those of the ash soil composition and the treated fly ash, which are close to 1 200 °C. The primary component in the furnace coke sample is pyroxene, accounting for 51%, followed by calcium (sodium) feldspar and orthoclase feldspar, accounting for 30%. The simulation results demonstrate that when the wind speed of the front arch and the wind speed of the back arch is 41 m/s and 38 m/s, respectively, the gas flow field and temperature field distribution in the throat and the front and rear arch areas in the furnace are optimized, the gas erosion of the front arch and the reflux zone at the throat are improved, and the suppression effect on the coking phenomenon is maximized. The research findings provide important guidance and engineering application value for predicting and mitigating coking in waste incinerators, improving boiler thermal efficiency, and enhancing operational economy.关键词：coking characteristics;high ash household waste;coking prediction;CFD171|381|0更新时间：2025-03-21
- “在城市移动源减污降碳领域，专家基于PEMS测试方法，研究了混凝土搅拌车的真实排放特征，为协同推进减污降碳提供可靠参考。”摘要：Objective With the increasing emphasis on urban air pollution prevention and control efforts, studying the emission characteristics of concrete mixer trucks has become a critical factor in raising the synergetic control of environmental pollution and carbon emissions from mobile sources. This is particularly important given their high activity levels in urban central areas as heavy diesel vehicles. Most existing studies have primarily focused on heavy-duty freight vehicles, such as tractors, transport trucks, and dump trucks, while comparatively less attention has been given to concrete mixer trucks, which frequently operate in urban areas and pose potential threats to human health. In addition, most studies have concentrated on emissions under standard or controlled driving conditions. However, the actual operating conditions of engineering vehicles, including concrete mixer trucks, differ from those of typical heavy-duty vehicles. Therefore, conducting emission studies based on real-world conditions is essential for analyzing emission variations under different operating scenarios and for effectively controlling emissions from mobile sources.Methods This study selected concrete mixer trucks with high activity levels and representative operating areas in Chengdu to investigate the real emission characteristics of these vehicles during actual task processes. Real-world emission measurements of the entire driving process were conducted using a portable emissions measurement system (PEMS). The equipment continuously collected and recorded exhaust and pollutant emission data during the vehicle’s operation, along with per-second data on engine performance. In addition, it captured relevant environmental parameters, geographical location data, and other onboard diagnostics (OBD) information in real time. The three test vehicles selected were newly purchased National VI concrete mixer trucks, each having been in operation for less than three months. Specifically, Vehicle 1 accumulated a mileage of 4 712 km, Vehicle 2 accumulated 3 927 km, and Vehicle 3 accumulated 4 453 km. The study was conducted based on the actual task routes and processes of concrete mixer trucks, with one complete task cycle considered as a single test cycle. The test starting point, endpoint, and equipment installation site were located at a concrete mixing station in Chengdu. A total of 38 105 data points were collected, including 14 380 from Vehicle 1, 8 502 from Vehicle 2, and 15 223 from Vehicle 3. An analysis of the activity levels and operating conditions of the concrete mixer trucks was performed based on the test data, and the emission characteristics of CO2, CO, and NOx under different operating conditions and task periods were examined separately.Results and Discussions The research results indicated that: 1) The three selected concrete mixer trucks exhibited noticeable variations in emission factors for CO2, CO, and NOx under different typical driving conditions. Throughout the entire process, the average emission factors for CO2, CO, and NOx were 843.65, 1.21, and 2.29 g/(kW·h), respectively. During transportation periods, the average emission factors were 713.47, 1.06, and 0.51 g/(kW·h), while during waiting periods, they were 1 330.45, 2.35, and 6.64 g/(kW·h), respectively. 2) The distribution of task time for mixer trucks was significantly influenced by daily project scheduling and queue waiting times. The transportation period was the primary stage affecting CO2 and CO emissions, with emission rates remaining relatively low during waiting periods and showing minimal change with increasing waiting time. However, during waiting and unloading periods, NOx emissions accounted for the highest proportion, exceeding 70% of the total emissions throughout the entire process. The emission intensity of NOx increased significantly with prolonged waiting time. 3) The actual working conditions of mixer trucks primarily involved low-load operations, with overall operating speeds typically remaining within 50 km/h. The vehicle specific power (VSP) was predominantly distributed in the [0, 2] kW/t range, with limited instances of acceleration. Even under different driving routes, significant differences were not observed, contrasting with typical heavy-duty vehicle driving conditions. In practical tasks, waiting times for mixer trucks were substantial, and prolonged idling contributed to the accumulation of pollutant emissions. Based on driving characteristics, it was determined that the emission intensity of mixer trucks exhibited a significant positive correlation with VSP, with acceleration conditions within the low-speed range (< 20 km/h) resulting in higher emissions. 4) Compared to reference vehicles, mixer trucks exhibited emissions under different conditions that demonstrated some similarities to those of reference vehicles. This indicated that under similar conditions, the emission characteristics of mixer trucks and typical heavy-duty vehicles shared certain similarities. Therefore, emission control strategies for typical heavy-duty vehicles provided some guidance for mixer trucks operating under similar conditions. However, for mixer trucks, where NOx emissions were most influenced during the waiting and unloading stages, specific considerations needed to be addressed.Conclusions A comparative analysis of engine power parameters, fuel combustion parameters, and exhaust emissions parameters recorded in PEMS indicated that CO2, CO, and NOx emissions are mainly influenced by vehicle power output and fuel combustion. In addition, CO and NOx emissions are also affected by exhaust gas temperature and the operating temperature of the selective catalytic reduction (SCR) system. Based on an analysis of the entire task process of mixer trucks under actual road conditions, environmental management strategies for concrete mixer trucks are proposed, including optimizing driving routes and schedules to avoid road congestion, reducing vehicle waiting time, strictly controlling the operating temperature of the SCR system during vehicle operation, ensuring a consistent supply of urea for the SCR system, and standardizing driver behavior. These measures aim to provide reliable references for the synergetic control of environmental pollution and carbon emissions from urban mobile sources.关键词：PEMS;concrete mixer trucks;real-world operating conditions;emission characteristics;synergetic control of environmental pollution and carbon emissions290|477|0更新时间：2025-03-21
ENVIRONMENTAL ENGINEERING
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