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3D simulation of image-defined complex internal features using the numerical manifold method

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Science china(Technological Sciences) 2024年第4期67卷 1023-1039页

作者： WU Jie MA GuoWei School of Civil and transportation Engineering Hebei University of TechnologyTianjin 300401China Tianjin Key Laboratory for Prefabricated Building and intelligent Construction Tianjin 300401China

The numerical simulation of internal features,such as inclusions and voids,is important to analyze their impact on the performance of composite ***,the complex geometries of internal features and the induced continuous-discontinuous(C-D)deformation fields are challenges to their numerical *** this study,a 3D approach using a simple mesh to simulate irregular internal geometries is developed for the first *** the help of a developed voxel crack model,image models that are efficient when recording complex geometries are directly imported into the *** reconstructions,which are usually labor-intensive,are excluded from this ***,using image models as the geometric input,image processing techniques are applied to detect material interfaces and develop contact ***,the C-D deformations of the complex internal features are directly calculated based on the numerical manifold *** accuracy and convergence of the developed3D approach are examined based on multiple *** 3D C-D simulation of sandstones with naturally formed complex microfeatures demonstrates the capability of the developed approach.

关键词： 3D continuous-discontinuous simulation image-based simulation complex internal features numerical manifold method voxel crack model structured mesh

A review of vehicle detection methods based on computer vision

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Journal of Intelligent and Connected Vehicles

Journal of intelligent and Connected Vehicles 2024年第1期7卷 1-18页

作者： Changxi Ma Fansong Xue School of Traffic and transportation Lanzhou Jiaotong UniversityLanzhou 730070China Key Laboratory of Railway Industry on Plateau Railway transportation intelligent Management and Control Lanzhou 730070China

With the increasing number of vehicles,there has been an unprecedented pressure on the operation and maintenance of intelligent transportation systems and transportation *** order to achieve faster and more accurate identification of traffic vehicles,computer vision and deep learning technology play a vital role and have made significant *** study summarizes the current research status,latest findings,and future development trends of traditional detection algorithms and deep learning-based detection *** the detection algorithms based on deep learning,this study focuses on the representative convolutional neural network ***,it examines the two-stage and one-stage detection algorithms,which have been extensively utilized in the field of intelligent transportation *** to traditional detection algorithms,deep learning-based detection algorithms can achieve higher accuracy and *** single-stage detection algorithm is more efficient for real-time detection,while the two-stage detection algorithm is more accurate than the single-stage detection *** the follow-up research,it is important to consider the balance between detection efficiency and detection ***,vehicle missed detection and false detection in complex scenes,such as bad weather and vehicle overlap,should be taken into *** will ensure better application of the research findings in engineering practice.

关键词： intelligent transportation system computer vision deep learning vehicle detection object detection algorithm

An efficient approach for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic excitations

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Earthquake Engineering and Engineering Vibration 2024年第3期23卷 677-690页

作者： Huang Huan Li Yingxiong Li Yuyu College of Water Conservancy and Civil Engineering South China Agricultural UniversityGuangzhou 510642China Institute of Smart City and intelligent transportation Southwest Jiaotong UniversityChengdu 611756China

An efficient approach is proposed for the equivalent linearization of frame structures with plastic hinges under nonstationary seismic *** concentrated plastic hinges,described by the Bouc-Wen model,are assumed to occur at the two ends of a linear-elastic beam *** auxiliary differential equations governing the plastic rotational displacements and their corresponding hysteretic displacements are replaced with linearized differential ***,the two sets of equations of motion for the original nonlinear system can be reduced to an expanded-order equivalent linearized equation of motion for equivalent linear *** solve the equation of motion for equivalent linear systems,the nonstationary random vibration analysis is carried out based on the explicit time-domain method with high ***,the proposed treatment method for initial values of equivalent parameters is investigated in conjunction with parallel computing technology,which provides a new way of obtaining the equivalent linear systems at different time *** on the explicit time-domain method,the key responses of interest of the converged equivalent linear system can be calculated through dimension reduction analysis with high *** examples indicate that the proposed approach has high computational efficiency,and shows good applicability to weak nonlinear and medium-intensity nonlinear systems.

关键词： nonstationary random vibration plastic hinge equivalent linearization method explicit time-domain method parallel computation

Low-Rank Optimal Transport for Robust Domain Adaptation

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1667-1680页

作者： Bingrong Xu Jianhua Yin Cheng Lian Yixin Su Zhigang Zeng IEEE the School of Automation Wuhan University of TechnologyWuhan 430070China intelligent transportation systems Research Center Wuhan University of TechnologyWuhan 430063 Chongqing Research Institute Wuhan University of TechnologyChongqingChina the School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 the Key Laboratory of Image Processing and intelligent Control of Education Ministry of china Wuhan 430074China

When encountering the distribution shift between the source(training) and target(test) domains, domain adaptation attempts to adjust the classifiers to be capable of dealing with different domains. Previous domain adaptation research has achieved a lot of success both in theory and practice under the assumption that all the examples in the source domain are welllabeled and of high quality. However, the methods consistently lose robustness in noisy settings where data from the source domain have corrupted labels or features which is common in reality. Therefore, robust domain adaptation has been introduced to deal with such problems. In this paper, we attempt to solve two interrelated problems with robust domain adaptation:distribution shift across domains and sample noises of the source domain. To disentangle these challenges, an optimal transport approach with low-rank constraints is applied to guide the domain adaptation model training process to avoid noisy information influence. For the domain shift problem, the optimal transport mechanism can learn the joint data representations between the source and target domains using a measurement of discrepancy and preserve the discriminative information. The rank constraint on the transport matrix can help recover the corrupted subspace structures and eliminate the noise to some extent when dealing with corrupted source data. The solution to this relaxed and regularized optimal transport framework is a convex optimization problem that can be solved using the Augmented Lagrange Multiplier method, whose convergence can be mathematically proved. The effectiveness of the proposed method is evaluated through extensive experiments on both synthetic and real-world datasets.

关键词： Domain adaptation low-rank constraint noise corruption optimal transport

Coupled Numerical Simulation of Electromagnetic and Flow Fields in a Magnetohydrodynamic Induction Pump

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Fluid Dynamics & Materials Processing 2024年第4期20卷 889-899页

作者： He Wang Ying He College of transportation Ludong UniversityYantai264025China College of intelligent Manufacturing City College of HuizhouHuizhou516025China

Magnetohydrodynamic(MHD)induction pumps are contactless pumps able to withstand harsh *** rate of fluid flow through the pump directly affects the efficiency and stability of the *** explore the influence of induction pump settings on the related delivery speed,in this study,a numerical model for coupled electromagnetic and flow field effects is introduced and used to simulate liquid metal lithium flow in the induction *** effects of current intensity,frequency,coil turns and coil winding size on the velocity of the working fluid are *** is shown that the first three parameters have a significant impact,while changes in the coil turns have a negligible *** maximum increase in working fluid velocity within the pump for the parameter combination investigated in this paper is approximately 618%.As the frequency is increased from 20 to 60 Hz,the maximum increase in the mean flow rate of the working fluid is approximately 241%.These research findings are intended to support the design and optimization of these devices.

关键词： Magnetic fluid multi-physical field coupling induction pump numerical simulation liquid metal conveying

intelligent fault diagnosis methods toward gas turbine: A review

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Chinese Journal of Aeronautics 2024年第4期37卷 93-120页

作者： Xiaofeng LIU Yingjie CHEN Liuqi XIONG Jianhua WANG Chenshuang LUO Liming ZHANG Kehuan WANG School of transportation Science and Engineering Beihang UniversityBeijing 100191China systems Engineering Research Institute China State Shipbuilding CorporationBeijing 100094China

Fault diagnosis plays a significant role in conducting condition-based maintenance and health management for gas turbines(GTs) to improve reliability and reduce costs. Various diagnosis methods developed by modeling engine systems or certain components implement faults detection and diagnosis based on the measurement of systemic parameters deviations. However, these conventional model-based methods are hindered by limitations of inability to handle the nonlinear nature, measurement uncertainty, fault coupling and other implementing problems. Recently, the development of artificial intelligence algorithms has provided an effective solution to the above problems, triggering broad researches for data-driven fault diagnosis methods with better accuracy,dynamic performance, and universality. This paper presents a systematic review of recently proposed intelligent fault diagnosis methods for GT engines, according to the classification of shallow learning methods, deep learning methods and hybrid intelligent methods. Moreover, the principle of typical algorithms, the evolution of enhanced methods, and the assessment of pros and cons are summarized to conclude the present status and look forward to the future in the field of GT fault diagnosis. Possible directions for development in method validation, information fusion, and interpretability of intelligent diagnosis methods are concluded in the end to provide insightful concepts for scholars in related fields.

关键词： Fault diagnosis Health management Gas turbine Artificial intelligence intelligent diagnosis method

Protection of Omicron Sub-Lineage Infection Against Reinfection with Another Omicron Sub-Lineage:Systematic Review,Meta-Analysis,and Meta-Regression-Worldwide,2022-2023

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china CDC weekly 2024年第26期6卷 624-628,I0001-I0009页

作者： Xu Guo Zuyao Cheng Junhong Li Yudan Song Hui Zheng Yamin Wang Chao Ma Zijian Feng National Key Laboratory of intelligent Tracking and Forecasting for Infectious Disease National Immunization ProgramChinese Center for Disease Control and PreventionBeijingChina Chinese Preventive Medicine association BeijingChina

Summary What is already known about this topic?Both the decline in immunity over time and the evolution of the virus play a role in the level of protection offered by a prior *** is added by this report?Point estimates indicated variations in protection levels based on the initial infecting variant and the reinfecting *** was a consistent correlation between real-world protection,antigenic distance,and humoral immunity ***,shorter antigenic distances and higher humoral immunity levels corresponded to enhanced real-world *** are the implications for public health practice?Our findings suggest that virological and immunological studies could help identify and assess the epidemic risk posed by new variants before they become *** incorporation of the latest variants into the antigen components of the coronavirus disease 2019(COVID-19)vaccines can significantly contribute to effective epidemic prevention and control measures.

关键词： immunity prevention shorter

Multi-population particle swarm optimization algorithm for automatic design of steel frames

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Frontiers of Structural and Civil Engineering 2024年第1期18卷 89-103页

作者： Wenchen SHAN Jiepeng LIU Yao DING Y.Frank CHEN Junwen ZHOU Institute of Smart City and intelligent transportation Southwest Jiaotong UniversityChengdu 610000China School of Civil Engineering Chongqing UniversityChongqing 400045China Department of Civil Engineering the Pennsylvania State UniversityMiddletownPA 17057USA

Steel structures are widely used;however,their traditional design method is a trial-and-error procedure which is neither efficient nor cost ***,a multi-population particle swarm optimization(MPPSO)algorithm is developed to optimize the weight of steel frames according to standard design *** are made to improve the algorithm performances including the constraint-based strategy,piecewise mean learning strategy and multi-population cooperative *** proposed method is tested against the representative frame taken from American standards and against other steel frames matching Chinese design *** related parameter influences on optimization results are *** the representative frame,MPPSO can achieve greater efficiency through reduction of the number of analyses by more than 65% and can obtain frame with the weight for at least 2.4%lighter.A similar trend can also be observed in cases subjected to Chinese design *** addition,a migration interval of 1 and the number of populations as 5 are recommended to obtain better MPPSO *** purpose of the study is to propose a method with high efficiency and robustness that is not confined to structural scales and design *** aims to provide a reference for automatic structural optimization design problems even with dimensional *** proposed method can be easily generalized to the optimization problem of other structural systems.

关键词： steel frame multi-population particle swarm optimization automatic structural optimization design

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1786-1801页

作者： Sheng Qi Rui Wang Tao Zhang Weixiong Huang Fan Yu Ling Wang College of systems Engineering National University of Defense TechnologyChangsha 410073China College of systems Engineering National University of Defense TechnologyChangsha 410073and also with the Xiangjiang LaboratoryChangsha 410205China College of transportation and Engineering Central South UniversityChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and ***,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational ***,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables *** paper is dedicated to addressing the challenges posed by *** start,we introduce innovative objective functions customized to mine maximum and minimum candidate *** substantial enhancement dramatically improves the efficacy of frequent pattern *** this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific ***,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero *** novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function *** extensively tested our algorithm across eight benchmark problems and four real-world *** results demonstrate that our approach achieves competitive solutions across various challenges.

关键词： Evolutionary algorithms pattern mining sparse large-scale multi-objective problems(SLMOPs) sparse large-scale optimization.