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On dynamic analysis method for large-scale train-track-substructure interaction

Railway Engineering Science 2022年第2期30卷 162-182页

作者： Lei Xu School of Civil Engineering Central South UniversityChangsha 410075China National Engineering Laboratory for High-Speed Railway Construction Changsha 410075China

Train–track–substructure dynamic interaction is an extension of the vehicle–track coupled dynamics.It contributes to evaluate dynamic interaction and performance between train–track system and its substructures.For the first time,this work devotes to presenting engineering practical methods for modeling and solving such large-scale train–track–substructure interaction systems from a unified viewpoint.In this study,a train consists of several multi-rigid-body vehicles,and the track is modeled by various finite elements.The track length needs only satisfy the length of a train plus boundary length at two sides,despite how long the train moves on the track.The substructures and their interaction matrices to the upper track are established as independent modules,with no need for additionally building the track structures above substructures,and accordingly saving computational cost.Track–substructure local coordinates are defined to assist the confirming of the overlapped portions between the train–track system and the substructural system to effectively combine the cyclic calculation and iterative solution procedures.The advancement of this model lies in its convenience,efficiency and accuracy in continuously considering the vibration participation of multi-types of substructures against the moving of a train on the track.Numerical examples have shown the effectiveness of this method;besides,influence of substructures on train–track dynamic behaviors is illustrated accompanied by clarifying excitation difference of different track irregularity spectrums.

关键词： Train Track dynamic interaction Railway substructures Finite elements Dynamics system Iterative solution Tunnel Bridge

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DCVAE-adv:A Universal Adversarial Example Generation Method for White and Black Box Attacks

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Tsinghua Science and Technology 2024年第2期29卷 430-446页

作者： Lei Xu Junhai Zhai College of Mathematics and Information Science Hebei UniversityBaoding 071002China

Deep neural network(DNN)has strong representation learning ability,but it is vulnerable and easy to be fooled by adversarial examples.In order to handle the vulnerability of DNN,many methods have been proposed.The general idea of existing methods is to reduce the chance of DNN models being fooled by observing some designed adversarial examples,which are generated by adding perturbations to the original images.In this paper,we propose a novel adversarial example generation method,called DCVAE-adv.Different from the existing methods,DCVAE-adv constructs adversarial examples by mixing both explicit and implicit perturbations without using original images.Furthermore,the proposed method can be applied to both white box and black box attacks.In addition,in the inference stage,the adversarial examples can be generated without loading the original images into memory,which greatly reduces the memory overhead.We compared DCVAE-adv with three most advanced adversarial attack algorithms:FGSM,AdvGAN,and AdvGAN++.The experimental results demonstrate that DCVAE-adv is superior to these state-of-the-art methods in terms of attack success rate and transfer ability for targeted attack.Our code is available at https://***/xzforeverlove/DCVAE-adv.

关键词： deep neural network adversarial examples white box attack black box attack robustness

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Learning deep IA bidirectional intelligence

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Frontiers of Information Technology & Electronic Engineering 2020年第4期21卷 558-562页

作者： Lei Xu Centre for Cognitive Machines and Computational Health(CMaCH) School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Neural Computation Research Centre Brain and Intelligence Sci-Tech InstituteZhangjiang LabShanghai 201210China

There has been a framework sketched for learning deep bidirectional intelligence.The framework has an inbound that features two actions:one is the acquiring action,which gets inputs in appropriate patterns,and the other is A-S cognition,derived from the abbreviated form of words abstraction and self-organization,which abstracts input patterns into concepts that are labeled and understood by self-organizing parts involved in the concept into structural hierarchies.The top inner domain accommodates relations and a priori knowledge with the help of the A-I thinking action that is responsible for the accumulation-amalgamation and induction-inspiration.The framework also has an outbound that comes with two actions.One is called I-S reasoning,which makes inference and synthesis(I-S)and is responsible for performing various tasks including image thinking and problem solving,and the other is called the interacting action,which controls,communicates with,and inspects the environment.Based on this framework,we further discuss the possibilities of design intelligence through synthesis reasoning.

关键词： Abstraction Least mean square error reconstruction(Lmser) Cognition Image thinking Abstract thinking Synthesis reasoning

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An Overview and Perspectives On Bidirectional Intelligence: Lmser Duality, Double IA Harmony,and Causal Computation

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IEEE/CAA Journal of Automatica Sinica 2019年第4期6卷 865-893页

作者： Lei Xu IEEE the Center for Cognitive Madmnes and Computational Health(CMaCH) School of Electronic Information and Electrical EngineeringShanghai Jiao Tong University Neural Computation Research Centre in Brain and Intelligence Science-Technology Institute Shanghai ZhangJiang National Lab

Advances on bidirectional intelligence are overviewed along three threads,with extensions and new perspectives.The first thread is about bidirectional learning architecture,exploring five dualities that enable Lmser six cognitive functions and provide new perspectives on which a lot of extensions and particularlly flexible Lmser are proposed.Interestingly,either or two of these dualities actually takes an important role in recent models such as U-net,ResNet,and Dense Net.The second thread is about bidirectional learning principles unified by best yIng-yAng(IA)harmony in BYY system.After getting insights on deep bidirectional learning from a bird-viewing on existing typical learning principles from one or both of the inward and outward directions,maximum likelihood,variational principle,and several other learning principles are summarised as exemplars of the BYY learning,with new perspectives on advanced topics.The third thread further proceeds to deep bidirectional intelligence,driven by long term dynamics(LTD)for parameter learning and short term dynamics(STD)for image thinking and rational thinking in harmony.Image thinking deals with information flow of continuously valued arrays and especially image sequence,as if thinking was displayed in the real world,exemplified by the flow from inward encoding/cognition to outward reconstruction/transformation performed in Lmser learning and BYY learning.In contrast,rational thinking handles symbolic strings or discretely valued vectors,performing uncertainty reasoning and problem solving.In particular,a general thesis is proposed for bidirectional intelligence,featured by BYY intelligence potential theory(BYY-IPT)and nine essential dualities in architecture,fundamentals,and implementation,respectively.Then,problems of combinatorial solving and uncertainty reasoning are investigated from this BYY IPT perspective.First,variants and extensions are suggested for AlphaGoZero like searching tasks,such as traveling salesman problem(TSP)and attributed graph matching(AGM)that ar

关键词： Autoencoder LMSER duality outward attention associative recall concept formation imagining pattern transformation STD vs LTD RPCL skip connection feedback variational least redundancy Bayesian Ying Yang IA system best harmony best matching image thinking rational thinking intelligence potential theory Alpha-TSP Alpha-AGM graph matching ME Player BYY Follower constraint satisfaction causal potential theory

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The effects of different electrode materials on seed germination of Solanum nigrum L.and its Cd accumulation in soil

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Journal of Environmental Sciences 2022年第3期34卷 291-299页

作者： Lei Xu Huiping Dai Lidia Skuza Shuhe Wei Key Laboratory of Pollution Ecology and Environment Engineering Institute of Applied EcologyChinese Academy of SciencesShenyang 110016China College of Biological Science&Engineering Shaanxi Province Key Laboratory of Bio-resourcesShaanxi University of TechnologyHanzhong 723001China Institute of Biology Centre for Molecular Biology and BiotechnologyUniversity of SzczecinSzczecin 71-415Poland University of Chinese Academy of Sciences Beijing 100039China

The effects of different electrode on Solanum nigrum L.seed germination were determined.The result showed that germination percentage(GP)of seeds in treatment T2(titanium elec-trode)was 26.6%higher than in control(CK,without electric field).High potassium and calcium concentrations were beneficial for seed enzymatic activity in treatment T2,which could partly explain the increase in GP.Cd accumulation(μg/pot)in S.nigrum treated with any electric field was significantly higher(p<0.05)than in CK without electric field.Specif-ically,Cd accumulation under the treatment T3(stainless steel electrode)was the highest both in roots and shoots;this accumulation in shoots and roots were 74.7%and 67.4%higher for stainless steel than in CK.This increase must have been associated with a higher Cd concentration in plants and did not exert a significant effect on the biomass.In par-ticular,Cd concentrations in roots and shoots under stainless steel treatment were both significantly higher than in CK(p<0.05),which had to be related to the higher available Cd concentration in the soil in the middle region.Furthermore,it could be attributed to al-tered soil pH and other soil properties.Moreover,none of the biomasses were significantly affected(p<0.05)by different electrode materials compared to CK.

关键词： Cd contaminated soil Solanum nigrum L. DC electric field Electrode materials Seed germination

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An efficient approach for mesoscale fracture modeling of fully-graded hydraulic concrete

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Water Science and Engineering 2022年第4期15卷 337-347页

作者： Lei Xu lei Jiang Ye-fei Huang Qing-wen Ren College of Water Conservancy and Hydropower Engineering Hohai UniversityNanjing 210098China

Large coarse aggregates used in fully-graded hydraulic concrete necessitate large specimens for numerical modeling.This leads to a high computational cost for mesoscale modeling and thus slows the development of multiscale modeling of hydraulic mass concrete structures.To overcome this obstacle,an efficient approach for mesoscale fracture modeling of fully-graded hydraulic concrete was developed based on the concept of the governing mesostructure.The mesostructure was characterized by a critical aggregate size.Coarse aggregates smaller than the critical size were homogenized into mortar matrices.Key issues in mesostructure generation of fully-graded hydraulic concrete are discussed,as is the development of mesoscale finite element modeling methodology.The basic concept and implementation procedures of the proposed approach are also described in detail.The numerical results indicated that the proposed approach not only significantly improves the compu-tational efficiency of mesoscale modeling but also captures the dominant fracturing mechanism at the mesoscale and reproduces reasonable fracture properties at the macroscale.Therefore,the proposed approach can serve as a basis for multiscale fracture modeling of hydraulic mass concrete structures.

关键词： Fully-graded hydraulic concrete Mesoscale Fracture modeling Governing mesostructure Critical aggregate size

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Coarse-to-fine waterlogging probability assessment based on remote sensing image and social media data

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Geo-Spatial Information Science 2021年第2期24卷 279-301,I0007页

作者： Lei Xu Ailong Ma State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingWuhan UniversityWuhanChina Collaborative Innovation Center of Geospatial Technology Wuhan UniversityWuhanChina

Urban waterlogging probability assessment is critical to emergency response and policymaking.Remote Sensing(RS)is a rich and reliable data source for waterlogging monitoring and evaluation through water body extraction derived from the pre-and post-disaster RS images.However,RS images are usually limited to the revisit cycle and cloud cover.To solve this issue,social media data have been considered as another data source which are immune to the weather such as clouds and can reflect the real-time public response for disaster,which leads itself a compensation for RS images.In this paper,we propose a coarse-to-fine waterlogging probability assessment framework based on multisource data including real-time social media data,near real-time RS image and historical geographic information,in which a coarse waterlogging probability map is refined by using the real-time information extracted from social media data to acquire a more accurate waterlogging probability.Firstly,to generate a coarse waterlogging probability map,the historical inundated areas are derived from Digital Elevation Model(DEM)and historical waterlogging points,then the geographic features are extracted from DEM and RS image,which will be input to a Random Forest(RF)classifier to estimate the likelihood of hazards.Secondly,the real-time waterlogging-related information is extracted from social media data,where the Convolutional Neural Network(CNN)model is applied to exploit the semantic information of sentences by capturing the local and position-invariant features using convolution kernel.Finally,fine waterlogging probability map scan be generated based on morphological method,in which real-time waterlogging-related social media data are taken as isolated highlight point and used to refine the coarse waterlogging probability map by a gray dilation pattern considering the distance-decay effect.The 2016 Wuhan waterlogging and 2018 Chengdu water-logging are taken as case studies to demonstrate the effectiveness of the proposed framework.It can be conclud

关键词： Remote sensing social media urban waterlogging data fusion

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Experiments on rockburst proneness of pre-heated granite at different temperatures: Insights from energy storage, dissipation and surplus

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Journal of Rock Mechanics and Geotechnical Engineering 2022年第5期14卷 1343-1355页

作者： Lei Xu Fengqiang Gong Zhixiang Liu School of Resources and Safety Engineering Central South UniversityChangsha410083China School of Civil Engineering Southeast UniversityNanjing211189China

Many underground engineering projects show that rockburst can occur in rocks at great depth and high temperature, and temperature is a critical factor affecting the intensity of rockburst. In general, temperature can affect the energy storage, dissipation, and surplus in rock. To explore the influence of temperature on the energy storage and dissipation characteristics and rockburst proneness, the present study has carried out a range of the uniaxial compression(UC) and single-cyclic loading-unloading uniaxial compression(SCLUC) tests on pre-heated granite specimens at 20℃-700℃. The results demonstrate that the rockburst proneness of pre-heated granite initially increases and subsequently decreases with the increase of temperature. The temperature of 300℃ has been found to be the threshold for rockburst proneness. Meanwhile, it is found that the elastic strain energy density increases linearly with the total input strain energy density for the pre-heated granites, confirming that the linear energy property of granite has not been altered by temperature. According to this inherent property, the peak elastic strain energy of pre-heated granites can be calculated accurately. On this basis, utilising the residual elastic energy index, the rockburst proneness of pre-heated granite can be determined quantitatively. The obtained results from high to low are: 317.9 k J/m^(3)(300℃), 264.1 k J/m^(3)(100℃), 260.6 k J/m^(3)(20℃), 235.5 k J/m^(3)(500℃), 158.9 k J/m^(3)(700℃), which are consistent with the intensity of actual rockburst for specimens. In addition, the relationship between temperature and energy storage capacity(ESC) of granite was discussed, revealing that high temperature impairs ESC of rocks, which is essential for reducing the rockburst proneness. This study provides some new insights into the rockburst proneness evaluation in high-temperature rock engineering.

关键词： Pre-heated granite Temperature effect Linear energy storage law Rockburst proneness Residual elastic energy index

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Unloading phosphate for starch synthesis in cereal grains

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Molecular Plant 2021年第8期14卷 1232-1233页

作者： Lei Xu Keke Yi Key Laboratory of Plarft Nutrition and Fertilizers Ministry of Agriculture and Rural AffairsInstitute of Agricultural Resources and Regional PlanningChinese Academy of Agricultural SciencesBeijing 100081China

The macronutrient phosphorus(P)is essential for plant growth and of vital importance to crop yield.It is taken up from the soil in the form of inorganic orthophosphate[PO_(4)^(3-),HPO_(4)^(2-),H_(2)PO_(4)^(-)(Pi)]by plant roots.As Pi readily forms insoluble complexes and precipitates with organic matter and mineral cations,Pi bioavailability in the soil is usually low and often limits crop growth and final yield.

关键词： synthesis roots readily

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Multi-level coarse-grained discrete element method modeling of cylinder particle flow in a rotating drum

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Particuology 2024年第5期88卷 218-238页

作者： Lei Xu Xiukai Wu Shuai Wang Shiyi Bao Institute of Process Equipment and Control Engineering Zhejiang University of TechnologyHangzhou 310023China Engineering Research Center of Process Equipment and Remanufacturing Ministry of EducationZhejiang University of TechnologyHangzhou 310023China College of Mechanical Engineering Zhejiang University of TechnologyHangzhou 310023China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou 310027China

The coarse-grained discrete element method(DEM)is probably a feasible option for simulating an actual drum-type biomass boiler,which contains over 10 million cylinder particles.A multi-level study was conducted based on particle and coarse-grained level data to evaluate the adequacy of the coarse-grained approach in terms of geometrical characteristics,kinematic features,and dynamic properties.Two scaling laws for contact parameters were used and compared during the simulations.The results show that the coarse-grained approach can accurately predict the positions of the free surface and active-passive interface,the mixing index,and the orientation properties.Deviations in the velocity fields may occur due to the worse flowability of coarse-grained particles near the free surface.The efficiency is significantly improved by the coarse-grained model compared with the corresponding original case(the same DEM code without a coarse-grained model was used for the original simulations).

关键词： Coarse-grained method Discrete element method(DEM) Cylinder particle Rotating drum Granular flow

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