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An elastoplastic damage model for stratified rocks using Pietruszczak–Mroz anisotropic theory

Journal of Rock Mechanics and Geotechnical Engineering 2025年

作者： Susheng Wang Qiang Zhang Qingfu Huang Pengfei Yin Jiuchang Zhang Key Laboratory of Rock Mechanics and Geohazards of Zhejiang Province School of Civil Engineering Shaoxing University Shaoxing 312000 China School of Mechanics and Civil Engineering China University of Mining and Technology Xuzhou 221116 China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing 100048 China Power China Kunming Engineering Corporation Limited Kunming 650051 China Department of Civil Engineering Yunnan Minzu University Kunming 650504 China Yunnan Provincial Department of Education Engineering Research Center for Building Digital and Energy Saving Technology Yunnan Minzu University Kunming 650504 China

The mechanical properties of stratified rocks are closely related not only to the stress state but also to the inherent structural anisotropy, which can be represented by the occurrence of bedding planes. This research aims to enhance the understanding of the anisotropic deformation and failure behaviors of stratified rocks by proposing a novel coupled elastoplastic-damage constitutive model. In this constitutive model, a scalar anisotropic parameter (stress-structure mixed invariant) based on the Pietruszczak–Mroz anisotropic theory is incorporated into a nonlinear yield surface, which accounts for the combined effects of the stress state and bedding structure on the anisotropic strength behaviors of stratified rocks. A damage-driven function governs the expansion and contraction of the anisotropic yield surface in the pre-peak strain hardening and post-peak strain-softening regions. The strength and deformation characteristics under multiaxial stress conditions are represented by incorporating the Lode’s angle into the yield and plastic potential functions. Numerical simulations are conducted to facilitate a comparison with the conventional and true triaxial compression test data for several stratified rocks. The simulation results demonstrate good agreement with the test data, validating the effectiveness of the proposed constitutive model. This study provides theoretical and technical support for addressing engineering challenges involving stratified rocks.

关键词： Stratified rocks Inherent anisotropy Coupled elastoplastic-damage model Microstructure tensor Pietruszczak–Mroz anisotropic theory

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Rethinking Lightweight Convolutional Neural Networks for Efficient and High-quality Pavement Crack Detection

arXiv

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arXiv 2021年

作者： Li, Kai Yang, Jie Ma, Siwei Wang, Bo Wang, Shanshe Tian, Yingjie Qi, Zhiquan School of Computer Science Institute of Digital Media Peking University Beijing100871 China School of Mathematics Sciences University of Chinese Academy of Sciences Beijing100049 China Advanced Institute of Information Technology Peking University Hangzhou310005 China School of Information Technology and Management University of International Business and Economics Beijing100029 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China MOE Social Science Laboratory of Digital Economic Forecasts and Policy Simulation University of Chinese Academy of Sciences No. 3 South Yitiao Zhongguancun Haidian District Beijing100190 China

Pixel-level road crack detection has always been a challenging task in intelligent transportation systems. Due to the external environments, such as weather, light, and other factors, pavement cracks often present low contrast, poor continuity, and different sizes in length and width. However, most of the existing studies pay less attention to crack data under different situations. Meanwhile, recent algorithms based on deep convolutional neural networks (DCNNs) have promoted the development of cutting-edge models for crack detection. Nevertheless, they usually focus on complex models for good performance, but ignore detection efficiency in practical applications. In this article, to address the first issue, we collected two new databases (i.e. Rain365 and Sun520) captured in rainy and sunny days respectively, which enrich the data of the open source community. For the second issue, we reconsider how to improve detection efficiency with excellent performance, and then propose our lightweight encoder-decoder architecture termed CarNet. Specifically, we introduce a novel olive-shaped structure for the encoder network, a light-weight multi-scale block and a new up-sampling method in the decoder network. Numerous experiments show that our model can better balance detection performance and efficiency compared with previous models. Especially, on the Sun520 dataset, our CarNet significantly advances the state-of-the-art performance with ODS F-score from 0.488 to 0.514. Meanwhile, it does so with an improved detection speed (104 frame per second) which is orders of magnitude faster than some recent DCNNs-based algorithms specially designed for crack detection. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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DID Code:A Bridge Connecting the Materials Genome Engineering Database w让h Inheritable Integrated Intelligent Manufacturing

引用

Engineering 2020年第6期6卷 612-620页

作者： William Yi Wang Peixuan Li Deye Lin Bin Tang Jun Wang Quanmei Guan Qian Ye Haixing Dai Jun Gao Xiaoli Fan Hongchao Kou Haifeng Song Feng Zhou Jijun Ma Zi-Kui Liu Jinshan Li Weimin Liu State Key Laboratory of Solidification Processing Northwestern Polytechnical UniversityXi'an 710072China CAEP Software Center for High Performance Numerical Simulation Institute of Applied Physics and Computational MathematicsBeijing 100088China CRRC Tangshan Co. Ltd.Tangshan 063035China Beijing Star Travel Space Technology Co. Ltd.Beijing 100013China Department of Materials Science and Engineering Pennsylvania State UniversityUniversity ParkPA 16802USA

A data identifier(DID)is an essential tag or label in all kinds of databases—particularly those related to integrated computational materials engineering(ICME),inheritable integrated intelligent manufacturing(I3M),and the Industrial Internet *** the guidance and quick acceleration of the developme nt of advanced materials,as envisioned by official documents worldwide,more investigations are required to construct relative numerical standards for material *** work proposes a universal DID format consisting of a set of build chains,which aligns with the classical form of identifier in both international and national standards,such as ISO/IEC 29168-1:2000,GB/T 27766-2011,GA/T 543.2-2011,GM/T 0006-2012,GJB 7365-2011,SL 325-2014,SL 607-201&WS 363.2-2011,and QX/T *** build chain is made up of capital letters and numbers,with no ***,the total length of each build chain is not restricted,which follows the formation of the Universal Coded Character Set in the international standard of ISO/IEC *** on these rules,the proposed DID is flexible and convenient for extendi ng and sharing in and between various cloud-based ***,classical two-dimensional(2D)codes,including the Hanxin Code,Lots Perception Matrix(LP)Code,Quick Response(Q.R)code,Grid Matrix(GM)code,and Data Matrix(DM)Code,can be constructed and precisely recognized and/or decoded by either smart phones or specific *** utilizing these 2D codes as the fingerprints of a set of data linked with cloud-based platforms,progress and updates in the composition-processing-structure-property-performance workflow process can be tracked spontaneously,paving a path to accelerate the discovery and manufacture of advanced materials and enhance research productivity,performance,and collaboration.

关键词： Data identifier Database digital twin Integrated computational materials engineering

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A Method to Create Training Dataset for Dehazing with Cyclegan

A Method to Create Training Dataset for Dehazing with Cycleg...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Hui Zhang Fan Mou Shangqi Duan Shuangde Huang Shengwei Wang Debin Xu Zezhong Zheng Kunming Power Supply Bureau of Yunnan Power Grid Co. Ltd. Kunming Yunnan PRC School of Resources and Environment University of Electronic Science and Technology of China Chengdu Sichuan PRC Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Land and Resources Shenzhen Guangdong PRC State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan Hubei PRC State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences Beijing PRC Guangxi Key Laboratory for Spatial Information and Geomatics Guilin University of Technology Guilin Guangxi PRC

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Haze usually blurs the characteristics of images shotted in adverse weather conditions. It brings many challenges for computer vision such as object detection. Due to the lack of effective training dataset of remote sensing image, the dehazing usually utilize the physical model rather than the deep learning approach based on a large number of training dataset. An effective method to create training dataset may provide some new ideas for remote sensing image dehazing. In this paper, a novel approach based on the visual features rather than the physical counterparts is developed to create a training dataset for remote sensing images dehazing. Firstly, 400 haze images and 400 clear images with size of 240×240 pixels were gathered from Landsat 8. Secondly, the dataset was utilized to train the cycle-consistent generative adversarial network (CycleGAN) to derive an image transform model which can convert a clear image into a haze one. Thirdly, 4000 clear images with size of 240×240 pixels were collected from Landsat 8 and the images were transformed into the haze images with our model. Finally, the ratio of training dataset and testing dataset is set as 4:1. The haze images created by us were selected as the input and the original clear images were chosen as the output to train the convolutional neural networks to derive the dehazing models. The created dataset and the dehazing models derived were tested, and the experimental results showed that our approach is better to keep the brightnessinformation of the original image, but it is not good at keeping the chroma information.

关键词： Atmospheric modeling Training Remote sensing Scattering Testing Transforms Generative adversarial networks

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Change of Glacial Lake in Karakoram Range

Change of Glacial Lake in Karakoram Range

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fan Mou Danyang Wang Jiaxi Liu Zezhong Zheng Liming Jiang Guoqing Zhou Fangrong Zhou School of Resources and Environment University of Electronic Science and Technology of China Chengdu Sichuan PRC Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Land and Resources Shenzhen Guangdong PRC State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan University Wuhan Hubei PRC State Key Laboratory of Remote Sensing Science Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences Beijing PRC Guangxi Key Laboratory for Spatial Information and Geomatics Guilin University of Technology Guilin Guangxi PRC Institute of Geodesy and Geophysics Chinese Academy of Sciences Wuhan Hubei PRC Electric Power Research Institute Yunnan Power Grid Co. Ltd. Kunming Yunnan PRC

ISBN: (数字)9781728163741

ISBN: (纸本)9781728163758

Global warming results in the rapid melting of glacial lakes in the Himalayas. In this paper, we took the Karakoram range in the Himalayas as the study area, and we derived the glacial lake area in 2001, 2014, and 2017 with semantic segmentation algorithm. Firstly, five high-resolution images in Mount Lucania were collected from Google Earth. Secondly, each image was labelled, and 80000 training images with the size of 256×256 pixels were derived using augmentation approach. Thirdly, a model of the stacking network of U-Net and SegNet based on these training images to extract the glacial lake was trained. Then, another five images of Karakoram range were derived from Google Earth as a testing dataset to demonstrate the performance of training model. Finally, the glacial lakes were extracted from the images of Karakoram range in the same month in 2001, 2014 and 2017. Our result showed that the area of the glacial lake in Karakoram range increased rapidly from 2001 to 2014, but decreased from 2014 to 2017.

关键词： Lakes Training Image segmentation Earth Stacking Semantics Internet

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Analysis of Topography and Composition of the Von Kármán Impact Crater

引用

IOP Conference Series: Earth and Environmental Science 2021年第1期658卷

作者： Jinlong Hou Li Li Shiwei Li College of Resource Environment and Tourism Capital Normal University Beijing 100048 China State Key Laboratory Incubation Base of Urban Environmental Processes and Digital Simulation Beijing 100048 China Beijing Laboratory of Water Resources Security Beijing Municipal Education Commission Beijing 100048 China College of Geomatics Science and Technology Xi'an University of Science and Technology Xi'an 710054 China

The Vo n Kármán impact crater in the Chang'E-4 landing area is located in in the Northwestern South Pole-Aitken (SPA) basin on the back of the Moon, and the analysis of its topography and compositional characteristics is essential for the landing of the probe and the exploration of the lunar surface, which plays a fundamental role in obtaining information on the geomorphology and geology of the lunar surface. In this paper, the topography of the Vo n Kármán impact crater is analyzed based on DEM, slope and terrain roughness, then the compositional characteristics of the Von Kármán impact crater are analyzed according to TiO2 and FeO content through combining LRO LOLA data and Clementine UV-VIS data. This study is a basis for revealing the surface characteristics and structure of the Moon.

关键词：

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Medical Additive Manufacturing: From a Frontier technology to the Research and Development of Products

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Engineering 2020年第11期6卷 1217-1221页

作者： Guixing Qiu Wenjiang Ding Wei Tian Ling Qin Yu Zhao Lianmeng Zhang Jian Lu Daijie Chen Guangyi Yuan Chengtie Wu Bingheng Lu Ruxu Du Jimin Chen Mo Elbestawi Zhongwei Gu Dichen Li Wei Sun Yuanjin Zhao Jie He Dadi Jin Bin Liu Kai Zhang Jianmo Li Kam WLeong Dewei Zhao Dingjun Hao Yingfang Ao Xuliang Deng Huilin Yang ShaoKeh Hsu Yingqi Chen Long Li Jianping Fan Guohui Nie Yun Chen Hui Zeng Wei Chen Yuxiao Lai Department of Orthopedics Peking Union Medical College HospitalChinese Academy of Medical Science 8 Peking Union Medical CollegeBejjing 100730.China National Engineering Research Center of Light Alloys Net Forming&State Key Laboratony of Metal Matrix Composite Shanghai Jiao Tong UniversityShanghai 200240China Notional Engineering Research Center of Mg Materials and Applicarions and School of Materials Science 8r Engineering.Shanghai Jlao Tong University Shanghai 200240China Department of Spine Surgery Beijing Jishuitan HospitalBeijing 100035China Center for Troanslational Medicine Research and Development Institute of Biomedical and Health EngineeringShenzhen Insitute of Advanced Technology.Chinese Academy of SciencesShenzhen 518055China Guangdong Engineering Laboratony of Biomaterials Additive Manufacturing Guangdong 518055China Musculoskeletal Research Laboratory of the Department of Orthopedics 8 Traumatology and Innovative Orthopedic Biomaterial and Drug Translational Research Laboratory Li Ka Shing Institute of Health SciencesThe Chinese University of Hong KongHong Kong 999077.China State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Center for Advanced Structural Materials City University of Hong Kong Shenzhen Research InstiuteShenzhen 518057.China Hong Kong Branch of National Precious Metals Material Engineering Research Center Department of Material Science and EngineeringCity Untiversity of Hong KongHong Kong 999077.China Department of Mechanical Engineering ity Untiversity of Hong Kong.Hong Kong 9977 China School of Pharmacy.Shanghai Jiao Tong University Shanghai 200240China China State Instute of Pharmaceutical Industry Shanghai Institute of Pharmaceutical IndustryShonghai 201203China Shanghai Innovation Instinute for Materials Shanghai 200444.China State Key Laboratory of High-Performance Ceramies and Superfine Microstructure Shanghai Institute of CeramicsChinese Acadermy 0f SciencesShanghai 200050Ch

*** and development(R&D)and the challenges of raw materials for medical additive manufacturing Raw materials for medical additive manufacturing have a wide range of commonalities that are also seen in many other fields,making them an important basis in the field of three-dimensional(3D)*** and challenges related to material types,powder properties,formability,viscoelasticity,and so forth also share common *** example,many metal materials are used in the field of aviation,while metals,polymers,and inorganic materials are used in the field of *** most widely used materials in biomedicine are *** homogeneous and non-homogeneous composites are also available for 3D printing,and impose an additional challenge in additive manufacturing;the use of heterogeneous composites in 3D printing is particularly challenging.

关键词： composites printing additive

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Constraints on the two-dimensional pseudospin-12 Mott insulator description of Sr2IrO4

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Physical Review B 2022年第24期105卷 245130-245130页

作者： B. Zwartsenberg R. P. Day E. Razzoli M. Michiardi M. X. Na G. Zhang J. D. Denlinger I. Vobornik C. Bigi B. J. Kim I. S. Elfimov E. Pavarini A. Damascelli Quantum Matter Institute University of British Columbia Vancouver Canada BC V6T 1Z4 Department of Physics and Astronomy University of British Columbia Vancouver Canada BC V6T 1Z1 Max Planck Institute for Chemical Physics of Solids Nöthnitzer Straße 40 01187 Dresden Germany Key Laboratory of Materials Physics Institute of Solid State Physics HFIPS Chinese Academy of Sciences Hefei 230031 People's Republic of China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley California 94720 USA Istituto Officina dei Materiali (IOM)-CNR Laboratorio TASC in Area Science Park S.S.14 Km 163.5 I-34149 Trieste Italy Dipartimento di Fisica Universit di Milano Via Celoria 16 I-20133 Milano Italy Department of Physics Pohang University of Science and Technology Pohang 790-784 South Korea Center for Artificial Low Dimensional Electronic Systems Institute for Basic Science (IBS) 77 Cheongam-Ro Pohang 790-784 Republic of Korea Max Planck Institute for Solid State Research Heisenbergstraße 1 D-70569 Stuttgart Germany Institute for Advanced Simulation Forschungszentrum Jülich D-52425 Jülich Germany JARA High-Performance Computing Forschungszentrum Jülich D-52425 Jülich Germany

Sr2IrO4 has often been described via a simple, one-band pseudospin-12 model subject to electron-electron interactions on a square lattice, fostering analogies with cuprate superconductors believed to be well described by a similar model. In this work we argue—based on a detailed study of the low-energy electronic structure by circularly polarized spin and angle-resolved photoemission spectroscopy combined with dynamical mean-field theory calculations—that a pseudospin-12 model fails to capture the full complexity of the system. We show instead that a realistic multiband Hubbard Hamiltonian, accounting for the full correlated t2g manifold, provides a detailed description of the interplay between spin-orbital entanglement and electron-electron interactions and yields quantitative agreement with experiments. Our analysis establishes that the j3/2 states make up a substantial percentage of the low-energy spectral weight, i.e., approximately 74% as determined from the integration of the j-resolved spectral function in the 0 to −1.64eV energy range. The results in our work are of relevance not only to Ir-based materials but also more generally to multiorbital materials with closely spaced energy scales.

关键词： Spin-orbit coupling High-temperature superconductors Mott insulators Angle-resolved photoemission spectroscopy Dynamical mean field theory Hubbard model Spin-resolved photoemission spectroscopy

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Spin-Triplet Excitonic Insulator: The Case of Semihydrogenated Graphene

引用

Physical Review Letters 2020年第16期124卷 166401-166401页

作者： Zeyu Jiang Wenkai Lou Yu Liu Yuanchang Li Haifeng Song Kai Chang Wenhui Duan Shengbai Zhang State Key Laboratory of Low-Dimensional Quantum Physics and Collaborative Innovation Center of Quantum Matter Department of Physics Tsinghua University Beijing 100084 China SKLSM Institute of Semiconductors Chinese Academy of Sciences P.O. Box 912 Beijing 100083 China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing 100088 China Key Lab of advanced optoelectronic quantum architecture and measurement (MOE) and Advanced Research Institute of Multidisciplinary Science Beijing Institute of Technology Beijing 100081 China CAEP Software Center for High Performance Numerical Simulation Beijing 100088 China Beijing Academy of Quantum Information Sciences Beijing 100193 China Institute for Advanced Study Tsinghua University Beijing 100084 China Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute Troy New York 12180 USA

While various excitonic insulators have been studied in the literature, due to the perceived too-small spin splitting, spin-triplet excitonic insulator is rare. In two-dimensional systems such as a semihydrogenated graphene (known as graphone), however, it is possible, as revealed by first-principles calculations coupled with Bethe-Salpeter equation. The critical temperature, given by an effective Hamiltonian, is 11.5 K. While detecting excitonic insulators is still a daunting challenge, the condensation of triplet excitons will result in spin superfluidity, which can be directly measured by a transport experiment. Nonlocal dielectric screening also leads to an unexpected phenomenon, namely, an indirect-to-direct transition crossover between single-particle band and exciton dispersion in the semihydrogenated graphene, which offers yet another test by experiment.

关键词： Excitons Graphene First-principles calculations

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Constraints on the two-dimensional pseudo-spin 1/2 Mott insulator description of Sr2IrO4

arXiv

引用

arXiv 2022年

作者： Zwartsenberg, Berend Day, Ryan P. Razzoli, Elia Michiardi, Matteo Na, Meng Xing Zhang, Guoren Denlinger, Jonathan D. Vobornik, Ivana Bigi, Chiara Kim, Bum Joon Elfimov, Ilya S. Pavarini, Eva Damascelli, Andrea Quantum Matter Institute University of British Columbia VancouverBCV6T 1Z4 Canada Department of Physics and Astronomy University of British Columbia VancouverBCV6T 1Z1 Canada Max Planck Institute for Chemical Physics of Solids Nöthnitzer Straße 40 Dresden01187 Germany Key Laboratory of Materials Physics Institute of Solid State Physics Hfips Chinese Academy of Sciences Hefei230031 China Advanced Light Source Lawrence Berkeley National Laboratory BerkeleyCA94720 United States -CNR Laboratorio Tasc Area Science Park S.S.14 Km 163.5 TriesteI-34149 Italy Dipartimento di Fisica Universitá di Milano Via Celoria 16 MilanoI-20133 Italy Department of Physics Pohang University of Science and Technology Pohang790-784 Korea Republic of 77 Cheongam-Ro Pohang790-784 Korea Republic of Max Planck Institute for Solid State Research Heisenbergstraße 1 StuttgartD-70569 Germany Institute for Advanced Simulation Forschungszentrum Jülich JülichD-52425 Germany Jara High-Performance Computing Forschungszentrum Jülich Jülich Germany

Sr2IrO4has often been described via a simple, one-band pseudo-spin 1/2 model, subject to electron-electron interactions, on a square lattice, fostering analogies with cuprate superconductors, believed to be well described by a similar model. In this work we argue - based on a detailed study of the low-energy electronic structure by circularly polarized spin and angle-resolved photoemission spectroscopy combined with dynamical mean-field theory calculations - that a pseudo-spin 1/2 model fails to capture the full complexity of the system. We show instead that a realistic multi-band Hubbard Hamiltonian, accounting for the full correlated t2gmanifold, provides a detailed description of the interplay between spin-orbital entanglement and electron-electron interactions, and yields quantitative agreement with experiments. Our analysis establishes that the j3/2states make up a substantial percentage of the low energy spectral weight, i.e. approximately 74% as determined from the integration of the j-resolved spectral function in the 0 to -1.64 eV energy range. The results in our work are not only of relevance to iridium based materials, but more generally to the study of multi-orbital materials with closely spaced energy scales. © 2022, CC BY-NC-ND.

关键词： Electron-electron interactions

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