A data-driven method for the deformation analysis of layered rocks

被引:0
作者
Feng, Fanding [1 ]
Yang, Diansen [1 ]
Jiang, Qinghui [1 ]
机构
[1] Wuhan Univ, Sch Civil Engn, Wuhan 430072, Peoples R China
基金
中国国家自然科学基金;
关键词
Data-driven computational mechanics; Data-driven identification; Layered rocks; Field measurements; Stress-strain database; DIGITAL IMAGE CORRELATION; MODEL; IDENTIFICATION; MECHANICS; NOISE;
D O I
10.1016/j.ijrmms.2025.106030
中图分类号
P5 [地质学];
学科分类号
0709 ; 081803 ;
摘要
This paper proposes a data-driven method for the deformation analysis of layered rocks, which consists of generating a stress-strain database and using a data-driven computational solution. The method does not require defining the material's constitutive relationship to conduct analysis of layered rock deformation under loading of the same material. First, the data-driven identification (DDI) algorithm infers and builds a stress-strain database of the material based on the strain field and loading force. Then, this database is used to calculate the response of the same material structure with arbitrary geometry and boundary conditions using data-driven computational mechanics (DDCM). The specific workflow of the method is demonstrated, and the computational accuracy and reliability are verified through an experimental application example. The method naturally combines the DDI algorithm and the DDCM solver, providing a new concept for analysing the deformation of layered rocks. Through this method, it is possible to conduct more accurate deformation analysis of layered rocks without defining their constitutive relationships. This has significant engineering application value in the design of excavations for layered rock slopes, foundations, and underground caverns.
引用
收藏
页数:14
相关论文
共 40 条
[1]  
Adhikary DP, 1997, Int J Rock Mech Min Sci, V34, DOI [10.1016/S1365-1609(97)00201-3, DOI 10.1016/S1365-1609(97)00201-3]
[2]   A kd-tree-accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data [J].
Bahmani, Bahador ;
Sun, WaiChing .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2021, 382
[3]   Data-driven rate-dependent fracture mechanics [J].
Carrara, P. ;
Ortiz, M. ;
De Lorenzis, L. .
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS, 2021, 155
[4]   Data-driven fracture mechanics [J].
Carrara, P. ;
De Lorenzis, L. ;
Stainier, L. ;
Ortiz, M. .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2020, 372
[5]   Model-free data-driven simulation of inelastic materials using structured data sets, tangent space information and transition rules [J].
Ciftci, Kerem ;
Hackl, Klaus .
COMPUTATIONAL MECHANICS, 2022, 70 (02) :425-435
[6]   Data-driven hyperelasticity, Part I: A canonical isotropic formulation for rubberlike materials [J].
Dal, Husnu ;
Denli, Funda Aksu ;
Acan, Alp Kagan ;
Kaliske, Michael .
JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS, 2023, 179
[7]  
Dalémat M, 2019, CONSTITUTIVE MODELS FOR RUBBER XI, P311
[8]   Measuring stress field without constitutive equation [J].
Dalemat, Marie ;
Coret, Michel ;
Leygue, Adrien ;
Verron, Erwan .
MECHANICS OF MATERIALS, 2019, 136
[9]   Magnetic Field Simulation With Data-Driven Material Modeling [J].
De Gersem, Herbert ;
Galetzka, Armin ;
Ion, Ion Gabriel ;
Loukrezis, Dimitrios ;
Roemer, Ulrich .
IEEE TRANSACTIONS ON MAGNETICS, 2020, 56 (08)
[10]   Model-Free Data-Driven inelasticity [J].
Eggersmann, R. ;
Kirchdoerfer, T. ;
Reese, S. ;
Stainier, L. ;
Ortiz, M. .
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 2019, 350 :81-99