Data-driven algorithm based on the scaled boundary finite element method and deep learning for the identification of multiple cracks in massive structures
S Jiang, W Deng, ET Ooi, L Sun, C Du - Computers & Structures, 2024 - Elsevier
Structural defect identification is a vital aspect of structural health monitoring used to assess
the safety of engineering structures. However, quantitatively determining the dimensions of …
the safety of engineering structures. However, quantitatively determining the dimensions of …
BINN: A deep learning approach for computational mechanics problems based on boundary integral equations
J Sun, Y Liu, Y Wang, Z Yao, X Zheng - Computer Methods in Applied …, 2023 - Elsevier
We proposed the boundary-integral type neural networks (BINN) for the boundary value
problems in computational mechanics. The boundary integral equations are employed to …
problems in computational mechanics. The boundary integral equations are employed to …
A novel damage identification algorithm by combing the boundary element method and a series connection neural network
Y Yang, Z Zhan, Y Liu - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
A novel damage identification approach based on a model-driven and a data-driven
combined algorithm is developed. By using this approach with only boundary strains, the …
combined algorithm is developed. By using this approach with only boundary strains, the …
Neural PDE solvers for irregular domains
Neural network-based approaches for solving partial differential equations (PDEs) have
recently received special attention. However, most neural PDE solvers only apply to …
recently received special attention. However, most neural PDE solvers only apply to …
[HTML][HTML] AI for PDEs in solid mechanics: A review
In recent years, deep learning has become ubiquitous and is empowering various fields. In
particular, the combination of artificial intelligence and traditional science (AI for science …
particular, the combination of artificial intelligence and traditional science (AI for science …
SBFEM and Bayesian inference for efficient multiple flaw detection in structures
Bayesian inference is a powerful technique for damage/flaw detection in critical structures.
This paper explores the application of Bayesian inference to identify the flaws …
This paper explores the application of Bayesian inference to identify the flaws …
Adaptive sinh transformation Gaussian quadrature for 2D potential problems using deep learning
W Zhou, X Yang, Y Chen - Engineering Analysis with Boundary Elements, 2023 - Elsevier
In the boundary element method (BEM), the sinh transformation method is an effective
method for evaluating nearly singular integrals, but a relationship between the integration …
method for evaluating nearly singular integrals, but a relationship between the integration …
数据驱动的半无限介质裂纹识别模型研究
江守燕, 邓王涛, 孙立国, 杜成斌 - 力学学报, 2024 - lxxb.cstam.org.cn
摘要缺陷识别是结构健康监测的重要研究内容, 对评估工程结构的安全性具有重要的指导意义,
然而, 准确确定结构缺陷的尺寸十分困难. 论文提出了一种创新的数据驱动算法 …
然而, 准确确定结构缺陷的尺寸十分困难. 论文提出了一种创新的数据驱动算法 …
Scaled boundary finite element based two-level learning approach for structural flaw identification
A comprehensive framework that combines classification and regression techniques through
machine learning (ML) algorithms to address the inverse problem of flaw identification and …
machine learning (ML) algorithms to address the inverse problem of flaw identification and …
A collaborating approach for hole detection with the numerical manifold method and Elman neural network
GY Zheng, CL Li, DL Guo, HH Zhang, XL Ji… - … Analysis with Boundary …, 2024 - Elsevier
Structural health monitoring plays a significant role in the field of public safety, of which flaws
(such as holes and cracks) identification is a very challenging topic. In this work, an inverse …
(such as holes and cracks) identification is a very challenging topic. In this work, an inverse …