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 …

We proposed the boundary-integral type neural networks (BINN) for the boundary value
problems in computational mechanics. The boundary integral equations are employed to …

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 …

Neural network-based approaches for solving partial differential equations (PDEs) have
recently received special attention. However, most neural PDE solvers only apply to …

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 …

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 …

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 …

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 …

A comprehensive framework that combines classification and regression techniques through
machine learning (ML) algorithms to address the inverse problem of flaw identification and …

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 …