Physics-informed deep learning for computational elastodynamics without labeled data
Numerical methods such as finite element have been flourishing in the past decades for
modeling solid mechanics problems via solving governing partial differential equations …
modeling solid mechanics problems via solving governing partial differential equations …
Deep learning-accelerated designs of tunable magneto-mechanical metamaterials
Metamaterials are artificially structured materials with unusual properties, such as negative
Poisson's ratio, acoustic band gap, and energy absorption. However, metamaterials made of …
Poisson's ratio, acoustic band gap, and energy absorption. However, metamaterials made of …
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 …
Optimal sensor placement in structural health monitoring using discrete optimization
H Sun, O Büyüköztürk - Smart Materials and Structures, 2015 - iopscience.iop.org
The objective of optimal sensor placement (OSP) is to obtain a sensor layout that gives as
much information of the dynamic system as possible in structural health monitoring (SHM) …
much information of the dynamic system as possible in structural health monitoring (SHM) …
From diffuse damage to sharp cohesive cracks: A coupled XFEM framework for failure analysis of quasi-brittle materials
Failure of quasi-brittle materials is governed by crack formation and propagation which can
be characterized by two phases:(i) diffuse material degradation process with initial crack …
be characterized by two phases:(i) diffuse material degradation process with initial crack …
A hybrid optimization algorithm with Bayesian inference for probabilistic model updating
A hybrid optimization methodology is presented for the probabilistic finite element model
updating of structural systems. The model updating process is formulated as an inverse …
updating of structural systems. The model updating process is formulated as an inverse …
[HTML][HTML] Multiple crack detection in 3D using a stable XFEM and global optimization
A numerical scheme is proposed for the detection of multiple cracks in three dimensional
(3D) structures. The scheme is based on a variant of the extended finite element method …
(3D) structures. The scheme is based on a variant of the extended finite element method …
基于数据驱动的大体积结构裂缝深度反演.
江守燕， 杜成斌， 孙立国 - … Mechanics/Gongcheng Lixue, 2023 - search.ebscohost.com
裂缝是混凝土结构的主要病害, 查明裂缝的深度能够为结构的耐久性和安全性评价提供可靠的
信息, 但同时也是混凝土结构检测的难点之一. 提出了一种基于数据驱动的学习算法 …
信息, 但同时也是混凝土结构检测的难点之一. 提出了一种基于数据驱动的学习算法 …
[HTML][HTML] 基于有限元技术的疲劳裂纹扩展方法研究进展
苏玉昆， 马涛， 赵晓鑫， 张光亮， 朱加雷， 张鹏 - 力学进展, 2024 - lxjz.cstam.org.cn
疲劳裂纹是引起工程结构断裂失效的重要因素之一. 目前疲劳裂纹扩展的有限元仿真商业软件有
ANSYS, ABAQUS, FRANC3D, ZENCRACK 等, 这些软件为疲劳裂纹扩展过程的研究提供了 …
ANSYS, ABAQUS, FRANC3D, ZENCRACK 等, 这些软件为疲劳裂纹扩展过程的研究提供了 …
Flaw classification and detection in thin‐plate structures based on scaled boundary finite element method and deep learning
S Jiang, C Wan, L Sun, C Du - International Journal for …, 2022 - Wiley Online Library
The identification of internal structural flaws is an important research topic in structural health
monitoring. At present, structural safety inspections based on nondestructive testing …
monitoring. At present, structural safety inspections based on nondestructive testing …