Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
Plain weave composite is a long-lasting type of fabric composite that is stable enough when
being handled. Open-hole composites have been widely used in industry, though they have …
being handled. Open-hole composites have been widely used in industry, though they have …
Predicting stress, strain and deformation fields in materials and structures with graph neural networks
Develo** accurate yet fast computational tools to simulate complex physical phenomena
is a long-standing problem. Recent advances in machine learning have revolutionized the …
is a long-standing problem. Recent advances in machine learning have revolutionized the …
Stressgan: A generative deep learning model for two-dimensional stress distribution prediction
Using deep learning to analyze mechanical stress distributions is gaining interest with the
demand for fast stress analysis. Deep learning approaches have achieved excellent …
demand for fast stress analysis. Deep learning approaches have achieved excellent …
A data-driven approach to full-field nonlinear stress distribution and failure pattern prediction in composites using deep learning
An image-based deep learning framework is developed to predict nonlinear stress
distribution and failure pattern in microstructural representations of composite materials in …
distribution and failure pattern in microstructural representations of composite materials in …
A machine learning-based surrogate finite element model for estimating dynamic response of mechanical systems
An efficient approach for improving the predictive understanding of dynamic mechanical
system variability is developed in this work. The approach requires low model assessment …
system variability is developed in this work. The approach requires low model assessment …
Data-driven methods for stress field predictions in random heterogeneous materials
Predicting full-field stress responses is of fundamental importance to assessing materials
failure and has various engineering applications in design optimization, manufacturing …
failure and has various engineering applications in design optimization, manufacturing …
Advanced composite materials and structures
M Soori - Journal of Materials and Engineering Structures « …, 2023 - revue.ummto.dz
Composite materials are used to produce multi-objective structures such as fluid reservoirs,
transmission pipes, heat exchangers, pressure vessels due to high strength and stiffness to …
transmission pipes, heat exchangers, pressure vessels due to high strength and stiffness to …
[HTML][HTML] StressD: 2D Stress estimation using denoising diffusion model
Finite element analysis (FEA), a common approach for simulating stress distribution for a
given geometry, is generally associated with high computational cost, especially when high …
given geometry, is generally associated with high computational cost, especially when high …
Predicting mechanically driven full-field quantities of interest with deep learning-based metamodels
Using simulation to predict the mechanical behavior of heterogeneous materials has
applications ranging from topology optimization to multi-scale structural analysis. However …
applications ranging from topology optimization to multi-scale structural analysis. However …
Deep learning prediction of stress fields in additively manufactured metals with intricate defect networks
In context of the universal presence of defects in additively manufactured (AM) metals,
efficient computational tools are required to rapidly screen AM microstructures for …
efficient computational tools are required to rapidly screen AM microstructures for …