SOURCE-LINKED INTELLIGENCE
DeepFEAv2: Deep Learning for Transient Finite Element Analysis Beyond Structured Meshes
Finite Element Analysis (FEA) is widely used for transient mechanical simulations, but its high computational cost limits real-time and high-resolution applications. Deep learning surrogate models can reduce this cost; however, many existing approaches are restricted to steady-state prediction or cannot jointly predict Node- and Element-based Outputs (NEO) over time. The state-of-the-art DeepFEA framework has addressed these issues but remains limited to structured finite element (FE) meshes. To overcome this limitation, this study proposes DeepFEAv2, a deep learning surrogate framework that e
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T13:51:17.000Z
First collected: 2026-09-23T04:11:12.117Z. This is not the publication date.