DeepFEAv2: Deep Learning for Transient Finite Element Analysis Beyond Structured Meshes

arXiv:2609.26426 · cs.LG, cs.AI, cs.CE · Submitted 2026-09-22 · Read on arXiv

cs.LG, cs.AI, cs.CE

Submitted: 2026-09-22

Updated: 2026-09-22

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Deep Learning — 24× in this paper
• Accuracy — 13× in this paper · explained in 1 episode
• Consistency — 9× in this paper · explained in 3 episodes
• Latent Space — 8× in this paper · explained in 7 episodes
• Finite Element Analysis — 7× in this paper
• Loss Function — 5× in this paper · explained in 2 episodes
• Aggregation — 4× in this paper · explained in 1 episode
• Benchmark — 4× in this paper · explained in 2 episodes
• Element-Centric Autoencoder — 4× in this paper
• Latent Temporal Evolution — 4× in this paper
• Node- and Element-based Outputs — 4× in this paper
• Node-Element Loss Optimization — 4× in this paper
• Feature Extraction — 3× in this paper · explained in 2 episodes
• GNNs — 3× in this paper · explained in 2 episodes
• Latent Representation — 3× in this paper · explained in 2 episodes
• Mesh Connectivity-Based Grouping — 3× in this paper
• Node-Element Decoder — 3× in this paper
• Temporal consistency — 3× in this paper · explained in 2 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• D Linear Elastic Model — 1× in this paper
• Graph Neural Networks (GNNs) — 1× in this paper · explained in 7 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Physics-Informed Neural Networks (PINNs) — 1× in this paper · explained in 6 episodes
• Reduced-Order Modeling — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes

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