A bilevel Proxy-FEA diagnostic framework is introduced and tested on a simplified LDED32 stripe benchmark to reveal proxy misalignment with FEA labels and a stress-distortion trade-off in RL-guided scan-order optimization.
Michaleris, Modeling metal deposition in heat transfer analyses of additive man- ufacturing processes, Finite Elements in Analysis and Design 86 (2014) 51–60
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Reinforcement Learning for Laser Additive Manufacturing Scan-Order Optimisation: A Bilevel Proxy--FEA Diagnostic Framework for Reward and World-Model Diagnosis
A bilevel Proxy-FEA diagnostic framework is introduced and tested on a simplified LDED32 stripe benchmark to reveal proxy misalignment with FEA labels and a stress-distortion trade-off in RL-guided scan-order optimization.