9 citations · 9 across the 4 of their papers we have counts for
3 papers · 1 filter
Adversarial Agents on Topology Optimization: Understanding the Fragility and Robustness of Deep Learning-based and Physics-Based Design Models under Adversarial Perturbation
Hoang Anh Nguyen, Yuan Hong, Hongyi Xu
Topology optimization, using both physic-based approaches and deep learning surrogates, serves as a cornerstone for generative design agents in cyber-manufacturing systems. While d…
Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling
Ge Song, Kiarash Naghavi Khanghah, Anandkumar Patel +2
Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex 'black-box' models. This paper…
GPT-Micro: A large language paradigm for accelerated, inexpensive, and thermodynamics-consistent discovery of constitutive models in manufacturing
Soumik Dutta, Kiarash Naghavi Khanghah, Sania Shree +4
Constitutive modeling of the relationship between process-imposed material states and fundamental material properties is critical to control of material microstructure in manufactu…