Engineering Design
Engineering design research is increasingly leveraging artificial intelligence to improve efficiency and innovation. Current efforts focus on developing and applying deep generative models, Bayesian optimization, and large language models to handle diverse data types (images, text, CAD models) and optimize complex design processes, often incorporating physics-informed operators to enhance model accuracy and generalization. This work aims to create more efficient and effective design tools, accelerating the development of new products and systems across various engineering disciplines.
Papers
BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement
Yuhao Du, Shunian Chen, Wenbo Zan, Peizhao Li, Mingxuan Wang, Dingjie Song, Bo Li, Yan Hu, Benyou Wang
The impact of AI on engineering design procedures for dynamical systems
Kristin M. de Payrebrune, Kathrin Flaßkamp, Tom Ströhla, Thomas Sattel, Dieter Bestle, Benedict Röder, Peter Eberhard, Sebastian Peitz, Marcus Stoffel, Gulakala Rutwik, Borse Aditya, Meike Wohlleben, Walter Sextro, Maximilian Raff, C. David Remy, Manish Yadav, Merten Stender, Jan van Delden, Timo Lüddecke, Sabine C.Langer, Julius Schultz, Christopher Blech