145 citations · 339 across the 28 of their papers we have counts for
7 papers · 1 filter
Topology-Agnostic Graph U-Nets for Scalar Field Prediction on Unstructured Meshes
Kevin Ferguson, Yu-hsuan Chen, Yiming Chen +3
Machine-learned surrogate models to accelerate lengthy computer simulations are becoming increasingly important as engineers look to streamline the product design cycle. In many ca…
Scalar Field Prediction on Meshes Using Interpolated Multi-Resolution Convolutional Neural Networks
Kevin Ferguson, Andrew Gillman, James Hardin +1
Scalar fields, such as stress or temperature fields, are often calculated in shape optimization and design problems in engineering. For complex problems where shapes have varying t…
Generative Manufacturing: A requirements and resource-driven approach to part making
Hongrui Chen, Aditya Joglekar, Zack Rubinstein +6
Advances in CAD and CAM have enabled engineers and design teams to digitally design parts with unprecedented ease. Software solutions now come with a range of modules for optimizin…
VIRL: Volume-Informed Representation Learning towards Few-shot Manufacturability Estimation
Yu-hsuan Chen, Jonathan Cagan, Levent Burak kara
Designing for manufacturing poses significant challenges in part due to the computation bottleneck of Computer-Aided Manufacturing (CAM) simulations. Although deep learning as an a…
SNF-ROM: Projection-based nonlinear reduced order modeling with smooth neural fields
Vedant Puri, Aviral Prakash, Levent Burak Kara +1
Reduced order modeling lowers the computational cost of solving PDEs by learning a low-order spatial representation from data and dynamically evolving these representations using m…
Multi-scale Topology Optimization using Neural Networks
Hongrui Chen, Xingchen Liu, Levent Burak Kara
A long-standing challenge is designing multi-scale structures with good connectivity between cells while optimizing each cell to reach close to the theoretical performance limit. W…
Curve-based Neural Style Transfer
Yu-hsuan Chen, Levent Burak Kara, Jonathan Cagan
This research presents a new parametric style transfer framework specifically designed for curve-based design sketches. In this research, traditional challenges faced by neural sty…