no code implementations • 22 Mar 2023 • Phong C. H. Nguyen, Joseph B. Choi, H. S. Udaykumar, Stephen Baek
Recently, machine learning (ML) has emerged as a promising solution that can either serve as a surrogate for, accelerate or augment traditional numerical methods.
no code implementations • 15 Nov 2022 • Joseph B. Choi, Phong C. H. Nguyen, Oishik Sen, H. S. Udaykumar, Stephen Baek
Specifically, methods in the literature are evaluated in terms of their capacity to learn from a small/limited number of data, computational complexity, generalizability/scalability to other material species and operating conditions, interpretability of the model predictions, and the burden of supervision/data annotation.
1 code implementation • 8 Nov 2022 • Phong C. H. Nguyen, Yen-Thi Nguyen, Pradeep K. Seshadri, Joseph B. Choi, H. S. Udaykumar, Stephen Baek
We introduce a new approach for SDT simulation by using deep learning to model the mesoscale energy localization of shock-initiated EM microstructures.
1 code implementation • 4 Apr 2022 • Phong C. H. Nguyen, Yen-Thi Nguyen, Joseph B. Choi, Pradeep K. Seshadri, H. S. Udaykumar, Stephen Baek
The thermo-mechanical response of shock-initiated energetic materials (EM) is highly influenced by their microstructures, presenting an opportunity to engineer EM microstructure in a "materials-by-design" framework.
no code implementations • 5 Apr 2020 • Sehyun Chun, Sidhartha Roy, Yen Thi Nguyen, Joseph B. Choi, H. S. Udaykumar, Stephen S. Baek
Emerging multi-scale predictive models of HE response to loads account for the physics at the meso-scale, i. e. at the scale of statistically representative clusters of particles and other features in the microstructure.
no code implementations • 8 Oct 2019 • Sehyun Chun, Nima Hamidi Ghalehjegh, Joseph B. Choi, Chris W. Schwarz, John G. Gaspar, Daniel V. McGehee, Stephen S. Baek
A new convolutional neural network (CNN) architecture for 2D driver/passenger pose estimation and seat belt detection is proposed in this paper.