6 papers
Dynamic Image-Informed Selection of Biomechanical Tumor Growth Models
Abdullah Al Noman, Pratyush Kumar Singh, David A Hormuth +1
Glioblastoma progression is strongly influenced by evolving mechanical interactions between the tumor and surrounding brain tissue. However, the extent to which finite-deformation…
Evidence-Guided Neural Architecture Selection under Uncertainty for Subject-Specific Blood Glucose Forecasting
Md Azharul Islam, Dwyer Deighan, Tarunraj Singha +1
Reliable neural architecture selection is an open challenge in time-series forecasting under limited, noisy, and heterogeneous data, where standard heuristic architecture design an…
Stochastic Deep Learning Surrogate Models for Uncertainty Propagation in Microstructure-Properties of Ceramic Aerogels
Md Azharul Islam, Dwyer Deighan, Shayan Bhattacharjee +4
This study presents an integrated computational framework that, given synthesis parameters, predicts the resulting microstructural morphology and mechanical response of ceramic aer…
UQ of 2D Slab Burner DNS: Surrogates, Uncertainty Propagation, and Parameter Calibration
Georgios Georgalis, Alejandro Becerra, Kenneth Budzinski +4
The goal of this paper is to demonstrate and address challenges related to all aspects of performing a complete uncertainty quantification analysis of a complicated physics-based s…
Chance-Constrained Optimal Design of Porous Thermal Insulation Systems Under Spatially Correlated Uncertainty
Pratyush Kumar Singh, Danial Faghihi
This paper presents a computationally efficient method for the optimal design of silica aerogel porous material systems, balancing thermal insulation performance with mechanical st…
A Framework for Strategic Discovery of Credible Neural Network Surrogate Models under Uncertainty
Pratyush Kumar Singh, Kathryn A. Farrell-Maupin, Danial Faghihi
The widespread integration of deep neural networks in developing data-driven surrogate models for high-fidelity simulations of complex physical systems highlights the critical nece…