1 citations · 3 across the 13 of their papers we have counts for
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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…
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…
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…
Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration
Baoshan Liang, Luke Lozenski, Umberto Villa +1
We discuss solution algorithms for calibrating a tumor growth model using imaging data posed as a deterministic inverse problem. The forward model consists of a nonlinear and time-…
Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth
Baoshan Liang, Jingye Tan, Luke Lozenski +4
Reliably predicting the future spread of brain tumors using imaging data and on a subject-specific basis requires quantifying uncertainties in data, biophysical models of tumor gro…
A Predictive Discrete-Continuum Multiscale Model of Plasticity With Quantified Uncertainty
Jingye Tan, Umberto Villa, Nima Shamsaei +3
Multiscale models of materials, consisting of upscaling discrete simulations to continuum models, are unique in their capability to simulate complex materials behavior. The fundame…
A Probabilistic Design Method for Fatigue Life of Metallic Component
Danial Faghihi, Subhasis Sarkar, Mehdi Naderi +2
In the present study, a general probabilistic design framework is developed for cyclic fatigue life prediction of metallic hardware using methods that address uncertainty in experi…