248 citations · 349 across the 7 of their papers we have counts for
8 papers
An Uncertainty-aware Deep Learning Framework-based Robust Design Optimization of Metamaterial Units
Zihan Wang, Anindya Bhaduri, Hongyi Xu +1
Mechanical metamaterials represent an innovative class of artificial structures, distinguished by their extraordinary mechanical characteristics, which are beyond the scope of trad…
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field
Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi +6
Modern computational methods, involving highly sophisticated mathematical formulations, enable several tasks like modeling complex physical phenomenon, predicting key properties an…
Accelerated multiscale mechanics modeling in a deep learning framework
Ashwini Gupta, Anindya Bhaduri, Lori Graham-Brady
Microstructural heterogeneity affects the macro-scale behavior of materials. Conversely, load distribution at the macro-scale changes the microstructural response. These up-scaling…
Stress field prediction in fiber-reinforced composite materials using a deep learning approach
Anindya Bhaduri, Ashwini Gupta, Lori Graham-Brady
Computational stress analysis is an important step in the design of material systems. Finite element method (FEM) is a standard approach of performing stress analysis of complex ma…
An efficient optimization based microstructure reconstruction approach with multiple loss functions
Anindya Bhaduri, Ashwini Gupta, Audrey Olivier +1
Stochastic microstructure reconstruction involves digital generation of microstructures that match key statistics and characteristics of a (set of) target microstructure(s). This p…
Probabilistic modeling of discrete structural response with application to composite plate penetration models
Anindya Bhaduri, Christopher S. Meyer, John W. Gillespie +3
Discrete response of structures is often a key probabilistic quantity of interest. For example, one may need to identify the probability of a binary event, such as, whether a struc…
Stochastic collocation approach with adaptive mesh refinement for parametric uncertainty analysis
Anindya Bhaduri, Yanyan He, Michael D. Shields +2
Presence of a high-dimensional stochastic parameter space with discontinuities poses major computational challenges in analyzing and quantifying the effects of the uncertainties in…
An efficient adaptive sparse grid collocation method through derivative estimation
Anindya Bhaduri, Lori Graham-Brady
For uncertainty propagation of highly complex and/or nonlinear problems, one must resort to sample-based non-intrusive approaches [1]. In such cases, minimizing the number of funct…