most citedDifference-Based Deep Learning Framework for Stress Predictions in Heterogeneous Media

55 citations · 74 across the 5 of their papers we have counts for

collaborators

5 papers

physics.app-ph2022★ 1 cited

Parameterization-based Neural Network: Predicting Non-linear Stress-Strain Response of Composites

Haotian Feng, Pavana Prabhakar

Composite materials like syntactic foams have complex internal microstructures that manifest high-stress concentrations due to material discontinuities occurring from hollow region…

physics.app-ph2022★ 1 cited

Physics-Constrained Neural Network for Design and Feature-Based Optimization of Weave Architectures

Haotian Feng, Sabarinathan P Subramaniyan, Hridyesh Tewani +1

Woven fabrics play an essential role in everyday textiles for clothing/sportswear, water filtration, and retaining walls, to reinforcements in stiff composites for lightweight stru…

physics.app-ph2022★ 15 cited

Role of Material Directionality on the Mechanical Response of Miura-Ori Composite Structures

Haotian Feng, Guanjin Yan, Pavana Prabhakar

This paper aims to understand the role of directional material properties on the mechanical responses of origami structures. We consider the Miura-Ori structures our target model d…

physics.app-ph2020★ 2 cited

Densification Mechanics of Polymeric Syntactic Foams

Pavana Prabhakar, Haotian Feng, Sabarinathan P Subramaniyan +1

In this paper, a fundamental understanding of the densification mechanics of polymeric syntactic foams under compressive loading is established. These syntactic foams are closed ce…

physics.app-ph2020★ 55 cited

Difference-Based Deep Learning Framework for Stress Predictions in Heterogeneous Media

Haotian Feng, Pavana Prabhakar

Stress analysis of heterogeneous media, like composite materials, using Finite Element Analysis (FEA) has become commonplace in design and analysis. However, determining stress dis…