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20172026
most citedAssessment of unsteady flow predictions using hybrid deep learning based reduced order models

106 citations · 883 across the 63 of their papers we have counts for

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physics.comp-ph2025

A Phase Field Formulation of Frictional Sliding Contact for 3D Fully Eulerian Fluid Structure Interactions

Biswajeet Rath, Rajeev K. Jaiman

Frictional sliding contact in hydrodynamic environments can be found in a range of engineering applications. Accurate modeling requires an integrated numerical framework capable of…

physics.comp-ph2021

An Interface-Driven Adaptive Variational Procedure for Fully Eulerian Fluid-Structure Interaction via Phase-field Modeling

Biswajeet Rath, Xiaoyu Mao, Rajeev K. Jaiman

In this paper, we present a novel interface-driven adaptive variational procedure using a fully Eulerian description of fluid-structure interaction. The proposed fully-Eulerian pro…

physics.comp-ph2020★ 29 cited

A variational interface-preserving and conservative phase-field method for the surface tension effect in two-phase flows

Xiaoyu Mao, Vaibhav Joshi, Rajeev Jaiman

We present a finite element based variational interface-preserving and conservative phase-field formulation for the modeling of incompressible two-phase flows with surface tension…

physics.comp-ph2018

A Hybrid Data-driven Deep Learning Technique for Fluid-Structure Interaction

T. P. Miyanawala, R. K. Jaiman

This paper is concerned with the development of a hybrid data-driven technique for unsteady fluid-structure interaction systems. The proposed data-driven technique combines the dee…

physics.comp-ph2017★ 18 cited

3D Common-Refinement Method for Non-Matching Meshes in Partitioned Variational Fluid-Structure Analysis

Yulong Li, Yun Zhi Law, Vaibhav Joshi +1

We present a three-dimensional (3D) common-refinement method for non-matching meshes between discrete non-overlapping subdomains of incompressible fluid and nonlinear hyperelastic…