Rajeev K. Jaiman

According to our database, Rajeev K. Jaiman authored at least 22 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A finite element-inspired hypergraph neural network: Application to fluid dynamics simulations.

Rui Gao, Indu Kant Deo, Rajeev K. Jaiman

J. Comput. Phys., 2024

H-SIREN: Improving implicit neural representations with hyperbolic periodic functions.

Rui Gao, Rajeev K. Jaiman

CoRR, 2024

Continual Learning of Range-Dependent Transmission Loss for Underwater Acoustic using Conditional Convolutional Neural Net.

Indu Kant Deo, Akash Venkateshwaran, Rajeev K. Jaiman

CoRR, 2024

2023

An interface preserving and residual-based adaptivity for phase-field modeling of fully Eulerian fluid-structure interaction.

Biswajeet Rath, Xiaoyu Mao, Rajeev K. Jaiman

J. Comput. Phys., September, 2023

An interface and geometry preserving phase-field method for fully Eulerian fluid-structure interaction.

Xiaoyu Mao, Rajeev Jaiman

J. Comput. Phys., March, 2023

2022

Node-Element Hypergraph Message Passing for Fluid Dynamics Simulations.

Rui Gao, Indu Kant Deo, Rajeev K. Jaiman

CoRR, 2022

Combined space-time reduced-order model with 3D deep convolution for extrapolating fluid dynamics.

Indu Kant Deo, Rui Gao, Rajeev Jaiman

CoRR, 2022

Quasi-Monolithic Graph Neural Network for Fluid-Structure Interaction.

Rui Gao, Rajeev Jaiman

CoRR, 2022

Convolutional recurrent autoencoder network for learning underwater ocean acoustics.

Wrik Mallik, Rajeev K. Jaiman, Jasmin Jelovica

CoRR, 2022

Learning Wave Propagation with Attention-Based Convolutional Recurrent Autoencoder Net.

Indu Kant Deo, Rajeev Jaiman

CoRR, 2022

Deep convolutional neural network for shape optimization using level-set approach.

Wrik Mallik, Neil Farvolden, Jasmin Jelovica, Rajeev K. Jaiman

CoRR, 2022

2021

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

Xiaoyu Mao, Vaibhav Joshi, Rajeev K. Jaiman

J. Comput. Phys., 2021

Kinematically consistent recurrent neural networks for learning inverse problems in wave propagation.

Wrik Mallik, Rajeev K. Jaiman, Jasmin Jelovica

CoRR, 2021

A robust and accurate finite element framework for cavitating flows with moving fluid-structure interfaces.

Suraj R. Kashyap, Rajeev K. Jaiman

Comput. Math. Appl., 2021

2020

A variational flexible multibody formulation for partitioned fluid-structure interaction: Application to bat-inspired drones and unmanned air-vehicles.

Vaibhav Joshi, Rajeev K. Jaiman, Carl Ollivier-Gooch

Comput. Math. Appl., 2020

2018

A 3D common-refinement method for non-matching meshes in partitioned variational fluid-structure analysis.

Yulong Li, Yun Zhi Law, Vaibhav Joshi, Rajeev K. Jaiman

J. Comput. Phys., 2018

An adaptive variational procedure for the conservative and positivity preserving Allen-Cahn phase-field model.

Vaibhav Joshi, Rajeev K. Jaiman

J. Comput. Phys., 2018

A positivity preserving and conservative variational scheme for phase-field modeling of two-phase flows.

Vaibhav Joshi, Rajeev K. Jaiman

J. Comput. Phys., 2018

2017

A positivity preserving variational method for multi-dimensional convection-diffusion-reaction equation.

Vaibhav Joshi, Rajeev K. Jaiman

J. Comput. Phys., 2017

2014

A stable second-order scheme for fluid-structure interaction with strong added-mass effects.

Jie Liu, Rajeev K. Jaiman, Pardha S. Gurugubelli

J. Comput. Phys., 2014

2007

Erratum to "Conservative load transfer along curved fluid-solid interface with non-matching meshes" [J. Comput. Phys. 218(1) (2006) 372-397].

Rajeev K. Jaiman, Xiangmin Jiao, Philippe H. Geubelle, Eric Loth

J. Comput. Phys., 2007

2006

Conservative load transfer along curved fluid-solid interface with non-matching meshes.

Rajeev K. Jaiman, Xiangmin Jiao, Philippe H. Geubelle, Eric Loth

J. Comput. Phys., 2006