activity
20212026
most citedPARC: Physics-Aware Recurrent Convolutional Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials

31 citations · 112 across the 10 of their papers we have counts for

collaborators

10 papers

physics.comp-ph2026

Lumina: An AI-Augmented Multiscale Material Informatics Framework for Extreme Aero-Chemo-Thermo-Mechanical Regimes

Pradeep Kumar Seshadri, Vigneshwaran N, Sudaroli Dhananjeyan +8

Predictive simulations and experimental design involving extreme aero-chemo-thermo-mechanical regimes require high-fidelity material representation across diverse physical states.…

physics.comp-ph2026

High-fidelity simulations of shock initiation of an energetic crystal-binder system due to flyer impact

Shobhan Roy, Pradeep K. Seshadri, Chukwudubem Okafor +2

Meso-scale simulations of energy localization at hotspots provide closure models for multiscale frameworks of shock-to-detonation transition (SDT). Validation of such meso-scale ca…

cs.LG2025★ 1 cited

A physics-aware deep learning model for shear band formation around collapsing pores in shocked reactive materials

Xinlun Cheng, Bingzhe Chen, Joseph Choi +5

Modeling shock-to-detonation phenomena in energetic materials (EMs) requires capturing complex physical processes such as strong shocks, rapid changes in microstructural morphology…

physics.comp-ph2025

Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic Material

Shahab Azarfar, Joseph B. Choi, Phong CH. Nguyen +4

Coupling of physics across length and time scales plays an important role in the response of microstructured materials to external loads. In a multi-scale framework, unresolved (su…

cs.LG2024★ 3 cited

PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling

Phong C. H. Nguyen, Xinlun Cheng, Shahab Azarfar +6

Modeling unsteady, fast transient, and advection-dominated physics problems is a pressing challenge for physics-aware deep learning (PADL). The physics of complex systems is govern…

cond-mat.mtrl-sci2022★ 30 cited

A physics-aware deep learning model for energy localization in multiscale shock-to-detonation simulations of heterogeneous energetic materials

Phong C. H. Nguyen, Yen-Thi Nguyen, Pradeep K. Seshadri +3

Predictive simulations of the shock-to-detonation transition (SDT) in heterogeneous energetic materials (EM) are vital to the design and control of their energy release and sensiti…

cond-mat.mtrl-sci2022★ 31 cited

PARC: Physics-Aware Recurrent Convolutional Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials

Phong C. H. Nguyen, Yen-Thi Nguyen, Joseph B. Choi +3

The thermo-mechanical response of shock-initiated energetic materials (EM) is highly influenced by their microstructures, presenting an opportunity to engineer EM microstructure in…

physics.flu-dyn2021★ 19 cited

Leading Edge Vortex Dynamics of Airfoils, Pitching Continuously at High Amplitudes

Akhil Aravind, Pradeep Kumar Seshadri, Ashoke De

Airfoils pitching in the stalled regime have been of keen interest in recent years due to their desirable aerodynamic force characteristics. In this study, we are numerically inves…

physics.flu-dyn2021★ 7 cited

Flow Past Stationary and Oscillating Airfoil at Low Reynolds number Using Sharp Interface Immersed Boundary Approach

Pradeep Kumar Seshadri, Ashoke De

The present study reports on flow past airfoils (stationary and moving) using sharp interface immersed-boundary approach. Non-boundary conforming approach like immersed-boundary me…

physics.flu-dyn2021★ 21 cited

Investigation of Shock Wave Interactions involving Stationary and Moving Wedges

Pradeep Kumar Seshadri, Ashoke De

The present study investigates the shock wave interactions involving stationary and moving wedges using a sharp interface immersed boundary method combined with a fifth order weigh…