2 citations · 2 across the 9 of their papers we have counts for
8 papers · 1 filter
Predictive Uncertainty for Neural CAE Surrogates
Kaustubh Tangsali, Mohammad Amin Nabian, Kelvin Lee +2
Neural surrogates can substantially accelerate computer-aided engineering (CAE) workflows, but their use in design requires uncertainty estimates that remain meaningful across vary…
High-Fidelity Industrial Crash Dynamics Prediction via Geometry-Aware Operator Learning with Memory-Efficient Low-Rank Attention
Deepak Akhare, Mohammad Amin Nabian, Corey Adams +2
Automotive crashworthiness optimization remains a safety-critical challenge, requiring the management of large-scale nonlinear structural deformations and energy dissipation throug…
GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer
Corey Adams, Rishikesh Ranade, Ram Cherukuri +1
We present GeoTransolver, a multiscale geometry-aware physics attention transformer for Computer Aided Engineering (CAE). GeoTransolver extends the Transolver backbone with GALE (G…
MoWE : A Mixture of Weather Experts
Dibyajyoti Chakraborty, Romit Maulik, Peter Harrington +3
Data-driven weather models have recently achieved state-of-the-art performance, yet progress has plateaued in recent years. This paper introduces a Mixture of Experts (MoWE) approa…
A Mixture of Experts Gating Network for Enhanced Surrogate Modeling in External Aerodynamics
Mohammad Amin Nabian, Sanjay Choudhry
The computational cost associated with high-fidelity CFD simulations remains a significant bottleneck in the automotive design and optimization cycle. While ML-based surrogate mode…
A Benchmarking Framework for AI models in Automotive Aerodynamics
Kaustubh Tangsali, Rishikesh Ranade, Mohammad Amin Nabian +5
In this paper, we introduce a benchmarking framework within the open-source NVIDIA PhysicsNeMo-CFD framework designed to systematically assess the accuracy, performance, scalabilit…
Accelerating Transient CFD through Machine Learning-Based Flow Initialization
Peter Sharpe, Rishikesh Ranade, Kaustubh Tangsali +3
Transient computational fluid dynamics (CFD) simulations are essential for many industrial applications, but suffer from high compute costs relative to steady-state simulations. Th…
DoMINO: A Decomposable Multi-scale Iterative Neural Operator for Modeling Large Scale Engineering Simulations
Rishikesh Ranade, Mohammad Amin Nabian, Kaustubh Tangsali +4
Numerical simulations play a critical role in design and development of engineering products and processes. Traditional computational methods, such as CFD, can provide accurate pre…