5 papers
CarCrashNet: A Large-Scale Dataset and Hierarchical Neural Solver for Data-Driven Structural Crash Simulation
Mohamed Elrefaie, Dule Shu, Matthew Klenk +1
Crash simulation is a cornerstone of modern vehicle development because it reduces the need for costly physical prototypes, accelerates safety-driven design iteration, and increasi…
BlendedNet++: A dataset and benchmark for field-resolved aerodynamics and inverse design of blended wing body aircraft
Nicholas Sung, Steven Spreizer, Mohamed Elrefaie +2
The conceptual design of Blended Wing Body (BWB) aircraft is often constrained by the high computational cost of resolving complex aerodynamics over a high-dimensional design space…
CarBench: A Comprehensive Benchmark for Neural Surrogates on High-Fidelity 3D Car Aerodynamics
Mohamed Elrefaie, Dule Shu, Matt Klenk +1
Benchmarking has been the cornerstone of progress in computer vision, natural language processing, and the broader deep learning domain, driving algorithmic innovation through stan…
BlendedNet: A Blended Wing Body Aircraft Dataset and Surrogate Model for Aerodynamic Predictions
Nicholas Sung, Steven Spreizer, Mohamed Elrefaie +3
BlendedNet is a publicly available aerodynamic dataset of 999 blended wing body (BWB) geometries. Each geometry is simulated across about nine flight conditions, yielding 8830 conv…
TripOptimizer: Generative 3D Shape Optimization and Drag Prediction using Triplane VAE Networks
Parsa Vatani, Mohamed Elrefaie, Farhad Nazarpour +1
The computational cost of traditional Computational Fluid Dynamics-based Aerodynamic Shape Optimization severely restricts design space exploration. This paper introduces TripOptim…