2 citations · 2 across the 4 of their papers we have counts for
4 papers
TRACE: Spatiotemporal Contact Memory Graph Network Simulator for Granular Dynamics
Changjian Zhou, Negin Yousefpour, Jie Qi +3
Learned graph simulators provide an efficient alternative to high-fidelity solvers for granular dynamics. However, granular motion depends strongly on inter-granular contact histor…
PhysGuard: Fisher-Guided Gradient Projection for Sim-to-Real Neural PDE Surrogates
Changjian Zhou, Junfeng Fang, Negin Yousefpour +3
Neural operator models trained on simulation data often lose accuracy when applied to experimental measurements due to the sim-to-real gap. Standard fine-tuning with limited real d…
Physics-Inspired Deep Learning and Transferable Models for Bridge Scour Prediction
Negin Yousefpour, Bo Wang
This paper introduces scour physics-inspired neural networks (SPINNs), a hybrid physics-data-driven framework for bridge scour prediction using deep learning. SPINNs integrate phys…
Application of Long-Short Term Memory and Convolutional Neural Networks for Real-Time Bridge Scour Prediction
Tahrima Hashem, Negin Yousefpour
Scour around bridge piers is a critical challenge for infrastructures around the world. In the absence of analytical models and due to the complexity of the scour process, it is di…