DamFormer: Generalizing Morphologies in Dam Break Simulations Using Transformer Model
Fluid Dynamics
2024-10-28 v1 Machine Learning
Abstract
The interaction of waves with structural barriers such as dams breaking plays a critical role in flood defense and tsunami disasters. In this work, we explore the dynamic changes in wave surfaces impacting various structural shapes, e.g., circle, triangle, and square, by using deep learning techniques. We introduce the DamFormer, a novel transformer-based model designed to learn and simulate these complex interactions. The model was trained and tested on simulated data representing the three structural forms.
Cite
@article{arxiv.2410.18998,
title = {DamFormer: Generalizing Morphologies in Dam Break Simulations Using Transformer Model},
author = {Zhaoyang Mul and Aoming Liang and Mingming Ge and Dashuai Chen and Dixia Fan and Minyi Xu},
journal= {arXiv preprint arXiv:2410.18998},
year = {2024}
}