An Explainable Deep Learning for Data-Driven Turbulence Model Feature Discovery

This work presents an explainable deep learning for turbulence modelling feature discovery in several flow configurations where conventional approaches perform poorly. The proposed neural network-based turbulence model predicts the Reynolds stress based on the mean flow quantities. Furthermore, the...

ver descrição completa

Detalhes bibliográficos

Principais autores:	Muhammad Ridho Alhafiz, Lavi Rizki Zuhal, Duong Viet Dung, Pramudita Satria Palar
Formato:	Artigo
Idioma:	Inglês
Publicado em:	IEEE 2025-01-01
coleção:	IEEE Access
Assuntos:	Turbulence modeling neural network explainability Shapley additive explanations feature discovery
Acesso em linha:	https://ieeexplore.ieee.org/document/11136158/
Tags:	Adicionar Tag Sem tags, seja o primeiro a adicionar uma tag!