A Perspective on Machine Learning Methods in Turbulence Modelling

10/23/2020
by   Andrea Beck, et al.
0

This work presents a review of the current state of research in data-driven turbulence closure modeling. It offers a perspective on the challenges and open issues, but also on the advantages and promises of machine learning methods applied to parameter estimation, model identification, closure term reconstruction and beyond, mostly from the perspective of Large Eddy Simulation and related techniques. We stress that consistency of the training data, the model, the underlying physics and the discretization is a key issue that needs to be considered for a successful ML-augmented modeling strategy. In order to make the discussion useful for non-experts in either field, we introduce both the modeling problem in turbulence as well as the prominent ML paradigms and methods in a concise and self-consistent manner. Following, we present a survey of the current data-driven model concepts and methods, highlight important developments and put them into the context of the discussed challenges.

READ FULL TEXT

Authors

page 6

page 7

page 27

12/21/2020

A Comprehensive Survey of Machine Learning Based Localization with Wireless Signals

The last few decades have witnessed a growing interest in location-based...
03/01/2020

Scalable Learning Paradigms for Data-Driven Wireless Communication

The marriage of wireless big data and machine learning techniques revolu...
09/01/2019

Modeling and simulation of large-scale Systems: a systematic comparison of modeling paradigms

A trend across most areas where simulation-driven development is used is...
12/11/2019

Nonparametric Universal Copula Modeling

To handle the ubiquitous problem of "dependence learning," copulas are q...
11/21/2019

Accurate Hydrologic Modeling Using Less Information

Joint models are a common and important tool in the intersection of mach...
10/27/2021

A Scalable Inference Method For Large Dynamic Economic Systems

The nature of available economic data has changed fundamentally in the l...
06/10/2018

Neural Networks for Data-Based Turbulence Models

In this work, we present a novel, data-based approach to turbulence mode...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.