Description 
1 online resource (xii, 164 pages) : illustrations (some color) 
Series 
SpringerBriefs in mathematics, 21918201 

SBMAC SpringerBriefs 

SpringerBriefs in mathematics, 21918201

Contents 
Introduction  Fluids and Deep Learning: A Brief Review  Fluid Modeling through NavierStokes Equations and Numerical Methods  Why Use Neural Networks for Fluid Animation  Modeling Fluids through Neural Networks  Fluid Rendering  Traditional Techniques  Advanced Techniques  Deep Learning in Rendering  Case Studies  Perspectives  Discussion and Final Remarks  References 
Summary 
This book is an introduction to the use of machine learning and datadriven approaches in fluid simulation and animation, as an alternative to traditional modeling techniques based on partial differential equations and numerical methods – and at a lower computational cost. This work starts with a brief review of computability theory, aimed to convince the reader – more specifically, researchers of more traditional areas of mathematical modeling – about the power of neural computing in fluid animations. In these initial chapters, fluid modeling through NavierStokes equations and numerical methods are also discussed. The following chapters explore the advantages of the neural networks approach and show the building blocks of neural networks for fluid simulation. They cover aspects related to training data, data augmentation, and testing. The volume completes with two case studies, one involving Lagrangian simulation of fluids using convolutional neural networks and the other using Generative Adversarial Networks (GANs) approaches 
Bibliography 
Includes bibliographical references and index 
Notes 
Online resource; title from PDF title page (SpringerLink, viewed December 4, 2023) 
Subject 
Deep learning (Machine learning)


Fluid mechanics  Computer simulation


Deep learning (Machine learning)


Fluid mechanics  Computer simulation.

Form 
Electronic book

Author 
Almeida, Liliane Rodrigues de, author


Apolinário, Antonio Lopes, author


Silva, Leandro Tavares da, author

ISBN 
9783031423338 

303142333X 
