£143.68

Springer - Data Analysis for DNS of Turbulent Combustion Book

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Description

Master the complexities of large data sets in fluid dynamics with this specialized text from Springer. This book provides essential methodologies for analyzing data produced by the direct numerical simulation (DNS) of turbulence and combustion. It offers a deep dive into the development of models suitable for large eddy simulations, covering both established techniques and emerging methods in the field. Written by internationally respected experts, the chapters move beyond traditional intuition and experience. Instead, they present a formal, data-driven standpoint that helps researchers and engineers recognize the limitations of current approaches. By adopting these rigorous analytical perspectives, readers can better navigate the transition from equation-based analysis to modern machine learning applications in combustion science. This resource is designed for professionals and students looking to advance their understanding of how data-driven insights can transform the study of turbulent combustion.

Key Features

Provides detailed methodologies for analyzing large data sets generated by direct numerical simulation (DNS) of turbulence and combustion.

Explains the development of models used to analyze large eddy simulations for improved accuracy in fluid dynamics research.

Covers a wide range of techniques, including both common industry standards and newly emerging analytical methods.

Offers a formal, data-driven perspective on DNS to help researchers move beyond reliance on experience and intuition.

Features expert contributions from internationally respected authors to ensure high-level academic and technical depth.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
29 May 2021
Listed Since
02 May 2021

Barcode

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