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Data Analysis for Direct Numerical Simulations of Turbulent Combustion

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Cover of 'Data Analysis for Direct Numerical Simulations of Turbulent Combustion'

Table of Contents

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    Book Overview
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    Chapter 1 Analysis of Flame Topology and Burning Rates
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    Chapter 2 Dissipation Element Analysis of Inert and Reacting Turbulent Flows
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    Chapter 3 Computational Singular Perturbation Method and Tangential Stretching Rate Analysis of Large Scale Simulations of Reactive Flows: Feature Tracking, Time Scale Characterization, and Cause/Effect Identification. Part 1, Basic Concepts
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    Chapter 4 Computational Singular Perturbation Method and Tangential Stretching Rate Analysis of Large Scale Simulations of Reactive Flows: Feature Tracking, Time Scale Characterization, and Cause/Effect Identification. Part 2, Analyses of Ignition Systems, Laminar and Turbulent Flames
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    Chapter 5 Chemical Explosive Mode Analysis for Diagnostics of Direct Numerical Simulations
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    Chapter 6 Higher Order Tensors for DNS Data Analysis and Compression
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    Chapter 7 Data-Driven Modal Decomposition Techniques for High-Dimensional Flow Fields
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    Chapter 8 Dynamic Mode Decomposition: A Tool to Extract Structures Hidden in Massive Datasets
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    Chapter 9 Physics-Informed Data-Driven Prediction of Turbulent Reacting Flows with Lyapunov Analysis and Sequential Data Assimilation
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    Chapter 10 Data-Based Modeling for the Crank Angle Resolved CI Combustion Process
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    Chapter 11 From Discrete and Iterative Deconvolution Operators to Machine Learning for Premixed Turbulent Combustion Modeling
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    Chapter 12 Analysis of Turbulent Reacting Jets via Principal Component Analysis
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    Chapter 13 Application of an Evolutionary Algorithm to LES Modelling of Turbulent Premixed Flames
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    Chapter 14 Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation
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Title
Data Analysis for Direct Numerical Simulations of Turbulent Combustion
Published by
Springer International Publishing, June 2020
DOI 10.1007/978-3-030-44718-2
ISBNs
978-3-03-044717-5, 978-3-03-044718-2
Editors

Pitsch, Heinz, Attili, Antonio

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 22%
Student > Doctoral Student 3 11%
Researcher 3 11%
Student > Master 1 4%
Professor 1 4%
Other 2 7%
Unknown 11 41%
Readers by discipline Count As %
Engineering 10 37%
Energy 2 7%
Computer Science 2 7%
Medicine and Dentistry 1 4%
Design 1 4%
Other 0 0%
Unknown 11 41%