Data Analysis for Direct Numerical Simulations of Turbulent Combustion

2020 ◽

pp. 135-155

Author(s):

Nicholas Arnold-Medabalimi ◽

Cheng Huang ◽

Karthik Duraisamy

Keyword(s):

Flow Fields ◽

Data Driven ◽

High Dimensional ◽

Decomposition Techniques ◽

Modal Decomposition ◽

Dimensional Flow

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Higher Order Tensors for DNS Data Analysis and Compression

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_6 ◽

2020 ◽

pp. 109-134

Author(s):

Hemanth Kolla ◽

Konduri Aditya ◽

Jacqueline H. Chen

Keyword(s):

Data Analysis ◽

Higher Order ◽

Higher Order Tensors

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Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_14 ◽

2020 ◽

pp. 273-292

Author(s):

Shashank Yellapantula ◽

Marc T. Henry de Frahan ◽

Ryan King ◽

Marc Day ◽

Ray Grout

Keyword(s):

Machine Learning ◽

Numerical Simulation ◽

Direct Numerical Simulation

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Analysis of Turbulent Reacting Jets via Principal Component Analysis

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_12 ◽

2020 ◽

pp. 233-251

Author(s):

Giuseppe D’Alessio ◽

Antonio Attili ◽

Alberto Cuoci ◽

Heinz Pitsch ◽

Alessandro Parente

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis

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Data-Based Modeling for the Crank Angle Resolved CI Combustion Process

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_10 ◽

2020 ◽

pp. 197-213

Author(s):

Jan Schilliger ◽

Nils Keller ◽

Severin Hänggi ◽

Thivaharan Albin ◽

Christopher Onder

Keyword(s):

Combustion Process ◽

Crank Angle

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Physics-Informed Data-Driven Prediction of Turbulent Reacting Flows with Lyapunov Analysis and Sequential Data Assimilation

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_9 ◽

2020 ◽

pp. 177-196

Author(s):

Luca Magri ◽

Nguyen Anh Khoa Doan

Keyword(s):

Data Assimilation ◽

Reacting Flows ◽

Data Driven ◽

Sequential Data ◽

Lyapunov Analysis ◽

Turbulent Reacting Flows ◽

Sequential Data Assimilation

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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

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_4 ◽

2020 ◽

pp. 65-88

Author(s):

M. Valorani ◽

F. Creta ◽

P. P. Ciottoli ◽

R. Malpica Galassi ◽

D. A. Goussis ◽

...

Keyword(s):

Singular Perturbation ◽

Time Scale ◽

Large Scale ◽

Turbulent Flames ◽

Singular Perturbation Method ◽

Rate Analysis ◽

Computational Singular Perturbation ◽

Scale Characterization ◽

Tracking Time ◽

Large Scale Simulations

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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

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_3 ◽

2020 ◽

pp. 43-64 ◽

Cited By ~ 1

Author(s):

M. Valorani ◽

F. Creta ◽

P. P. Ciottoli ◽

R. Malpica Galassi ◽

D. A. Goussis ◽

...

Keyword(s):

Singular Perturbation ◽

Time Scale ◽

Large Scale ◽

Singular Perturbation Method ◽

Rate Analysis ◽

Computational Singular Perturbation ◽

Basic Concepts ◽

Scale Characterization ◽

Tracking Time ◽

Large Scale Simulations

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From Discrete and Iterative Deconvolution Operators to Machine Learning for Premixed Turbulent Combustion Modeling

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_11 ◽

2020 ◽

pp. 215-232

Author(s):

P. Domingo ◽

Z. Nikolaou ◽

A. Seltz ◽

L. Vervisch

Keyword(s):

Machine Learning ◽

Turbulent Combustion ◽

Combustion Modeling ◽

Premixed Turbulent Combustion ◽

Iterative Deconvolution

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Dynamic Mode Decomposition: A Tool to Extract Structures Hidden in Massive Datasets

Data Analysis for Direct Numerical Simulations of Turbulent Combustion ◽

10.1007/978-3-030-44718-2_8 ◽

2020 ◽

pp. 157-176

Author(s):

T. Grenga ◽

M. E. Mueller

Keyword(s):

Dynamic Mode Decomposition ◽

Dynamic Mode ◽

Massive Datasets ◽

Mode Decomposition

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Data Analysis for Direct Numerical Simulations of Turbulent Combustion
Latest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Data-Driven Modal Decomposition Techniques for High-Dimensional Flow Fields

Higher Order Tensors for DNS Data Analysis and Compression

Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation

Analysis of Turbulent Reacting Jets via Principal Component Analysis

Data-Based Modeling for the Crank Angle Resolved CI Combustion Process

Physics-Informed Data-Driven Prediction of Turbulent Reacting Flows with Lyapunov Analysis and Sequential Data Assimilation

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

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

From Discrete and Iterative Deconvolution Operators to Machine Learning for Premixed Turbulent Combustion Modeling

Dynamic Mode Decomposition: A Tool to Extract Structures Hidden in Massive Datasets

Export Citation Format

Data Analysis for Direct Numerical Simulations of Turbulent CombustionLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Data-Driven Modal Decomposition Techniques for High-Dimensional Flow Fields

Higher Order Tensors for DNS Data Analysis and Compression

Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation

Analysis of Turbulent Reacting Jets via Principal Component Analysis

Data-Based Modeling for the Crank Angle Resolved CI Combustion Process

Physics-Informed Data-Driven Prediction of Turbulent Reacting Flows with Lyapunov Analysis and Sequential Data Assimilation

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

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

From Discrete and Iterative Deconvolution Operators to Machine Learning for Premixed Turbulent Combustion Modeling

Dynamic Mode Decomposition: A Tool to Extract Structures Hidden in Massive Datasets

Data Analysis for Direct Numerical Simulations of Turbulent Combustion
Latest Publications