Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification

Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification

We apply binary classification theory to assess the (in)stability prediction accuracy of thermoacoustic models. It is shown that by applying such methods to compare a large set of stability predictions and experiments it is possible to gain valuable qualitative insight in different aspects of predic...

Full description

Bibliographic Details
Main Authors: Maarten Hoeijmakers, Ines Lopez Arteaga, Viktor Kornilov, Henk Nijmeijer, Philip de Goey
Format: Article
Language:English
Published: SAGE Publishing 2013-09-01
Series:International Journal of Spray and Combustion Dynamics
Online Access:https://doi.org/10.1260/1756-8277.5.3.201
id doaj-be43c1cca9f8498b9a344f46a647f551
record_format Article
spelling doaj-be43c1cca9f8498b9a344f46a647f5512020-11-25T03:07:53ZengSAGE PublishingInternational Journal of Spray and Combustion Dynamics1756-82771756-82852013-09-01510.1260/1756-8277.5.3.20110.1260_1756-8277.5.3.201Accuracy Assessment of Thermoacoustic Instability Models Using Binary ClassificationMaarten Hoeijmakers0Ines Lopez Arteaga1Viktor Kornilov2Henk Nijmeijer3Philip de Goey4 Department of Mechanical Engineering, Eindhoven University of Technology, Netherlands KTH Royal Institute of Technology, Department of Aeronautical and Vehicle Engineering, Marcus Wallenberg Laboratory, Sweden Department of Mechanical Engineering, Eindhoven University of Technology, Netherlands Department of Mechanical Engineering, Eindhoven University of Technology, Netherlands Department of Mechanical Engineering, Eindhoven University of Technology, NetherlandsWe apply binary classification theory to assess the (in)stability prediction accuracy of thermoacoustic models. It is shown that by applying such methods to compare a large set of stability predictions and experiments it is possible to gain valuable qualitative insight in different aspects of prediction quality. The approach is illustrated with a 2-port model and a large experimental data set. The presented framework provides an unified and practical tool to answer questions such as (i) What is the chance that a stable prediction will be correct? and (ii) How conservative is the model? It is shown that the most suitable quality indicator is strongly dependent on the actual purpose of the model. The method provides a solid starting point for model comparison and optimization.https://doi.org/10.1260/1756-8277.5.3.201
collection DOAJ
language English
format Article
sources DOAJ
author Maarten Hoeijmakers
Ines Lopez Arteaga
Viktor Kornilov
Henk Nijmeijer
Philip de Goey
spellingShingle Maarten Hoeijmakers
Ines Lopez Arteaga
Viktor Kornilov
Henk Nijmeijer
Philip de Goey
Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification
International Journal of Spray and Combustion Dynamics
author_facet Maarten Hoeijmakers
Ines Lopez Arteaga
Viktor Kornilov
Henk Nijmeijer
Philip de Goey
author_sort Maarten Hoeijmakers
title Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification
title_short Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification
title_full Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification
title_fullStr Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification
title_full_unstemmed Accuracy Assessment of Thermoacoustic Instability Models Using Binary Classification
title_sort accuracy assessment of thermoacoustic instability models using binary classification
publisher SAGE Publishing
series International Journal of Spray and Combustion Dynamics
issn 1756-8277
1756-8285
publishDate 2013-09-01
description We apply binary classification theory to assess the (in)stability prediction accuracy of thermoacoustic models. It is shown that by applying such methods to compare a large set of stability predictions and experiments it is possible to gain valuable qualitative insight in different aspects of prediction quality. The approach is illustrated with a 2-port model and a large experimental data set. The presented framework provides an unified and practical tool to answer questions such as (i) What is the chance that a stable prediction will be correct? and (ii) How conservative is the model? It is shown that the most suitable quality indicator is strongly dependent on the actual purpose of the model. The method provides a solid starting point for model comparison and optimization.
url https://doi.org/10.1260/1756-8277.5.3.201
work_keys_str_mv AT maartenhoeijmakers accuracyassessmentofthermoacousticinstabilitymodelsusingbinaryclassification
AT ineslopezarteaga accuracyassessmentofthermoacousticinstabilitymodelsusingbinaryclassification
AT viktorkornilov accuracyassessmentofthermoacousticinstabilitymodelsusingbinaryclassification
AT henknijmeijer accuracyassessmentofthermoacousticinstabilitymodelsusingbinaryclassification
AT philipdegoey accuracyassessmentofthermoacousticinstabilitymodelsusingbinaryclassification
_version_ 1724668628976009216

Similar Items