Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition

Efficient analysis and storage of data is an integral but often challenging task when working with computation fluid dynamics mainly due to the amount of data it can output. Methods centered around the proper orthogonal decomposition were used to analyze, compress, and model various simulation cases...

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Main Author: Blanc, Trevor Jon
Format: Others
Published: BYU ScholarsArchive 2014
Subjects:
Online Access:https://scholarsarchive.byu.edu/etd/5303
https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6302&context=etd
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spelling ndltd-BGMYU2-oai-scholarsarchive.byu.edu-etd-63022019-05-16T03:33:53Z Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition Blanc, Trevor Jon Efficient analysis and storage of data is an integral but often challenging task when working with computation fluid dynamics mainly due to the amount of data it can output. Methods centered around the proper orthogonal decomposition were used to analyze, compress, and model various simulation cases. Two different high-fidelity, time-accurate turbomachinery simulations were investigated to show various applications of the analysis techniques. The first turbomachinery example was used to illustrate the extraction of turbulent coherent structures such as traversing shocks, vortex shedding, and wake variation from deswirler and rotor blade passages. Using only the most dominant modes, flow fields were reconstructed and analyzed for error. The reconstructions reproduced the general dynamics within the flow well, but failed to fully resolve shock fronts and smaller vortices. By decomposing the domain into smaller, independent pieces, reconstruction error was reduced by up to 63 percent. A new method of data compression that combined an image compression algorithm and the proper orthogonal decomposition was used to store the reconstructions of the flow field, increasing data compression ratios by a factor of 40.The second turbomachinery simulation studied was a three-stage fan with inlet total pressure distortion. Both the snapshot and repeating geometry methods were used to characterize structures of static pressure fluctuation within the blade passages of the third rotor blade row. Modal coefficients filtered by frequencies relating to the inlet distortion pattern were used to produce reconstructions of the pressure field solely dependent on the inlet boundary condition. A hybrid proper orthogonal decomposition method was proposed to limit burdens on computational resources while providing high temporal resolution analysis.Parametric reduced order models were created from large databases of transient and steady conjugate heat transfer and airfoil simulations. Performance of the models were found to depend heavily on the range of the parameters varied as well as the number of simulations used to traverse that range. The heat transfer models gave excellent predictions for temperature profiles in heated solids for ambitious parameter ranges. Model development for the airfoil case showed that accuracy was highly dependent on modal truncation. The flow fields were predicted very well, especially outside the boundary layer region of the flow. 2014-07-01T07:00:00Z text application/pdf https://scholarsarchive.byu.edu/etd/5303 https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6302&context=etd http://lib.byu.edu/about/copyright/ All Theses and Dissertations BYU ScholarsArchive proper orthogonal decomposition reduced order models reduced order reconstruction data compression computational fluid dynamics post-processing domain decomposition computational fluid dynamics coherent structures turbomachinery pressure distortion conjugate heat transfer Mechanical Engineering
collection NDLTD
format Others
sources NDLTD
topic proper orthogonal decomposition
reduced order models
reduced order reconstruction
data compression
computational fluid dynamics
post-processing
domain decomposition
computational fluid dynamics
coherent structures
turbomachinery
pressure distortion
conjugate heat transfer
Mechanical Engineering
spellingShingle proper orthogonal decomposition
reduced order models
reduced order reconstruction
data compression
computational fluid dynamics
post-processing
domain decomposition
computational fluid dynamics
coherent structures
turbomachinery
pressure distortion
conjugate heat transfer
Mechanical Engineering
Blanc, Trevor Jon
Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition
description Efficient analysis and storage of data is an integral but often challenging task when working with computation fluid dynamics mainly due to the amount of data it can output. Methods centered around the proper orthogonal decomposition were used to analyze, compress, and model various simulation cases. Two different high-fidelity, time-accurate turbomachinery simulations were investigated to show various applications of the analysis techniques. The first turbomachinery example was used to illustrate the extraction of turbulent coherent structures such as traversing shocks, vortex shedding, and wake variation from deswirler and rotor blade passages. Using only the most dominant modes, flow fields were reconstructed and analyzed for error. The reconstructions reproduced the general dynamics within the flow well, but failed to fully resolve shock fronts and smaller vortices. By decomposing the domain into smaller, independent pieces, reconstruction error was reduced by up to 63 percent. A new method of data compression that combined an image compression algorithm and the proper orthogonal decomposition was used to store the reconstructions of the flow field, increasing data compression ratios by a factor of 40.The second turbomachinery simulation studied was a three-stage fan with inlet total pressure distortion. Both the snapshot and repeating geometry methods were used to characterize structures of static pressure fluctuation within the blade passages of the third rotor blade row. Modal coefficients filtered by frequencies relating to the inlet distortion pattern were used to produce reconstructions of the pressure field solely dependent on the inlet boundary condition. A hybrid proper orthogonal decomposition method was proposed to limit burdens on computational resources while providing high temporal resolution analysis.Parametric reduced order models were created from large databases of transient and steady conjugate heat transfer and airfoil simulations. Performance of the models were found to depend heavily on the range of the parameters varied as well as the number of simulations used to traverse that range. The heat transfer models gave excellent predictions for temperature profiles in heated solids for ambitious parameter ranges. Model development for the airfoil case showed that accuracy was highly dependent on modal truncation. The flow fields were predicted very well, especially outside the boundary layer region of the flow.
author Blanc, Trevor Jon
author_facet Blanc, Trevor Jon
author_sort Blanc, Trevor Jon
title Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition
title_short Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition
title_full Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition
title_fullStr Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition
title_full_unstemmed Analysis and Compression of Large CFD Data Sets Using Proper Orthogonal Decomposition
title_sort analysis and compression of large cfd data sets using proper orthogonal decomposition
publisher BYU ScholarsArchive
publishDate 2014
url https://scholarsarchive.byu.edu/etd/5303
https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=6302&context=etd
work_keys_str_mv AT blanctrevorjon analysisandcompressionoflargecfddatasetsusingproperorthogonaldecomposition
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