Keywords
Reduced order methods, Heat Transfer, Akaike Information Criterion
Abstract
Reduced order methods using spectral representations show promise in facilitating and accelerating heat transfer analyses. This paper proposes a taxonomy for reduced order methods, classifying a method as reduced order compression, modelling, or analysis. The performance of bases formed with analytical and empirical eigenfunctions are compared for representative reduced order tasks. The Akaike Information Criterion is applied in a novel way to compare the performance of these bases. The present study finds that both bases are parsimonious for reduced order compression tasks. Empirical eigenfunctions are more robust to for reduced order modelling with variations in modelling parameters such as thermal diffusivity. Analytical eigenfunctions are more robust for reduced order analysis in the presence of noise. The Akaike Information Criterion is shown to provide an unambiguous optimal truncation criterion for reduced order analysis applications in the presence of noise.
BYU ScholarsArchive Citation
Bates, Jakob G.; Jones, Matthew R.; Dillon, Christopher R.; and Tencer, John, "Comparison of Empirical and Analytical Eigenfunctions as Bases for Reduced Order Methods in Heat Transfer" (2024). Student Works. 377.
https://scholarsarchive.byu.edu/studentpub/377
Document Type
Report
Publication Date
2024-01-09
Language
English
College
Ira A. Fulton College of Engineering
Department
Mechanical Engineering
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