A coupled POD-Kriging approach for the simulation of a multi-stream heat exchanger

Proper Orthogonal Decomposition (POD) is a well-examined order reduction method. In this paper, it is implemented as a non-intrusive method for the cost-effective simulation of a multi-stream heat exchanger. Three-dimensional fluid-solid domains are analyzed conjugately, and the numerical results provide snapshots. The dimensionless vector-valued approach is suggested for the extraction of the base vectors. The Kriging (KRG) method is employed to approximate the coefficients of the bases. Reynolds numbers of the flow streams are variable parameters in the snapshots, and the field is reconstructed at two Reynolds number combinations. The field is reconstructed for two situations: one with full interpolation of the POD weighting coefficients and another with partial extrapolation for them. The deviation of the results is calculated regarding the corresponding CFD solution as the reference. In 96% of the comparative test cases, the estimated total heat exchanges and exit temperatures via POD have deviations less than 20%, and a substantial reduction in computational cost is attained. A deviation accumulation is observed due to the integration in post-processing. The partial extrapolation increases the deviation of heat exchange and temperature all over the domain because of the unified analysis.

Authors

Institutions

Publication Details

Journal
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Published
2025-04-14
DOI
https://doi.org/10.1177/09544062251331382
Citations
1
Primary Topic
Probabilistic and Robust Engineering Design
Type
article
Field-Weighted Citation Impact
1.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A coupled POD-Kriging approach for the simulation of a multi-stream heat exchanger

Ali Ashrafizadeh, Yasser Shafiei-alamooti
1 citations
Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science
Probabilistic and Robust Engineering Design
1.40
article

A coupled POD-Kriging approach for the simulation of a multi-stream heat exchanger

Ali Ashrafizadeh, Yasser Shafiei-alamooti
article en
1 citations

Abstract

Proper Orthogonal Decomposition (POD) is a well-examined order reduction method. In this paper, it is implemented as a non-intrusive method for the cost-effective simulation of a multi-stream heat exchanger. Three-dimensional fluid-solid domains are analyzed conjugately, and the numerical results provide snapshots. The dimensionless vector-valued approach is suggested for the extraction of the base vectors. The Kriging (KRG) method is employed to approximate the coefficients of the bases. Reynolds numbers of the flow streams are variable parameters in the snapshots, and the field is reconstructed at two Reynolds number combinations. The field is reconstructed for two situations: one with full interpolation of the POD weighting coefficients and another with partial extrapolation for them. The deviation of the results is calculated regarding the corresponding CFD solution as the reference. In 96% of the comparative test cases, the estimated total heat exchanges and exit temperatures via POD have deviations less than 20%, and a substantial reduction in computational cost is attained. A deviation accumulation is observed due to the integration in post-processing. The partial extrapolation increases the deviation of heat exchange and temperature all over the domain because of the unified analysis.

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering ScienceVol. 239(14)
Takestan Islamic Azad University (IR), K. N. Toosi University of Technology (IR)
National Iranian Gas Company
Openalex Percentile: Top 17%
Probabilistic and Robust Engineering Design
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.