TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Methods to design optimum heat sink geometries

Tutkimustuotosvertaisarvioitu

Standard

Methods to design optimum heat sink geometries. / Karvinen, Reijo; Lampio, Kaj.

International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China. 2018. s. 5041-5048 IHTC16-23247.

Tutkimustuotosvertaisarvioitu

Harvard

Karvinen, R & Lampio, K 2018, Methods to design optimum heat sink geometries. julkaisussa International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China., IHTC16-23247, Sivut 5041-5048, 1/01/00. https://doi.org/10.1615/IHTC16.hte.023247

APA

Karvinen, R., & Lampio, K. (2018). Methods to design optimum heat sink geometries. teoksessa International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China (Sivut 5041-5048). [IHTC16-23247] https://doi.org/10.1615/IHTC16.hte.023247

Vancouver

Karvinen R, Lampio K. Methods to design optimum heat sink geometries. julkaisussa International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China. 2018. s. 5041-5048. IHTC16-23247 https://doi.org/10.1615/IHTC16.hte.023247

Author

Karvinen, Reijo ; Lampio, Kaj. / Methods to design optimum heat sink geometries. International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China. 2018. Sivut 5041-5048

Bibtex - Lataa

@inproceedings{70cb0bca622d43f9813f016bc2db860b,
title = "Methods to design optimum heat sink geometries",
abstract = "This paper gives a short review of recent studies dealing with optimization of conjugated heat transfer of fin arrays. First, some results considering optimal geometries of single fins are presented to give some idea on how fin shape affects heat transfer. The main emphasis is on fin arrays, which can be solved with CFD, but it requires plenty of CPU-time and is thus often rejected in optimization of industrial applications. If the most time consuming phase of the solution, the convective heat transfer, is handled using analytical results and only conduction is solved numerically, we have a fast performing tool for design and optimization process. With this approach, the CPU-time is many orders of magnitude smaller than in the case of pure numerical solution with CFD. The accuracy of the results is checked by comparing them to experimental, and in some simple cases, to numerically calculated results. After testing the accuracy of the model, it is applied using multi-objective optimization to fin arrays cooled by natural and forced convection. The selected optimization algorithm was a multi-objective version of particle swarm optimization (PSO) algorithm, which works well.",
author = "Reijo Karvinen and Kaj Lampio",
year = "2018",
month = "8",
day = "10",
doi = "10.1615/IHTC16.hte.023247",
language = "English",
pages = "5041--5048",
booktitle = "International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China",

}

RIS (suitable for import to EndNote) - Lataa

TY - GEN

T1 - Methods to design optimum heat sink geometries

AU - Karvinen, Reijo

AU - Lampio, Kaj

PY - 2018/8/10

Y1 - 2018/8/10

N2 - This paper gives a short review of recent studies dealing with optimization of conjugated heat transfer of fin arrays. First, some results considering optimal geometries of single fins are presented to give some idea on how fin shape affects heat transfer. The main emphasis is on fin arrays, which can be solved with CFD, but it requires plenty of CPU-time and is thus often rejected in optimization of industrial applications. If the most time consuming phase of the solution, the convective heat transfer, is handled using analytical results and only conduction is solved numerically, we have a fast performing tool for design and optimization process. With this approach, the CPU-time is many orders of magnitude smaller than in the case of pure numerical solution with CFD. The accuracy of the results is checked by comparing them to experimental, and in some simple cases, to numerically calculated results. After testing the accuracy of the model, it is applied using multi-objective optimization to fin arrays cooled by natural and forced convection. The selected optimization algorithm was a multi-objective version of particle swarm optimization (PSO) algorithm, which works well.

AB - This paper gives a short review of recent studies dealing with optimization of conjugated heat transfer of fin arrays. First, some results considering optimal geometries of single fins are presented to give some idea on how fin shape affects heat transfer. The main emphasis is on fin arrays, which can be solved with CFD, but it requires plenty of CPU-time and is thus often rejected in optimization of industrial applications. If the most time consuming phase of the solution, the convective heat transfer, is handled using analytical results and only conduction is solved numerically, we have a fast performing tool for design and optimization process. With this approach, the CPU-time is many orders of magnitude smaller than in the case of pure numerical solution with CFD. The accuracy of the results is checked by comparing them to experimental, and in some simple cases, to numerically calculated results. After testing the accuracy of the model, it is applied using multi-objective optimization to fin arrays cooled by natural and forced convection. The selected optimization algorithm was a multi-objective version of particle swarm optimization (PSO) algorithm, which works well.

U2 - 10.1615/IHTC16.hte.023247

DO - 10.1615/IHTC16.hte.023247

M3 - Conference contribution

SP - 5041

EP - 5048

BT - International Heat Transfer Conference, IHTC-16, August 10-15, 2018, Beijing, China

ER -