Tampere University of Technology

TUTCRIS Research Portal

A new method to optimize natural convection heat sinks

Research output: Contribution to journalArticleScientificpeer-review

Standard

A new method to optimize natural convection heat sinks. / Lampio, K.; Karvinen, R.

In: Heat and Mass Transfer/Waerme- und Stoffuebertragung, Vol. 54, No. 8, 08.2018, p. 2571-2580.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Lampio, K & Karvinen, R 2018, 'A new method to optimize natural convection heat sinks', Heat and Mass Transfer/Waerme- und Stoffuebertragung, vol. 54, no. 8, pp. 2571-2580. https://doi.org/10.1007/s00231-017-2106-4

APA

Lampio, K., & Karvinen, R. (2018). A new method to optimize natural convection heat sinks. Heat and Mass Transfer/Waerme- und Stoffuebertragung, 54(8), 2571-2580. https://doi.org/10.1007/s00231-017-2106-4

Vancouver

Lampio K, Karvinen R. A new method to optimize natural convection heat sinks. Heat and Mass Transfer/Waerme- und Stoffuebertragung. 2018 Aug;54(8):2571-2580. https://doi.org/10.1007/s00231-017-2106-4

Author

Lampio, K. ; Karvinen, R. / A new method to optimize natural convection heat sinks. In: Heat and Mass Transfer/Waerme- und Stoffuebertragung. 2018 ; Vol. 54, No. 8. pp. 2571-2580.

Bibtex - Download

@article{6c62137930b040fc91a5a4fa6cfa05ef,
title = "A new method to optimize natural convection heat sinks",
abstract = "The performance of a heat sink cooled by natural convection is strongly affected by its geometry, because buoyancy creates flow. Our model utilizes analytical results of forced flow and convection, and only conduction in a solid, i.e., the base plate and fins, is solved numerically. Sufficient accuracy for calculating maximum temperatures in practical applications is proved by comparing the results of our model with some simple analytical and computational fluid dynamics (CFD) solutions. An essential advantage of our model is that it cuts down on calculation CPU time by many orders of magnitude compared with CFD. The shorter calculation time makes our model well suited for multi-objective optimization, which is the best choice for improving heat sink geometry, because many geometrical parameters with opposite effects influence the thermal behavior. In multi-objective optimization, optimal locations of components and optimal dimensions of the fin array can be found by simultaneously minimizing the heat sink maximum temperature, size, and mass. This paper presents the principles of the particle swarm optimization (PSO) algorithm and applies it as a basis for optimizing existing heat sinks.",
author = "K. Lampio and R. Karvinen",
year = "2018",
month = "8",
doi = "10.1007/s00231-017-2106-4",
language = "English",
volume = "54",
pages = "2571--2580",
journal = "HEAT AND MASS TRANSFER",
issn = "0947-7411",
publisher = "Springer Verlag",
number = "8",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - A new method to optimize natural convection heat sinks

AU - Lampio, K.

AU - Karvinen, R.

PY - 2018/8

Y1 - 2018/8

N2 - The performance of a heat sink cooled by natural convection is strongly affected by its geometry, because buoyancy creates flow. Our model utilizes analytical results of forced flow and convection, and only conduction in a solid, i.e., the base plate and fins, is solved numerically. Sufficient accuracy for calculating maximum temperatures in practical applications is proved by comparing the results of our model with some simple analytical and computational fluid dynamics (CFD) solutions. An essential advantage of our model is that it cuts down on calculation CPU time by many orders of magnitude compared with CFD. The shorter calculation time makes our model well suited for multi-objective optimization, which is the best choice for improving heat sink geometry, because many geometrical parameters with opposite effects influence the thermal behavior. In multi-objective optimization, optimal locations of components and optimal dimensions of the fin array can be found by simultaneously minimizing the heat sink maximum temperature, size, and mass. This paper presents the principles of the particle swarm optimization (PSO) algorithm and applies it as a basis for optimizing existing heat sinks.

AB - The performance of a heat sink cooled by natural convection is strongly affected by its geometry, because buoyancy creates flow. Our model utilizes analytical results of forced flow and convection, and only conduction in a solid, i.e., the base plate and fins, is solved numerically. Sufficient accuracy for calculating maximum temperatures in practical applications is proved by comparing the results of our model with some simple analytical and computational fluid dynamics (CFD) solutions. An essential advantage of our model is that it cuts down on calculation CPU time by many orders of magnitude compared with CFD. The shorter calculation time makes our model well suited for multi-objective optimization, which is the best choice for improving heat sink geometry, because many geometrical parameters with opposite effects influence the thermal behavior. In multi-objective optimization, optimal locations of components and optimal dimensions of the fin array can be found by simultaneously minimizing the heat sink maximum temperature, size, and mass. This paper presents the principles of the particle swarm optimization (PSO) algorithm and applies it as a basis for optimizing existing heat sinks.

U2 - 10.1007/s00231-017-2106-4

DO - 10.1007/s00231-017-2106-4

M3 - Article

VL - 54

SP - 2571

EP - 2580

JO - HEAT AND MASS TRANSFER

JF - HEAT AND MASS TRANSFER

SN - 0947-7411

IS - 8

ER -