Heat sink design optimization using the thermal bottleneck concept

Bornoff, Robin; Blackmore, B. S.; Parry, John

doi:10.1109/stherm.2011.5767181

Cited by 13 publications

(5 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Note that, as discussed in Section 2.2, the steady-state temperature of the heat sink T s is directly connected to the maximum junction temperature T j via formulas (3) and (2). Therefore, all aforementioned optimization problems can be alternatively formulated such that a minimal value for T s is sought instead of…”

Section: Heat Sink Design Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Power Module Heat Sink Design Optimization with Ensembles of Data-Driven Polynomial Chaos Surrogate Models

Loukrezis¹,

Gersem²

2022

Preprint

View full text Add to dashboard Cite

We consider the problem of optimizing the design of a heat sink used for cooling an insulated gate bipolar transistor (IGBT) power module. The thermal behavior of the heat sink is originally estimated using a high-fidelity computational fluid dynamics (CFD) simulation, which renders numerical optimization too computationally demanding. To enable optimization studies, we substitute the CFD simulation model with an inexpensive polynomial surrogate model that approximates the relation between the device's design features and a relevant thermal quantity of interest. The surrogate model of choice is a data-driven polynomial chaos expansion (DD-PCE), which learns the aforementioned relation by means of polynomial regression.Advantages of the DD-PCE include its applicability in small-data regimes and its easily adaptable model structure. Once trained and tested in terms of prediction accuracy, the DD-PCE replaces the high-fidelity simulation model in optimization algorithms aiming to identify heat sink designs that optimize the thermal behavior of the IGBT under geometrical and operational constraints. Optimized heat sink designs are obtained for a computational cost much smaller than utilizing the original model in the optimization procedure. Comparisons against alternative surrogate modeling techniques illustrate why the DD-PCE should be preferred in the considered setting.

show abstract

Section: Heat Sink Design Optimizationmentioning

confidence: 99%

“…A common approach in heat sink design is to combine simulation models with numerical optimization methods in order to optimize the heat sink's geometry with respect to a quantity of interest (QoI) related to the thermal behavior of the device [2][3][4][5][6]. This optimization is commonly conducted under cost-and sizerelated constraints.…”

Section: Introductionmentioning

confidence: 99%

Power Module Heat Sink Design Optimization with Ensembles of Data-Driven Polynomial Chaos Surrogate Models

Loukrezis¹,

Gersem²

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Rather than using CFD modeling as a standalone heat sink design tool, this technique can complement analytical and semi-empirical thermal design tools, by providing a more accurate assessment of heat sink thermofluid performance [31] and offering useful heat transfer visualizations [32]. Numerical visualization can enable a designer to understand and interact with the physical heat transfer mechanisms, and assist in identifying solutions.…”

Section: Computational Fluid Dynamics Modelingmentioning

confidence: 99%

Air cooled heat sink design optimization in free convection

Rodgers¹,

Eveloy²

2013

29th IEEE Semiconductor Thermal Measurement and Management Symposium

View full text Add to dashboard Cite

The optimization of heat sink performance is becoming ever more critical in passively air-cooled applications. In this paper, an overview of analytical, semi-empirical and Computational Fluid Dynamics (CFD)-based methodologies for air-cooled heat sink design optimization in free convection is presented. The advantages and potential limitations of these design techniques are summarized. A multi-faceted heat sink design strategy is advocated, which combines the analysis techniques presented with experimentation. The need to incorporate sustainability and formal optimization in the design process is highlighted.

show abstract

“…Thermal BottleNeck distribution was also used to directly modify fin thickness of a pre-optimized heatsink [4]. The Thermal BottleNeck values in each fin were noted and the fin thicknesses modified in an attempt to equalize the BN in each fin, leading to a marked improvement in thermal performance.…”

Section: Introductionmentioning

confidence: 99%

“…It was observed that the heatsink grew as a tree-like structure from the center of the heat source. This process was also applied to grow the heatsink where the Thermal BottleNeck was largest [3], producing slightly improved behaviour compared to using surface temperature to drive the additive design process.Thermal BottleNeck distribution was also used to directly modify fin thickness of a pre-optimized heatsink [4]. The Thermal BottleNeck values in each fin were noted and the fin thicknesses modified in an attempt to equalize the BN in each fin, leading to a marked improvement in thermal performance.…”

mentioning

confidence: 99%

Subtractive design: A novel approach to heatsink improvement

Bornoff

Wilson

Parry

2016

2016 32nd Thermal Measurement, Modeling &Amp; Management Symposium (SEMI-THERM)

Self Cite

View full text Add to dashboard Cite

Typical Heatsink design includes base and fin thickness, fin height, and fin gap optimization. In situations where material cost or mass of the heat sink are also a design priority further optimization with respect to mass removal can be significant.This paper discusses a method to further improve a heat sink topology by the systematic removal of heat sink mass where the Thermal BottleNeck (BN) Number was found to be lowest. NomenclatureRth -Thermal Resistance (DegC/W) = (Tb -Ta) / P Tb -Heatsink base temperature (above center of heat source) Ta -Ambient temperature P -Dissipated power BN -Thermal BottleNeck Number IntroductionTypical heat sink design involves balancing trade-offs between parameters such as heat spreading, heat sink mass, airflow bypass, and manufacturability. A typical optimization would include varying a small number of dimensional parameters of the heat sink and a temperature rise used as the objective cost function. A Computational Fluid Dynamics (CFD) simulation offers the opportunity to consider the spatial distribution of heat transfer effectiveness and, based on that, changes made to the geometry topology with the intention to further improve the design. Previous studies have considered elements of this approach [1].An earlier study [2] explored an additive methodology to heatsink design. In that study the heatsink fins were allowed to grow where the surface temperature was the highest, as part of an iterative design process. The heatsink topology evolved over a number of cycles until no further performance gains were achieved. It was observed that the heatsink grew as a tree-like structure from the center of the heat source. This process was also applied to grow the heatsink where the Thermal BottleNeck was largest [3], producing slightly improved behaviour compared to using surface temperature to drive the additive design process.Thermal BottleNeck distribution was also used to directly modify fin thickness of a pre-optimized heatsink [4]. The Thermal BottleNeck values in each fin were noted and the fin thicknesses modified in an attempt to equalize the BN in each fin, leading to a marked improvement in thermal performance.

show abstract

Heat sink design optimization using the thermal bottleneck concept

Cited by 13 publications

References 0 publications

Power Module Heat Sink Design Optimization with Ensembles of Data-Driven Polynomial Chaos Surrogate Models

Power Module Heat Sink Design Optimization with Ensembles of Data-Driven Polynomial Chaos Surrogate Models

Air cooled heat sink design optimization in free convection

Subtractive design: A novel approach to heatsink improvement

Contact Info

Product

Resources

About