Topology optimization for the conduction cooling of a heat-generating volume with orthotropic material

Page, L.G.; Dirker, Jaco; Meyer, Josua P.

doi:10.1016/j.ijheatmasstransfer.2016.08.020

Cited by 27 publications

(5 citation statements)

References 30 publications

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“…Using the simulation results, the heat transfer path of the machine tool can be optimized. For the structural optimization, the main methods include the construction theory, topology optimization, and bionic optimization to optimize the material distribution within a specific load, constraint, area, and performance [18][19][20]. For the optimization of convective heat transfer, the commonly used method is to increase the heat dissipation of the cooling system and balance the temperature field through controlling the cooling parameters and optimizing the cooling channel [21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Thermoelectric-based cooling system for high-speed motorized spindle II: Optimization and validation strategy

Fan

Wang

et al. 2022

Int J Adv Manuf Technol

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With the development of motorized spindle, the cooling effect and the distribution of cooling capacity become the crucial problem of cooling system. An optimization method for ThermoElectric-based Cooling System (TECS) is proposed based on the conservation of energy to distribute the cooling capacity. The main strategy of the proposed optimization method is to make the cold and heat input at different regions of the spindle sleeve equal in real-time through optimizing the contact area between the Heat Conduction Sleeve (HCS) and spindle sleeve. The numerical simulation and thermal characteristics experiments are carried to verify the effect of the proposed optimization method and the TECS. The simulation and experimental results show that the maximum temperature rise and thermal elongation of the TECS-based motorized spindle are reduced 56.7% and 58.6% compared with water-cooled motorized spindle, and the temperature distribution of the spindle sleeve is more uniform. It is meaningful to improve the accuracy of motorized spindle.

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Section: Introductionmentioning

confidence: 99%

Thermoelectric-based cooling system for high-speed motorized spindle II: Optimization and validation strategy

Fan

Wang

et al. 2022

Int J Adv Manuf Technol

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“…Various constructal designs have been derived for volume (area)‐to‐point problems with different constraints, boundary conditions, element shapes, and optimization objectives. [ 3–11 ] Many algorithms, eg, the solid isotropic with material penalization (SIMP) method, [ 12–18 ] rational approximation of material properties method, [ 19 ] evolutionary structural optimization method, [ 20,21 ] level‐set method, [ 22–24 ] cellular automaton algorithm, [ 25,26 ] deep learning approach, [ 27 ] genetic algorithm (GA), [ 28,29 ] simulated annealing (SA), [ 28,30 ] PSO, [ 31 ] bionic optimization, [ 30,32–41 ] and calculus of variations, [ 42,43 ] have been applied to the field of volume (area)‐to‐point heat conduction.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective optimization of area‐to‐point heat conduction structure using binary quantum‐behaved PSO and Tchebycheff decomposition method

et al. 2020

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A multiobjective optimization of area‐to‐point heat conduction to minimize both mean temperature and temperature variance is conducted based on a decomposition‐based multiobjective binary quantum‐behaved particle swarm optimization (PSO) method (MOMBQPSO/D). The MOMBQPSO/D adopts the framework of the multiobjective evolutionary algorithm based on decomposition and modifies the binary quantum‐behaved PSO. In the first step of the MOMBQPSO/D, the multiobjective area‐to‐point problem is divided into a series of subproblems using Tchebycheff decomposition method. Next, all the subproblems are solved simultaneously using the modified binary quantum‐behaved PSO. Finally, a series of Pareto optimal solutions representing the conducting path structures are stepwise selected from the solutions to the subproblems. The features of the Pareto optimality‐based conducting paths and cooling performance are described. In addition, the effects of the conductive material quantity, optimization objective, heat sink location, and heat source distribution on the conducting path structure and cooling performance are discussed.

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“…[3][4][5] Topology optimization in heat transfer problem has been an active topic during the last 20 years. The review paper by Dbouk 6 summarizes well the researches for optimizing two-dimensional and three-dimensional thermal problems based on conductive, [7][8][9][10] convective, 11,12 and conjugate heat transfer. 13,14 In the heat conduction problem, there are three representative loads -internal thermal flux, heat generation, and heat transfer through conduction or convection boundaries.…”

Section: Introductionmentioning

confidence: 99%

Topology design optimization of conductive thermal problems subject to design-dependent load using density gradients

Yoon

Koo

2019

Advances in Mechanical Engineering

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In this article, a design sensitivity analysis method is developed for topology optimization of steady-state conductive thermal problems subject to design-dependent thermal loads using density gradients-based boundary detection. In a real physical heat conduction problem, a design-dependent thermal load through the convective boundary is an important factor; however, it is not easy to impose boundary conditions in heat conduction problem due to the difficulties of exact boundary representation. Here, the detection of convection boundaries is available by the density distinction between void and materials, which is similar to a gradient operator in image processing. Applying density gradients and Dirac delta function of densities, we impose a design-dependent load effect on thermal analysis and perform the design sensitivity analysis for topology optimization. At each optimization process, it is noted that the results of thermal analysis and the design sensitivities are influenced by the design-dependent thermal load. Through demonstrative numerical examples, the proposed approach using density gradients is proven to work yielding meaningful optimization results. The developed approach is applicable to the plant engineering and nuclear industries where thermo-mechanical coupling occurs inevitably by the thermal convection.

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Topology optimization for the conduction cooling of a heat-generating volume with orthotropic material

Cited by 27 publications

References 30 publications

Thermoelectric-based cooling system for high-speed motorized spindle II: Optimization and validation strategy

Thermoelectric-based cooling system for high-speed motorized spindle II: Optimization and validation strategy

Multiobjective optimization of area‐to‐point heat conduction structure using binary quantum‐behaved PSO and Tchebycheff decomposition method

Topology design optimization of conductive thermal problems subject to design-dependent load using density gradients

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