Multi-objective Design Optimization of Branching, Multifloor, Counterflow Microheat Exchangers

2014 ◽  
Vol 136 (10) ◽  
Author(s):  
Abas Abdoli ◽  
George S. Dulikravich
Keyword(s):  
Conjugate Heat Transfer ◽  
Flow Direction ◽  
Heat Removal ◽  
Heat Transfer Analysis ◽  
Multi Objective Optimization ◽  
Pumping Power ◽  
Power Requirement ◽  
Multi Objective ◽  
Removal Capacity ◽  
Temperature Nonuniformity

Heat removal capacity, coolant pumping power requirement, and surface temperature nonuniformity are three major challenges facing single-phase flow microchannel compact heat exchangers. In this paper multi-objective optimization has been performed to increase heat removal capacity, and decrease pumping power and temperature nonuniformity in complex networks of microchannels. Three-dimensional (3D) four-floor configurations of counterflow branching networks of microchannels were optimized to increase heat removal capacity from surrounding silicon substrate (15 × 15 × 2 mm). Each floor has four different branching subnetworks with opposite flow direction with respect to the next one. Each branching subnetwork has four inlets and one outlet. Branching patterns of each of these subnetworks could be different from the others. Quasi-3D conjugate heat transfer analysis has been performed by developing a software package which uses quasi-1D thermofluid analysis and a 3D steady heat conduction analysis. These two solvers were coupled through their common boundaries representing surfaces of the cooling microchannels. Using quasi-3D conjugate analysis was found to require one order of magnitude less computing time than a fully 3D conjugate heat transfer analysis while offering comparable accuracy for these types of application. The analysis package is capable of generating 3D branching networks with random topologies. Multi-objective optimization using modeFRONTIER software was performed using response surface approximation and genetic algorithm. Diameters and branching pattern of each subnetwork and coolant flow direction on each floor were design variables of multi-objective optimization. Maximizing heat removal capacity, while minimizing coolant pumping power requirement and temperature nonuniformity on the hot surface, were three simultaneous objectives of the optimization. Pareto-optimal solutions demonstrate that thermal loads of up to 500 W/cm2 can be managed with four-floor microchannel cooling networks. A fully 3D thermofluid analysis was performed for one of the optimal designs to confirm the accuracy of results obtained by the quasi-3D simulation package used in this paper.

Multi-Objective Design Optimization of Multi-Floor, Counterflow Micro Heat Exchangers

2013 ◽  
Author(s):  
Abas Abdoli ◽  
George S. Dulikravich
Keyword(s):  
Pressure Drop ◽  
Heat Exchangers ◽  
Flow Direction ◽  
Heat Removal ◽  
Heat Transfer Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Removal Capacity ◽  
Branching Networks ◽  
Analysis Package

Heat removal capacity, coolant pumping pressure drop and surface temperature non-uniformity are three major challenges facing single-phase flow microchannel compact heat exchangers. In this paper multi-objective optimization has been performed to increase heat removal capacity, and decrease pressure drop and temperature non-uniformity in single-flow microchannels. Three-dimensional (3D) 4-floor branching networks have been applied to increase heat removal capacity of a microchannel from silicon substrate (15×15×2 mm). Each floor has four different branching sub-networks with opposite flow direction with respect to the next one. Each branching network has four inlets and one outlet. However, branching patterns of each of these sub-networks could be different from the others. Conjugate heat transfer analysis has been performed by developing a software package which uses quasi-1D thermo-fluid analysis and a 3D steady heat conduction analysis. These two solvers are coupled through their common boundaries representing surfaces of the cooling microchannels. Using quasi-1D solver significantly decreases computing time and its results are in good agreement with 3D Navier-Stokes equations solver for these types of application. The analysis package is capable of generating 3D branching networks with random topologies. 1341 random cooling networks were simulated using this analysis package. Multi-objective optimization using modeFrontier software was performed using response surface approximation and genetic algorithm. Diameters and branching pattern of each sub-network and coolant flow direction on each floor were design variables of multi-objective optimization. Maximizing heat removal capacity, minimizing pressure drop and temperature non-uniformity on the hot surface were three simultaneous objectives of the optimization. Pareto-optimal solutions demonstrate that thermal loads of up to 500 W/cm2 can be managed with 3D 4-floor microchannel cooling networks.

Optimization of 3D Branching Networks of Microchannels for Microelectronic Device Cooling

2010 ◽  
Author(s):  
George S. Dulikravich ◽  
Thomas J. Martin
Keyword(s):  
Heat Transfer ◽  
Conjugate Heat Transfer ◽  
Stokes Equations ◽  
Heated Surface ◽  
Heat Diffusion ◽  
Heat Transfer Analysis ◽  
Pumping Power ◽  
Multi Objective ◽  
Branching Networks ◽  
3D Network

The aim of this work is to present a methodology to develop cost-effective thermal management solutions for microelectronic devices, capable of removing maximum amount of heat and delivering maximally uniform surface temperature distributions. The topological and geometrical characteristics of multiple-story three-dimensional branching networks of microchannels were developed using multi-objective optimization. The design variables which will be subject to optimization in this analysis are the geometric parameters of the microchannel network, i.e. the number of network floors in a 3D network, the amount of branching levels per floor, the connectivity of the cooling channels, their cross-sectional areas and lengths. A conjugate heat transfer analysis software package (CHETSOLP) and an automatic 3D microchannel network generator (3DBNGEN) were developed and coupled with a multi-objective particle-swarm optimization (MOPSO) algorithm with a goal of creating a design tool for 3D networks of optimized coolant flow channels. Numerical algorithms in the conjugate heat transfer solution package include a quasi-1D thermo-fluid solver (COOLNET) and a 3D steady heat diffusion solver, which were validated against results from high-fidelity Navier-Stokes equations solver and analytical solutions for basic fluid dynamics test cases. The conjugate heat transfer solution is achieved by simultaneous prediction of the quasi-1D internal flow-field in the microchannel network and 3D internal temperature field in the solid substrate [1]. Minimization of the pumping power requirement and maximization of total heat removal subject to temperature uniformity (at the heated surface) were the objectives. Pareto-optimal solutions demonstrate that thermal loads of up to 400 W/cm2 can be managed with 3D multi-floor microchannel networks, with pumping power requirements that are up to 50% lower with respect to pumping power requirements in currently used high-performance cooling technologies, such as jet impingement and hybrid impingement-microchannel flow.

Performance Analysis of Single-Phase Space Thermal Radiators and Optimization through Taguchi-Neuro-Genetic Approach

2021 ◽  
pp. 1-18
Author(s):  
P B Chiranjeevi ◽  
Ashok V ◽  
K. Srinivasan ◽  
Thirumalachari Sundararajan
Keyword(s):  
Heat Transfer ◽  
Performance Analysis ◽  
Conjugate Heat Transfer ◽  
Computational Time ◽  
Maximum Diameter ◽  
Genetic Approach ◽  
Pumping Power ◽  
Power Requirement ◽  
Space Applications ◽  
Heat Rejection

Abstract In the thermal management of spacecraft, space thermal radiators play a vital role as heat sinks. A serial radiator with proven advantages in ground applications is proposed and analyzed for space applications. From the performance analysis, specific heat rejection of serial radiator is found to be higher than parallel radiator by 80% for maximum diameter of tube, 47% for maximum thickness of fin, and 75% for maximum pitch of tubes under consideration. Also, serial radiator requires four times higher pumping power than parallel radiator with geometric parameters and a maximum mass flow rate under consideration. In serial radiators, the cross conduction between the fins has a significant effect on its thermal performance. Thus, conjugate heat transfer simulations and optimization operations are to be performed iteratively to optimize the serial radiator, which is computationally costly. To reduce the computational time, Artificial Neural Network is trained using conjugate heat transfer simulations data and combined with the genetic algorithm to perform optimization. Taguchi's orthogonal arrays provided the partial fraction of conjugate heat transfer simulations set to train the ANN. Taguchi-Neuro-Genetic approach, a process that combines the features of three powerful techniques in different optimization phases, is used to optimize both parallel and serial radiators. The optimization aims to obtain a configuration that provides the lowest mass and lowest pumping power requirement for given heat rejection. Optimization results show that the conventional parallel radiator is about 20% heavier and requires about 35% more pumping power than the proposed serial radiator.

Optimized Multi-Floor Throughflow Micro Heat Exchangers

2013 ◽  
Author(s):  
Abas Abdoli ◽  
George S. Dulikravich
Keyword(s):  
Heat Transfer ◽  
Conjugate Heat Transfer ◽  
Stokes Equations ◽  
Flow Direction ◽  
Computing Time ◽  
Heat Transfer Analysis ◽  
Maximum Temperature ◽  
Fluid Analysis ◽  
Response Surface Approximations ◽  
Hot Surface

Multi-floor networks of straight-through liquid cooled microchannels have been investigated by performing conjugate heat transfer in a silicon substrate of size 15×15×1 mm. Two-floor and three-floor cooling configurations were analyzed with different numbers of microchannels on each floor, different diameters of the channels, and different clustering among the floors. Thickness of substrate was calculated based on number of floors, diameter of floors and vertical clustering. Direction of microchannels on each floor changes by 90 degrees from the previous floor. Direction of flow in each microchannel is opposite of the flow direction in its neighbor channels. Conjugate heat transfer analysis was performed by developing a software package which uses quasi-1D thermo-fluid analysis and a 3D steady heat conduction analysis. These two solvers are coupled through their common boundaries representing surfaces of the cooling microchannels. Using quasi-1D solver significantly decreases overall computing time and its results are in good agreement with 3D Navier-Stokes equations solver for these types of application. Multi-objective optimization with modeFRONTIER software was performed using response surface approximations and genetic algorithm. Maximizing total amount of heat removed, minimizing coolant pressure drop, minimizing maximum temperature on the hot surface, and minimizing non-uniformity of temperature on the hot surface were four simultaneous objectives of the optimization. Pareto-optimal solutions demonstrate that thermal loads of 800 W cm−2 can be effectively managed with such multi-floor microchannel cooling networks. Two-floor microchannel configuration was also simulated with 1,000 W cm−2 uniform thermal load and shown to be feasible.

Multi-Objective Optimization of the Impingement-Film Cooling Structure of a Gas Turbine Endwall Using Conjugate Heat Transfer Simulations

2017 ◽  
Vol 10 (2) ◽  
Author(s):  
Zhongran Chi ◽  
Haiqing Liu ◽  
Shusheng Zang
Keyword(s):  
Heat Transfer ◽  
Film Cooling ◽  
Conjugate Heat Transfer ◽  
Pareto Front ◽  
Parametric Design ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Lift Off ◽  
Optimization Search

This paper discusses the approach of cooling design optimization of a high-pressure turbine (HPT) endwall with applied 3D conjugate heat transfer (CHT) computational fluid dynamics (CFD). This study involved the optimization of the spacing of impingement jet array and the exit width of shaped holes, which are different for each cooling cavity. The optimization objectives were to reduce the wall-temperature level and to increase the aerodynamic performance. The optimization methodology consisted of an in-house parametric design and CFD mesh generation tool, a CHT CFD solver, a database of CFD results, a metamodel, and an algorithm for multi-objective optimization. The CFD tool was validated against experimental data of an endwall at CHT conditions. The metamodel, which could efficiently estimate the optimization objectives of new individuals without CFD runs, was developed and coupled with nondominated sorting genetic algorithm II (NSGA II) to accelerate the optimization process. Through the optimization search, the Pareto front of the problem was found in each iteration. The accuracy of metamodel with more iterations was improved by enriching database. But optimal designs found by the last iteration are almost identical with those of the first iteration. Through analyzing extra CFD results, it was demonstrated that the design variables in the Pareto front successfully reached the optimal values. The optimal pitches of impingement arrays could be decided accommodating the local thermal load while avoiding jet lift-off of film coolant. It was also suggested that cylindrical film holes near throat should be beneficial to both aerodynamic and cooling performances.

Multi-Objective Optimization of the Impingement-Film Cooling Structure of a HPT Endwall Using Conjugate Heat Transfer CFD

2016 ◽  
Author(s):  
Zhongran Chi ◽  
Haiqing Liu ◽  
Shusheng Zang
Keyword(s):  
Heat Transfer ◽  
Genetic Algorithm ◽  
Wall Temperature ◽  
Conjugate Heat Transfer ◽  
Pareto Front ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Multi Objective ◽  
Lift Off ◽  
Optimization Search

This paper discusses the approach of cooling design optimization of a HPT endwall with 3D Conjugate Heat Transfer (CHT) CFD applied. This study involved the optimization of the spacing of impingement jet array and the exit width of shaped holes, which were different for each cooling cavity. The optimization objectives were to reduce the wall temperature level and also to increase the aerodynamic performance of the gas turbine. The optimization methodology consisted of an in-house parametric design & CFD mesh generation tool, a CHT CFD solver, a database of wall temperature distributions, a metamodel, and a genetic algorithm (GA) for evolutionary multi-objective optimization. The CFD tool was validated against experimental data of an endwall at CHT conditions. The metamodel, which could efficiently predict the aerodynamic loss and the wall temperature distribution of a new individual based on the database, was developed and coupled with Non-dominated Sorting Genetic Algorithm II (NSGA-II) to accelerate the optimization process. Through optimization search, the Pareto front of the problem was found costing only tens of CFD runs. By comparing with additional CFD results, it was demonstrated that the design variables in the Pareto front successfully reached the optimal values. The optimal spacing of each impingement array was decided accommodating the local thermal load while avoiding jet lift-off of film coolant. It was also suggested that using cylindrical film holes near throat could benefit both aerodynamics and cooling.

Multi-Objective Optimization of Micro Pin-Fin Arrays for Cooling of High Heat Flux Electronics

2015 ◽  
Author(s):  
Sohail R. Reddy ◽  
George S. Dulikravich
Keyword(s):  
Heat Flux ◽  
Cross Section ◽  
High Heat ◽  
Heat Transfer Analysis ◽  
Maximum Temperature ◽  
High Heat Flux ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Pin Fin ◽  
Pin Fin Arrays

The thermal management capability of various candidates of micro-pin fin arrays is investigated. An integrated circuit having a footprint of 4 × 3 mm with micro-pin fin array having circular, airfoil and convex cross-section is considered. The three pin fin cross-sections along with the cooling schemes are optimized to handle a uniform heat flux of 500 W/cm2 applied to the top surface of the electronic chip. A fully three-dimensional, steady-state conjugate heat transfer analysis was performed on each cooling configuration and a constrained multi-objective optimization was carried out for each of the three micro-pin fin shapes to find pin fin designs configurations capable of cooling such high heat fluxes. The design variables were the geometric parameters defining each pin fin cross section, height of the chip and inlet speed of the coolant. The two simultaneous objectives were to minimize maximum temperature and pressure drop (pumping power), while keeping the maximum temperature below 85°C. A response surface was constructed for each objective function and was coupled with a genetic algorithm to arrive at a Pareto frontier of the best trade-off solutions. Stress-deformation analysis incorporating the hydrodynamic and thermal loads was performed on each of the three optimized configurations. The maximum displacement was found to be on the nano-level, and the Von-Mises stress for each configuration was found to be significantly below the yield strength of Silicon.

Sign in / Sign up

Export Citation Format

Share Document