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.

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.

scholarly journals A Three-Dimensional Numerical and Multi-Objective Optimal Design of Wavy Plate-Fins Heat Exchangers

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 9
Author(s):  
Chao Yu ◽  
Xiangyao Xue ◽  
Kui Shi ◽  
Mingzhen Shao
Keyword(s):  
Heat Exchangers ◽  
Cfd Simulation ◽  
Three Dimensional ◽  
Basis Functions ◽  
Approximation Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Colburn Factor ◽  
Heat Exchange Efficiency

This paper presents a method for optimizing wavy plate-fin heat exchangers accurately and efficiently. It combines CFD simulation, Radical Basis Functions (RBF) with multi-objective optimization to improve the performance. The optimization of the Colburn factor j and the friction coefficient f is regarded as a multi-objective optimization problem, due to the existence of two contradictory goals. The approximation model was obtained by Radical Basis Functions, and the shape of the heat exchanger was optimized by multi-objective genetic algorithm (MOGA). The optimization results showed that j increased by 17.62% and f decreased by 20.76%, indicating that the heat exchange efficiency was significantly enhanced and the fluid structure resistance reduced. Then, from the aspects of field synergy and tubulence energy, the performance advantage of the optimized structure was further confirmed.

Multi-objective optimization of a recuperative gas turbine cycle using non-dominated sorting genetic algorithm

2011 ◽  
Vol 225 (8) ◽  
pp. 1041-1051 ◽  
Author(s):  
H Sayyaadi ◽  
H R Aminian
Keyword(s):  
Genetic Algorithm ◽  
Gas Turbine ◽  
Heat Exchangers ◽  
Mixed Integer ◽  
Design Stage ◽  
Tube Length ◽  
Pareto Optimal ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Gas Turbine Cycle

A regenerative gas turbine cycle with two particular tubular recuperative heat exchangers in parallel is considered for multi-objective optimization. It is assumed that tubular recuperative heat exchangers and its corresponding gas cycle are in design stage simultaneously. Three objective functions including the purchased equipment cost of recuperators, the unit cost rate of the generated power, and the exergetic efficiency of the gas cycle are considered simultaneously. Geometric specifications of the recuperator including tube length, tube outside/inside diameters, tube pitch, inside shell diameter, outer and inner tube limits of the tube bundle and the total number of disc and doughnut baffles, and main operating parameters of the gas cycle including the compressor pressure ratio, exhaust temperature of the combustion chamber and the air mass flowrate are considered as decision variables. Combination of these objectives anddecision variables with suitable engineering and physical constraints (including NO x and CO emission limitations) comprises a set of mixed integer non-linear problems. Optimization programming in MATLAB is performed using one of the most powerful and robust multi-objective optimization algorithms, namely non-dominated sorting genetic algorithm. This approach is applied to find a set of Pareto optimal solutions. Pareto optimal frontier is obtained, and a final optimal solution is selected in a decision-making process.

Multi-Objective Design Optimization of Topology and Performance of Branching Networks of Cooling Passages

2006 ◽  
Author(s):  
Maickel Gonzalez ◽  
Ramon J. Moral ◽  
Thomas J. Martin ◽  
Debasis Sahoo ◽  
George S. Dulikravich ◽  
...  
Keyword(s):  
Pressure Drop ◽  
Design Optimization ◽  
Total Pressure ◽  
Pareto Front ◽  
Total Heat ◽  
Pareto Optimal ◽  
Pumping Power ◽  
Multi Objective ◽  
Branching Networks ◽  
Number Of Branches

The objective of this study was to develop an automatic, self-sufficient, preliminary design algorithm for optimization of topologies of branching networks of internal cooling passages. The software package includes a random branches generator, a quasi 1-D thermo-fluid analysis code COOLNET, and multi-objective hybrid optimizer. COOLNET analysis software has the same trends as shown in an earlier publication depicting the results of a similar analysis code used by Pratt & Whitney. The hybrid multi-objective optimization code was verified against classical test cases involving multiple objectives. The number of branches per level was optimized in order to minimize coolant mass flow rate, total pressure drop, and maximize total heat removed. Optimization with four levels of fractal branching channel networks was tested. This optimization varied the number of branching channels extending from each single channel. COOLNET needed approximately forty iterations on average to analyze each configuration. The number of iterations necessary for each geometry depended on the number of branches per configuration. The hybrid multi-objective optimizer needed 500 iterations to create a converged Pareto front of optimized branching network configurations for the case of four branching levels. A population of 60 designs was used. The total number of function evluations analyzed was 30,000. The entire design optimization process takes approximately 3 hours on a single 3.0 GHz Pentium IV processor. In this work the total number of Pareto-optimal designs was 100. After finding the Pareto front points, the user has to decide which optimized cooling network configuration is the best for the desired application. It was demonstrated that this can be accomplished by utilizing Pareto-optimal solutions to create a curve representing pumping power vs. total heat removed and by observing which designs provide favorable break-even energy transfer. The magnitude of the ratio of heat transferred to total pressure drop and ratio of heat transfer to pumping power could be further increased by incorporating the channel’s hydraulic diameter, cross sectional area, lengths, and wall roughness as optimization variables.

scholarly journals Multi-objective optimization of CuO based organic Rankine cycle operated using R245ca

2019 ◽  
Vol 116 ◽  
pp. 00062 ◽  
Author(s):  
Parth Prajapati ◽  
Vivek Patel
Keyword(s):  
Heat Transfer ◽  
Thermal Efficiency ◽  
Heat Exchangers ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Working Fluid ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Source Fluid

The present work deals with multi objective optimization of nanofluid based Organic Rankine Cycle (ORC) to utilise waste heat energy. Working fluid considered for the study is R245ca for its good thermodynamic properties and lower Global Warming Potential (GWP) compared to the conventional fluids used in the waste heat recovery system. Heat Transfer Search (HTS) algorithm is used to optimize the objective functions which tends to maximize thermal efficiency and minimize Levelised Energy Cost (LEC). To enhance heat transfer between the working fluid and source fluid, nanoparticles are added to the source fluid. Application of nanofluids in the heat transfer system helps in maximizing recovery of the waste heat in the heat exchangers. Based on the availability and cost, CuO nanoparticles are considered for the study. Effect of Pinch Point Temperature Difference (PPTD) and concentration of nanoparticles in heat exchangers is studied and discussed. Results showed that nanofluids based ORC gives maximum thermal efficiency of 18.50% at LEC of 2.59 $/kWh. Total reduction of 7.11% in LEC can be achieved using nanofluids.

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