One Convenient Method to Calculate Performance and Optimize Configuration for Annular Radiator Using Heat Transfer Unit Simulation

Xu, Zhe; Guo, Yingqing; Yang, Huarui; Mao, Haotian; Yu, Zongling; Li, Rui

doi:10.3390/en13010271

Cited by 8 publications

(7 citation statements)

References 44 publications

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“…CFD simulation technology is adopted to obtain heat transfer capacity and air-side pressure drop of AR using ANSYS commercial software. In order to reduce the burden of simulation which will cause high computing resource requirements and large time consumption, HTU which is used in Xu et al 29 is also used in this method. As shown in Figure 1, two kinds of HTUs in total, which are HTU A and HTU B, can be obtained by dividing AR according to the symmetrical axis and the central angle of annular substrate finned area.…”

Section: Simulation Methodsmentioning

confidence: 99%

“…The method of performance analysis used in most of the previous researches is emulating a heat exchanger as a whole directly, which is not realistic for AR simulation as the mesh number will be extremely huge in this way. In the research of Xu et al, 29 one kind of heat transfer unit (HTU) of AR was proposed and one theoretical arithmetic method combining with HTU CFD simulation was adopted to predict heat transfer capacity and air-side pressure drop of AR. In addition, number of fins in circumferential direction (NFCD) and fin height (FH) of AR were optimized to increase the heat transfer capacity and decrease the air-side pressure drop by NSGA-II.…”

Section: Introductionmentioning

confidence: 99%

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Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Guo

Yang³

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR.

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Section: Simulation Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Guo

Yang³

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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“…This kind of optimization has infinite amount of good solution if it would be on the Pareto front [19]. For multi objective optimization Pareto diagram is a highly preferred option [19][20][21][22][23][24].…”

Section: Pareto-vector Length Optimizationmentioning

confidence: 99%

Heat Sink Shape and Topology Optimization with Pareto-Vector Length Optimization for Air Cooling

Szodrai

2020

Energies

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Localized air cooling can be used for various purposes, e.g.: electronic equipment cooling, and air conditioning. The paper emphasizes that the connection between the air-flow and cooling has to fulfill a contradictory requirement (low pressure loss and effective cooling). The cooling and the pressure loss are dependent on the moisture content of the air flow. In the study, heat sink geometries were examined at various fresh air relative humidity, temperature and flowrates with commercially available simulation software (Ansys Fluent). The most favorable option was chosen by Pareto-vector length optimization. For optimization, head loss coefficient and temperature coefficient were used. Firstly, 108 cases were made to evaluate the sensitivity of the optimization parameters. Secondly, on 40 finned heat sinks with different fin width and quantity optimization were made. Thirdly, a prototype was made from the favorite solution where the performance was evaluated. For the measurement two type: TEC1-12706 thermoelectric cooling devices (TEC) were used for cooling. The difference between the measured and the modelled cooled air temperatures was 3%.

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“…The applicability of finned tubes to a large condenser system with a bundle layout was verified. Xu et al [9] computed the heat transfer capacity and air-side pressure drop of an annular radiator (AR) using a combined heat transfer unit (HTU) simulation and plate-and-fin heat exchanger (PFHX) performance calculation formulas. Results indicated that their optimization method could provide significant guidance for AR design.…”

Section: Introductionmentioning

confidence: 99%

Optimal Shape of Non-Linear Partially Wet Annular Fins for Maximum Efficiency

Huang

Chung

2021

Energies

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Heat exchangers with annular finned-tube type and partially wetted condition are utilized widely in engineering systems, such as air-conditioning systems and refrigeration systems. In addition, the physical properties of fin materials should be considered as functions of temperature in reality and thus become a non-linear problem. Based on the above two conditions, an optimal partially wet annular fin design problem, with temperature-dependent thermal properties of the fin, to yield optimal fin efficiency was investigated in the present work, which has not been examined previously and it is the novelty of this study. An iterative regularization algorithm using the conjugate gradient method (CGM) is considered as the optimization tool based on the desired fin efficiency under a fixed fin volume constraint. The partially wet annular fin condition can result if the relative humidity of surrounding air is between 80 and 90%. Finally, the optimal fin shape, with the highest computed efficiency among examined fins under identical operational conditions, can be obtained. It is found that when the Biot numbers for ambient air (Bia) and relative humidity (f) increased, the optimum computed fin efficiency and interfacial radius between wet and dry fin domains (rwd) will be increased, and the estimated optimum fin shape also changed. However, the shape of optimal fin remained approximately unchanged when the Biot numbers for the inner tube (Bii), the thermal conductivities of the tube (kw) and fin (kf) varied. It reveals that Bii, kw and kf have an insignificant influence on the optimal shape of the annular fin in a partially wet condition.

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One Convenient Method to Calculate Performance and Optimize Configuration for Annular Radiator Using Heat Transfer Unit Simulation

Cited by 8 publications

References 44 publications

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Performance calculation and configuration optimization of annular radiator by heat transfer unit simulation and a multi-objective genetic algorithm

Heat Sink Shape and Topology Optimization with Pareto-Vector Length Optimization for Air Cooling

Optimal Shape of Non-Linear Partially Wet Annular Fins for Maximum Efficiency

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