紧凑型换热器内流动与换热特性的数值模拟与优化研究

发布时间：2021-07-22 07:42

　　紧凑型换热器较传统换热器具有相对较大的换热面积和体积比,不仅能够大幅减少换热器尺寸、质量从而降低制造成本,还具有更高的换热效率。紧凑型换热器包括管翅式和板翅式两种。在紧凑换热器内,气体流动侧较低的换热系数往往限制换热器的整体换热性能,因而寻求新方法来改善气侧换热性能是十分重要的。基于上述目的,一种与一次表面相连的二次扩展表面如肋片或涡发生器等形式被设计提出,扩展表面能够提高换热面积并通过扰乱流场来强化近壁和核心流区域的换热。由于涉及参数数目繁多,考虑全局所有参数的紧凑型换热器设计十分复杂,而且紧凑型换热器的优化常常涉及启发式计算方法。在本文的第一部分,一种多目标优化的方法被提出来,这种方法基于并结合差分进化算法、遗传算法和自适应模拟退火算法（复合DE-GA-ASA算法）。这种复合DE-GA-ASA算法旨在通过结合三种基础算法的长处提高算法整体的健壮性。采用基准问题来检验这种算法的性能,而后将其成功应用到锯齿型板翅式换热器的优化设计中。研究结果表明这种复合DE-GA-ASA算法能够有效实现板翅式换热器的优化设计。此外,还探究了板翅式换热器中各参数对于优化设计的影响。研究中考虑的板翅式换热... 

【文章来源】：浙江大学浙江省 211工程院校 985工程院校 教育部直属院校

【文章页数】：133 页

【学位级别】：博士

【文章目录】：
Abstract
摘要
Nomenclature
1. Introduction
    1.1. Heat transfer enhancement techniques
    1.2. Review on simulation and optimization of compact heat exchangers
        1.2.1. Optimization of plate-fin heat exchanger
        1.2.2. Combining numerical simulation and optimization
    1.3. Motivations and objectives
    1.4. Overview and outline
2. Numerical and optimization methods
    2.1. Multi-objective optimization method
        2.1.1 Optimization algorithms
        2.1.2. Combined DE-GA-ASA
    2.2. Numerical method
        2.2.1. Components of numerical solution method
        2.2.2 Finite Volume (FV) method
        2.2.3 Numerical modeling of Turbulence
    2.3. Combining numerical simulation and optimization method
        2.3.1. Design variables and objective functions
        2.3.2. Artificial neural network (ANN)
        2.3.3. Combining CFD, ANN and MOA
    2.4. Decision making criteria
3. Optimal design of plate-fin heat exchanger
    3.1. Mathematical modeling
        3.1.1. Thermal modeling
        3.1.2. Economic modeling
    3.2. Design of plate-fin heat exchanger by combined DE-GA-ASA algorithm
    3.3. Validation
    3.4. Case study
        3.4.1. Objective functions, design parameters and constraints
    3.5. Resulsts and discussions
        3.5.1. Optimal parameters investiagation
        3.5.2. Optimum parameters
        3.5.3. Selection of final optimum solution
    3.6. Summary
4. Optimal configuration of vortex generator in a plate-fin channel
    4.1. Model description
        4.1.1. Physical model
        4.1.2. Numerical model and boundary conditions
    4.2. Parameters definition and mesh sensitivity
    4.3. Results and discussions
        4.3.1. Numerical validation
        4.3.2. Flow structure and heat transfer analysis
        4.3.3. Flow loss analysis
        4.3.4. Optimization results
    4.4. Summary
5. Numerical study and optimization of attack angle of vortex generator andcorrugation height in wavy fin-and-tube heat exchanger
    5.1. Model description
        5.1.1. Physical model
        5.1.2. Governing equations and boundary conditions
    5.2. Parameters definition
    5.3. Mesh independence and validation model
    5.4. Results and discussions
        5.4.1. Flow pattern and temperature contours
        5.4.2. Heat transfer and fluid flow performance
        5.4.3. Optimization results
    5.5. Summary
6. Experimental and numerical study on louvered fin and flat tube heat exchangers
    6.1. Experimental test facility
        6.1.1. Test heat exchangers
        6.1.2. Test conditions
    6.2. Experimental results and discussions
    6.3. Numerical analysis
        6.3.1. Governing equations and boundary condtitions
        6.3.2. Numerical method
        6.3.3. Performance parameters
        6.3.4. Numerical results and discussions
    6.4. Summary
7. Conclusions and suggestions
    7.1. Conclusions
    7.2. Suggestions
References
Appendix A. Pseudo codes for DE, GA and ASA
Appendix B. Weights and biases (plate-fin channel)
Appendix C. Weigts and biases (Wavy finned-tube exchanger)
Acknowledgement
Curriculum vitae


【参考文献】：
期刊论文
[1]Improved NSGA-Ⅱ Multi-objective Genetic Algorithm Based on Hybridization-encouraged Mechanism[J]. Sun Yijie*,Shen Gongzhang School of Automation Science and Electrical Engineering,Beijing University of Aeronautics and Astronautics,Beijing 100191,China.  Chinese Journal of Aeronautics. 2008(06)



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