基于多目标遗传算法的舰载液冷板散热优化设计
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摘要
本文针对舰载液冷板的散热、压力损失等问题,采用变截面流道设计提高流场内的雷诺系数,以达到高效换热的目标。为提高计算效率,利用BP网络建立液冷板的散热函数关系。以设备关键器件最高温度与液冷板的循环压差为设计目标,以流道内的翘片截面的几何尺寸与变截面长度为设计变量,采用增加惩罚算子的NGSA-2算法进行优化计算,取得了液冷系统的pareto前沿解集,并依据实际使用环境,选取一组解进行了工程实施验证,此优化方法的应用对液冷板的设计具有重要的指导意义。
Aiming at the problem of marine cooling plate heat exchange and pressure loss, Using the variable cross-section channel design to improve the Reynolds coefficient, in order to achieve the goal of efficient heat exchanger. building functional relationships of liquid cooling plate by Using BP network, In order to improve the computational efficiency. With the highest temperature of key device and cooling plate circulation pressure as the design object, and the geometry size of the fin section in channel and the length of variable cross-section as design variables, No-dominated Sorting Genetic Algorithm with punishment operator is used to obtain Pareto front solution of the cooling system. According to the actual use environment, a set of solutions is selected for engineering verification,The using of this optimization method has an important guiding significance for design of cooling plate.
Aiming at the problem of marine cooling plate heat exchange and pressure loss, Using the variable cross-section channel design to improve the Reynolds coefficient, in order to achieve the goal of efficient heat exchanger. building functional relationships of liquid cooling plate by Using BP network, In order to improve the computational efficiency. With the highest temperature of key device and cooling plate circulation pressure as the design object, and the geometry size of the fin section in channel and the length of variable cross-section as design variables, No-dominated Sorting Genetic Algorithm with punishment operator is used to obtain Pareto front solution of the cooling system. According to the actual use environment, a set of solutions is selected for engineering verification,The using of this optimization method has an important guiding significance for design of cooling plate.
引文
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[2]雷俊禧,朱冬生,王长宏,等.电子芯片液体冷却技术研究进展[J].科学技术与工程,2008,8(15):4258-4263,4269.
[3]周海峰,邱颖霞,鞠金山.电子设备液冷技术研究进展[J].电子机械工程,2016,32(4):7-10,15
[4]薛梅.车载雷达户外液冷机箱设计与研究[C]//中国电子学会电子机械工程分会,中国电子学会电子机械工程分会2009年机械电子学学术会议论文集.2009:5.
[5]解金华,邹吾松.某机载S形深孔液冷板优化设计[J].电子机械工程,2014,30(4):1-4.
[6]尹本浩,蒋威威,何冰.液冷电子设备的冷板流阻匹配研究[J].电子机械工程,2013,29(2):1-4.
[7]李松,王皓,覃加念.微通道高热流换热分析研究[J].机械科学与技术,2012,30(3):384-387.
[8]田立新,文尚胜,黄伟明.大功率LED液冷热沉结构与换热效果研究[J].光学学报,2015,35(3):1-8.
[9]余建祖,高红霞,等.电子设备热设计及分析技术[M].北京:北京航空航天大学出版社,2008.
[10]RAJEEV S,KRISNAMOORTHY CS.Genetic algorithmbased methodology for design optimization of reinforced concrete frames[J].Computer-aided civil and infrasetrucer engineering,1999(20):208-212.
[11]闵惜琳,刘国华.人工神经网络结合遗传算法在建模和优化中的应用[J].计算机应用研究,2002(1):79-80.
[12]DEB K,AARAWAL S,PRATAP A,et al.A fast elitist nondominated sorting genetic algorithm for multi-objective optimization:NSGA-Ⅱ[C]//Proc of the Parallel Problem Solving form NatureⅥCon.Paria,2000.849-858.