摘要
基于遗传算法,分别以火积耗散数和总成本为目标函数,对ADS的液态LBE-氦气换热器进行多参数优化。结果表明,两种优化方法使换热器有效度分别提高10.5%和3.8%,总成本分别降低5.9%和27.0%,但优化过程分别以增加传热面积和牺牲传热性能为代价。综合对比两种优化方法得到的换热器性能、成本消耗、收益等因素,发现以火积耗散数为目标函数的优化方法更具优势。
The multi-parameter optimization of the liquid LBE-helium heat exchanger in ADS was conducted by genetic algorithm with entransy dissipation number and total cost as objective functions.The results show that the effectiveness of heat exchanger increases by 10.5% and 3.8%,and the total cost reduces by 5.9% and 27.0%respectively with two optimization methods.Nevertheless,the optimization processes trade off increasing heat transfer area and decreasing heat transfer effectiveness respectively against achieving optimization targets.By comprehensively considering heat exchanger performance and cost-benefit,the optimization method with entransy dissipation number as the objective function is found to be more advantageous.
出处
《原子能科学技术》
EI
CAS
CSCD
北大核心
2015年第7期1266-1272,共7页
Atomic Energy Science and Technology
基金
中国科学院战略性先导科技专项资助项目(XDA03010500)
关键词
ADS
遗传算法
换热器优化
火积耗散数
总成本
ADS
genetic algorithm
heat exchanger optimization
entransy dissipation number
total cost
