Data for: Multi-objective heat transfer optimization of 2D helical microfins using NSGA-II

This is a Pareto archive from 10 generations of an NSGA-II algorithm seeking to minimize friction factor and maximize heat transfer for a micro-fin tube. The design parameters are fin height, helix angle, and number of starts. The flow rate and Reynolds number is held constant. The archive consists of 80 non-dominated individuals with geometry and corresponding friction factor and heat transfer.

本数据集为针对微翅片管（micro-fin tube）开展的非支配排序遗传算法II（NSGA-II）运行10代后得到的帕累托存档集（Pareto archive），该算法目标为最小化摩擦因子（friction factor）并最大化传热性能。本次实验的设计参数为翅片高度、螺旋升角与头数，且流速与雷诺数（Reynolds number）保持恒定。该存档集共包含80个非支配个体，每个个体均附带几何构型信息以及对应的摩擦因子与传热性能数据。