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Laser texturing of AISI 304 stainless steel: experimental analysis and genetic algorithm optimisation to control the surface wettability

机译:AISI 304不锈钢激光纹理:实验分析和遗传算法优化控制表面润湿性

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摘要

This paper deals with an experimental investigation of roughness influence on contact angle measurements and proposes a genetic algorithm to identify an empirical regression model to combine roughness and contact angles. A ns-pulsed laser was adopted to ablate different patterns on the surfaces of AISI 304 samples. During the tests, number of repetitions, hatch distance, laser scan speed and laser scanning strategy were changed. To assess the effect of these parameters on the wettability, a multilevel factorial design was developed and tested. The analysis of variance was adopted to determine which and how the laser parameters influence the roughness and the contact angle. A significant change in the wettability is due to the produced textures on the sample surfaces, with contact angles in the range 30-110 degrees. The optimal regression model based on genetic algorithms was able to relate inputs and outputs with a mean error lower than 5%.
机译:本文涉及对接触角测量的粗糙度影响的实验研究,并提出了一种遗传算法来识别粗糙度和接触角的经验回归模型。 采用NS-脉冲激光在AISI 304样品的表面上烧蚀不同的图案。 在测试期间,更改了重复次数,舱口距离,激光扫描速度和激光扫描策略。 为了评估这些参数对润湿性的影响,开发并测试了多级因子设计。 采用对方差分析来确定激光参数对粗糙度和接触角的影响。 润湿性的显着变化是由于样品表面上产生的纹理,接触角在30-110度范围内。 基于遗传算法的最佳回归模型能够将输入和输出相关,平均误差低于5%。

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