Predictive Analysis of Water Wettability and Corrosion Resistance of Secondary AlSi10MnMg(Fe) Alloy Manufactured by Vacuum-Assisted High Pressure Die Casting
Amir Kordijazi, Swaroop K. Behera, Arthur Jamet, Ana Isabel Fernández-Calvo, Pradeep Rohatgi
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引用次数: 0
Abstract
In the present study, a predictive analysis was performed to investigate the effect of droplet size, section size and type of the primary and secondary AlSi10MnMg alloys manufactured by vacuum-assisted high pressure die casting on wettability of the cast samples with water, since wettability influences corrosion resistance. Additionally, corrosion resistance of samples was studied using a linear polarization experiment. Contact angle (CA) measurements were performed on the specimens using a goniometer. An Artificial Neural Network was then developed to predict the contact angle values as a function of the predictor variables. The developed model was able to predict unseen CA values with excellent accuracy with the Pearson correlation coefficient of 0.96 between the predicted and observed CA. The modeling results show that the type of alloy (primary or secondary) is the most significant factor affecting CA, where almost 80% of CA variation is the result of changing the type of alloy. Confocal microscopy images demonstrate that this is attributed to the change in the heterogeneity of the surface, which affects contact angle values. The corrosion studies reveal that corrosion resistance is dependent on the type of alloy and surface roughness. The primary alloy possesses more corrosion resistance than the secondary alloy. This is due to the larger fraction of intermetallic compounds in the microstructure of the secondary alloy, which serve as galvanic sites in the corrosion reaction accelerating corrosion rate. Moreover, the non-uniformity induced by larger surface roughness is detrimental to the corrosion resistance of the samples. These results indicate that the data-driven approach used in this research is very promising not only to predict the performance, but also to optimize and design high-performance corrosion resistant surfaces of cast aluminum alloys.
由于润湿性会影响耐腐蚀性,因此本研究进行了预测分析,以研究通过真空辅助高压压铸制造的一级和二级 AlSi10MnMg 合金的液滴尺寸、截面尺寸和类型对铸样与水的润湿性的影响。此外,还利用线性极化实验研究了样品的耐腐蚀性。使用测角仪对试样进行了接触角(CA)测量。然后开发了一个人工神经网络来预测作为预测变量函数的接触角值。所开发的模型能够非常准确地预测未见的接触角值,预测值与观测值之间的皮尔逊相关系数为 0.96。建模结果表明,合金类型(一次合金或二次合金)是影响 CA 的最重要因素,几乎 80% 的 CA 变化都是由改变合金类型造成的。共聚焦显微镜图像表明,这是由于表面异质性的变化影响了接触角值。腐蚀研究表明,耐腐蚀性取决于合金类型和表面粗糙度。初级合金比次级合金具有更强的耐腐蚀性。这是因为二次合金的微观结构中金属间化合物的比例较大,在腐蚀反应中可作为电偶位点,从而加快腐蚀速度。此外,较大的表面粗糙度引起的不均匀性也不利于样品的耐腐蚀性。这些结果表明,本研究采用的数据驱动方法不仅在预测性能方面大有可为,而且在优化和设计铸铝合金的高性能耐腐蚀表面方面也大有可为。
期刊介绍:
The International Journal of Metalcasting is dedicated to leading the transfer of research and technology for the global metalcasting industry. The quarterly publication keeps the latest developments in metalcasting research and technology in front of the scientific leaders in our global industry throughout the year. All papers published in the the journal are approved after a rigorous peer review process. The editorial peer review board represents three international metalcasting groups: academia (metalcasting professors), science and research (personnel from national labs, research and scientific institutions), and industry (leading technical personnel from metalcasting facilities).