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Effect of in-flight particle characteristics on the coating properties of atmospheric plasma-sprayed 8 mol% Y2O3-ZrO2 electrolyte coating studying by artificial neural networks

机译:空中粒子特性对人工神经网络研究大气等离子喷涂8 mol%Y2O3-ZrO2电解质涂层涂层性能的影响

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摘要

In-flight particle characteristics (surface temperature and velocity upon impact) are among the most important parameters which influence the coating microstructures and properties in atmospheric plasma spraying (APS) process. The purpose of this paper is to study hydrogen fraction used as secondary plasma forming gas on the in-flight particle surface temperature and by extension on the coating microstructures of atmospheric plasma-sprayed 8 mol% yttria stabilized zirconia electrolyte coatings implementing in particular artificial neural networks (ANN). Then, the predicted in-flight particle characteristics were on the one hand compared to experimental values and on the other hand correlated to some of the coating structural attributes (porosity and gas specific permeability). The predicted results were in good accordance with the experimental data. Results showed that the H-2 flow rate had obvious influence on particle temperature and had almost no significant effect on particle velocity. Increasing the particle temperatures induced dense coating microstructure and improved the gas-tightness performance.
机译:飞行中的粒子特性(撞击时的表面温度和速度)是影响大气等离子喷涂(APS)过程中涂层微观结构和性能的最重要参数之一。本文的目的是研究在飞行中的颗粒表面温度上用作二次等离子体形成气体的氢馏分,并扩展到大气等离子体喷涂的8 mol%氧化钇稳定的氧化锆电解质涂层的涂层微观结构,这些涂层特别是在人工神经网络中实现的(ANN)。然后,一方面将预测的飞行中粒子特性与实验值进行比较,另一方面将其与某些涂层结构属性(孔隙率和气体比渗透率)相关。预测结果与实验数据吻合良好。结果表明,H-2流速对颗粒温度有明显影响,而对颗粒速度几乎没有显着影响。颗粒温度的升高引起致密的涂层微观结构,并改善了气密性。

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