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Application of support vector regression for optimization of vibration flow field of high-density polyethylene melts characterized by small angle light scattering

机译:通过小角度光散射特征的高密度聚乙烯熔体优化支持向量回归的应用

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摘要

In this paper, the vibration flow field parameters of polymer melts in a visual slit die are optimized by using intelligent algorithm. Experimental small angle light scattering (SALS) patterns are shown to characterize the processing process. In order to capture the scattered light, a polarizer and an analyzer are placed before and after the polymer melts. The results reported in this study are obtained using high-density polyethylene (HDPE) with rotation speed at 28 rpm. In addition, support vector regression (SVR) analytical method is introduced for optimization the parameters of vibration flow field. This work establishes the general applicability of SVR for predicting the optimal parameters of vibration flow field.
机译:本文通过智能算法优化了视觉狭缝模具中聚合物熔体的振动流场参数。实验小角度光散射(SAL)图案显示为表征加工过程。为了捕获散射光,在聚合物熔体之前和之后放置偏振器和分析仪。本研究报告的结果是使用高密度聚乙烯(HDPE)在28rpm的转速获得的结果。此外,还引入了支持向量回归(SVR)分析方法以优化振动流场的参数。这项工作建立了SVR的一般适用性,用于预测振动流场的最佳参数。

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