This paper addresses the development of an inversion scheme based on Markov Chain Monte Carlo integrating process modelling with monitoring data for the real-time probabilistic estimation of unknown stochastic input parameters such as heat transfer coefficient and resin thermal conductivity and process outcomes during the manufacture of fibrous composites materials. Kriging was utilized to build an efficient surrogate model of the composite curing process based on finite element modelling. The utilization of an inverse scheme with real-time temperature monitoring driving the estimation of process parameters during manufacture results in real-time probabilistic prediction of process outcomes.

中文翻译：

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不确定条件下复合材料固化传热问题的实时逆解

本文讨论了基于马尔可夫链蒙特卡罗集成过程建模与监测数据的反演方案的开发，以实时概率估计未知的随机输入参数，如传热系数和树脂热导率以及纤维制造过程中的过程结果。复合材料。克里金法被用来建立一个基于有限元建模的复合材料固化过程的有效替代模型。使用具有实时温度监控的逆向方案在制造期间驱动过程参数的估计导致过程结果的实时概率预测。