Aiming at the high computational costs of the current multi-source X-ray radiation numerical simulations, a multi-source X-ray evaluation method based on a synergistic effect model is studied. First, based on the advantage of the low computational cost of single-source X-ray radiation numerical simulations, a hierarchical Gaussian process model is used to construct a superimposed single-source numerical simulation data fusion model. Second, by constructing composite correlation functions, the data fusion ability of the Gaussian process model is improved. The unknown parameters in the data fusion evaluation model are solved with the help of the Markov chain Monte Carlo method and a nonlinear optimization algorithm. Based on the obtained sampling values of the unknown parameters, an approximate solution method for the estimated value of the superimposed single-source X-ray radiation numerical simulations with unknown input conditions is given. Then a synergistic effect model is constructed based on the established linear regression surrogate model. The synergistic evaluation of multi-source X-ray radiation tests based on single-source X-ray radiation numerical simulation superimposed test data is studied. Finally, carbon-fiber-reinforced polymer experiments show the proposed method in better than existing Kriging methods, for prediction of multi-source X-ray radiation data.

中文翻译：

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基于协同效应模型的碳纤维增强高分子材料抗辐射性能评价方法


针对当前多源X射线辐射数值模拟计算成本高的问题，该文研究了一种基于协同效应模型的多源X射线评价方法。首先，基于单源X射线辐射数值模拟计算成本低的优势，采用分层高斯过程模型构建叠加单源数值模拟数据融合模型;其次，通过构建复合相关函数，提高了高斯过程模型的数据融合能力;数据融合评价模型中的未知参数借助马尔可夫链蒙特卡洛方法和非线性优化算法进行求解。基于得到的未知参数采样值，给出了输入条件未知的叠加单源X射线辐射数值模拟估计值的近似求解方法。然后，基于建立的线性回归代理模型构建协同效应模型。研究了基于单源 X 射线辐射数值模拟叠加测试数据的多源 X 射线辐射测试的协同评价。最后，碳纤维增强聚合物实验表明，所提出的方法在预测多源 X 射线辐射数据方面优于现有的 Kriging 方法。