A dimension-reduction based maximum entropy method for probabilistic ultimate load prediction in composite corrugated sandwich panels. (July 2022) - Li, Feng; Li, Hongfeng; Wei, Tonghui; Zhao, Heng
Abstract: Composite sandwich structures with excellent properties are extensively applied in aerospace. However, the mechanical properties of composite sandwich structures are variable and uncertain due to materials, processes, and processing technologies. In this study, a probability prediction method of ultimate load value in composite corrugated sandwich panels (CCSP) is proposed by combining the dimension reduction method (DRM) and the maximum entropy method (MEM). This new method is used to study the influence of fiber parameter uncertainty on the ultimate load value of CCSP. First, an n -dimensional response function about the ultimate load of CCSP is reduced in dimension. Then the first four statistical moments of this function are obtained by Taylor expansion. Finally, through fitting with MEM, the probability density function about the ultimate load of CCSP is obtained. To verify the correctness of the new method, a comparative analysis is carried out with the Monte Carlo simulation (MCS). The errors of the results are all less than 6.4%, indicating the new method can effectively predict the ultimate load value of CCSP with probability and greatly reduce finite element calculation time. The sensitivity of the ultimate load value of CCSP to basic input variables is also studied.