Uncertainty analysis of residual strength of porous laminates in hot and humid environment based on polynomial chaos expansion
Source abstract
Abstract
In view of the fact that composite material structures will be affected by multi-source uncertainty factors during use, a new method for predicting the uncertainty of the residual strength of porous laminates in hot and humid environments is proposed based on the PCE method. The influence of different hot and humid environments on the uncertainty of residual strength of porous composite laminates was studied through experimental and numerical methods. The elastic mechanical parameters of composite materials are used as random variables, and the expression of a generalized polynomial chaos expansion model for porous laminates in hot and humid environments is derived; The Hermite polynomial is introduced and the pseudo spectral projection method is used to solve the polynomial coefficients. The probability density and moment function of composite laminates under temperature and humidity changes are calculated. The results show that the output results based on polynomial chaos expansion method are generally consistent with the experimental values, and it can effectively and accurately predict the dispersion of residual strength of composite plates with holes under actual working conditions; Comparing the output results of the polynomial chaos expansion method with the Monte Carlo method, the deviations of the average and standard deviation of the two methods are controlled within 1 and 2.1%, respectively. However the calculation time of the PCE method is only 6% of that of the Monte Carlo method. The proposed polynomial chaos algorithm has the advantages of high efficiency and fast calculation speed in solving the uncertain response problem of composite materials.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Probabilistic and Robust Engineering Design · Structural Response to Dynamic Loads · Structural Health Monitoring Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
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