COMPOSITES SCIENCE AND ENGINEERING ›› 2026, Vol. 0 ›› Issue (4): 107-114.DOI: 10.19936/j.cnki.2096-8000.20260428.013

• DESIGN AND TECHNIQUE • Previous Articles     Next Articles

Prediction of residual strength of porous laminates in humid and hot environment based on Bayesian theory

JIA Baohui1, ZHOU Jiaxing1*, XIAO Haijian2, REN Peng3   

  1. 1. School of Transportation Science and Engineering, Civil Aviation University of China, Tianjin 300300, China;
    2. School of Safety Science and Engineering, Civil Aviation University of China, Tianjin 300300, China;
    3. School of Aeronautical Engineering, Civil Aviation University of China, Tianjin 300300, China
  • Received:2025-04-01 Published:2026-06-16

Abstract: Composite laminates are widely used due to their superior properties. In the humid and hot environment, the residual strength of the porous composite laminates decreases significantly and the dispersion increases.Considering the actual service conditions, this paper carries out experimental and simulation studies on the static tensile strength of composite laminates under six hygrothermal conditions.Based on the simulation data as the foundation for evaluating the residual strength of the laminate, the Bayesian theory combined with the experimental data was used to evaluate the residual strength of the laminate theoretically, and the distribution characteristics of the residual strength parameters of the laminate in the humid and hot environment was obtained. The Metrohast-Hastings algorithm is used to obtain the numerical solution of the residual strength of the laminate, and the distribution characteristics of temperature and humidity of the residual strength of the composite laminate is given by numerical inversion. The strength of the perforated laminate structure is given by the 90% and 99% quantiles, where temperature and humidity are the functions of the independent variables. The model can effectively predict the residual strength and dispersion of porous laminates in hot and humid environments.

Key words: composite materials, laminated, humid and hot environments, Bayesian theory, probabilistic analysis

CLC Number: