The maximum likelihood estimation is a widely used approach to the parameter estimation. However, the conventional algorithm makes the estimation procedure of three‐parameter Weibull distribution difficult. Therefore, this paper proposes an evolutionary strategy to explore the good solutions based on the maximum likelihood method. The maximizing process of likelihood function is converted to an optimization problem. The evolutionary algorithm is employed to obtain the optimal parameters for the likelihood function. Examples are presented to demonstrate the proposed method. The results show that the proposed method is suitable for the parameter estimation of the three‐parameter Weibull distribution.

Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy.

A numerical investigation on propeller-induced flow effects in tractor configurations on a Zimmerman wing-fuselage using the cambered thin airfoil is presented in this paper. The Reynolds number based on the mean aerodynamic chord was 1.3 × 10⁵. Significant aerodynamic performance benefits could be found for a propeller in the tractor configuration. The numerical results showed that the propeller slipstream effect on the wings was highly dependent on the size of the propeller, and the major slipstream effect was working at 60% inboard wingspan, whereas less effects were observed towards the wingtip. The propeller slipstream increased the local angle of attack on the up-going blade side. This effect simultaneously augmented the section lift. The unsteady Reynolds-averaged Navier–Stokes (URANS) simulations helped to improve understanding of the interaction of the propeller wake and the wing-fuselage, which is an important aspect to guide the design of future efficient and controllable micro air vehicles. The results indicated that, in MAV designs, the slipstream from the propeller had a significant effect on the wing aerodynamics, regarding both performance and stability of the vehicle.

This article presents an approach that combines the active global Kriging method and multidisciplinary strategy to investigate the problem of evidence‐based multidisciplinary design optimization. The global Kriging model is constructed by introducing a so‐called learning function and using actively selected samples in the entire optimization space. With the Kriging model, the plausibility, Pl, of failure is obtained with evidence theory. The multidisciplinary feasible and collaborative optimization strategies of multidisciplinary design optimization are combined with the evidence‐based reliability analysis. Numerical examples are provided to illustrate the efficiency and accuracy of the proposed method. The numerical results show that the proposed algorithm is effective and valuable, which is valuable in engineering application.