Study On The Reliability Design Of Composite Structures And The Optimization Methods

By virtue of its excellent properties, such as the high specific strength and high specific modulus, the Fiber Reinforced Plastics (FRP) has been widely used as structural materials in aircraft, space, marine and automobile, etc. The study on the FRP structures, especially on the reliability analysis and reliability-based optimization design (RBOD) has become an important concern. Many achievements have been made in the reliability-based studies utilizing the probability theory, but little has been done considering the non-probability or the mixed uncertainty factors. On the other hand, since the reliability analysis of structures usually involves a large number of failure modes, and the reliability analysis itself involves the solution to an optimization problem, the RBOD is computationally very expensive in general. Therefore, it is necessary to establish a theoretical framework of RBOD which can incorporate different uncertainty sources, and to develop a corresponding optimization strategy which can effectively solve the RBOD problems.Achievements in this paper are listed as follows:(1) A reliability-based design model and the optimal strategy under the mixture of random and interval variables is established. The method proposed is then employed to solve the reliability-based optimization design of composite structures. In reliability-based design (RBD), uncertainties are usually treated stochastically, and the variables are assumed to follow certain probability distribution. However, in many practical engineering applications, distributions of some random variables may not be precisely known, the possible values of these variables are only known to lie within specified intervals. In such cases, the random and interval variables are mixed together. In this paper, we proposed a method for analyzing the structural reliability and undertaking RBD under the mixture of random and interval variables. A formulation of percentile performance (inverse reliability analysis technique) is presented to directly evaluate the reliability constraints. This technique can avoid singularity problems which may occur in solving a direct reliability model during the iterative reliability assessment procedure. And to alleviate the computational burden, a sequential sing-loop procedure is employed to replace the computationally expensive double-loop procedure. With the proposed method, we studied the reliability-based optimization design of composite structures under the mixed uncertainties.(2) A new approach for the particle swarm optimization (PSO) is proposed to improve the convergence performance of the algorithm, and it is applied to the RBOD problems. To overcome the disadvantage of slow search speed and premature convergence in the basic PSO, two special mutation-interference operators are introduced. And the improved PSO method is then applied to the RBDO of laminated composites. Numerical examples show that the improved PSO has high convergence and good stability, and it is efficient in dealing with the probabilistic optimal design of composite structures.(3) The method for the reliability-based optimal design of complex structures is studied. For solving the RBOD problem of complex structures, it is important to make the calculation cost feasible while ensuring the design results with good accuracy. The present paper proposed a method combing PSO and ANSYS to answer the requirement. In the proposed method, ANSYS is employed to accurately calculate the response of structures, and PSO is used to find the global optimum solution. As an illustration and application of the proposed method, the reliability-based optimum design of a composite pressure vessel is worked out. Numerical examples show that the method combing PSO and ANSYS has great potential in solving the reliability-based design problem of complex structures.