Structure Dynamic Reliability Analysis Of Solid Rocket Motor Viscoelasticity Grains

Structure dynamic reliability of Solid Rocket Motor (SRM) grain is analyzed based on Monte Carlo viscoelastic stochastic finite element method. Advance technique is applied to increase the efficiency on account of the inefficiency of direct Monte Carlo simulation (MCS). Considering the randomness of grain material and exterior load, structure dynamic reliability is analyzed in combination with several reliability models, thus provides new ideas and reference for structural analysis and design of SRM grain. The main work and achievements of this paper are summarized as follows:Based on Herrmann variational principle, a new type of viscoelastic incremental finite element method is presented. It is suitable for nearly-incompressible viscoelastic grain. At the same time a hexahedron generalized conforming element with high accuracy are adopted in order to gain high precision for 3D grain. This method is accurate and effective, and needs less memory space, then provides the basis for viscoealstic stochastic analysis.Monte Carlo simulation method is used to simulate random field and stochastic process. Random field is translated to discrete random variables set, and then these correlated variables are converted into independent ones respectively through correlation structures factorization. Trigonometric series is used to simulate Gaussian stationary stochastic processes, and effective FFT method is adopted in particular. Based on AR and MA system, ARMA model with rigorous mathematic foundation offers the basis for simulating random excitation.Considering the randomness of Poisson ratio and relaxation modulus, Latin Hypercube Sampling technique is applied to increase the efficiency, then the relations of the random parameters and stochastic response is analyzed. On the basis of a series of numerical experiments with a few design points, response surface methodology based on second-order polynomial is comparative accurate and more effective, thus suitable for engineering application.Aiming at nearly incompressible effect and the deficiency of quasi-static analysis, a new type of incremental finite element method on the basis of Hamilton variational theorem is developed for dynamic response analysis of viscoelasticity structure. Considering the randomness of excitation, an efficient simulation procedure based on Monte Carlo simulation is presented. A simple criterion is established for indicating the importance of each dynamical response sample. According to this criterion, Russian Roulette&Split method is applied to deal with the selected samples. The efficiency of this algorithm is much higher than that of direct MCS while the number of response samples in the low probability regions is increased. This method can be directly used for stochastic analysis of nonlinear dynamical systems to gain more accurate result. Based on Herrmann variational principle and Total Lagrangian method, a new type of viscoelastic incremental finite element method with large deformation is presented. It is also suitable for nearly-incompressible viscoelastic grain. In combination with improved Monte Carlo simulation method, it is suitable for stochastic response of complex grain with large deformation.Considering the randomness of SRM grain material parameters, Latin Hypercube Sampling and response surface methodology need fewer samples to gain adequacy stochastic response information. Dynamic reliability and its variational trend of the SRM grain are analyzed in combination with failure criterion. Random load is simulated by improved Monte Carlo simulation method, and reliability is quite accurate with less effort.In conclusion, efficient simulation procedures have been successfully applied to analyzed structure reliability of SRM grain with stochastic parameters or under random excitation. Some developments have been gained both in methods and applications. The research in this paper offers an effective and universal approach for engineering application.