Reliability Analysis of Deep-Water Explosion Test Vessel Based on Fuzzy Interval

Abstract

The safety of such a high-security structure as a deep-water explosion test vessel in service is still in the exploration stage. The reliability of the vessel needs to be analyzed in order to prevent the underwater explosion shock wave and other explosion products on the test equipment causing great damage to the experimental personnel. The safety of such a high-security structure as a deep-water explosion test vessel in service has gradually attracted the attention of scholars. The reliability of the vessel needs to be analyzed in order to prevent the shock wave of underwater explosion and other explosion products on the test equipment causing great damage to the experimental personnel. In this paper, the dynamic response test data of a deepwater explosion test vessel in service under different conditions and the Elman neural network are used to establish the dynamic response prediction model of the deepwater explosion test vessel, and using the established model to make dynamic response prediction in the next experiment; the vessel yield strength and modulus of elasticity are taken as random variables, and the container dynamic strain prediction interval is the interval variable, the random-interval reliability model is established by using the interval variable and random variable. The random variables of the model are transformed into interval variables, and the interval variables are fuzzified using the affiliation function to calculate the reliability index. Since the interval variable obtained from the model will change with the change of the container dynamic test data, the interval reliability index calculated by the stochastic-interval reliability analysis model can quantify the reliability of the container and can be used as a reference for the subsequent use of the container by reducing the reliability index to calculate the service life and drug filling amount.