Reliability Analysis of Pressure Vessel Interval Based on Intelligent Search Algorithm

Pressure vessels are mostly made of high-strength steel, metal and some alloys, and the probability statistics of their uncertain parameters are difficult to obtain or can not be obtained at all.At this time, the interval reliability method will be a more reasonable method.Firstly, the interval reliability analysis model of this type of pressure vessel is established, and the calculation expressions of mean value, standard deviation and deviation of fiber stress are derived by using the interval factor method.The interval reliability design of this type of pressure vessel is realized by using the interval reliability calculation method, and the influence of the fluctuation of structural uncertainty parameters on the design size of the vessel thickness is investigated.Examples show that the design results of interval reliability meet the safety requirements, but the accuracy is not as high as that of probabilistic reliability method.Secondly, the approximate model of the stress constraint function is constructed according to the trained BP neural network and the stress intensity evaluation criteria, and then the objective function, the approximate model of the stress constraint function and the value range of the design variables are combined to form a complete optimization mathematical model.The optimized mathematical model is optimized by the cuckoo search algorithm, and the minimum design variable value of the objective function is obtained.Finally, the two independently evolved subpopulations are fused with each other through fixed algebra to strengthen the information exchange between different individuals.Combined with the advantages of intelligent search algorithm, it has a good optimization effect in the optimal design of pressure vessel.