Optimization of dome shape for filament wound pressure vessels using data-driven evolutionary algorithms

Filament wound glass/epoxy and carbon/epoxy pressure vessels were designed using a data-driven evolutionary approach along with a classical mechanics-based analysis. Analytical solutions for three known end domes (a spherical shell, a geodesic-isotensoid shell and a shell based on minimizing of the Tsai-Hill's criterion) and end dome based on Hoffman's criterion were used to create surrogate models through two different evolutionary optimization algorithms: Evolutionary Neural Net (EvoNN) and Bi-objective Genetic Programming (BioGP) and bi-objective evolutionary optimization studies were carried out using them. Composite pressure vessels are manufactured by means of filament (helical) winding. The stresses in the end domes were evaluated analytically and compared with each other. Hoffman strength criterion was chosen for the evaluation of the critical areas of the shells. Moreover, the best dome shape for given material and polar hole/equator ratio was selected for various types of failure.

Automated summary

Filament wound glass/epoxy and carbon/epoxy pressure vessels were designed using a data-driven evolutionary approach and classical mechanics-based analysis. Analytical solutions for three known end domes and an end dome based on Hoffman's criterion were used to create surrogate models through two different evolutionary optimization algorithms. Composite pressure vessels are manufactured by filament winding. The stresses in the end domes were evaluated analytically and compared, and the critical areas of the shells were evaluated using the Hoffman strength criterion. The best dome shape for given material and polar hole/equator ratio was selected to address various types of failure.