Optimization of dual-zone reinforcement for composite case dome based on RBF neural network surrogate model

Traditional full-area reinforcement of composite case domes results in excessive redundant case mass. Sectional reinforcement technology for these domes has been applied in engineering practice, yet the corresponding process often relies on engineering experience, and the influence mechanism of its process parameters on case stress remains unclear. To address this, aiming at case dome failure under internal pressure, its failure mode, strain response and burst pressure were analyzed and accurately predicted based on composite progressive damage theory; subsequently, a dual-zone reinforcement optimization model was established via RBF neural network surrogate model (using common unidirectional/woven fabrics), revealing how layer ratio and reinforcement range affect stress at failure-prone dome locations and obtaining optimal parameters. Results show weak axial stiffness near the dome equator requires woven fabric reinforcement extending to the case cylinder, while 90° unidirectional/woven composite reinforcement with proper layer ratio suits the joint shoulder; hydrostatic burst tests confirmed optimized cases burst at the cylinder with a 14.85% increase in the performance factor, providing theoretical support for composite case dome design.