Gun firing is a process that converts propellant chemical energy to projectile kinetic energy and other kinds of energies. In order to explore the energy conversion process, firstly, the interior ballistics mathematical model and the barrel-projectile finite element model are built and solved. Then, the related variable values and energy values are obtained and discussed. Finally, for improving energy efficiency, the interval uncertainty optimization problem is modeled, and then solved using the two-layer nested optimization strategy and back-propagation (BP) neural network surrogate model. Calculation results show that, after optimization, the heat efficiency raises from 31.13% to 33.05% and the max rifling stress decreases from 893.68 to 859.76 Mpa, which would improve the firing performance and prolong the lifetime of the gun barrel.