A review of methods to optimize hydraulic design and cavitation suppression of centrifugal fire pumps

In modern firefighting scenarios, centrifugal fire pumps require enhanced hydraulic efficiency, cavitation resistance, and operational reliability while demanding accelerated development cycles. This study systematically investigates advancements in the hydraulic optimization design and cavitation suppression of centrifugal fire pumps. For performance enhancement, gradient-based optimization methods are analyzed, with emphasis on the adjoint method for fast iterative solution through the coupled solution of flow and adjoint equations. In the application of optimization methods based on intelligent optimization algorithms, the collaborative optimization method integrating intelligent optimization algorithms and surrogate models is explored, introducing how ensemble learning enhances nonlinear relationship modeling accuracy. In the cavitation suppression, the active methods and passive methods are reviewed, and the mechanism of the bionic structures, superhydrophobic surfaces, and other methods to delay the flow separation is analyzed. Future research priorities include multidisciplinary collaborative optimization methods, material structure, and gas–liquid two-phase flow, providing theoretical foundations for next-generation high-performance centrifugal fire pumps.