Intelligent parameter optimization of sealed airbag vessels with preventing water hammer in cascaded pressurized water transmission system: Based on MOPSO algorithm

Abstract

For long-distance water transmission projects utilizing cascade pressurized pump stations in mountainous regions, the configuration and optimization of water hammer protection equipment are indispensable. In practical engineering applications, the setup of water hammer protection equipment is not solely determined by the pipeline's ultimate pressure. Hence, a comprehensive evaluation of safety and cost factors should be conducted, while ensuring that the pipeline's carrying capacity is not exceeded. This paper opts for sealed airbag vessels as the water hammer protection equipment, aiming to optimize water transmission safety and equipment procurement costs. Utilizing the Bentley Hammer v10.08 and MATLAB R2023 software platforms, and incorporating the Latin Hypercube Sampling (LHS) method decomposed by Cholesky, stepwise regression analysis, Multi-objective Particle Swarm Optimization (MOPSO) algorithm, and fuzzy membership normalization evaluation method, a conceptual analysis module is developed. This module simulates the sampling of the optimization variables within the constraints to obtain a high-quality set of expected samples. A high-precision objective function formulation was derived by fitting the data with higher dispersion. A comprehensive evaluation of several Pareto optimal solutions was performed to identify a high-reliability water hammer protection scheme for the entire pipeline. It indicates that the optimal selection of water hammer protection equipment reduces transient positive pressure head and transient negative pressure head by 37.66 % and 63.74 % respectively, compared to the system without protection equipment. And compared to the equipment purchase cost before optimization, it can save 28.37 %. This research will provide theoretical guidance for rational selection of sealed airbag air vessels.