Volume 43 Issue 2
Feb.  2023
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CHEN Yuanjie, CHEN Zhengshou, DU Bingxin, XIE Yingxiao, JIANG Hua. Optimum design of self-driven rotary water-jet sprayer based on ESGA genetic algorithm[J]. Explosion And Shock Waves, 2023, 43(2): 024201. doi: 10.11883/bzycj-2022-0155
Citation: CHEN Yuanjie, CHEN Zhengshou, DU Bingxin, XIE Yingxiao, JIANG Hua. Optimum design of self-driven rotary water-jet sprayer based on ESGA genetic algorithm[J]. Explosion And Shock Waves, 2023, 43(2): 024201. doi: 10.11883/bzycj-2022-0155

Optimum design of self-driven rotary water-jet sprayer based on ESGA genetic algorithm

doi: 10.11883/bzycj-2022-0155
  • Received Date: 2022-04-12
  • Rev Recd Date: 2022-07-20
  • Available Online: 2022-09-13
  • Publish Date: 2023-02-25
  • The self-driven rotary sprayer using ultra-high-pressure water jet is widely used in the rust removal of ship hulls, and its layout directly affects the efficiency and quality of ship derusting. Hitherto, the design of sprayer layout primarily depends on practical engineering experiences, due to the lack of support from accurate optimization techniques and theoretical analysis. In order to solve the layout optimization problem associated with self-driven rotary sprayers using ultra-high-pressure water jet, an improved elitist strategy genetic algorithm (ESGA) based on conventional genetic algorithm (GA) is proposed. By designing appropriate evolutionary operations, the ESGA algorithm can skip crossover and mutation operations on the fittest individuals in the population, and then directly copy the fittest individual to the next generation. Thus, the global convergence ability and robustness of the algorithm are improved effectively. By fully combining the sweep impinging performance and trajectory characteristics of rotary sprayer, a sweep impinging discrete-time model for self-driven rotary sprayer using ultra-high-pressure water jet is developed to quantify the evenness of impinging energy distribution on target surface perpendicular to the sprayer movement path. Aiming at enhancing the evenness of impinging energy distribution and improving hydrodynamic performance, the layout of self-driven rotary sprayer is optimized via the GA and ESGA algorithms. It is found that the evenness of the impinging energy distribution related to the self-driven rotary sprayer with a rod-like shape, which is optimized by the ESGA algorithm, is improved by 47.2% compared with that of the original layout scheme. The ESGA algorithm provides faster convergence speed and higher convergence precision, superior to the conventional GA. The experimental test results indicated that the rust-removing efficiency of self-driven rotary sprayer, optimized by the ESGA algorithm, is increased by 42.0% when compared with original layout scheme. It is worth noting that the improved ESGA algorithm optimization approach is feasible, and some sprayer layouts with better hydrodynamic performance can be easily achieved in fewer convergence iterations, providing adequate theoretical basis and application support for the layout optimization.
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