The noise caused by vibration in hydraulic pipelines is a significant issue in maintaining submarine stealth. This study focuses on a specific submarine’s local hydraulic system to investigate water hammer pressures, considering how component parameters affect water hammer generation and transmission (Chaudhry in Applied hydraulic transients. Springer, 2012) [1]. Using the maximum water hammer as an excitation, the study conducts a fluid–structure interaction (FSI) analysis to understand pipeline vibration characteristics. Additionally, the study explores the impact of clamp bolt pre‐tightening through simulation. Modal tests are then conducted on various pipeline specifications. Results indicate that the simulation and test results have an error within 10%, validating the model’s accuracy. Building on this, the study uses genetic algorithms to optimize pipeline passive vibration control, with clamp position as the independent variable and maximum stress as the dependent variable. Finite element verification demonstrates that this optimization effectively reduces pipeline vibration stress.

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Study and Analysis of Advanced System for Monitoring the Water Hammering Action in Closed Conduit

  • Sahil Riyaz,
  • Ashish Kumar Kashyap,
  • Astha Gupta

摘要

The noise caused by vibration in hydraulic pipelines is a significant issue in maintaining submarine stealth. This study focuses on a specific submarine’s local hydraulic system to investigate water hammer pressures, considering how component parameters affect water hammer generation and transmission (Chaudhry in Applied hydraulic transients. Springer, 2012) [1]. Using the maximum water hammer as an excitation, the study conducts a fluid–structure interaction (FSI) analysis to understand pipeline vibration characteristics. Additionally, the study explores the impact of clamp bolt pre‐tightening through simulation. Modal tests are then conducted on various pipeline specifications. Results indicate that the simulation and test results have an error within 10%, validating the model’s accuracy. Building on this, the study uses genetic algorithms to optimize pipeline passive vibration control, with clamp position as the independent variable and maximum stress as the dependent variable. Finite element verification demonstrates that this optimization effectively reduces pipeline vibration stress.