Optimizing Ventilation Coefficients for High Speed Underwater Vehicles

The innovative approach of ventilated supercavitation offers a pathway to reduce drag around underwater vehiclesby creating a gas-filled cavity. The formation ventilation coefficient is pivotal in determining the gas volume neededfor supercavity creation. Traditional empirical models for predicting this coefficient are based on free surface waterexperiments, which do not reflect the conditions in closed-wall water tunnels where wall effects can altersupercavity dynamics.This study introduces a new empirical model that leverages existing experimental data to accurately predict theventilation needs for supercavities in such tunnels, taking into account the blockage effects of tunnel walls. Themodel’s validity extends across a wide range of Froude numbers and has been corroborated with variousexperimental data sets. Utilizing a pattern search optimization algorithm, the model’s empirical constants were finetuned,showcasing its capability to reliably predict the relationship between the ventilation coefficient and cavitationnumber across different tunnel environments. It also accurately determines the necessary ventilation rate forsupercavity initiation and maintenance. In essence, this research provides a refined tool for optimizing underwatervehicle performance, contributing to the advancement of marine vehicle engineering by enhancing efficiencythrough precise ventilation control.

کلیدواژه ها:

Ventilation rate ، artificial supercavitation ، closed-wall water tunnel ، pattern search.optimization ، supercavity formation