| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 1720061 | Applied Ocean Research | 2014 | 10 Pages |
•Four correlation equations for air entrainment into the IRS device have been developed using finite volume method. Furthermore, the outlet temperature of the IRS device is predicted by developing the correlation equations.•The outlet temperature (Tnz/T∞) of IRS device is lowered with bottom funnel diameter (Dbf/Dnz), which is very much important for infrared stealth technology.•The funnel overlap height (Hov/Dnz) has a significant effect on the mass entertainment. An optimum funnel overlap height has been found out, for which the mass entrainment in to the IRS device is the maximum.•The diameter of the bottom funnel has a second highest effect on mass entertainment.•The hot nozzle fluid entrains more air into the IRS device than the cold nozzle fluid.
In the present research, the conservation equations for mass, momentum, energy as well as the equations for k and ɛ have been solved numerically to compute the rate of air entrained into an Infrared Suppression (IRS) device using finite volume method. Hence, four different correlations (Eqs. (15), (16), (17) and (18)) have been developed to predict the mass suction over a wide range of operating parameters which have been used to design the IRS device for naval or merchant ship. The nozzle exit Reynolds number, diameter of bottom funnels, funnel overlap height, nozzle distance from the bottom funnel as well as nozzle fluid temperature are varied over a wide range of 5 × 103 ≤ Re ≤ 106, 1.42 ≤ Dbf/Dnz ≤ 1.77, −0.16 ≤ Hov/Dnz ≤ 0.16, −0.1633 ≤ Hnz/Dnz ≤ 0.1633, and 1 ≤ Tnz/T∞ ≤ 2, respectively; so as to develop the above correlations. Furthermore, two correlation equations (Eqs. (19) and (20)) have been developed to predict the outlet temperature of the IRS device. The present computational results have also been validated with the results of existing literature as well as with some of our own experimental results. Correlation equations (Eqs. (15), (16), (17), (18), (19) and (20)) have been developed by carrying out a regression analysis through a computer program written in Engineering Equation Solver (EES).
