Powering Prediction for Surface Effect Ships Based on Model Results

Abstract

A method employing the laws of dynamic similarity to scale experimental model data is presented for predicting the powering performance of large surface effect ships. The data are reduced to individual com- ponents, including cushion wavemaking drag, sidewall and appendage frictional and form drags, aerodynamic drag, and seal drag. These components are appropriately scaled by either Froude or Reynolds scaling laws. Water channel and model dimension effects on wavemaking drag are discussed and a technique for calculating sidewall wetted area is presented. An experimentally derived algorithm characterizing seal-induced and frictional drag is explained. Drag predictions are compared with experimental trials data. HE drag prediction technique presently used for scaling the model drag of a surface effect ship (SES) is different from that developed by Froude, in that both the frictional and wavemaking drag terms can be accurately determined. The basic drag components are broken down into two classes: 1) those which are due to lift provided by the pressure region which dimensionally (or Froude) scale, and 2) those which are due to friction and must account for skin-friction coefficient changes with Reynolds number between the model and the prototype. The first theories,1 which were developed to describe the resistance characteristics of the SES, broke the components into the wavemaking drag due to the pressure region and the frictional drag of the sidewalls. Seal drag estimates were based on early British expressions derived for hovercraft. SES technology has been advanced significantly since these early estimations were made. The various drag components have been studied extensively, largely through model experiments, and are now understood in much greater depth. The resistance of an SES is usually estimated either from a theoretical approach (which has usually been correlated with or supplemented by experimental data), or one whereby experimentally derived model data are used extensively. The theoretical approach is used in parametric or sizing studies where one examines the effect of weight, length-to-beam ratio, or other parameters of a generalized design. These parametric prediction programs, however, may not be adequate to estimate the impact of the sometimes subtle physical differences between specific designs such as sidewall deadrise angle or chine effects, airflow rate effects, or the inherent differences between planing or bag and finger seals. These design-related differences can only be evaluated adequately through the use of model experiments and the analysis of the data. This paper summarizes a technique used