Page 51: of Marine News Magazine (May 2017)
Inland Waterways
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Parametric Submarine/SWATH model
Example optimized design variant useful information to designers and operators alike. In an Example optimized designs effort to reduce fuel consumption, ship operators are often The use of NavCad for optimized design can be for the interested in the effect of initial trim on the performance “whole system” or a “component”. Recent published stud- of the vessel. This supplemental tool will provide an es- ies of “whole system” optimized design with NavCad in- sential assessment of the effect of initial trim on bare-hull clude an AUV, waterjet-driven patrol boat, and a motor resistance for ships large and small. yacht. A very successful “component” optimized design study was for a bulbous bow retro? t.
Distributed-analytical optimization
The Analytical Distributed-Volume Method (ADVM) System optimizations module is a bare-hull resistance prediction method that A variety of optimized designs have been conducted using can be used to supplement a parametric-statistical method. NavCad coupled with the CAESES software as the execu-
Inspired by analytical wave-making theory, it is a predic- tive third-party tool for the management of the geometry tion of ship resistance where the hull form is described by and optimization processes. NavCad is the simulation solver the longitudinal distribution of the immersed volume and responsible for all resistance and propulsion predictions.
not by parameters. Calculation of wave-making and vis- An AUV system optimization project highlighted a para- cous drag, including a careful prediction of form factor metric-statistical optimization using NavCad’s Submarine/ and frictional drag coef? cients, completes the computa- SWATH prediction methods. The hull was described as tion of total bare-hull resistance. HydroComp’s design a body-of-revolution shape with three zones – fore, mid, mission for the module was to provide a method that was: and aft (as shown in the graphic below). The design objec- • computationally ef