Trans RINA, Vol 152, Part B2, Intl J Small Craft Tech, 2010 Jul-Dec


The models of all configurations converge at the upper limit of mast height so another sensitivity analysis is conducted for the effect of mast height on cost. Mast height is not an input, so this was explored by altering the limit values for mast height. The results, shown in Figure 8, show how cost and mass increase with mast height.


A similar investigation was carried out to see the effect of constraining the draught. The draught limit is steadily reduced from 2.8m to 1.23m. The results, shown in Table 4, yield what might at first reading be a surprising result – the sail area, displacement and GM do not change significantly as draught is decreased. This is because, again, the model is driven by usable interior volume rather than performance and stability. For a cruising yacht, the need to optimise performance is less strong than that for a racing yacht, therefore the model accepts hydrodynamically non-optimal shapes as a trade-off for space and cost optimisation.


All the model results up to this point have been for the 5 goals listed in section 3 above. Curiosity led us to investigate the effect of reducing the goals incrementally from 5 down to 1 (the one being cost). The results are shown in Table 5.


The model was also run with different weightings to the goals. The results showed little change because the optimal point was already on the boundary of the feasible design space, as set by the yacht database used. If the constraints of existing design practice were relaxed, the effect of changing weightings and goal numbers would most likely be stronger.


An indication of the validity of the results is shown in Table 4 where the model output is presented alongside a benchmark comparison of the successful Van de Stadt 34 design, which represents a typical yacht that, in the authors’ experience, is well suited to the specified goals. It can be seen that the optimised designs are similar to the benchmark, validating to some extent the technique used.


6. CONCLUSIONS


A multiple-objective optimisation technique is employed to develop a mathematical model for the preliminary design of


sailing cruising yachts configuration. The


model is applied to a set of owner’s requirements for 3 cabins, 2 cabins and 1 cabin configurations.


The use of the model demonstrates that principal design parameters could be quickly


decision support problem technique. 7.


Work is


FUTURE WORK necessary


to develop subroutines for the preparation of the lines plan from the known principal 8. determined using the 9. 7. design parameters, which would enable


calculations for the coefficients and stability particulars. Subroutines are required for


the calculation of


structural weight of the hull and detailed costing of construction and other items to develop a better realistic model. Replacement of the present velocity prediction routine may be made by developing a better method using detailed analysis.


8. 1. REFERENCES


ERNST G., BIRMINGHAM R. & MESBASHI E. 2007. Application


of artificial neural


networks in preliminary sailing yacht design. International Journal of Small Craft Technology vol 149 part B1, Royal Institution of Naval Architects.


2.


CLAUSEN H.B., LUTZEN M., FRIIS- HANSEN A. & BJORNBOE N. 2001. Bayesian and neural networks for preliminary ship design. Marine Technology vol 38 no 4. Society of Naval Architects and Marine Engineers.


3.


ARTANA K.B. & ISHIDA K. 2003. Spreadsheet modeling to determine optimum ship main dimensions and power requirements at basic design stage. Marine Technology vol 40 no 1. Society of Naval Architects and Marine Engineers.


4.


VAN OOSSANEN P. 2003. A Concept Exploration Model for Sailing Yachts, The Modern Yacht Conference, 17-18 September, 2003. Royal Institution of Naval Architects. Southampton ,UK: 17-28.


5.


JACQUIN E., BELLEVRE D., ALESSANDRINI B. & CORDIER S. 2002 Yacht Optimisation based on Genetic Algorithm using RANSE Solver, High Performance Yacht Design Conference, 4-6 December 2002. Royal Institution of Naval Architects. Auckland, New Zealand.


6.


WOLF R., DICKMANN J. & BOAS R. 2005. Ship Design using Heuristic Optimization Methods. 46th AIAA structures, Structural Dynamics and Materials Conference, 18-21 April 2005. Austin, USA.


MISTREE, F, SMITH, W.F, KAMAL, S.J. & BRAS, B.A. 1991. Designing Decisions: Axioms, Models, and Marine Applications, Proc. Fourth International Marine Systems Design Conference (IMSDC’91), 26-30 May, 1991. Kobe, Japan: 1-24.


MISTREE, F, HUGHES, O.F. & BRAS, B.A. 1992. Compromise Decision Support Problem and Adaptive Linear Programming Algorithm, Progress in Astronautics and Aeronautics 150 (1992), 251-290.


PAL, P.K. 1991. Rationalised Design of Sailing Yachts, Proc. Fourth International Marine Systems Design Conference (IMSDC’91), 26-30 May, 1991. Kobe, Japan: 141-153.


accurate the


B-78


©2010: The Royal Institution of Naval Architects


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