CFD-based multi-objective optimisation of S60 Catamaran considering Demihull shape and separation
Applied Ocean Research, ISSN: 0141-1187, Vol: 97, Page: 102071
2020
- 40Citations
- 34Captures
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Article Description
A computational fluid dynamics (CFD)-based multi-objective optimisation procedure is proposed for the development and application of the in-house solver OPTShip-SJTU. A free-form deformation (FFD) method is adopted to modify the non-uniform rational basis-spline (NURBS) surfaces of a ship and thus automatically reconstruct ship hull form. A Reynolds-averaged Navier–Stokes (RANS) solver, naoe-FOAM-SJTU, is applied to evaluate the hydrodynamic performance of a ship in the complex flow phenomena. The Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is used to search a global optimal set (called Pareto front) in approximation models constructed by the Kriging method. In this study, a S60 catamaran is optimised for resistance reduction based on a consideration of the demihull shape and separation. Three free-form deformation (FFD)-related parameters and the separation distance of the demihulls are selected as four design variables with two geometric constraints imposed. The total resistance for Froude numbers ( Fr ) = 0.4 and 0.45 are taken as the two objective functions. The optimal catamarans are obtained through an optimisation process and three of these are selected for further validation by a RANS-based method. The hydrodynamic performance of the initial and optimal catamarans is compared in terms of resistance, wave elevation, pressure distribution, cross flow, interference factors and longitudinal wave cuts, which confirms the reliability of the ship design optimisation.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0141118719303670; http://dx.doi.org/10.1016/j.apor.2020.102071; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85078702006&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0141118719303670; https://dx.doi.org/10.1016/j.apor.2020.102071
Elsevier BV
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