In the present paper,the hydrodynamic performance of stepped planing craft is investigated by computational fluid dynamics(CFD)analysis.For this purpose,the hydrodynamic resistances of without step,one-step,and two-st...In the present paper,the hydrodynamic performance of stepped planing craft is investigated by computational fluid dynamics(CFD)analysis.For this purpose,the hydrodynamic resistances of without step,one-step,and two-step hulls of Cougar planing craft are evaluated under different distances of the second step and LCG from aft,weight loadings,and Froude numbers(Fr).Our CFD results are appropriately validated against our conducted experimental test in National Iranians Marine Laboratory(NIMALA),Tehran,Iran.Then,the hydrodynamic resistance of intended planing crafts under various geometrical and physical conditions is predicted using artificial neural networks(ANNs).CFD analysis shows two different trends in the growth rate of resistance to weight ratio.So that,using steps for planing craft increases the resistance to weight ratio at lower Fr and decreases it at higher Fr.Additionally,by the increase of the distance between two steps,the resistance to weight ratio is decreased and the porpoising phenomenon is delayed.Furthermore,we obtained the maximum mean square error of ANNs output in the prediction of resistance to weight ratio equal to 0.0027.Finally,the predictive equation is suggested for the resistance to weight ratio of stepped planing craft according to weights and bias of designed ANNs.展开更多
文摘In the present paper,the hydrodynamic performance of stepped planing craft is investigated by computational fluid dynamics(CFD)analysis.For this purpose,the hydrodynamic resistances of without step,one-step,and two-step hulls of Cougar planing craft are evaluated under different distances of the second step and LCG from aft,weight loadings,and Froude numbers(Fr).Our CFD results are appropriately validated against our conducted experimental test in National Iranians Marine Laboratory(NIMALA),Tehran,Iran.Then,the hydrodynamic resistance of intended planing crafts under various geometrical and physical conditions is predicted using artificial neural networks(ANNs).CFD analysis shows two different trends in the growth rate of resistance to weight ratio.So that,using steps for planing craft increases the resistance to weight ratio at lower Fr and decreases it at higher Fr.Additionally,by the increase of the distance between two steps,the resistance to weight ratio is decreased and the porpoising phenomenon is delayed.Furthermore,we obtained the maximum mean square error of ANNs output in the prediction of resistance to weight ratio equal to 0.0027.Finally,the predictive equation is suggested for the resistance to weight ratio of stepped planing craft according to weights and bias of designed ANNs.
