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Unidirectional Radial-Air-Turbine OWC Wave Energy Converters

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Unidirectional Radial-Air-Turbine OWC Wave Energy Converters ( unidirectional-radial-air-turbine-owc-wave-energy-converters )

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Energies 2019, 12, 2791 8 of 22 Energies 2019, 12, x FOR PEER REVIEW 8 of 22 8 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 φ (a) 7 6 5 4 3 2 1 0 CFD EXP (-) EXP (+) (b) 15 10 5 0 CFD EXP (-) EXP (+) -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 φ (c) 0.5 0.4 0.3 0.2 0.1 CFD EXP (-) EXP (+) 0 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 φ FFigiguurere6.6.CCoomppaarrininggththeeaacccuurraaccyyoof fcocomppuutatatitoionnaal lflfuluididddyynnaamicicss(C(CFFDD) )rerseusultlstswwitihthppuubblilsihsheded eexxppereirmimenentatlarlerseuslutslt(sSe(tSoegtuocghuicehtiael.t,2a0l.0,22);0(0a2))C;(a,)(bC)C,a(nbd)(Cc)η.an(Hdo(rciz)oηnta.l(aHxiosr:iflzonwtacloeaffixisc:iefnlot)w. TTAA 5. Numerical Optimisation of the Outward Flow Radial Turbine coefficient). 5. NTuhmeeoripctailmOispatimonissatuiodnyoisf tahneiOteuratwtivaerdpFrolocwessRwadhiiaclhTbuergbiinseby performing CFD simulations on the initial geometry of the inflow turbine. Then, the output parameters are defined, and design The optimisation study is an iterative process which begins by performing CFD simulations on exploration is used to create a design population by varying the input parameters. In this study, the initial geometry of the inflow turbine. Then, the output parameters are defined, and design design of experiments method (DOE) was used to determine the design space and characterize the exploration is used to create a design population by varying the input parameters. In this study, turbine performance based on a minimum number of actual analysis runs. The DOE conducts a series design of experiments method (DOE) was used to determine the design space and characterize the of experiments within the specified variation range of the input parameters set and minimizes the turbine performance based on a minimum number of actual analysis runs. The DOE conducts a series quantity of the required analysis runs to determine the parameters impacts. The central composite of experiments within the specified variation range of the input parameters set and minimizes the design (CCD), based on a fractional factorial design was used to reduce the number of experiments by quantity of the required analysis runs to determine the parameters impacts. The central composite sacrificing less meaningful high-order interactions [44]. A second-order analysis was used with the design (CCD), based on a fractional factorial design was used to reduce the number of experiments capability to model the interaction between the input parameters and surface curvatures appropriately. by sacrificing less meaningful high-order interactions [44]. A second-order analysis was used with The general form of a second-order model explained in [45] is: the capability to model the interaction between the input parameters and surface curvatures appropriately. The general form of a sencond-ordner model enxplained in [45] is: y = a0 + 􏰚 aixi+ 􏰚 aiixi2 + 􏰚 􏰚 aijxixj (5) y = a i =+ 1 a x +i = 1 a x 2 + i = 1 j < ai x x 0 ii ii i ij i j (5) nnn  i=1  i=1  i=1 j

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