ABSTRACT

The power predicted by the model test is closely linked to hull form factors, derived from either the Prohaska method, Computational Fluid Dynamics (CFD), or alternative methodologies. However, each method of determining the form factor (k) has its challenges. Thus, regression analysis of k based on CFD based form factors has emerged as a viable approach. This paper introduces and examines two formulas: one for k at different draft and another for change of form factor between drafts, denoted as Δk. The regression process of the empirical formula, as well as the accuracy and applicability of the resulting the regression formula, are thoroughly discussed herein. The analysis reveals a strong agreement between k and Δk values obtained through regression and those derived from CFD. The adoption of the newly proposed regression formula reduces reliance on experimental and computational methods of calculating the form factor, thereby facilitating easier evaluation for designers and other stakeholders concerned with predicting power under varying draft conditions.

SENSITIVITY OF FORM FACTOR TO SHIP POWER PREDICTION

Form factor k is very important for accurate prediction of power. It was found that the accurate predictions of the form factor between different drafts(Δk) are also important if power at different drafts are concerned. Many factors might influence the value of k and Δk.

Sensitivity analysis of the form factor

The value of the ship form factor mainly affects the predicted ship resistance, which can be calculated according to the ITTC1978 formula (ITTC, 2011) based on the model test results.

(equation)

where the subscripts "m" and "s" represent "model-scale" and "full-scale", respectively; Ct is the coefficient of total resistance; Cf is the coefficient of frictional resistance; ΔCf is the roughness allowance; Caa is the coefficient of air resistance; k is the form factor.

According to Eq.1, for a constant Ctm, Cts decreases with an increasing form factor. For a ship with Cts = 2.0 × −10−3 and CfmCfs = 1.6 × 10−3, assuming that the form factor is overpredicted by 0.01 (i.e. Δk = 0.01), a deviation of −0.8% in the Cts is expected, according to Eq.2.

(equation)

This means that a deviation in the form factor as small as 0.01 leads to a deviation of about 0.8% in the total resistance. The correlation between them mainly depends on the value of (CfmCfs)/Cts, which may be different for distinct hull forms.

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