Alternative Empirical Formula for Predicting the Frictional Drag Penalty due to Fouling on the Ship Hull using the Design of Experiments (DOE) Method
Biofouling is known as one of the main problems in the maritime sector because it can increase the surface roughness of the ship’s hull, which will increase the hull’s frictional resistance and consequently, the ship’s fuel consumption and emissions. It is thus important to re...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Universitas Indonesia
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/014fb52bf30247debe24a97af0b25414 |
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| Sumario: | Biofouling is known as one of
the main problems in the maritime sector because it can increase the surface
roughness of the ship’s hull, which will increase the hull’s frictional
resistance and consequently, the ship’s
fuel consumption and emissions. It is thus important to reduce the impact of
biofouling by predicting the value of
. Such prediction using
existing empirical methods is still a challenge today, however. Granville’s
similarity law scaling method can predict accurately because it can be adjusted
for all types of roughness using the roughness function
variable as the input, but it requires
iterative calculations using a computer, which is difficult for untrained
people. Other empirical methods are more practical to use but are less flexible
because they use only one input. The variance of
is very important to represent the biofouling
roughness that grew randomly. This paper proposes an alternative formula for
predicting the value of
that is more practical and flexible using the
modern statistical method, the Design of Experiments (DOE), particularly
two-level full factorial design. For each factor, the code translation method
using nonlinear regression combined with optimization of constants was
utilized. The alternative formula was successfully created and subjected to a
validation test. Its error, calculated against the result of the Granville
method, had a coefficient of determination R2= 0.9988 and an error rate of
±7%, which can even become ±5% based on 93.9% of 1,000 random calculations. |
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