Achieving Drag Reduction with Hullform Improvement in Different Optimizing Methods
Published at : 17 Dec 2020
Volume : IJtech
Vol 11, No 7 (2020)
DOI : https://doi.org/10.14716/ijtech.v11i7.4468
Sulistyawati, W., Suranto, P.J., 2020. Achieving Drag Reduction with Hullform Improvement in Different Optimizing Methods. International Journal of Technology. Volume 11(7), pp. 1370-1379
| Wiwin Sulistyawati | Faculty of Engineering, Universitas Pembangunan Nasional Veteran Jakarta, Jl. RS Fatmawati Raya, Pondok Labu, Jakarta Selatan, 12450, Indonesia |
| Purwo Joko Suranto | Faculty of Engineering, Universitas Pembangunan Nasional Veteran Jakarta, Jl. RS Fatmawati Raya, Pondok Labu, Jakarta Selatan, 12450, Indonesia |
In general, evaluation of ship
hydrodynamic efficiency could be produced by an energy-efficient and
concentrated cost function. An optimization method with the representation of
hull geometry is one of the preliminary design steps that are most appropriate
for evaluating hydrodynamic performance. This work presents a comparison of two
numerical methods for optimizing the shape of the hull concerning the minimization
of total ship resistance in calm water conditions. The optimization method uses
a theoretical approach based on Michell's integral and Rankine source methods.
The discussion of the two methods emphasizes the comparison of wave resistance,
total resistance, wave profiles, and wave contour. The optimized hull form
comparison of total resistance between Michell's integral and Rankine source
methods decreased by 3.79% and 4.0%, respectively. Comparing wave resistance
with decreases by 5.52% based on Michell's integral method and 13.33% by the
Rankine source method, the wave profiles generated by these two methods present
a fair amount of compatibility. The wave contour illustrates a reasonably
straightforward agreement on the optimal hull but are dissimilar on the initial
hull.
Optimization; Michell's integral; Rankine source method; Resistance; Series 60; Wave contour; Wave profiles
The
fundamentals of ship hydrodynamics are to obtain a design with minimum
resistance following a specified speed and displacement. Total resistance is of
the utmost importance for the ship, directly affecting speed, power
requirements, and fuel consumption. The hydrodynamic performance of the ship
can be enhanced by reducing friction and pressure resistance. Several recent
techniques have been carried out to achieve reduced drag on ships, i.e.,
improvements to the hull structure (Ibrahim et al.,
2018), micro bubble injection (Sindagi
et al., 2018; Zhang et al., 2019),
and optimization techniques (Park et al., 2015; Samuel et al.,
2015; Choi 2015; Lu et al.,
2016; Lu et al., 2019).
The hull's geometric optimization is considered a relatively reliable and
appropriate method of evaluating ship hydrodynamics. Objective functions,
design variables, and limits to obtain optimal hydrodynamic efficiency
concerning drag components and vessel performance, such as stability and
seakeeping, are considered primary objective functions. It has supported
computational optimization that has developed into a practical and fast design
technique that automatically
generates an optimal
hull design to
reduce drag. Fast-
The advancement of Computational Fluid Dynamics (CFD) has expanded the domain of hydrodynamic
problems effectively in viscous flow solving, domain decomposition, turbulence
solver, and physical details of the phenomenon's flow field. The development of
CFD computing technology has proven to be useful for evaluating the
hydrodynamic performance of ships to produce an optimum hull and attempts to
obtain a drag reduction (Yanuar et al., 2017; Wang
and Yao, 2018; Zhang et al., 2019; Yanuar et al., 2020). The Rankine
source method and Reynolds Averaged Navier Stokes (RANS) based viscous flow methods are potential
flow panel methods that were developed in several studies with quite advanced
techniques. The Rankine source method is considered fast, efficient, and highly
precise in potential flow theory, e.g., Rankine source method with the
optimization algorithm Nonlinear Programming Method (NLP) in monohull (Zhang and Zhang, 2015) and multihull optimization
(Von Graefe et al., 2013; Von Graefe et al., 2015).
The Michell integral method or thin ship theory is considered a more
straightforward and faster CFD method (Tuck and
Lazauskas, 1998). Several studies (Yanuar
and Sulistyawati, 2018; Sulistyawati et al., 2020a; Sulistyawati et al., 2020b;
Sulistyawati et al., 2020c) used Michell theory to investigate the
hydrodynamic characteristics of pentamarans and compared them with experiments.
Any deviations from the Michell integral method were deemed necessary for
development. A boundary layer correction for potential flow or the tangency
correction of the wave resistance oscillation problem at a small Froude number,
Fr, in Michell's theory was delivered by (Baši? et al., 2018). However, these numerical results still require verification with
experimental studies to test their validity.
This study represents a method of ship hull form optimization with the
Michell integral. The hull is defined by inputting data with a grid offset
setting into 21 stations and 21 water lines, a genetic algorithm in
multi-objective optimizations to approximate the optimized hull with a minimum
wave and total resistance in calm water. Two simple tools based on Michell's
theory were quite applicable for investigating resistance performance and
optimization (Sulistyawati et al., 2020b; Sulistyawati
et al., 2020c). The results were compared with the Rankine source method
(Zhang and Zhang, 2015). The Godzilla
optimization tool (Lazauskas, 1996) and
Flotilla (Lazauskas, 1999) were used for the
optimization of the resistance components and contour of the wave elevation.
Conforming to this study's purpose, which
investigated the comparison of Michell's integral theory and the Rankine source
method, several analyses were carried out on the total resistance, wave
resistance, wave profile, and its contours. The optimal model produced by the
two methods showed good graphical conformity even with significant differences.
Unfortunately, the research of (Zhang and
Zhang, 2015) were not carried out at a higher speed, Fr
> 0.32. In contrast, the approach with the Michell integral method was
deficient at low speeds. Theoretically, the Michell integral method linearizes
the shape of the hull and free surface conditions. The form factor approach is
perhaps less precise, and the friction factor dominates at low speed. It is,
therefore, very likely that this is the reason for a considerable discrepancy
between the two methods. The Rankine source method considers the nonlinear on
the actual free surface and nonlinear hull surface conditions.
Improvements in the complicated numerical
Michell integral should consider the tool's viscous and nonlinear effects,
which is needed to obtain more accurate results. Computation between the
optimization of these two methods showed differences in the resistance
component, wave profile, and contour. It is necessary to review the subsequent
analysis of water conditions and the towing experiment at a higher speed.
This
research was ?nancially supported by funding internal research of UPN Veteran
Jakarta on RIKNAS 2020 following KEP. REKTOR No. 346/ UN61.0/HK.02/2020. The
authors also thank Dr. Leo Lazaukas at the University of Adelaide for solution
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