HYDRODYNAMIC AND HULLFORM OPTIMIZATION OF TUGBOAT OPERATING IN ONNE PORT
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A method for optimizing of hull forms with respect to their hydrodynamic performance in calm and rough water is presented. The method is based on an initial optimization of a parent hull form for tugboat and the improvement of the resulting optimum hull form for calm water resistance. In the first part of the method, variant hull forms differing from a parent in the main dimensions and/or in one or more hull form parameters such as CWP, LCF, CB, LCB, KB, CP are automatically generated and their tugboat qualities evaluated. When appropriate ranges for the principal characteristics and parameters of the hull form under investigation are prescribed, a formal optimization procedure is used to obtain the variant with the best tugboat behaviour. The weighted sum of the resonant values of selected tugboat operating in Onne port Harcourt responses for a number of tugboat speeds and headings in regular waves forms the objective function. Hooke & Jeeves Algorithm is used to accomplish the optimization. The procedure results in a set of trends regarding the proposed variations of the selected hull form parameters, within the specified constraints. These trends are then applied on the parent hull to derive an optimized hull form with fair lines. Subsequently this hull form can be locally modified to improve its calm water resistance or, as it should be done, its propulsion characteristics.
The applicability of the method is demonstrated in two cases: a conventional reefer tugboat and a naval destroyer. Scaled models of the parent and the optimized hull forms have been tested for calm water resistance and tugboat. In both cases the validity of the methodology is demonstrated.
TABLE OF CONTENTS
COVER PAGE
TITLE PAGE
APPROVAL PAGE
DEDICATION
ACKNOWLEDGEMENT
ABSTRACT
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF THE PROJECT
-
AIM OF THE PROJECT
- SIGNIFICANCE OF THE PROJECT
- SCOPE OF THE PROJECT
CHAPTER TWO
LITERATURE REVIEW
- REVIEW OF RELATED STUDIES
- HYDRODYNAMIC OPTIMIZATION IN TUGBOAT DESIGN
CHAPTER THREE
- METHODOLOGY
3.1 DESCRIPTION OF THE METHOD
3.2 HULL FORM DESCRIPTION
3.3 HULL FORM VARIANTS
3.4 ANALYTICAL TOOLS FOR SEAKEEPING AND RESISTANCE CALCULATIONS
3.5 THE FIGURE OF MERIT
3.6 THE OPTIMIZATION PROBLEM
3.7 APPLICATION OF THE METHOD
CHAPTER FOUR
4.1 THE REEFER TUGBOAT CASE
4.2 THE DESTROYER CASE
CHAPTER FIVE
5.1 DISCUSSION AND CONCLUSIONS
REFERENCES
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF THE STUDY
In general, tugboats are used to convey many kinds of surface vessels, including unactuated vessels, such as barge ships and offshore structures. This requires an adequate model for tugboat operation to precisely take into account surge, sway, and yaw motions. We present an optimization method of tugboat operation. Fifty years after the development of the first practical strip theory by Korvin- Kroukovsky (1955), analytical seakeeping prediction methods are widely used for the evaluation of the seakeeping qualities of tugboats. Twenty-five years ago, Bales (1980) published a paper treating the optimization of the seakeeping performance of Destroyer-type hull forms, based on the analytical predictions. By that time the analytical tools available to the profession were considered reliable enough to be used for optimization purposes, in contrast to seakeeping experiments which cannot be practically used for the same purpose, due to excessive time and cost involved. Bales used analytical results to derive a regression formula correlating the performance of this type of ships in head seas and at various speeds to certain empirically selected hull form parameters.
Grigoropoulos and Loukakis (1988) presented a new method for developing hull forms with superior seakeeping qualities. The new method, described in Grigoropoulos (1989), was used for the analytical development of an optimized hull form for a tugboat. Models of both the parent and the optimum hull forms were tested and the analytical optimization procedure was experimentally verified.
1.2 AIM AND OBJECTIVES OF THE STUDY
The main aim of this study is to carry out the optimization of hull forms with respect to their hydrodynamic performance of a tugboat operating in Onne Portharcourt in calm and rough water.
1.3 SCOPE OF THE STUDY
In this paper, the aforementioned method is further extended and improved to take advantage of modern computer-aided design (CAD) and Computational Fluid Dynamics (CFD) tools, currently available to the profession. Utilizing these tools, the hull form of a modern destroyer was optimized with respect to both its performance in calm water and in waves. Model tests with the parent and the optimized hull forms verified the efficiency of the optimization methodology. Furthermore, additional calculations for the reefer vessel have been carried out, extending the optimization gains.
1.4 SIGNIFICANCE OF THE STUDY
This study will serve as a means of improving tugboat calm water resistance thereby improving the operation of the tugboat.
1.5 REVIEW OF RELATED WORKS
In the last decade, different types of control strategies using tugboats have been proposed. Braganzae et al. (2007) presented control strategies for the positioning of an unactuated vessel by multiple, autonomous tugboats. An adaptive control strategy was designed, and thrust forces of tugboats arranged in opposing pairs were obtained from this strategy. The tug force directions remained fixed throughout the maneuver, and the number of tugboats used was also fixed at six.
Esposito et al. (2008) presented a strategy that allowed a swarm of autonomous tugboats to move a large object on the water. A tracking controller and force allocation strategy were suggested and verified using a 1:36 scale model of a U.S. Navy ship. The thrust allocation was performed by solving the linearly constrained least-squares problem to obtain the thrust forces and tug force directions of the tugboats. Bidikli et al. (2016) proposed a robust controller for an unactuated surface vessel manipulated by autonomous tugboats. The stability of the novel control methodology was investigated via Lyapunov stability analysis. They used tug force direction as a fixed average value that changes over time as a sinusoidal function.
Studies using optimization techniques were conducted to allocate the thrust force of tugboats.
Bui et al. (2011) and Bui and Kim (2011) proposed an approach for ship berthing with the assistance of autonomous tugboats. An adaptive controller and sliding mode controller were presented to cope with the uncertainty of the system. The thrust force and tug force direction were determined by using a redistributed pseudo-inverse (RPI) algorithm in these studies, and the number of tugboats used was also fixed at four.
Similarly, Gao et al. (2019) used the optimization technique for controlling the thrusters of a ship. They controlled the ship with three azimuth thrusters and one tunnel thrust using an optimization method to follow a specific trajectory. Also, Kamil et al. (2019) analysed ship berthing, which is similar to this study.
Shi et al. [2021] numerically evaluated the resistance at full scale of a zero-emission, highspeed catamaran, in both deep and shallow water, for a Froude number (Fn) ranging from 0.2 to 0.8. The numerical methods are validated by the available model and a blind validation, using two different flow solvers. The total resistance is highly affected by the pressure component, which is maximized at Fn = 0.58 in deep water and at Fn = 0.30 in shallow water, when the secondary trough is created at the stern, leading to the largest trim angle. The vessel witnesses a hump near the critical speed (Fn = 0.30) in shallow water, due to the interaction between the wave systems created by the demi-hulls.
Deng et al. [2021] study the principal dimensions and the hull form of a bulk carrier, to optimize its hydrodynamic performance. They considered ship resistance and seakeeping, while maneuverability was estimated by empirical methods. A new parent ship was chosen from 496 sets of hulls, after comprehensive consideration. A further hull form optimization was performed on the new parent ship, according to the minimum wave-making resistance.
He concluded that optimization with respect to the principal dimensions provides a high quality parent ship, which can be further optimized for both the principal dimensions and the hull form parameters.
Zoon and Park [2021] use the component mode method to carry out vibration analyses when they design local structures on ships. The method provides natural mode functions and, eventually, reasonable natural frequencies. In their study, they use adaptive polynomials as additional flexible model functions, or a purely mathematical approach, with very good numerical results.
Xu et al. [2021] used an RBF (radial basis function) neural network and NSGA-II (non-dominated sorting genetic algorithm) to optimize the hydraulic performance of the annular jet pump applied in submarine trenching and dredging. The suction angle, diffusion angle, area ratio and flow ratio were selected as the design variables. On the basis of CFD numerical simulation, an RBF neural network approximation model was established.
Finally, the NSGA-II algorithm was selected to carry out multi-objective optimization and obtain the optimal design variable combination. The results show that both optimization criteria, the jet pump efficiency and the head ratio, were accurately modelled via the RBF neural network, while the optimization resulted in a 30% increase in the head ratio and a slight improvement in the efficiency.
Doctors [2021] revisited the hydrodynamics supporting the design and development of the RiverCat class of catamaran ferries, which have operated in Sydney Harbor since 1991. They used more advanced software to account for the hydrodynamics of the transom demi-sterns that experience partial or full ventilation, depending on the vessel speed, which gives rise to hydrostatic drag. On the other hand, the transom creates hollowness in the water, causing effective hydrodynamic lengthening of the vessel, leading to a reduction in the wave resistance. The associated detailed analysis quite accurately predicts the phenomena and allows for the optimization of the vessel using affine transformations of the hull geometry, including the size of the transom.
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