Comparative Evaluation of Design Variations in Prototype Fast Boats: A Hydrodynamic Characteristic-Based Approach.

Autor: Diatmaja, Hananta, Prabowo, Aditya Rio, Adiputra, Ristiyanto, Muhayat, Nurul, Seung Jun Baek, Huda, Nurul, Tuswan, Tuswan, Zubaydi, Achmad, Nubli, Haris
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Zdroj: Mathematical Modelling of Engineering Problems; Oct2023, Vol. 10 Issue 5, p1487-1507, 21p
Abstrakt: As one of the world's largest archipelagic nations, Indonesia is tasked with the crucial responsibility of supervising and protecting its territorial waters from threats such as illegal fishing and damage to coral reefs. The effective and efficient execution of this task relies heavily on the use of fast patrol boats. Consequently, the need to investigate the hydrodynamic characteristics of these boats’ hulls is paramount. This study is primarily focused on the analysis and design of fast patrol boat hull prototypes. Our objective is to ascertain a practical design methodology that yields the optimal shape and size of the boat's hull. The adopted research methodology involved the design and analysis of eleven hull prototypes, evaluated based on resistance, stability, and seakeeping criteria. Five models were adapted from the reference ship, with a deadweight tonnage (DWT) variation of 2-3.5 tons. Three models employed the regression method with a block coefficient (CB) variation of 0.45-0.46, while the remaining three models utilized the scaling method, derived from the reference ship with the lowest resistance. The models in both the regression and scaling methods applied the primary size derived from the linear regression results of the five reference vessels. From the analysis, it was found that models developed using the regression method demonstrated superior hydrodynamic characteristics, denoted by consistently higher total values. This research provides valuable insights for the development of efficient fast patrol boats, which is crucial for the effective management of Indonesia's expansive maritime territory. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index