Optimization of space under main deck on landing craft utility (LCU) ships to increase loading capacity

• Autorzy: Sugeng S. , Ridwan M. , Sulaiman S. , Khristyson S. F.

Identyfikatory

DOI

10.12716/1001.16.01.10

• Języki publikacji: EN

Abstrakty

EN

With this optimization, the cargo will increase and the ship's revenue will also be more. The LCU ship that we know so far is a ship whose cargo is always above the main and the space under the main is unused Void Space. The purpose of this study is to determine the optimization value of the use of space under the main deck of the Landing Craft Utility (LCU) ships. method used in this study is a comparison with several previous ship approaches to produce evaluation results from the addition of loading space under the main deck and calculation of stability using computational software approximation. LCU design of under main deck space with a maximum vehicle value can accept a vertical moment of 2750 mm. With a structural strength of 13150 tons. A series of numerical experiments show that the proposed method can effectively produce a satisfactory LCU ship design optimization plan for ship owners.

Słowa kluczowe

EN

landing craft utility; loading capacity; main deck; void space; space under main deck; ship's stability; maximum vehicle value; ship's revenue

• Wydawca: Faculty of Navigation, Gdynia Maritime University
• Czasopismo: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
• Rocznik: 2022
• Tom: Vol. 16 No. 1
• Strony: 99--103
• Opis fizyczny: Bibliogr 21 poz., rys., tab.

Twórcy

autor

Sugeng S.

• Diponegoro University, Semarang, Indonesia

autor

Ridwan M.

• Diponegoro University, Semarang, Indonesia

autor

Sulaiman S.

• Diponegoro University, Semarang, Indonesia

autor

Khristyson S. F.

• Diponegoro University, Semarang, Indonesia

Bibliografia

• 1. Andersson, J. et al.: Review and comparison of methods to model ship hull roughness. Applied Ocean Research.103 99, 102119 (2020). https://doi.org/10.1016/j.apor.2020.102119.
• 2. Andric, J. et al.: Influence of different topological variants on optimized structural scantlings of passenger ship. Marine Structures. 78, 102981 (2021). https://doi.org/10.1016/j.marstruc.2021.102981.
• 3. Andric, J. et al.: Multi-level Pareto supported design methodology- application to RO-PAX structural design. Marine Structures. 67, 102638 (2019). https://doi.org/10.1016/j.marstruc.2019.102638.
• 4. Bulian, G. et al.: Complementing SOLAS damage ship stability framework with a probabilistic description for the extent of collision damage below the waterline. Ocean Engineering. 186, 106073 (2019). https://doi.org/10.1016/j.oceaneng.2019.05.055.
• 5. Cepowski, T.: The prediction of ship added resistance at the preliminary design stage by the use of an artificial neural network. Ocean Engineering. 195, 106657 (2020). https://doi.org/10.1016/j.oceaneng.2019.106657.
• 6. Dogrul, A. et al.: Scale effect on ship resistance components and form factor. Ocean Engineering. 209, 107428 (2020). https://doi.org/10.1016/j.oceaneng.2020.107428.
• 7. Francescutto, A.: Intact stability criteria of ships – Past, present and future. Ocean Engineering. 120, 312–317 (2016). https://doi.org/10.1016/j.oceaneng.2016.02.030.
• 8. Fu, T. et al.: Simulating the dynamic behavior and energy consumption characteristics of frozen sandy soil under impact loading. Cold Regions Science and Technology. 166, 102821 (2019). https://doi.org/10.1016/j.coldregions.2019.102821.
• 9. Jafaryeganeh, H. et al.: Application of multi-criteria decision making methods for selection of ship internal layout design from a Pareto optimal set. Ocean Engineering. 202, 107151 (2020). https://doi.org/10.1016/j.oceaneng.2020.107151.
• 10. Kaidi, S. et al.: Numerical modelling of the muddy layer effect on Ship’s resistance and squat. Ocean Engineering. 199, 106939 (2020). https://doi.org/10.1016/j.oceaneng.2020.106939.
• 11. Peng, H. et al.: Wave pattern and resistance prediction for ships of full form. Ocean Engineering. 87, 162–173 (2014). https://doi.org/10.1016/j.oceaneng.2014.06.004.
• 12. Priftis, A. et al.: Multi-objective robust early stage ship design optimisation under uncertainty utilising surrogate models. Ocean Engineering. 197, 106850 (2020). https://doi.org/10.1016/j.oceaneng.2019.106850.
• 13. Skoupas, S. et al.: Parametric design and optimisation of high-speed Ro-Ro Passenger ships. Ocean Engineering. 189, 106346 (2019). https://doi.org/10.1016/j.oceaneng.2019.106346.
• 14. Song, S. et al.: Validation of the CFD approach for modelling roughness effect on ship resistance. Ocean Engineering. 200, 107029 (2020). https://doi.org/10.1016/j.oceaneng.2020.107029.
• 15. Tan, X. et al.: Preliminary design of a tanker ship in the context of collision-induced environmental-risk-based ship design. Ocean Engineering. 181, 185–197 (2019). https://doi.org/10.1016/j.oceaneng.2019.04.003.
• 16. Terziev, M. et al.: A posteriori error and uncertainty estimation in computational ship hydrodynamics. Ocean Engineering. 208, 107434 (2020). https://doi.org/10.1016/j.oceaneng.2020.107434.
• 17. Tillig, F., Ringsberg, J.W.: Design, operation and analysis of wind-assisted cargo ships. Ocean Engineering. 211, 107603 (2020). https://doi.org/10.1016/j.oceaneng.2020.107603.
• 18. Weintrit, A., Neumann, T.: Advances in marine navigation and safety of sea transportation. Introduction. Advances in Marine Navigation and Safety of Sea Transportation - 13th International Conference on Marine Navigation and Safety of Sea Transportation, TransNav 2019. 1 (2019).
• 19. Weintrit, A., Neumann, T.: Safety of marine transport introduction. In: Safety of Marine Transport: Marine Navigation and Safety of Sea Transportation. pp. 1–4 (2015).
• 20. Yuan, Y. et al.: A design and experimental investigation of a large-scale solar energy/diesel generator powered hybrid ship. Energy. 165, 965–978 (2018). https://doi.org/10.1016/j.energy.2018.09.085.
• 21. Zhang, W. et al.: An integrated ship segmentation method based on discriminator and extractor. Image and Vision Computing. 93, 103824 (2020). https://doi.org/10.1016/j.imavis.2019.11.002.