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Computer-aided system for layout of fire hydrants on boards designed vessel using the Particle Swarm Optimization algorithm

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Języki publikacji
EN
Abstrakty
EN
The functional layout of fire safety equipment in technical spaces of ships is a time-consuming process. When designing a ship fire protection system, the designer must manually position each system component in such a way as to meet the requirements of regulations arising from the technical specification, various legal regulations of maritime conventions and classification societies of the vessel to be designed. Layout of fire hydrants assisted by a computer that is based on pre-defined criteria and various constraints could significantly support the designer in working easier and faster. This paper presents a prototype computer-aided design system that enables optimal placement of fire hydrants using the metaheuristic Particle Swarm Optimization (PSO) algorithm. This algorithm was used in Rhinoceros 3D software with its Grasshopper plugin for visualizing the arrangement of fire safety equipment. Various solution arrangements compared with the fire hydrant placement in real ships are illustrated by a case study. Demonstrating how design work can be facilitated and what potential benefits can be achieved are presented as well.
Słowa kluczowe
Rocznik
Tom
Strony
4--16
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
  • Damen Engineering Gdansk, Gdansk
  • Gdansk University of Technology, Gdansk, Poland
Bibliografia
  • 1. R. J. Cant and C. S. Langensiepen, “Methods for Automated Object Placement in Virtual Scenes,” in 11th International Conference on Computer Modelling and Simulation, UKSim 2009, 2009. doi: 10.1109/UKSIM.2009.69.
  • 2. K. Xu, J. Stewart, and E. Fiume, “Constraint-based automatic placement for scene composition,” in Proceedings – Graphics Interface, 2002.
  • 3. R. Z. Farahani, N. Asgari, N. Heidari, M. Hosseininia, and M. Goh, “Covering problems in facility location: A review,” Computers and Industrial Engineering, vol. 62, no. 1. 2012. doi: 10.1016/j.cie.2011.08.020.
  • 4. S. Dantrakul, C. Likasiri, and R. Pongvuthithum, “Applied p-median and p-center algorithms for facility location problems,” Expert Syst Appl, vol. 41, no. 8, 2014, doi: 10.1016/j.eswa.2013.11.046.
  • 5. B. Zhang, J. Peng, and S. Li, “Covering location problem of emergency service facilities in an uncertain environment,” Appl Math Model, vol. 51, 2017, doi: 10.1016/j. apm.2017.06.043.
  • 6. S. Y. Kim, B. Y. Moon, and S. C. Shin, “Evaluation criterion of machinery arrangement design in a ship engine room,” Journal of Ship Production, vol. 25, no. 3, 2009, doi: 10.5957/ jsp.2009.25.3.117.
  • 7. P. Gualeni, F. Perrera, M. Raimondo, and T. Vairo, “Accessibility for maintenance in the engine room: development and application of a prediction tool for operational costs estimation,” Ship Technology Research, 2022, doi: 10.1080/09377255.2021.2020949.
  • 8. J. K. Lee, K. H. Lee, N. S. Park, Y. U. Jang, J. Y. Bae, and H. S. Shim, “Integration of knowledge-base and CAD system for the machinery layout design of ships,” in Proceedings of the ASME Design Engineering Technical Conference, 1996. doi: 10.1115/96-DETC/DAC-1070.
  • 9. A. R. Chaudhuri and U. P. Thakur, “Design criteria of piping system for ships,” Journal of the Institution of Engineers (India), Part MR: Marine Engineering Division, vol. 81, no. 1, 2000.
  • 10. B. C. Lee, Y. Choi, and H. Chung, “Firefighting equipment arrangement optimization for an offshore platform considering travel distances,” J Mar Sci Eng, vol. 9, no. 5, 2021, doi: 10.3390/jmse9050503.
  • 11. X. Liu, B. Sun, Z. D. Xu, and X. Liu, “An adaptive Particle Swarm Optimization algorithm for fire source identification of the utility tunnel fire,” Fire Saf J, vol. 126, 2021, doi: 10.1016/j.firesaf.2021.103486.
  • 12. K. S. Lee, K. J. Han, and J. W. Lee, “Feasibility study on parametric optimization of daylighting in building shading design,” Sustainability (Switzerland), vol. 8, no. 12, 2016, doi: 10.3390/su8121220.
  • 13. D. Rutten, “Galapagos: On the logic and limitations of generic solvers,” Architectural Design, vol. 83, no. 2, 2013, doi: 10.1002/ad.1568.
  • 14. C. Waibel, T. Wortmann, R. Evins, and J. Carmeliet, “Building energy optimization: An extensive benchmark of global search algorithms,” Energy Build, vol. 187, 2019, doi: 10.1016/j.enbuild.2019.01.048.
  • 15. J. M. Cichocka, A. Migalska, W. N. Browne, and E. Rodriguez, “SILVEREYE – The implementation of particle swarm optimization algorithm in a design optimization tool,” in Communications in Computer and Information Science, 2017. doi: 10.1007/978-981-10-5197-5_9.
  • 16. T. Wortmann, “Opossum – Introducing and Evaluating a Model-based Optimization Tool for Grasshopper,” in Proceedings of the 22nd Conference on Computer Aided Architectural Design Research in Asia (CAADRIA), 2022. doi: 10.52842/conf.caadria.2017.283.
  • 17. I. Anton and D. TĂnase, “Informed Geometries. Parametric Modelling and Energy Analysis in Early Stages of Design,” in Energy Procedia, 2016. doi: 10.1016/j.egypro.2015.12.269.
  • 18. J. C. Lagarias, J. A. Reeds, M. H. Wright, and P. E. Wright, “Convergence properties of the Nelder-Mead simplex method in low dimensions,” SIAM Journal on Optimization, vol. 9, no. 1, 1998, doi: 10.1137/S1052623496303470.
  • 19. J. Kennedy and R. Eberhart, “Particle Swarm Optimization, Proceedings of IEEE International Conference on Neural Networks Vol. IV: 1942–1948.,” Neural Networks.
  • 20. L. M. Hiot et al., Handbook of Swarm Intelligence, vol. 8. 2010.
  • 21. S. Bhattacharyya and P. Dutta, Handbook of research on swarm intelligence in engineering. 2015. doi: 10.4018/978-1-4666-8291-7.
  • 22. G. O. Brown, “The history of the Darcy-Weisbach equation for pipe flow resistance,” in Proceedings of the Environmental and Water Resources History, 2002. doi: 10.1061/40650(2003)4.
  • 23. K. Rudzki, P. Gomulka, and A. T. Hoang, “Optimization Model to Manage Ship Fuel Consumption and Navigation Time,” Polish Maritime Research, vol. 29, no. 3, 2022, doi: 10.2478/pomr-2022-0034.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-bf4d5165-44e9-4b20-9e32-4b39d22648bb
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