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Original scientific paper

STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL

Ozren Bukovac   ORCID icon orcid.org/0000-0002-4388-0234 ; Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka
Vladimir Medica ; Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka
Vedran Mrzljak   ORCID icon orcid.org/0000-0003-0323-2600 ; Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka

Fulltext: english, pdf (899 KB) pages 57-70 downloads: 492* cite
APA 6th Edition
Bukovac, O., Medica, V. & Mrzljak, V. (2015). STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL. Brodogradnja, 66 (4), 57-70. Retrieved from https://hrcak.srce.hr/149804
MLA 8th Edition
Bukovac, Ozren, et al. "STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL." Brodogradnja, vol. 66, no. 4, 2015, pp. 57-70. https://hrcak.srce.hr/149804. Accessed 3 Aug. 2021.
Chicago 17th Edition
Bukovac, Ozren, Vladimir Medica and Vedran Mrzljak. "STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL." Brodogradnja 66, no. 4 (2015): 57-70. https://hrcak.srce.hr/149804
Harvard
Bukovac, O., Medica, V., and Mrzljak, V. (2015). 'STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL', Brodogradnja, 66(4), pp. 57-70. Available at: https://hrcak.srce.hr/149804 (Accessed 03 August 2021)
Vancouver
Bukovac O, Medica V, Mrzljak V. STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL. Brodogradnja [Internet]. 2015 [cited 2021 August 03];66(4):57-70. Available from: https://hrcak.srce.hr/149804
IEEE
O. Bukovac, V. Medica and V. Mrzljak, "STEADY STATE PERFORMANCES ANALYSIS OF MODERN MARINE TWO-STROKE LOW SPEED DIESEL ENGINE USING MLP NEURAL NETWORK MODEL", Brodogradnja, vol.66, no. 4, pp. 57-70, 2015. [Online]. Available: https://hrcak.srce.hr/149804. [Accessed: 03 August 2021]

Abstracts
Compared to the other marine engines for ship propulsion, turbocharged two-stroke low speed diesel engines have advantages due to their high efficiency and reliability. Modern low speed ”intelligent” marine diesel engines have a flexibility in its operation due to the variable fuel injection strategy and management of the exhaust valve drive. This paper carried out verified zerodimensional numerical simulations which have been used for MLP (Multilayer Perceptron) neural network predictions of marine two-stroke low speed diesel engine steady state performances. The developed MLP neural network was used for marine engine optimized operation control. The paper presents an example of achieving lowest specific fuel consumption and for minimization of the cylinder process highest temperature for reducing NOx emission. Also, the developed neural network was used to achieve optimal exhaust gases heat flow for utilization. The obtained data maps give insight into the optimal working areas of simulated marine diesel engine, depending on the selected start of the fuel injection (SOI) and the time of the exhaust valve opening (EVO).

Keywords
Marine two-stroke diesel engine; MLP neural network; Numerical simulation; Utilization; Start of fuel injection; Time of exhaust valve open

Hrčak ID: 149804

URI
https://hrcak.srce.hr/149804

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