Improvement of Marine Steam Turbine Conventional Exergy Analysis by Neural Network Application
1
Department of Automation and Electronics, Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia
2
Department of Thermodynamics and Energy Engineering, Faculty of Engineering, University of Rijeka, Vukovarska 58, 51000 Rijeka, Croatia
*
Author to whom correspondence should be addressed.
J. Mar. Sci. Eng. 2020, 8(11), 884; https://doi.org/10.3390/jmse8110884
Received: 13 October 2020 / Revised: 2 November 2020 / Accepted: 3 November 2020 / Published: 5 November 2020
(This article belongs to the Special Issue Marine Power Systems)
This article presented an improvement of marine steam turbine conventional exergy analysis by application of neural networks. The conventional exergy analysis requires numerous measurements in seven different turbine operating points at each load, while the intention of MLP (Multilayer Perceptron) neural network-based analysis was to investigate the possibilities for measurements reducing. At the same time, the accuracy and precision of the obtained results should be maintained. In MLP analysis, six separate models are trained. Due to a low number of instances within the data set, a 10-fold cross-validation algorithm is performed. The stated goal is achieved and the best solution suggests that MLP application enables reducing of measurements to only three turbine operating points. In the best solution, MLP model errors falling within the desired error ranges (Mean Relative Error) MRE < 2.0% and (Coefficient of Correlation) R2 > 0.95 for the whole turbine and each of its cylinders.
View Full-Text
Keywords:
exergy destruction; exergy efficiency; marine steam turbine; MLP neural network; turbine cylinders
▼
Show Figures
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
MDPI and ACS Style
Baressi Šegota, S.; Lorencin, I.; Anđelić, N.; Mrzljak, V.; Car, Z. Improvement of Marine Steam Turbine Conventional Exergy Analysis by Neural Network Application. J. Mar. Sci. Eng. 2020, 8, 884. https://doi.org/10.3390/jmse8110884
AMA Style
Baressi Šegota S, Lorencin I, Anđelić N, Mrzljak V, Car Z. Improvement of Marine Steam Turbine Conventional Exergy Analysis by Neural Network Application. Journal of Marine Science and Engineering. 2020; 8(11):884. https://doi.org/10.3390/jmse8110884
Chicago/Turabian StyleBaressi Šegota, Sandi; Lorencin, Ivan; Anđelić, Nikola; Mrzljak, Vedran; Car, Zlatan. 2020. "Improvement of Marine Steam Turbine Conventional Exergy Analysis by Neural Network Application" J. Mar. Sci. Eng. 8, no. 11: 884. https://doi.org/10.3390/jmse8110884
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
Search more from Scilit