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DC Field | Value | Language |
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dc.contributor.author | Palagi, L | - |
dc.contributor.author | Pesyridis, A | - |
dc.contributor.author | Sciubba, E | - |
dc.contributor.author | Tocci, L | - |
dc.date.accessioned | 2018-10-15T13:44:44Z | - |
dc.date.available | 2018-10-15T13:44:44Z | - |
dc.date.issued | 2018-10-13 | - |
dc.identifier.citation | Palagi, L., Pesyridis, A., Sciubba, E. and Tocci, L. (2019) 'Machine Learning for the prediction of the dynamic behavior of a small scale ORC system', Energy, 166, pp. 72-82. doi: 10.1016/j.energy.2018.10.059. | en_US |
dc.identifier.issn | 0360-5442 | - |
dc.identifier.uri | https://bura.brunel.ac.uk/handle/2438/16991 | - |
dc.description.sponsorship | This work was funded by the 2016 Scholarship of the Knowledge Center on OrganicRankine Cycle (KC ORC, www.kcorc.org), awarded to Lorenzo Tocci to work on this researchproject with Dr Pesyridis at Brunel University London. Entropea Labs is also acknowledgedfor the economic and technical support provided during the completion of this study. | - |
dc.description.sponsorship | 2016 Scholarship of the Knowledge Center on Organic Rankine Cycle (KC ORC, www.kcorc.org) | - |
dc.format.medium | Print-Electronic | - |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | artificial neural networks | en_US |
dc.subject | ORC | en_US |
dc.subject | dynamic system | en_US |
dc.subject | experimental ORC | en_US |
dc.title | Machine Learning for the prediction of the dynamic behavior of a small scale ORC system | en_US |
dc.type | Article | en_US |
dc.identifier.doi | https://doi.org/10.1016/j.energy.2018.10.059 | - |
dc.relation.isPartOf | Energy | - |
pubs.publication-status | Published | - |
dc.identifier.eissn | 1873-6785 | - |
Appears in Collections: | Dept of Mechanical and Aerospace Engineering Research Papers |
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Fulltext.pdf | 1.37 MB | Adobe PDF | View/Open |
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