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Open Access research that is tackling the climate emergency...

Addressing the energy challenge confronting society is a strategic research theme for Strathclyde. Researchers from across the institution, spanning multiple disciplines, are therefore working together to understand ways of reducing the environmental impacts of energy use, improving energy efficiency, coping with declining fossil fuel supplies, managing an ageing energy infrastructure, and devising policy or economic levers to achieve higher penetration of renewable energy systems and technologies. Strathprints makes this scholarly research content available Open Access thereby ensuring results are available to everyone in order meet the global climate challenge.

Explore some of this Open Access research from the departments of Mechanical & Aerospace Engineering, Electronic & Electrical Engineering, Civil & Environmental Engineering, Naval Architecture, Ocean & Marine Engineering, Economics, Entrepreneurship and the School of Government & Public Policy.

Or explore all of Strathclyde's Open Access research...

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Group by: Publication Date | Item type | No Grouping
Jump to: 2020 | 2018 | 2017 | 2016 | 2015
Number of items: 11.

2020

Raptodimos, Yiannis and Lazakis, Iraklis (2020) Application of NARX neural network for predicting marine engine performance parameters. Ships and Offshore Structures, 15 (4). pp. 443-452. ISSN 1754-212X

2018

Lazakis, I. and Raptodimos, Y. and Varelas, T. (2018) Predicting ship machinery system condition through analytical reliability tools and artificial neural networks. Ocean Engineering, 152. pp. 404-415. ISSN 0029-8018

Raptodimos, Yiannis and Lazakis, Iraklis (2018) Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications. Ships and Offshore Structures, 13 (6). pp. 649-656. ISSN 1754-212X

Raptodimos, Yiannis and Lazakis, Iraklis; (2018) Implementing unsupervised learning algorithm for marine engine data clustering applications. In: Proceedings of the 2018 Smart Ship Technology Conference. Royal Institution of Naval Architects, GBR.

2017

Raptodimos, Y and Lazakis, I; (2017) Fault tree analysis and artificial neural network modelling for establishing a predictive ship machinery maintenance methodology. In: International Conference on Smart Ship Technology 2017. Royal Institution of Naval Architects, GBR.

2016

Raptodimos, Yiannis and Lazakis, Iraklis; (2016) An artificial neural network approach for predicting the performance of ship machinery equipment. In: Maritime Safety and Operations 2016 Conference Proceedings. University of Strathclyde Publishing, GBR, pp. 95-101.

Dikis, K. and Lazakis, I. and Michala, A. L. and Raptodimos, Y. and Theotokatos, G.; Walls, Lesley and Revie, Matthew and Bedford, Tim, eds. (2016) Dynamic risk and reliability assessment for ship machinery decision making. In: Risk, Reliability and Safety. CRC/Taylor & Francis Group, GBR, pp. 685-692. ISBN 9781315374987

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Salinas, Raul and Moreno, Alfonso; Jin, HyunWoo and Tang, Huang and Akselsen, Odd M. and Lee, Yongwon, eds. (2016) Collection and analysis of data for ship condition monitoring aiming at enhanced reliability and safety. In: Proceedings of The Twenty-sixth (2016) International Ocean and Engineering Conference. Proceedings of the Annual International Offshore and Polar Engineering Conference, 4 . International Society of Offshore and Polar Engineers, GRC, pp. 828-835. ISBN 9781880653883

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Varelas, Takis and Drikos, Leonidas (2016) Ship sensors data collection and analysis for condition monitoring of ship structures and machinery systems. In: Smart Ship Technology, 2016-01-26 - 2016-01-27, The Royal Institution of Naval Architects.

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Varelas, Takis and Drikos, Leonidas; (2016) Ship sensors data collection and analysis for condition monitoring of ship structures and machinery systems. In: International Conference on Smart Ship Technology 2016. Royal Institution of Naval Architects, GBR. ISBN 9781909024502

2015

Raptodimos, Y. and Lazakis, I. and Varelas, T. and Papadakis, A. and Drikos, L. (2015) Defining ship structural and machinery onboard measurement campaign for energy efficient operations. In: International Conference on Shipping in Changing Climates, 2015-11-24 - 2015-11-26, Technology & Innovation Centre.

This list was generated on Tue Feb 7 21:22:18 2023 GMT.