Sameer Al-Dahidi (B.Sc. in Electrical Engineering, The Hashemite University, 2008; M.Sc. in Nuclear Energy - Operations Specialty - Ecole Centrale Paris and Université Paris - Sud 11, 2012; Ph.D. in Energetic and Nuclear Science and Technology (specific major is Predictive Maintenance in Energy Production Plants), Politecnico di Milano, 2016) is an Assistant Professor at the Mechanical and Maintenance Engineering Department, School of Applied Technical Sciences at the German Jordanian University since February, 2018.
His research aims at studying, developing and applying efficient computational methods and soft computing techniques (ensemble system, kernel regression methods, clustering techniques, etc.) for 1) addressing a number of open issues relevant for system health monitoring, fault diagnosis and prognosis, safety, risk analysis, maintenance optimization and handling the uncertainty and ambiguity in the information in safety-relevant industries such as nuclear and oil and gas and 2) the prediction of renewable energy productions.
In 2008-2010, he worked as an Electrical & Instruments Engineer at CCIC and Kharafi National in Oil & Gas and petrochemical mega projects in Kuwait and UAE. In 2010 and 2011, he did his internships at AREVA NP as part of his M.Sc. study in France.
Developing of computational methods and models for:
1) Health management (condition monitoring, diagnostics and prognostics, maintenance) of complex industrial components, systems and plants for improving operation and maintenance practices and increasing reliability, availability, production performance and safety while reducing overall corrective maintenance costs;
2) Renewable energy production prediction
Assistant Professor, Mechanical and Maintenance Engineering Department, School of Applied Technical Sciences, German Jordanian University, Madaba, Jordan.
Part-Time Lecturer, Mechanical Engineering Department, The Hashemite University, Zarqa, Jordan.
Post-Doctoral Research Fellow, Energy Department, Politecnico di Milano, Milan, Italy.
Early Stage Researcher at InnHF EU Project (Project ID 289837), Energy Department, Politecnico di Milano, Milan, Italy.
Visiting Ph.D. Candidate (Secondment Period – Research Collaboration), Chair System Science and the Energy Challenge, Fondation Electricité de France (EDF), CentraleSupélec, Laboratory of Industrial Engineering, Paris, France.
Visiting Ph.D. Candidate (Secondment Period – Research Collaboration), Chair System Science and the Energy Challenge, Fondation Electricité de France (EDF), CentraleSupélec, Laboratory of Industrial Engineering, Paris, France.
at HEMIS EU Project (Project reference FP7-ICT-314609, www.hemis-eu.org), Energy Department, Politecnico di Milano, Milan, Italy.
Master Student Intern (M2), AREVA NP, Paris La Defense, France.
Master Student Intern (M1), AREVA NP, Paris La Defense, France.
Electrical & Instruments Engineer (E&I), Consolidated Contractors International Company (CCIC), Abu-Dhabi, UAE.
Graduate Electrical & Instruments Engineer (E&I), Kharafi National Limited Company, Kuwait.
Lab Supervisor, Electrical Engineering Department, The Hashemite University, Jordan.
| 2019 | Al-Kouz, W.*; Al-Dahidi, S.*; Hammad, B.; Al-Abed, M,"Modeling and Analysis Framework for Investigating the Impact of Dust and Temperature on PV Systems’ Performance and Optimum Cleaning Frequency",Applied Sciences,9, 1397,2019 |
| 2019 | S. Al-Dahidi, O. Ayadi, M. Alrbai, and J. Adeeb,"Ensemble Approach of Optimized Artificial Neural Networks for Solar Photovoltaic Power Prediction",IEEE Access,vol. 7, 81741 - 81758,2019 |
| 2019 | O. Ayadi*, and S. Al-Dahidi,"Comparison of solar thermal and solar electric space heating and cooling systems for buildings in different climatic regions",Solar Energy, vol. 188, 545-560,2019 |
| 2018 | S. Al-Dahidi, O. Ayadi, J. Adeeb, M. Alrbai, B.R. Qawasmeh,"Extreme Learning Machines for Solar Photovoltaic Power Predictions",Energies,,vol. 11, 2725,2018 [View] |
| 2018 | S. Al-Dahidi, F. Di Maio, P. Baraldi, E. Zio, and R. Seraoui,"A Framework for Reconciliating Data Clusters from a Fleet of Nuclear Power Plants Turbines for Fault Diagnosis", Applied Soft Computing Journal,vol. 69, pp. 213-231,2018 [View] |
| 2017 | P. Baraldi, F. Di Maio, S. Al-Dahidi, E. Zio, and F. Mangili,"Prediction of Industrial Equipment Remaining Useful Life by Fuzzy Similarity and Belief Function Theory",Expert Systems with Applications,ISSN 0957-4174,2017 [View] |
| 2017 | S. Al-Dahidi, F. Di Maio, P. Baraldi, and E. Zio,"A Locally Adaptive Ensemble Approach for Data-Driven Prognostics of Heterogeneous Fleets",Journal of Risk and Reliability (Part O),Special issue of ESREL 2015. pp. 1-14,2017 [View] |
| 2016 | S. Al-Dahidi, F. Di Maio, P. Baraldi, and E. Zio,"Remaining Useful Life Estimation in Heterogeneous Fleets Working under Variable Operating Conditions",Reliability Engineering and System Safety Journal, vol. 156, pp. 109-124,2016 [View] |
| 2015 | S. Al-Dahidi, F. Di Maio, P. Baraldi, E. Zio, and R. Seraoui,"A Novel Ensemble Clustering for Operational Transients Classification with Application to a Nuclear Power Plant Turbine",International Journal of Prognostics and Health Management, vol. 6 (001-Special Issue Nuclear Energy PHM), pp. 1-21. ISSN 2153-2648,2015 |
| 2014 | S. Al-Dahidi, F. Di Maio, P. Baraldi, and E. Zio,"A Novel Fault Detection System Taking into Account Uncertainties in the Reconstructed Signals",Annals of Nuclear Energy,vol. 73, pp. 131-144,2014 [View] |
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