معرفی
Dr Saed Alrawash is a former researcher at Lancaster University with a PhD in Nuclear Engineering from Sejong University. His research focuses on applying machine learning and Monte Carlo methods to address challenges in nuclear safety and reactor design, particularly in locating Fukushima Daiichi fuel debris and optimizing nuclear fuel components. He holds extensive industry experience as a nuclear engineer at the Jordan Research and Training Reactor (2012-2017).
Education: PhD in Nuclear Engineering (2021, Sejong University).
Research Interests: Machine learning applications in radiation detection, nuclear core design simulations, Monte Carlo depletion analysis, and criticality safety studies. His work bridges advanced computational techniques with practical nuclear engineering problems such as spent fuel management and reactor commissioning challenges.
Publications & Datasets: Authored/co-authored peer-reviewed publications on fuel debris localization, burnable absorber studies, and criticality safety analysis. Associated with datasets on diamond detector calibration, neutron flux simulations, and Fukushima fuel debris prediction (available via Lancaster University repository).
