PhD thesis supervisor: dr. Rita Plukienė (apply for recommendation)
Optimization of spectrometric equipment of the Digital Twin of the Radiological Systems Network for radiation risk prediction in case of nuclear contamination
Due to the development of nuclear energy and the emergence of new nuclear facilities near the territory of Lithuania (Belarusian NPP, planned Polish NPP network) as well as the changing geopolitical situation, it is very important to optimize the radiation risk monitoring and nuclear emergency preparedness system in Lithuania. The radiological systems network acts as a Digital Twin, the purpose of which is to identify the source of radionuclides in real time after any nuclear incident, assess the risk of contamination and provide risk mitigation measures. The main focus of the work will be on the optimization of nuclear spectrometry methods used in the network. The aim is to optimize the analysis of gamma spectra using numerical simulations applying Monte Carlo modeling, which will facilitate the separation of overlapping gamma peaks, identification of radionuclides and assessment of their activity as well as the separation of sources of different origin. It is planned to optimize the methods for the identification and determination of activity of short-lived radionuclides measured in the network. It is also planned to use modern artificial intelligence-based software tools for faster spectrum analysis. It is planned to develop a data-driven gamma spectrum analysis package that includes (i) a trained model with clear artificial intelligence application scenarios, (ii) reference data sets created on the basis of Monte Carlo modeling, and (iii) an assessment of the performance and uncertainty of different detector types.