ul. Andrzeja Sołtana 7
michal.jedrzejczyk@ncbj.gov.pl
+48 22 273 1687
PhD Topic: Applying Approximate Bayesian Computation to reduce nuclear data uncertainties
Supervisor: Prof. Tomasz Kozłowski
The multiplication factor (keff) is a key parameter describing the dynamics of nuclear reactors. The uncertainty in its calculated value mostly originates from the imprecision with which neutron cross sections are known and is currently relatively large in simulations of any critical systems. In the last two decades, great advances have been made in regards to computational powers and Bayesian inference algorithms. The aim of this PhD is to use these advances, along with results of documented criticality experiments, to decrease the uncertainty in chosen neutron cross section values. This will in turn increase the precision with which keff is calculated, leading to the possibility of creating more robust nuclear reactor designs.
Seminars and conference talks:
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- Establishment of reasonable model to simulate emergency passive coolant system in HTTR reactor. 03.11.2020, Otwock, NCBJ, Division of Nuclear Energy and Environmental Studies.
- Applying Approximate Bayesian Computation to reduce nuclear data uncertainties. 09.12.2021, Warsaw, Poland, Graduate School of Physics and Chemistry.
Courses:
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- Statistical Mechanics – Prof. Stanisław Mrówczyński
- Physics of Nuclear Energy – Prof. Wacław Gudowski
- Scientific Writing – Dr. Andrzej Kupść
- Self-Management – Dr. Stefan Bulaszewski
- Advanced statistical techniques and data mining for nuclear data – Dr. Piotr Kopka
- Multiphysics reactor analysis – Prof. Tomasz Kozłowski
- Nuclear Fuels and Fuel Cycle – Dr. Grzegorz Niewiński
- Contemporary Nuclear Reactor Systems – Dr. Rafał Laskowski
- Classical Electrodynamics – Dr. Enrico Sessolo
- Classical Mechanics – Dr. Jakub Wagner
