Tungsten-based High Entropy Alloys Proposed as Plasma-facing Materials for Fusion Reactors
Muhammad Abdelghany
Abstract: High-Entropy Alloys (HEAs) have great potential to be employed in the extreme environments of nuclear systems such as fusion and fission reactors. This is because they exhibit high structure stability under irradiation and possess excellent mechanical properties at high temperatures. However, we have very little knowledge about the occurrence, structure, and properties of their crystalline phases and mostly our knowledge is restricted to alloys that are at the corner of their phase diagrams. One way of filling this gap is by predicting their behavior computationally using advanced modeling and simulation. The main challenge in this approach is developing a proper interatomic potential that allows us to model these alloys and predict their performance under fusion energy conditions.
In this presentation, I will discuss our approach to computationally develop an Embedded Atom Method (EAM) surface interatomic potential for a W-based HEA. This alloy, composed of W-Ta-Cr-V, was first proposed by our collaborators at Los Alamos National Lab as a plasma-facing material for fusion reactors. It was tested experimentally and showed outstanding resistance under irradiation. I will also outline the simulation results of this alloy done using DYNAMIX, a Monte Carlo Binary Collision Approximation (BCA) code developed in our group, which is used to understand ion-surface interactions.
Bio: Muhammad is currently a PhD student in the Nuclear, Plasma, and Radiological Engineering Department at the University of Illinois at Urbana-Champaign since 2017. He earned his B.Sc. degree with honors in Nuclear and Radiation Engineering from Alexandria University, Egypt in 2014. During his undergrad, he co-founded the first IEEE - Nuclear and Plasma Sciences Society (NPSS) student chapter in the world at Alexandria University.
His current research interest includes studying the thermodynamics driving forces that control the surface self-organization and nano-patterning during the highly non-equilibrium process of surface irradiation. He is also interested in developing advanced simulations to study the performance and plasma-material interactions of new materials in fusion system.
Comprehensive Framework for Data-driven Model Form Discovery of the Closure Laws in Thermal-Hydraulics Codes
Katarzyna Borowiec
Abstract: The two-phase two-fluid model is a basis of many thermal-hydraulics codes used in design, licensing and safety considerations of nuclear power plants. The model consists of system of conservation equations closed by the constitutive laws. Those laws derived based on years of experimental investigations are semi-empirical correlations that suffer from lack of generality and limited range of applicability. Increase of computational power, availability of new experiments and development of high-fidelity simulations increased number of validation data that can be used to discover missing physics. This presentation will focus on the physics-discovered data-driven model form methodology that leverages new data to improve modeling capabilities. The methodology has an advantage over the existing calibration techniques as it does not assume the form of model at the start of the analysis.
The methodology is applied to the closure laws of the CTF subchannel code to demonstrate its capabilities. The appropriate correction of the closure laws is derived, based on limited experimental data through reduced dimensionality modeling. The comparison with the validation dataset shows significant improvement of modeling capabilities.
Bio: Katarzyna Borowiec is a Ph.D. candidate in the Department of Nuclear, Plasma, and Radiological Engineering at UIUC, working with Prof. Tomasz Kozlowski. Katarzyna Borowiec received her bachelor’s degree in Physics from University of Warsaw in 2016. In 2016 she also received her bachelor’s degree in Power Engineering from Warsaw University of Technology. She received her master’s degree in Nuclear, Plasma and Radiological Engineering from University of Illinois at Urbana-Champaign in 2017.
Her research interests focus on development of Thermal-Hydraulics codes using data-driven approaches, application of machine learning techniques in nuclear industry and advancement of uncertainty quantification methodologies. In the summer of 2018 and 2019 she worked as a graduate intern at Oak Ridge National Laboratory, on the projects of Energy Storage Systems for Nuclear Reactors and Thermal-Hydraulics Coupling of CTF & TRACE.
