TY - JOUR AU - Kirchknopf, Péter AU - Batki, B. AU - Völgyesi, P. AU - Kató, Z. AU - Szalóki, I. TI - Application of machine learning methods for spent fuel characterization based on gamma spectrometry measurements JF - ANNALS OF NUCLEAR ENERGY J2 - ANN NUCL ENERGY VL - 205 PY - 2024 PG - 11 SN - 0306-4549 DO - 10.1016/j.anucene.2024.110601 UR - https://m2.mtmt.hu/api/publication/34860898 ID - 34860898 N1 - HUN-REN Centre for Energy Research, 1121-H Budapest, Konkoly-Thege Miklós út 29-33, Hungary Institute of Nuclear Techniques, Budapest University of Technology and Economics, 1111-H Budapest, Műegyetem rkp. 9, Hungary MVM Paks Nuclear Power Plant Ltd, H-7030 Paks, lot number: 8803/17, Hungary Export Date: 17 May 2024 CODEN: ANEND Correspondence Address: Batki, B.; HUN-REN Centre for Energy Research, 1121-H Budapest, Konkoly-Thege Miklós út 29-33, Hungary; email: balint.batki@ek.hun-ren.hu Funding text 1: The authors are grateful to the MVM Paks NPP Ltd. staff for providing the spent fuel parameter data and offering invaluable technical support for the measurements. A special acknowledgment is due to Gy\\u00F6rgy Hegyi from the Centre for Energy Research for sharing the Paks NPP fuel cycle calculation results. AB - Machine learning models have been developed to predict properties of spent nuclear fuel assemblies from Paks NPP, such as burnup, cooling time, initial enrichment, and Pu-239 content. Measured gamma spectra are processed, and activity ratios of fission products are calculated to serve as input features for Support Vector Regression, Random Forest, and Multi-Layer Perceptron models. Data uncertainty is considered during inference to produce prediction intervals, and input features are ranked using the Gini importance of Random Forest models. A deep learning approach using Convolutional Neural Networks has also been developed to predict the spent fuel parameters from the measured spectra directly. The new models can predict spent fuel parameters with great precision, outperforming earlier approaches that rely on nonlinear regression using a single feature to predict burnup and cooling time and can estimate initial enrichment and Pu-239 content. © 2024 The Author(s) LA - English DB - MTMT ER - TY - JOUR AU - Mohseni, Meysam AU - Sarsari, I.A. AU - Karbasizadeh, S. AU - Udvarhelyi, Péter AU - Hassanzada, Q. AU - Ala-Nissila, T. AU - Gali, Ádám TI - Vacancy-related color centers in two-dimensional silicon carbide monolayers JF - PHYSICAL REVIEW MATERIALS J2 - PHYS REV MAT VL - 8 PY - 2024 IS - 5 PG - 11 SN - 2475-9953 DO - 10.1103/PhysRevMaterials.8.056201 UR - https://m2.mtmt.hu/api/publication/34857976 ID - 34857976 LA - English DB - MTMT ER - TY - JOUR AU - Ficzere, Máté AU - Mészáros, Lilla Alexandra AU - Diószegi, Anna AU - Bánrévi, Zoltán AU - Farkas, Attila AU - Lenk, Sándor AU - Galata, Dorián László AU - Nagy, Zsombor Kristóf TI - UV imaging for the rapid at-line content determination of different colourless APIs in their tablets with artificial neural networks JF - INTERNATIONAL JOURNAL OF PHARMACEUTICS J2 - INT J PHARM VL - 657 PY - 2024 PG - 10 SN - 0378-5173 DO - 10.1016/j.ijpharm.2024.124174 UR - https://m2.mtmt.hu/api/publication/34845147 ID - 34845147 N1 - Department of Organic Chemistry and Technology, Faculty of Chemical Technology and Biotechnology, Budapest University of Technology and Economics, Műegyetem rkp 3., Budapest, H-1111, Hungary Department of Atomic Physics, Budapest University of Technology and Economics, Műegyetem rkp 3., Budapest, H-1111, Hungary Export Date: 17 May 2024 CODEN: IJPHD Correspondence Address: Kristóf Nagy, Z.; Department of Organic Chemistry and Technology, Műegyetem rkp 3., Hungary; email: zsknagy@oct.bme.hu Funding details: Budapesti Műszaki és Gazdaságtudományi Egyetem, BME Funding details: Emberi Eroforrások Minisztériuma, EMMI Funding details: Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, NKFIH Funding details: Magyar Tudományos Akadémia, MTA Funding details: Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, NKFIA Funding details: European Commission, EC, ÚNKP-23-3-I-BME-23, ÚNKP-23-5- BME-448 Funding text 1: Project no. RRF-2.3.1-21-2022-00015 has been implemented with the support provided by the European Union. This project was supported by the \\u00DANKP-23-3-I-BME-23 and \\u00DANKP-23-5- BME-448 New National Excellence Program of the Ministry of Human Capacities. The project supported by the Doctoral Excellence Fellowship Programme (DCEP) is funded by the National Research Development and Innovation Fund of the Ministry of Culture and Innovation and the Budapest University of Technology and Economics, under a grant agreement with the National Research, Development and Innovation Office. This paper was supported by the J\\u00E1nos Bolyai Scholarship of the Hungarian Academy of Sciences. LA - English DB - MTMT ER - TY - JOUR AU - László, István TI - George Green és a Green-függvény JF - FIZIKAI SZEMLE J2 - FIZIKAI SZEMLE VL - 74 PY - 2024 IS - 5 SP - 160 EP - 165 PG - 6 SN - 0015-3257 UR - https://m2.mtmt.hu/api/publication/34844719 ID - 34844719 LA - Hungarian DB - MTMT ER - TY - JOUR AU - Buzás, Attila AU - Kocsis, G. AU - Biedermann, C. AU - Cseh, G. AU - Szepesi, T. AU - Szucs, M. TI - A study of turbulent filaments in the edge plasma of the Wendelstein 7-X stellarator JF - NUCLEAR FUSION J2 - NUCL FUSION VL - 64 PY - 2024 IS - 6 PG - 13 SN - 0029-5515 DO - 10.1088/1741-4326/ad365e UR - https://m2.mtmt.hu/api/publication/34836200 ID - 34836200 N1 - Funding Agency and Grant Number: EUROfusionhttp://dx.doi.org/10.13039/100019784 [101052200]; European Union via the Euratom Research and Training Programme Funding text: The authors would express their gratitude to Daniel Carralero for his efforts and insight in analysing and discussing radial electric field profiles. This work has been carried out within the framework of the EUROfusion Consortium, funded by the European Union via the Euratom Research and Training Programme (Grant Agreement No 101052200 - EUROfusion). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them. AB - Filaments are studied by examining fast camera images on the Wendelstein 7-X stellarator. Fast cameras offer a unique perspective, revealing the complex 3D structure of filaments in the entire poloidal cross-section of the plasma. By correlating individual pixels, their location, shape, and movement are analyzed in standard and high-iota configurations. The presence of filaments is not uniform poloidally around. The number of active areas matches the number of magnetic islands in both configurations. Filaments are found to extend to multiple toroidal turns in standard configuration. No time delay is observed between the different toroidal sections. Such behavior is not seen in high-iota configuration. Filaments are observed within and without the edge shear layer, indicated by the direction of their poloidal rotation. Inside the shear layer, their velocity scatters around 1.25 km s-1, accompanied by a lifetime between 80 and 120 mu s. Outside, their velocity shows greater absolute values and variance, but still in a few km s-1 range. The similarities and differences between the two configurations are discussed and compared to previous results. LA - English DB - MTMT ER - TY - JOUR AU - Zhang, X. AU - Turiansky, M.E. AU - Razinkovas, L. AU - Maciaszek, M. AU - Broqvist, P. AU - Yan, Q. AU - Lyons, J.L. AU - Dreyer, C.E. AU - Wickramaratne, D. AU - Gali, Ádám AU - Pasquarello, A. AU - Van de Walle, C.G. TI - First-principles calculations of defects and electron-phonon interactions: Seminal contributions of Audrius Alkauskas to the understanding of recombination processes JF - JOURNAL OF APPLIED PHYSICS J2 - J APPL PHYS VL - 135 PY - 2024 IS - 15 PG - 9 SN - 0021-8979 DO - 10.1063/5.0205525 UR - https://m2.mtmt.hu/api/publication/34832941 ID - 34832941 N1 - Export Date: 6 May 2024 CODEN: JAPIA AB - First-principles calculations of defects and electron-phonon interactions play a critical role in the design and optimization of materials for electronic and optoelectronic devices. The late Audrius Alkauskas made seminal contributions to developing rigorous first-principles methodologies for the computation of defects and electron-phonon interactions, especially in the context of understanding the fundamental mechanisms of carrier recombination in semiconductors. Alkauskas was also a pioneer in the field of quantum defects, helping to build a first-principles understanding of the prototype nitrogen-vacancy center in diamond, as well as identifying novel defects. Here, we describe the important contributions made by Alkauskas and his collaborators and outline fruitful research directions that Alkauskas would have been keen to pursue. Audrius Alkauskas’ scientific achievements and insights highlighted in this article will inspire and guide future developments and advances in the field. © 2024 Author(s). LA - English DB - MTMT ER - TY - JOUR AU - Wilson, S.G. AU - Eaton, M.D. AU - Kópházi, József TI - Energy-Dependent, Self-Adaptive Mesh h(p)-Refinement of an Interior-Penalty Scheme for a Discontinuous Galerkin Isogeometric Analysis Spatial Discretization of the Multi-Group Neutron Diffusion Equation with Dual-Weighted Residual Error Measures JF - JOURNAL OF COMPUTATIONAL AND THEORETICAL TRANSPORT J2 - J COMPUT THEOR TRANSP PY - 2024 SN - 2332-4309 DO - 10.1080/23324309.2024.2334277 UR - https://m2.mtmt.hu/api/publication/34832886 ID - 34832886 N1 - Export Date: 3 May 2024 Correspondence Address: Wilson, S.G.; Nuclear Engineering Group, Exhibition Road, South Kensington, United Kingdom; email: seth.wilson16@imperial.ac.uk AB - Energy-dependent self-adaptive mesh refinement algorithms are developed for a symmetric interior-penalty scheme for a discontinuous Galerkin spatial discretization of the multi-group neutron diffusion equation using NURBS-based isogeometric analysis (IGA). The spatially self-adaptive algorithms employ both mesh (h) and polynomial degree (p) refinement. The discretized system becomes increasingly ill-conditioned for increasingly large penalty parameters; and there is no gain in accuracy for over penalization. Therefore, optimized penalty parameters are rigorously calculated, for general element types, from a coercivity analysis of the bilinear form. Local mesh refinement allows for a better allocation of computational resources; and thus, more accuracy per degree of freedom. Two a posteriori interpolation-based error measures are proposed. The first heuristically minimizes local contributions to the discretization error, which becomes competitive for global quantities of interest (QoIs). However, for localized QoIs, over energy-dependent meshes, certain multi-group components may become under-resolved. The second employs duality arguments to minimize important error contributions, which consistently and reliably reduces the error in the QoI. © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC. LA - English DB - MTMT ER - TY - JOUR AU - Sebestény, Dániel István AU - Panka, István AU - Batki, Bálint TI - Automated group constant parameterization for low sample sizes using different Machine learning approaches JF - ANNALS OF NUCLEAR ENERGY J2 - ANN NUCL ENERGY VL - 204 PY - 2024 PG - 10 SN - 0306-4549 DO - 10.1016/j.anucene.2024.110560 UR - https://m2.mtmt.hu/api/publication/34832872 ID - 34832872 N1 - Budapest University of Technology and Economics, Institute of Nuclear Techniques, Hungary HUN-REN Centre for Energy Research, Hungary Export Date: 3 May 2024 CODEN: ANEND Correspondence Address: Sebestény, D.Konkoly-Thege Miklós út 29-33, Hungary; email: sebesteny.daniel@ek.hun-ren.hu AB - This paper deals with group constant parameterization, a necessary step to utilize the results of assembly-level neutronics calculations at the full-core level. The focus is on low sample size problems when the commonly used linear interpolation approach is inadequate, a typical situation of using Monte Carlo codes for group constant generation. This work presents a newly developed code package for automated group constant parameterization. It implements several machine learning regression models − including a novel polynomial regression algorithm − performs hyperparameter optimization and selects the best model based on a detailed evaluation. The applicability of the new code package is demonstrated in a case study for a VVER-1200 fuel assembly covering both normal operation and transient conditions. In this example, the novel polynomial regression model provides a 73 pcm average error in kinf that leads to reactivity coefficients well within the desired precision. © 2024 The Authors LA - English DB - MTMT ER - TY - JOUR AU - Itatani, Masaki AU - Onishi, Yuhei AU - Suematsu, Nobuhiko J. AU - Lagzi, István László TI - Periodic Precipitation in a Confined Liquid Layer JF - JOURNAL OF PHYSICAL CHEMISTRY LETTERS J2 - J PHYS CHEM LETT VL - 15 PY - 2024 IS - 18 SP - 4948 EP - 4957 PG - 10 SN - 1948-7185 DO - 10.1021/acs.jpclett.4c00832 UR - https://m2.mtmt.hu/api/publication/34830134 ID - 34830134 N1 - Export Date: 17 May 2024 Correspondence Address: Itatani, M.; Department of Physics, Műegyetem rkp. 3, Hungary; email: masakiitatani.chem@gmail.com Correspondence Address: Lagzi, I.; Department of Physics, Műegyetem rkp. 3, Hungary; email: lagzi.istvan.laszlo@ttk.bme.hu Funding details: Nemzeti Kutatási Fejlesztési és Innovációs Hivatal, NKFIH, JP20H02712, JP21H01004, TKP2021-EGA-02, JP20H01871, JPJSBP 120213801, K146071 Funding details: Japan Society for the Promotion of Science, JSPS, 202260298 Funding text 1: The authors thank Professors A\\u0301gota To\\u0301th and Dezso\\u030B Horva\\u0301th (University of Szeged, Hungary) for the fruitful discussions. This work was supported by the JSPS Postdoctoral Fellowship Program for Overseas Researchers (Identification Number 202260298), the HUN-REN Hungarian Research Network, the National Research, Development and Innovation Office of Hungary (K146071), the Ministry of Culture and Innovation and the National Research, Development and Innovation Office under Grant TKP2021-EGA-02, Grant-in-Aid for Scientific Research (B) JSPS KAKENHI (JP21H01004, JP20H02712, and JP20H01871), and JSPS Japan\\u2013Hungary Bilateral Joint Research Project (JPJSBP 120213801). LA - English DB - MTMT ER - TY - JOUR AU - Erdélyi, Márton Kristóf AU - Sawin, Will AU - Tóth, Árpád TI - The purity locus of matrix Kloosterman sums JF - TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY J2 - T AM MATH SOC PY - 2024 SN - 0002-9947 DO - 10.1090/tran/9149 UR - https://m2.mtmt.hu/api/publication/34829054 ID - 34829054 N1 - Funding Agency and Grant Number: NKFIH Research Grants [K-135885, FK-127906]; Representation Theory Research Group; NSF [DMS-2101491]; Renyi Institute Lendulet Automorphic Research Group Funding text: The first author was supported by NKFIH Research Grants FK-127906 and K-135885 and by the Renyi Institute Lendulet Analytic Number Theory and Representation Theory Research Group. The second author was supported by NSF grant DMS-2101491. The third author was supported by by the Renyi Institute Lendulet Automorphic Research Group, and by NKFIH Research Grants K-135885. AB - We construct a perverse sheaf related to the the matrix exponential sums investigated by Erdélyi and Tóth [ Matrix Kloosterman sums , 2021, arXiv:2109.00762]. As this sheaf appears as a summand of certain tensor product of Kloosterman sheaves, we can establish the exact structure of the cohomology attached to the sums by relating it to the Springer correspondence and using the recursion formula of Erdélyi and Tóth. LA - English DB - MTMT ER -