Previous Issue
Volume 5, June
 
 

J. Nucl. Eng., Volume 5, Issue 3 (September 2024) – 7 articles

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Select all
Export citation of selected articles as:
19 pages, 2596 KiB  
Review
Trends and Perspectives on Nuclear Waste Management: Recovering, Recycling, and Reusing
by Maria Letizia Terranova and Odilon A. P. Tavares
J. Nucl. Eng. 2024, 5(3), 299-317; https://doi.org/10.3390/jne5030020 - 13 Aug 2024
Viewed by 124
Abstract
This paper focuses on the highly radioactive, long-lasting nuclear waste produced by the currently operating fission reactors and on the sensitive issue of spent fuel reprocessing. Also included is a short description of the fission process and a detailed analysis of the more [...] Read more.
This paper focuses on the highly radioactive, long-lasting nuclear waste produced by the currently operating fission reactors and on the sensitive issue of spent fuel reprocessing. Also included is a short description of the fission process and a detailed analysis of the more hazardous radioisotopes produced either by secondary reactions occurring in the nuclear installations or by decay of the fission fragments. The review provides an overview of the strategies presently adopted to minimize the harmfulness of the nuclear waste to be disposed, with a focus on the development and implementation of methodologies for the spent fuel treatments. The partitioning-conditioning and partitioning-transmutation options are analyzed as possible solutions to decrease the presence of long-lived highly radioactive isotopes. Also discussed are the chemical/physical approaches proposed for the recycling of the spent fuel and for the reusing of some technologically relevant isotopes in industrial and pharmaceutical areas. A brief indication is given of the opportunities offered by innovative types of reactors and/or of new fuel cycles to solve the issues presently associated with radioactive waste. Full article
Show Figures

Figure 1

25 pages, 8740 KiB  
Article
Open-Source Optimization of Hybrid Monte Carlo Methods for Fast Response Modeling of NaI (Tl) and HPGe Gamma Detectors
by Matthew Niichel and Stylianos Chatzidakis
J. Nucl. Eng. 2024, 5(3), 274-298; https://doi.org/10.3390/jne5030019 - 5 Aug 2024
Viewed by 260
Abstract
Modeling the response of gamma detectors has long been a challenge within the nuclear community. Significant research has been conducted to digitally replicate instruments that can cost over USD 100,000 and are difficult to operate outside of a laboratory setting. The large cost [...] Read more.
Modeling the response of gamma detectors has long been a challenge within the nuclear community. Significant research has been conducted to digitally replicate instruments that can cost over USD 100,000 and are difficult to operate outside of a laboratory setting. The large cost and availability prevent some from making use of such equipment. Subsequently, there have been multiple attempts to create cost-effective codes that replicate the response of sodium-iodide and high-purity germanium detectors for data derivation related to gamma-ray interaction with matter. While robust programs do exist, they are often subject to export controls and/or they are not intuitive to use. Through the use of hybrid Monte Carlo methods, MATLAB can be used to produce a fast first-order response of various gamma-ray detectors. The combination of a graphical user interface with a numerical-based script allows for open-source and intuitive code. When benchmarked with experimental data from Co-60, Cs-137, and Na-22, the code can numerically calculate a response comparable to experimental and industry-standard response codes. Evidence supports both savings in computational requirements and the inclusion of an intuitive user experience that does not heavily compromise data when compared to other standard codes, such as MCNP and GADRAS, or experimental results. When the application is installed on a Dell Intel i7 computer with 16 cores, the average time to simulate the benchmarked isotopes is 0.26 s. Installation on an HP Intel i7 four-core machine runs the same isotopes in 1.63 s. The results indicate that simple gamma detectors can be modeled in an open-source format. The anticipation for the MATLAB application is to be a tool that can be easily accessible and provide datasets for use in an academic setting requiring gamma-ray detectors. Ultimately, this article provides evidence that hybrid Monte Carlo codes in an open-source format can benefit the nuclear community in both computational time and up-front cost for access. Full article
(This article belongs to the Special Issue Monte Carlo Simulation in Reactor Physics)
Show Figures

Figure 1

14 pages, 4473 KiB  
Article
Validation of the SCALE/Polaris–PARCS Code Procedure With the ENDF/B-VII.1 AMPX 56-Group Library: Boiling Water Reactor
by Kang Seog Kim, Andrew Ward, Ugur Mertyurek, Mehdi Asgari and William Wieselquist
J. Nucl. Eng. 2024, 5(3), 260-273; https://doi.org/10.3390/jne5030018 - 1 Aug 2024
Viewed by 365
Abstract
The SCALE/Polaris–PARCS code procedure has been used in the confirmatory analysis for boiling water reactors by the US Nuclear Regulatory Commission. In this study, the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library was validated by [...] Read more.
The SCALE/Polaris–PARCS code procedure has been used in the confirmatory analysis for boiling water reactors by the US Nuclear Regulatory Commission. In this study, the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library was validated by comparing the simulated results with the measured data for operating boiling water reactors, including Peach Bottom Unit 2 cycles 1–3, Hatch Unit 1 cycles 1–3, and Quad Cities Unit 1 cycles 1–3. The uncertainties and biases of the SCALE/Polaris–PARCS code package for boiling water reactor physics analysis were evaluated in the validation for key nuclear parameters such as reactivity and traversing in-core probe data. Full article
Show Figures

Figure 1

14 pages, 5726 KiB  
Article
Validation of the SCALE/Polaris−PARCS Code Procedure with the ENDF/B-VII.1 AMPX 56-Group Library: Pressurized Water Reactor
by Kang Seog Kim, Byoung-Kyu Jeon, Andrew Ward, Ugur Mertyurek, Matthew Jessee and William Wieselquist
J. Nucl. Eng. 2024, 5(3), 246-259; https://doi.org/10.3390/jne5030017 - 23 Jul 2024
Viewed by 334
Abstract
This study was conducted to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library for pressurized water reactor (PWR) analysis, by comparing simulated results with measured data for critical experiments and operating PWRs. Uncertainties of [...] Read more.
This study was conducted to validate the SCALE/Polaris v6.3.0–PARCS v3.4.2 code procedure with the Evaluated Nuclear Data File (ENDF)/B-VII.1 AMPX 56-group library for pressurized water reactor (PWR) analysis, by comparing simulated results with measured data for critical experiments and operating PWRs. Uncertainties of the SCALE/Polaris–PARCS code procedure for PWR analysis were evaluated in the validation for the PWR key nuclear parameters such as critical boron concentrations, reactivity, control bank work, temperature coefficients, and pin and assembly power peaking factors. Full article
Show Figures

Figure 1

20 pages, 1293 KiB  
Article
Phenomenological Nondimensional Parameter Decomposition to Enhance the Use of Simulation Modeling in Fire Probabilistic Risk Assessment of Nuclear Power Plants
by Sari Alkhatib, Tatsuya Sakurahara, Seyed Reihani, Ernest Kee, Brian Ratte, Kristin Kaspar, Sean Hunt and Zahra Mohaghegh
J. Nucl. Eng. 2024, 5(3), 226-245; https://doi.org/10.3390/jne5030016 - 2 Jul 2024
Viewed by 558
Abstract
Simulation modeling is crucial in support of probabilistic risk assessment (PRA) for nuclear power plants (NPPs). There is a challenge, however, associated with simulation modeling that relates to the time and resources required for collecting data to determine the values of the input [...] Read more.
Simulation modeling is crucial in support of probabilistic risk assessment (PRA) for nuclear power plants (NPPs). There is a challenge, however, associated with simulation modeling that relates to the time and resources required for collecting data to determine the values of the input parameters. To alleviate this challenge, this article develops a formalized methodology to generate surrogate values of input parameters grounded on the decomposition of phenomenological nondimensional parameters (PNPs) while avoiding detailed data collection. While the fundamental principles of the proposed methodology can be applicable to various hazards, the developments in this article focus on fire PRA as an example application area for which resource intensiveness is recognized as a practical challenge. This article also develops a computational platform to automate the PNP decomposition and seamlessly integrates it with state-of-practice fire scenario analysis. The applicability of the computational platform is demonstrated through a multi-compartment fire case study at an NPP. The computational platform, with its embedded PNP decomposition methodology, can substantially reduce the effort required for input data collection and extraction, thereby facilitating the efficient use of simulation modeling in PRA and enhancing the fire scenario screening analysis. Full article
(This article belongs to the Special Issue Reliability Analysis and Risk Assessment of Nuclear Systems)
Show Figures

Figure 1

17 pages, 6706 KiB  
Article
Reinforcement Learning-Based Control Sequence Optimization for Advanced Reactors
by Khang H. N. Nguyen, Andy Rivas, Gregory Kyriakos Delipei and Jason Hou
J. Nucl. Eng. 2024, 5(3), 209-225; https://doi.org/10.3390/jne5030015 - 1 Jul 2024
Viewed by 355
Abstract
The last decade has seen the development and application of data-driven methods taking off in nuclear engineering research, aiming to improve the safety and reliability of nuclear power. This work focuses on developing a reinforcement learning-based control sequence optimization framework for advanced nuclear [...] Read more.
The last decade has seen the development and application of data-driven methods taking off in nuclear engineering research, aiming to improve the safety and reliability of nuclear power. This work focuses on developing a reinforcement learning-based control sequence optimization framework for advanced nuclear systems, which not only aims to enhance flexible operations, promoting the economics of advanced nuclear technology, but also prioritizing safety during normal operation. At its core, the framework allows the sequence of operational actions to be learned and optimized by an agent to facilitate smooth transitions between the modes of operations (i.e., load-following), while ensuring that all safety significant system parameters remain within their respective limits. To generate dynamic system responses, facilitate control strategy development, and demonstrate the effectiveness of the framework, a simulation environment of a pebble-bed high-temperature gas-cooled reactor was utilized. The soft actor-critic algorithm was adopted to train a reinforcement learning agent, which can generate control sequences to maneuver plant power output in the range between 100% and 50% of the nameplate power through sufficient training. It was shown in the performance validation that the agent successfully generated control actions that maintained electrical output within a tight tolerance of 0.5% from the demand while satisfying all safety constraints. During the mode transition, the agent can maintain the reactor outlet temperature within ±1.5 °C and steam pressure within 0.1 MPa of their setpoints, respectively, by dynamically adjusting control rod positions, control valve openings, and pump speeds. The results demonstrate the effectiveness of the optimization framework and the feasibility of reinforcement learning in designing control strategies for advanced reactor systems. Full article
Show Figures

Figure 1

12 pages, 1992 KiB  
Communication
New Mini Neutron Tubes with Multiple Applications
by Ka-Ngo Leung
J. Nucl. Eng. 2024, 5(3), 197-208; https://doi.org/10.3390/jne5030014 - 26 Jun 2024
Cited by 1 | Viewed by 1049
Abstract
Recent experimental investigations have demonstrated that a substantial amount of H/D ions can be formed by thermal desorption processes. Based on these new findings, new mini axial and coaxial-type neutron tubes have been developed for the production of high or [...] Read more.
Recent experimental investigations have demonstrated that a substantial amount of H/D ions can be formed by thermal desorption processes. Based on these new findings, new mini axial and coaxial-type neutron tubes have been developed for the production of high or low-energy neutrons via the d-d, d-10B, d-7Li or p-7Li nuclear reactions. By operating these mini neutron tubes with a high frequency AC high-voltage supply, short pulses of high intensity neutron beams can be generated. Multiple applications, such as carbon and well logging, neutron imaging, cancer therapy, medical isotope production, fission reactor start-up, fusion reactor material evaluation, homeland security and space exploration can be performed with the subcompact neutron generator system. It is shown that the performance of these new mini neutron tubes can exceed those of the conventional plasma-based neutron sources. Full article
Show Figures

Figure 1

Previous Issue
Back to TopTop