Field Of Nuclear Engineering Research Articles

Pak-France Relations During 21st Century: Strategic Alliances and Bilateral Cooperation

This research aims to critically analyse the bilateral relations between France and Pakistan during the 21st century. It emphasizes political, economic, social, cultural and military relationships between the two countries. Its purposes are to demonstrate the political ideologies and foreign policy objectives that influence Pakistan-France relations, to examine the nature of economic ties between Pakistan and France, to analyse the patterns of trade and investment that changed over time, to evaluate the Pakistan-France collaboration on military and security matters, and other key areas of cooperation, and to elucidate Pakistan-France political relations, the influence of pressure groups(political and religious) on their relationship, and to imposing allegations on France as a result of religious disparity in Pakistan. This study concludes that Pakistan and France are having high time collaborations in various sectors with a particular focus on working together in the fields of nuclear technology, defence cooperation, and resolving global security issues.

Development of advanced AI-based segmentation and prediction method for air entrainment in plunging water jets

Understanding air entrainment phenomena induced by plunging water jets is critical in the fields of nuclear and hydraulic engineering. Air entrainment is one of the key safety design parameters for nuclear systems. However, most existing studies rely on empirical correlations or curve-fitting models to estimate bubble penetration depth, and no agreed-upon calculation principle exists for varying jet conditions. To address these limitations, this research developed two advanced AI approaches: an improved YOLOv5 for segmenting air entrainment and the NSGA-III-BPNN method for predicting penetration depth. The improved YOLOv5 enables real-time segmentation and extraction of air entrainment motion and dynamics under diverse conditions, demonstrating high scalability and robustness. The penetration depth estimated using the improved YOLOv5 shows greater accuracy compared to conventional empirical correlationsand is more efficient than traditional image post-processing techniques for classifying shape regimes based on dynamic air entrainment patterns. To overcome the limitations of object segmentation, which typically relies on video or image data, the NSGA-III-BPNN method predicts maximum penetration depths with greater accuracy than YOLOv5, offering a more effective prediction model for air entrainment penetration depth. By leveraging advanced AI techniques, the research not only provides valuable segmentation data for refining computational fluid dynamics (CFD) modeling but also paves the way for significant advancements in both nuclear and hydraulic engineering.

Experimental validation of the 3-D neutron kinetics algorithm of RAPID using the JSI TRIGA Mark-II reactor

The high-fidelity simulation of reactor kinetics, with the ability of calculating detailed 3-D time-dependent distributions of the nuclear quantities of interest, is an important challenge in the field of nuclear engineering. As the industry moves towards innovative reactor designs and the financing and licensing of prototypes becomes increasingly complex, there is an increasing need of best-estimate and high-fidelity codes that are capable of replacing the computational tools that have been fine-tuned for LWRs using years of operation data and validation against benchmark facilities. Traditional neutron transport software either has to rely on significant modeling approximations or requires an impractical amount of computer time to calculate accurate and detailed solutions to the transport problems, failing to meet the need of the industry to simulate numerous scenarios over a relatively small time. RAPID is a software that relies on the Multi-stage Response-function Transport (MRT) methodology to achieve high-fidelity accurate solutions to the neutron transport problem by pre-calculating a database of response functions or coefficients that are then combined and interpolated to calculate the nuclear quantities of interest in seconds to minutes on a single computer core. In this article, the recently developed algorithms for 3-D time-dependent simulation of reactor kinetics and for control rods movement in the reactor core are validated using experiments performed at the Jožef Stefan Institute (JSI) TRIGA Mark-II reactor. The experiments were designed and performed with the goal of RAPID’s validation. In particular, time-dependent responses from four fission chambers located in the TRIGA core were collected and compared to RAPID-calculated values. The comparison of RAPID’s predictions to measured data shows very good agreement, demonstrating the ability of RAPID of calculating detailed 3-D time-dependent fission source distributions for a reactor kinetic problem that would be impractical to model with traditional neutron transport codes. In addition, it is demonstrated how RAPID is capable of obtaining a high level of accuracy within seconds to minutes on a single computer core, with a significant speedup with respect to state-of-the-art neutron transport methods.

Tailoring oxidation resistance of Cantor alloy by addition of Ta and Al

High-entropy alloys are widely investigated for applications in the nuclear engineering field, the aerospace sector, and various other high-temperature applications. High-temperature oxidation behaviour is a typical issue in such applications. In the current work, an effort is made to tailor the oxidation behaviour of Cantor alloy (CoCrFeMnNi) in the air at 1000 °C with the addition of Ta and Al. Both CoCrFeMnNiTa as well as CoCrFeMnNiAl alloys exhibit considerable resistance to oxide scale spallation as well as develop multi-layered complex oxide scales. CoCrFeMnNiTa primarily forms rutile-type CrTaO4 oxide, which drastically reduces the inward diffusion of oxygen and nitrogen and suppresses the escape of other alloying elements. Nonetheless, the better result is obtained through the Al addition, as evidenced by the comparatively lower oxidation rate constant of CoCrFeMnNiAl in comparison to CoCrFeMnNiTa alloy. This is attributed to the superior oxidation resistance for CoCrFeMnNiAl could be related to the emergence of distinctive Cr2O3 and Al2O3 scales. Additionally, the oxide scale of CoCrFeMnNiTa was not completely smooth and showed some spallation whereas the oxide scales of CoCrFeMnNiAl remained smooth, continuous, and had stronger oxide-substrate interface adhesion.

In situ XAFS-XRD study of the Zr-Y2O3 interaction at extra-high temperatures.

The in situ measurement technique for a metal/metal-oxide mixture at extra-high temperature above 2000 K has been desired in the field of nuclear safety engineering. In the present study, we succeeded in simultaneous XAFS-XRD measurements of the Zr oxidation [Zr + O → Zr(O) + ZrO2] up to 1952 K and ZrO2-Y2O3 reaction from 1952 to 2519 K. The chemical shift during Zr oxidation was observed in the absorption spectra around the Zr K-edge, and the interatomic cation-cation and cation-oxygen distances obtained by the fitting analysis of EXAFS during the Y2O3-ZrO2 reaction are explained. Also, the temperature dependency of the anharmonic effect was investigated by comparing the fitted second- and third-order cumulants with the theoretical ones in which the Morse potential was applied as an interatomic potential, giving a good explanation about the local structure dynamics. Finally, the applicability of the developed system to investigation of nuclear fuel materials, such as UO2-Zr, is discussed.

An International Data-Based Systems Agency IDA: Striving for a Peaceful, Sustainable, and Human Rights-Based Future

Digital transformation and “artificial intelligence (AI)”—which can more adequately be called “data-based systems (DS)”—comprise ethical opportunities and risks. Therefore, it is necessary to identify precisely ethical opportunities and risks in order to be able to benefit sustainably from the opportunities and to master the risks. The UN General Assembly has recently adopted a resolution aiming for ‘safe, secure and trustworthy artificial intelligence systems’. It is now urgent to implement and build on the UN General Assembly Resolution. Allowing humans and the planet to flourish sustainably in peace and guaranteeing globally that human dignity is respected not only offline but also online, in the digital sphere, and in the domain of DS, requires two policy measures: (1) human rights-based data-based systems (HRBDS): HRBDS means that human rights serve as the basis of digital transformation and DS. (2) International Data-Based Systems Agency (IDA): IDA should be established at the UN as a platform for cooperation in the field of digital transformation and DS, fostering human rights, security, and peaceful uses of DS, as well as a global supervisory institution and regulatory authority in digital transformation and DS. The establishment of IDA is realistic because humanity has already shown in its past that we are able to not always “blindly” pursue the technically possible but also to limit ourselves to what is technically feasible when humanity and the planet are at stake. For instance, humans researched the field of nuclear technology, developed the atomic bomb, and detonated it several times. Nonetheless, the same humans limited research and development in the field of nuclear technology to prevent even worse consequences by establishing the International Atomic Energy Agency (IAEA) at the UN.

Multiscale simulation study on radiation aging of EPDM and preparation of radiation-resistant materials

With the wide application of ethylene propylene diene monomer (EPDM) in the field of nuclear engineering, exploring the radiation aging mechanism of EPDM is of great significance to improve the radiation resistance of EPDM composites. In this paper, the radiation aging mechanism of EPDM was investigated by a combination of experiments and multiscale simulations, and EPDM composites with excellent radiation resistance were prepared. The radiation aging mechanism of EPDM involves the crosslinking and degradation of molecular chains. The aging of EPDM starts from the breakage of α-H in the 5-ethylidene-2-norbornene monomer. In addition, the screening strategy of radiation-resistant additives was proposed. Antioxidants N, N′-diphenyl-p-phenylene-diamine (H), N, N′-ditolyl-p-phenylenediamine (DTPD), and N, N′-di-2-naphthyl-p-phenylenediamine (DNP) were taken as the main research objects, and quantitative analysis was carried out from the aspects of chemical protection and physical protection. The screening results showed that DNP has excellent radiation resistance and migration resistance. The prepared EPDM-DNP composites showed outstanding radiation resistance with 94% tensile strength retention after 300 kGy irradiation. This work contributes to understand the mechanisms of radiation-induced material damage and guides the design of radiation-resistant materials.

Online practical education and training in nuclear engineering: A methodological framework

The education of students in the field of nuclear engineering must combine theoretical and practical teaching, this is the only way to produce quality graduates. Practical education generally includes two areas — experimental teaching and the use of advanced computational codes for the simulation of physical phenomena. The availability of practical education is not a matter of course for all students. The transfer of practical teaching to an online environment opens up a lot of possibilities even for universities that do not have a nuclear reactor, laboratories or extensive computing infrastructure at their disposal.The article deals with key aspects that must be respected when implementing online practical education and training. The listed tips and recommendations are based on the experience gained during the COVID pandemic and during the solution of the PADINE-TT project, which was a response to the development of online teaching and its inclusion in teaching at individual universities.

Does the nuclear engineering field perform worse in utilizing women? Evidence from South Korea

Despite its remarkable socioeconomic development, South Korea underperforms in terms of female labor force participation and women in leadership positions. As women appear to avoid nuclear engineering, we aim to evaluate its relative performance in attracting women to its labor force compared to other college majors. Using college-major level information from 2000, we test whether the female faculty share in nuclear engineering is lower than its counterparts. Although nuclear engineering has one of the lowest female faculty shares, its share exceeds that of agricultural science, business and economics, chemical engineering, chemistry, civil engineering, and industrial engineering once we properly control for gender composition among students and other compounding factors. In other words, once female students major in nuclear engineering, they are less likely to leave their fields compared to their counterparts in other disciplines. This result implies that if the nuclear engineering field aims to attract more women to its workforce, it is important to target them from the early stage of their careers.

Extension of particle-based in-situ visualization for multipoint VR visualization

In the field of nuclear engineering, complex simulations on exascale supercomputers generate large-scale data. To facilitate efficient analysis of such simulation data, one needs to share them among scientists at remote locations. However, data I/O and data transfer for such large-scale data are quite costly. To resolve these issues, we developed a remote in-situ visualization system IS-PBVR based on the particle-based volume rendering (PBVR), which is suitable for parallel processing on modern supercomputers. In this study, we extend IS-PBVR for VR visualization on multiple client PCs, thus developing a multi-point remote VR visualization. We apply this technique to fluid simulations on GPU-based supercomputers and verify its utility by sharing in-situ VR visualization between multiple client PCs.

Electron correlation effects on uranium isotope fractionation in U(VI)-U(VI) and U(IV)-U(VI) equilibrium isotopic exchange systems.

Uranium isotope fractionation has been extensively investigated in the fields of nuclear engineering and geochemical studies, yet the underlying mechanisms remain unclear. This study assessed isotope fractionations in U(VI)-U(VI) and U(IV)-U(VI) systems by employing various relativistic electron correlation methods to explore the effect of electron correlation and to realize accurate calculations of isotope fractionation coefficients (ε). The nuclear volume term, ln Knv, the major term in ε, was estimated using the exact two-component relativistic Hamiltonian in conjunction with either HF, DFT(B3LYP), MP2, CCSD, CCSD(T), FSCCSD, CASPT2, or RASPT2 approaches for small molecular models with high symmetry. In contrast, chemical species studied in prior experimental work had moderate sizes and were asymmetrical. In such cases, electron correlation calculations other than DFT calculations were not possible and so only the HF and B3LYP approaches were employed. For closed-shell U(VI)-U(VI) systems, the MP2, CCSD and CCSD(T) methods yielded similar ln Knv values that were intermediate between those for the HF and B3LYP methods. Comparisons with experimental results for U(VI)-U(VI) systems showed that the B3LYP calculations gave results closer to the experimental data than the HF calculations. Because of the open-shell structure of U(IV), multireference methods involving the FSCCSD, CASPT2 and RASPT2 techniques were used for U(IV)-U(VI) systems, but these calculations exhibited instability. The average-of-configuration HF method showed better agreement with the experimental ε values for U(IV)-U(VI) systems than the B3LYP method. Overall, electron correlation improved the description of ε for the U(VI)-U(VI) systems but challenges remain with regard to open-shell U(IV) calculations because an energy accuracy of 10-6-10-7Eh is required for ln Knv calculations.

TRIPOLI-4® calculations of neutron multiplicity counting rates of 3He array detectors and verification tests of an automatic MCNP-to-TRIPOLI conversion tool for recent ICSBEP subcritical experiments

TRIPOLI-4® is a general-purpose Monte Carlo radiation transport code developed at CEA Paris-Saclay center. It uses continuousenergy nuclear data to simulate neutron transport for diverse nuclear engineering fields. Neutron multiplication calculations of subcritical systems are important for application areas including criticality safety, reactor ex-core monitoring, and non-proliferation of nuclear materials. Subcritical experiments were performed by the LANL teams to improve subcritical simulation capabilities of MCNP code and to validate 3He based array detectors. Three of these experimental series based on Ni, W, and Cu reflected Pu spheres and related MCNP calculations were published on 2020 ICSBEP handbook. New automation conversion tool of MCNP geometries to TRIPOLI-4® ones has been available. In this study, the traditional manual modelling of above Pu-W and Pu-Cu cases (17 configurations including Cu and polyethylene reflectors) was first prepared. The MCNP/TRIPOLI-4® converted ones were secondly set for Pu-Cu cases. Finally the singles counting rate R1 (cts/s) in a single NPOD detector for Pu-W cases and in two NoMAD detectors for Pu-Cu cases were calculated. Generally, a good agreement of R1 was obtained between the TRIPOLI-4® calculations and the ICSBEP reported results. When using the polyethylene reflector layers in some Pu-Cu experiments, a difference of 5 to 16 % for R1 was observed between TRIPOLI-4 (Converted) results and the ICSBEP measured ones.

A Review of Irradiation-Tolerant Refractory High-Entropy Alloys

Along with the globalization of environmental problems and the rapid development of the field of nuclear technologies, the severe irradiation damage of materials has become a big issue, restricting the development of advanced nuclear reactor systems. Refractory high-entropy alloys (RHEAs) have the characteristics of a complex composition, a short-range order, and lattice distortion and possess a high phase stability, outstanding mechanical properties, and excellent irradiation resistance at elevated temperatures; thus, they are expected to be promising candidates for advanced nuclear reactors. This review summarizes the design, preparation, and irradiation resistance of irradiation-tolerant RHEAs. It encompasses a comprehensive analysis of various aspects, including the evolution of defects, changes in microstructure, and the degradation in properties. Furthermore, the challenges and insufficiently researched areas regarding these alloys are identified and discussed. Building on this foundation, the review also provides a forward-looking perspective, outlining potential avenues for future research.

Spanish contribution to the development and application of best estimate plus uncertainty methodologies: Past, present and future

Best-Estimate Plus Uncertainty (BEPU) nuclear safety analysis is an approach widely used in the field of nuclear engineering and reactor safety assessment. It aims to provide a more realistic assessment of reactor safety by considering a combination of best-estimate models and the quantification of the uncertainty of the input and code data.The Spanish research community in collaboration with the regulatory body and the industry has substantially contributed to the development and application of BEPU methodologies by taking an active role in the international joint efforts. The present article provides an overview of the key contributions performed by Spanish institutions. Many of the activities performed in BEPU are dedicated to the thermal-hydraulics field where Spanish researchers have contributed to both the development of forward and inverse uncertainty propagation methods. On the other hand, BEPU related works have also been performed in several other disciplines such as neutron-kinetics, fuel thermo-mechanics, computational fluid dynamics, containment, severe accident and in coupled multi-physics applications. All these contributions are first summarized to set the framework for a final section that provides the future challenges that lay ahead in the upcoming years in relation to the implementation of BEPU methods.

Scalable Inverse Uncertainty Quantification by Hierarchical Bayesian Modeling and Variational Inference

Inverse Uncertainty Quantification (IUQ) has gained increasing attention in the field of nuclear engineering, especially nuclear thermal-hydraulics (TH), where it serves as an important tool for quantifying the uncertainties in the physical model parameters (PMPs) while making the model predictions consistent with the experimental data. In this paper, we present an extension to an existing Bayesian inference-based IUQ methodology by employing a hierarchical Bayesian model and variational inference (VI), and apply this novel framework to a real-world nuclear TH scenario. The proposed approach leverages a hierarchical model to encapsulate group-level behaviors inherent to the PMPs, thereby mitigating existing challenges posed by the high variability of PMPs under diverse experimental conditions and the potential overfitting issues due to unknown model discrepancies or outliers. To accommodate computational scalability and efficiency, we utilize VI to enable the framework to be used in applications with a large number of variables or datasets. The efficacy of the proposed method is evaluated against a previous study where a No-U-Turn-Sampler was used in a Bayesian hierarchical model. We illustrate the performance comparisons of the proposed framework through a synthetic data example and an applied case in nuclear TH. Our findings reveal that the presented approach not only delivers accurate and efficient IUQ without the need for manual tuning, but also offers a promising way for scaling to larger, more complex nuclear TH experimental datasets.

Machine-learning-driven simulations on microstructure, thermodynamic properties, and transport properties of LiCl-KCl-LiF molten salt

The thermodynamic and transport properties of high-temperature chloride molten salt systems are of great significance for spent fuel reprocessing in the field of nuclear energy engineering. Here, by using machine learning based deep potential (DP) method, we train a high-precision force field model for the LiCl-KCl-LiF system. During force field training, adding new dataset through multiple iterations improves the accuracy of the force field model and its applicability to more configurations. The comparison of density functional theory (DFT) and DP results for the test dataset indicates that our trained DP model has the same accuracy as DFT. Then, we comprehensively investigate the local structure, thermophysical properties, and transport properties of the LiCl-KCl and LiCl-KCl-LiF molten salt systems using the trained DP model. The effects of temperature and LiF concentration on the above properties are analyzed. This work provides guidance for the training of machine learning force fields in molten salt systems and the study of basic physical properties of high-temperature chloride molten salt systems.

Synergistic effects between potassium bubbles and high-energy-rate forging enabled ultrahigh strength and ductility of tungsten alloy

The intrinsic brittleness of tungsten (W) significantly restricts its application as the primary material for plasma-facing components. In this study, we propose a novel approach to improve both the strength and ductility of W-based alloys based on the synergistic effects between potassium (K) bubbles and high-energy-rate forging. K doping was introduced into W, followed by a two-step high-energy-rate forging (HERF) process. This leads to laminated matrix grains with refined sizes and deformation textures, as well as an increase in the density of low-angle grain boundaries and smaller size K bubbles along the grain boundaries. As a result, the prepared W alloys exhibit a substantially reduced ductile-to-brittle transition temperature within the range of room temperature to 50 °C, along with a notable ultimate tensile strength of up to 1393 MPa. Impressively, these alloys also demonstrate remarkable elongation at 200 °C, reaching a value as high as 33.12%. The remarkable mechanical strength and exceptional ductility exhibited by these alloys highlight their considerable potential for commercial application in the field of nuclear fusion engineering.

Electrochemical synthesis of boron-containing coatings on Mg alloy for thermal neutron shielding

The work provides the results of the one-step formation of boron-containing coatings on an Mg–Mn–Ce alloy by plasma electrolytic oxidation. The results of studies of the composition, structure and morphology of heteroxide coatings are presented. It was established that the boron is contained in the coating mainly in the form of B or B2O3. The introduction of B changes the color of coatings, and also helps to increase their porosity. The method of determining the full cross section of the interaction of thermal neutron absorption efficiency by samples material using the installation of neutron-activation analysis based on 252Cf was developed. It was shown that the introduction of boron into the formed coatings allows to increase the macroscopic cross-section of the interaction of samples with thermal neutrons by 3.8 times. This effect opens the potential for the use of synthesized material in the field of nuclear technologies and aerospace industry.

Neutron transport calculation for the BEAVRS core based on the LSTM neural network

With the rapid development of computer technology, artificial intelligence and big data technology have undergone a qualitative leap, permeating into various industries. In order to fully harness the role of artificial intelligence in the field of nuclear engineering, we propose to use the LSTM algorithm in deep learning to model the BEAVRS (Benchmark for Evaluation And Validation of Reactor Simulations) core first cycle loading. The BEAVRS core is simulated by DRAGON and DONJON, the training set and the test set are arranged in a sequential fashion according to the evolution of time, and the LSTM model is constructed by changing a number of hyperparameters. In addition to this, the training set and the test set are retained in a chronological order that is different from one another throughout the whole process. Additionally, there is a significant pattern that is followed when subsetting both the training set and the test set. This pattern applies to both sets. The steps in this design are very carefully arranged. The findings of the experiments suggest that the model can be altered by making use of the appropriate hyperparameters in such a way as to bring the maximum error of the effective multiplication factor keff prediction of the core within 2.5 pcm (10–5), and the average error within 0.5266 pcm, which validated the successful application of machine learning to transport equations.

How to transfer knowledge to Generation Z

Abstract. With this paper, we aim to raise awareness of the challenges of generational transition in the German nuclear industry. We present potential solutions for transferring and preserving knowledge in the future. For approximately 60 years, Germany has operated nuclear facilities successfully and safely. Germany phased out the peaceful use of nuclear energy in 2023 by shutting down the last three nuclear power plants. At the same time, a generational shift is imminent within the next 5–10 years, as a significant number of knowledgeable experts will be retiring. Simultaneously, the first “fully digitalized” Generation Z, whose learning methods and preferences differ significantly from the previous generation (see Fig. 1), will enter the job market (McKinsey & Company et al., 2018). This requires the development and establishment of new methods and didactics (Chillakuri, 2020). Furthermore, educational institutions in Germany are reducing their curriculum offerings in the field of nuclear technology. This necessarily leads to the challenge of introducing and training a growing number of newcomers with limited prior knowledge in the complex field of nuclear technology. In our investigation, we focused on the development of new learning concepts. Various research approaches, studies, and internal evaluations were considered that addressed the learning preferences and styles of Generation Z (McKinsey & Company et al., 2018; Chillakuri, 2020; Cilliers, 2017). Generation Z is characterized by a strong commitment to digital technologies, a high affinity for collaboration, and a preference for interactive and visual learning methods. Unlike previous generations, Generation Z increasingly favours informal, flexible, and context-based learning (Cilliers, 2017). To address these attributes, a multilevel learning concept was developed. The concept includes various digital and asynchronous (on-demand) formats that facilitate an attractive and flexible learning environment. A variety of media types, such as e-learning videos, podcasts, animated films, and virtual realities, were well-received by the participants. Attention span, which has changed compared to previous generations, was taken into account. To maintain attention, playful elements (gamification) were inserted into the format. Additionally, online expert discussions were established, as personal exchanges convey experiences and emotions, leading to a higher level of memorability. The future of nuclear safety and competence in Germany depends on a successful transfer of knowledge in the coming years. A lack of adaptation of learning methods and didactics to the needs of current and future generations risks the loss of a significant portion of accumulated expertise. This loss poses a risk to nuclear safety, can drive up costs, and can lead to project delays of several years.