Hasil untuk "Nuclear engineering. Atomic power"

Jung Sung Kang, Seung Jun Lee

This study proposes a dynamic emergency operating procedural system to address the limitations of static, paper-based emergency operating procedures in nuclear power plants. Despite digital main control rooms, traditional procedures remain static and poorly suited to rapidly changing plant conditions. Operators must still search for relevant steps while ignoring those that do not apply, increasing workload and delaying decisions. The static format also hinders real-time tracking and verification, risking omission of safety-critical actions. To resolve these issues, this study developed the Emergency Guidance Intelligent System (EGIS), which provides real-time monitoring and required task blocks.EGIS comprises three core functions: the Task Block Browser, which delivers only necessary tasks in real-time using a functional-hierarchical task grouping framework; the Critical Safety Function Score Evaluator, which evaluates critical safety functions using fuzzy logic; and the Plant Status Monitor, which visualizes system status and consequence through Multilevel Flow Modeling. EGIS was verified using the Compact Nuclear Simulator with a Loss of Coolant Accident scenario. The results demonstrated that EGIS reduced operation time compared to conventional procedures while effectively replacing the role of traditional paper-based procedures. EGIS is expected to enhance the safety and efficiency of emergency operating procedures in nuclear power plants.

YAO Jiali1, 2, ZHANG Jiangmei2, , WANG Jiaqi1, 2

As an important pillar of modern science, the safety of nuclear technology is highly dependent on accurate neutron detection, and the n/γ discrimination technique in the composite radiation field is directly related to the reliability of detection. Among the n/γ discrimination techniques, the pulse shape discrimination (PSD) method is an important technique in nuclear radiation composite measurements, which works on the basis of the different decay times of fluorescence excitation of different charged particles in scintillators. In order to solve the problems of high hardware cost and hardware impact that existed in the early implementation of the PSD method through electronics hardware, the use of digital technology to achieve n/γ discrimination has gradually become the mainstream. The traditional discrimination methods are time-domain PSD method and frequency-domain PSD method. Among them, the time-domain PSD method has the problem of being affected by noise, and the frequency-domain PSD method has the problem of high hardware requirements. Currently, neural network-based discrimination algorithms were used to screen signals by extracting the variability of their internal information features, so they can circumvent the shortcomings of the time-domain and frequency-domain PSD methods while taking into account the high discrimination effect, which can greatly improve the upper limit of the discrimination performance, even though it requires complex algorithmic modelling and training processes, and has a large operating overhead. Therefore, in this study, in order to make full use of the dual features of time and frequency domains of impulse signals to improve the n/γ discrimination performance, an n/γ discrimination algorithm based on convolutional neural network, attention mechanism, and long and short-term memory neural network (CNN+Attention+LSTM) was proposed. Based on the CLYC detector experimental platform to obtain n/γ hybrid pulse data, the experimental data were screened using the charge comparison method and frequency gradient method. In this study, an intelligent n/γ discrimination was implemented using the module splicing method. Firstly, a sliding convolution filter was applied to the input to process the sequence data via CNN, and the data frequency domain features were extracted for discrimination using convolution kernel and pooling operation to reduce the dimensionality and retain the key modes. Next, feature weights were learned through network loss in the attention mechanism, allowing the model to focus more on important information. Finally, the sequential data were processed through the long-term dependency between the LSTM loop time step and the learning time step, using a gating mechanism to selectively memorize the long-term patterns and extract the data time-domain features for discrimination. This approach enables better feature discrimination by allowing effective feature maps to receive greater weights while ignoring unimportant features. The results show that the CNN-Attention-LSTM discrimination method can effectively improve the effectiveness of n/γ discrimination and provide a new idea for utilizing deeper impulse features.

Zutao Xiang, Liangxing Li, Xiangyang Xu et al.

The main coolant pump (MCP) operates in a high-temperature, high-flow, and corrosive liquid heavy metal environment, and structure analysis have complicated fluid-structure coupling problems. In order to study the coupling characteristics between the MCP blade and coolant, the present study conducts a two-way fluid-structure coupling analysis of liquid lead-bismuth MCP based on three potential impeller materials: T91 steel, Ti3SiC2, and 304 stainless steel. The deformation, equivalent stress, and modal results on moving blades of MCP under different flow conditions are investigated by employing the CFX and Mechanical modules. The results show that the blades made of Ti3SiC2 material exhibit optimal deformation resistance under different flow conditions, which is 11.18 μm at1.0Qd, while blades made of T91 steel experience the lowest maximum equivalent stress at 1.0Qd, which is 8.62 MPa. The maximum equivalent stress is concentrated at the inner edge of the blade, while the maximum deformation occurs at the outer edge of the blade, with both the maximum equivalent stress and deformation decreasing with increasing flowrate. Compared without coupling, the outlet velocity of the T91 steel impeller is the highest with coupling, which is 5.01 m/s. And head attenuation of the T91 steel impeller is the most serious, which is 2 %.

Qianxu Wang, Bin Li, Huihui Hong et al.

Large built-in cryopumps are widely used in nuclear fusion devices, the cryopumps studied in the paper are mainly used to provide a vacuum environment for beam generation and transmission. The cryopump is cooled by forced flow, so the supercritical helium flow heat transfer of the cryopump is investigated, the thermal load of the crysorbent panels of the unit pumping structure is calculated and analyzed by ANSYS Steady Thermal State software, meanwhile the supercritical helium flow heat transfer is simulated by ANSYS Fluent software, then the pressure drop of the fluid, temperature and flow uniformity are analyzed in different flow channels. The results show that the parallel structure with a tube diameter of 17.2 mm can reduce the pressure drop of the flow channel to 4.9E4 Pa, and the inlet velocity of the left and right branches are 1.96 m/s and 2.02 m/s, respectively, and the flow distribution is uniform, while the temperature field meets the requirements of the cryogenic pump. Finally, the model and calculation method are verified by using the laboratory cryopump, the simulation results coincide with the experimental results, which verifies the reliability of the simulation.

Ali Raza Mirza, Rizwan Abbas, Atif Shahbaz

We investigate the nuclear Stark effect induced in hydrogen-like atomic nuclei under super-intense laser fields. Since laser wavelengths are generally larger than nuclear dimensions, direct laser-nucleus interaction is unfeasible. Instead, this effect is induced indirectly through electron oscillations in the laser field, which produce a periodic electric field that shifts the nuclear energy levels. Using perturbation theory, we derive an expression for the energy shift and dynamic polarizability of the nucleus as a function of laser parameters. Our findings reveal that the Nuclear Stark effect can be controlled by adjusting the laser frequency and intensity, potentially enabling applications in nuclear and quantum optical systems.

Vladyslav Bulhakov, Giordano d'Aloisio, Claudio Di Sipio et al.

The introduction of large language models (LLMs) has enhanced automation in software engineering tasks, including in Model Driven Engineering (MDE). However, using general-purpose LLMs for domain modeling has its limitations. One approach is to adopt fine-tuned models, but this requires significant computational resources and can lead to issues like catastrophic forgetting. This paper explores how hyperparameter tuning and prompt engineering can improve the accuracy of the Llama 3.1 model for generating domain models from textual descriptions. We use search-based methods to tune hyperparameters for a specific medical data model, resulting in a notable quality improvement over the baseline LLM. We then test the optimized hyperparameters across ten diverse application domains. While the solutions were not universally applicable, we demonstrate that combining hyperparameter tuning with prompt engineering can enhance results across nearly all examined domain models.

Krzysztof Pachucki

We perform a complete calculation of $α\,(Z\,α)^5\,m$ radiative corrections to the finite nuclear size, the recoil finite size and the nuclear polarizability effects in atomic systems. Results confirm very good agreement for the mean square charge radii difference $r_d^2-r_p^2$ between the deuteron and the proton, as measured in {\em electronic} and muonic isotope shifts.

Martin Obaidi, Marc Herrmann, Elisa Schmid et al.

Sentiment analysis is an essential technique for investigating the emotional climate within developer teams, contributing to both team productivity and project success. Existing sentiment analysis tools in software engineering primarily rely on English or non-German gold-standard datasets. To address this gap, our work introduces a German dataset of 5,949 unique developer statements, extracted from the German developer forum Android-Hilfe.de. Each statement was annotated with one of six basic emotions, based on the emotion model by Shaver et al., by four German-speaking computer science students. Evaluation of the annotation process showed high interrater agreement and reliability. These results indicate that the dataset is sufficiently valid and robust to support sentiment analysis in the German-speaking software engineering community. Evaluation with existing German sentiment analysis tools confirms the lack of domain-specific solutions for software engineering. We also discuss approaches to optimize annotation and present further use cases for the dataset.

Paris Avgeriou, Nauman bin Ali, Marcos Kalinowski et al.

Increasingly, courses on Empirical Software Engineering research methods are being offered in higher education institutes across the world, mostly at the M.Sc. and Ph.D. levels. While the need for such courses is evident and in line with modern software engineering curricula, educators designing and implementing such courses have so far been reinventing the wheel; every course is designed from scratch with little to no reuse of ideas or content across the community. Due to the nature of the topic, it is rather difficult to get it right the first time when defining the learning objectives, selecting the material, compiling a reader, and, more importantly, designing relevant and appropriate practical work. This leads to substantial effort (through numerous iterations) and poses risks to the course quality. This chapter attempts to support educators in the first and most crucial step in their course design: creating the syllabus. It does so by consolidating the collective experience of the authors as well as of members of the Empirical Software Engineering community; the latter was mined through two working sessions and an online survey. Specifically, it offers a list of the fundamental building blocks for a syllabus, namely course aims, course topics, and practical assignments. The course topics are also linked to the subsequent chapters of this book, so that readers can dig deeper into those chapters and get support on teaching specific research methods or cross-cutting topics. Finally, we guide educators on how to take these building blocks as a starting point and consider a number of relevant aspects to design a syllabus to meet the needs of their own program, students, and curriculum.

WANG Xianghan1, HUANG Xiaolong1, YANG Dong2

The decay of atomic nuclei, a process characterized by the transformation of nuclei through the emission of particles or the capture of electrons, is a phenomenon of immense scientific significance. Its exploration and accurate analysis hold the key to unraveling the intricate structure of unstable nuclei, gaining insights into neutrino energy spectra, and validating the underlying principles of decay theories. One of the scientific pursuit of decay lies in the meticulous calculation of the decay spectrum. The decay spectrum serves as a fundamental aspect in the understanding of nuclear decay process. Its comprehensive consideration is pivotal for advancing our knowledge across various domains, from probing the depths of unstable nuclei to extracting valuable information regarding neutrino energy spectra. Moreover, it plays a crucial role in the validation and refinement of existing decay theories, contributing to the continuous evolution of our understanding of nuclear physics. The indispensable part in computing the decay energy spectrum is intricately tied to the consideration of the decay branching ratio. This parameter, crucial for understanding the relative probabilities of different decay pathways, is typically obtained through sophisticated measurement techniques. Commonly, researchers employ the γ-γ coincidence method or directly measure with total absorption spectrometer method to obtain data on β decay products. These methods provide essential information that serves as the foundation for unraveling the complexities inherent in the decay process. Simultaneously, the calculation of the decay spectrum at the transition of a single energy level is based on the Fermi decay theory. Rooted in quantum mechanics, this theory offers a comprehensive framework for calculating the transition probabilities associated with nuclear decay. It enhances the accuracy of predicting the decay spectrum, enabling to develop a nuanced understanding of the underlying physics governing these processes. In the context of this paper, the empirical focus was on the decay of 96Y, serving as a representative example. The experimental decay branching ratio data for 96Y decay meticulously evaluated and from TAGS were discussed. To further refine the computed decay spectrum, shape factor correction was introduced. The addition of shape factor correction represented an adjustment, aimed at improving the alignment between theoretical predictions and experimental observations. This correction mechanism ensures that the computed energy spectrum not only adheres closely to the experiment data but also reflects the intricacies of the underlying decay processes. Beyond its specific implications for the decay of 96Y, the necessity of fostering a deeper understanding of atomic decay processes and taking forbidden transitions into consideration was stressed.

LIU Haopo, LI Yunzhao, WU Hongchun, CAO Liangzhi

In analyzing the power density distribution within the core of a nuclear reactor, it is necessary to employ numerical methods to solve the neutron transport equation and obtain the neutron flux density distribution. Deterministic method, either the two-step or the one-step scheme, employed multi-group approximation techniques, which inevitably required the production of a special multi-group database and intricate resonance calculations. Although the probabilistic method could be calculated based on the continuous energy library, the computational efficiency could not meet the needs of large-scale engineering calculations. According to the characteristics of the microscopic cross-section data of the reaction between neutrons and nuclide nuclei under different energy conditions, the all-energy range was divided into resonance energy range and non-resonance energy range. In order to eliminate the multi-group approximation in the deterministic method, a method for calculating neutron transport equation in the non-resonant energy region based on function expansion was proposed. Initially, the non-resonant energy region was subdivided into segments, and within each segment, orthogonal polynomials serve as base functions for expanding the neutron flux density, which realized the processing of single energy independent variable in the neutron flight and absorption process, as well as the handling of double energy independent variable in the neutron scattering process. On the one hand, thermal neutrons were affected by the target nuclear thermal motion, chemical bond binding and scattering wave interference effect, leading to the phenomenon of up-scattering. On the other hand, fast neutrons were affected by a variety of different scattering reactions, resulting in down-scattering. Ultimately forming the coupling calculations between different energy ranges. Based on this foundation, the coupling calculation method between different energy segments in the non-resonant energy range was investigated, and an effective iterative calculation and numerical solution method was established. The solution for the neutron flux density distribution was transformed into solving the corresponding expansion coefficient moments, and then provided the distribution of neutron flux density and nuclear reaction rates within each energy segment. Finally, the neutron transport calculation program of continuous energy determination theory in non-resonant energy range was developed, and the different non-resonant nuclides were preliminarily verified, including single nuclide and multi-nuclide media. The computed results were compared with the existing continuous energy probabilistic neutron transport calculation program NECP-MCX. The verification results show that the relative deviation between the calculated values and the reference values is within 3.5%, demonstrating the feasibility of the continuous energy deterministic neutron transport calculation method based on function expansion.

Sang-Kyung Lee, Ser Gi Hong

The discrimination of the source for xenon gases' release can provide an important clue for detecting the nuclear activities in the neighboring countries. In this paper, three machine learning techniques, which are logistic regression, support vector machine (SVM), and k-nearest neighbors (KNN), were applied to develop the predictive models for discriminating the source for xenon gases’ release based on the xenon isotopic activity ratio data which were generated using the depletion codes, i.e., ORIGEN in SCALE 6.2 and Serpent, for the probable sources. The considered sources for the neighboring countries of South Korea include PWRs, CANDUs, IRT-2000, Yongbyun 5 MWe reactor, and nuclear tests with plutonium and uranium. The results of the analysis showed that the overall prediction accuracies of models with SVM and KNN using six inputs, all exceeded 90%. Particularly, the models based on SVM and KNN that used six or three xenon isotope activity ratios with three classification categories, namely reactor, plutonium bomb, and uranium bomb, had accuracy levels greater than 88%. The prediction performances demonstrate the applicability of machine learning algorithms to predict nuclear threat using ratios of xenon isotopic activity.

Sonja Hyrynsalmi, Ella Peltonen, Fanny Vainionpää et al.

In the extant literature, there has been discussion on the drivers and motivations of minorities to enter the software industry. For example, universities have invested in more diverse imagery for years to attract a more diverse pool of students. However, in our research, we consider whether we understand why students choose their current major and how they did in the beginning decided to apply to study software engineering. We were also interested in learning if there could be some signs that would help us in marketing to get more women into tech. We approached the topic via an online survey (N = 78) sent to the university students of software engineering in Finland. Our results show that, on average, women apply later to software engineering studies than men, with statistically significant differences between genders. Additionally, we found that marketing actions have different impacts based on gender: personal guidance in live events or platforms is most influential for women, whereas teachers and social media have a more significant impact on men. The results also indicate two main paths into the field: the traditional linear educational pathway and the adult career change pathway, each significantly varying by gender

Domantas Burba, Hubert Dunikowski, Martin Robert-de-Saint-Vincent et al.

Ultra-cold fermionic atoms, having two valence electrons, exhibit a distinctive internal state structure, wherein the nuclear spin becomes decoupled from the electronic degrees of freedom in the ground electronic state. Consequently, the nuclear spin states are well isolated from the environment, rendering these atomic systems an opportune platform for quantum computation and quantum simulations. Coupling with off-resonance light is an essential tool to selectively and coherently manipulate the nuclear spin states. In this paper, we present a systematic derivation of the effective Hamiltonian for the nuclear spin states of ultra-cold fermionic atoms due to such an off-resonance light. We obtain compact expressions for the scalar, vector and tensor light shifts taking into account both linear and quadratic contributions to the hyperfine splitting. The analysis has been carried out using the Green operator approach and solving the corresponding Dyson equation. Finally, we analyze different scenarios of light configurations which lead to the vector- and tensor-light shifts, as well as the pure spin-orbit coupling for the nuclear spin.

Qiang Li, Bin Li, Xiuwei Li et al.

To study the lubrication performance of tilting-pad thrust bearing (TPTBs) during start-up in nuclear pump, a hydrodynamic lubrication model of TPTBs was established based on the computational fluid dynamics (CFD) method and the fluid-structure interaction (FSI) technique. Further, a mesh motion algorithm for the transient calculation of thrust bearings was developed based on the user defined function (UDF).The result demonstrated that minimum film thickness increases first and then decreases with the rotational speed under start-up condition. The influence of pad tilt on minimum film thickness is greater than that of collar movement at low speed, and the establishment of dynamic pressure mainly depends on pad tilt and minimum film thickness increases. As the increase of rotational speed, the influence of pad tilt was abated, where the influence of the moving of the collar dominated gradually, and minimum film thickness decreases. For TPTBs, the circumferential angle of the pad is always greater than the radial angle. When the rotational speed is constant, the change rate of radial angle is greater than that of circumferential angle with the increase of loading forces. This study can provide reference for improving bearing wear resistance.

Xiaoman He, Jingqiong Zhang, Chi Lu et al.

Radiation resistance is a main obstacle for clinical treatment of lung squamous cell carcinoma (LUSC). Recent studies have demonstrated that long noncoding RNA (lncRNA) can participate in LUSC tumorigenesis and radiosensitivity. The current study explored the role and mechanism of lncRNA FOXD1-AS1 in mediating radioresistance of LUSC cells. Expression levels of FOXD1-AS1, miR-4801 and pumilio RNA binding family member 1 (PUM1) in LUSC cell lines were estimated by RT-qPCR. PUM1 protein expression in cells were quantified by western blotting. CCK-8 and colony formation assays were conducted to measure LUSC cell viability and proliferation, respectively. TUNEL assays were used to analyze LUSC cell apoptosis. Subcellular localization of FOXD1-AS1 was determined via subcellular fractionation assay. The regulatory relationship among FOXD1-AS1, miR-4801 and PUM1 was verified by RNA pulldown assay, luciferase reporter assay and RNA immunoprecipitation assay.LncRNA FOXD1-AS1 was upregulated in LUSC cells. Knockdown of FOXD1-AS1 affected LUSC cell biological behaviors before and after radiation, including suppressing cell proliferation and promoting apoptosis. Moreover, silencing FOXD1-AS1 significantly promoted the radiosensitivity of LUSC cell lines, as evidenced by further inhibited cell proliferative ability and greatly enhanced apoptotic rate in the experimental group received radiation treatment and FOXD1-AS1 knockdown. In addition, FOXD1-AS1 bound with miR-4801 that targeted PUM1. PUM1 was also upregulated in LUSC cells. PUM1 overexpression reversed the promoting impact of FOXD1-AS1 depletion on LUSC cell radiosensitivity. Overall, silencing of FOXD1-AS1 promotes the radiosensitivity of LUSC cells via the miR-4801/PUM1 axis.

Song Huang, Yu Song, Junlian Yin et al.

A reactor coolant pump (RCP) is essential for transporting coolant in the primary loop of pressurized water reactors. In the advanced passive reactor, the absence of a long pipeline between the steam generator and RCP serves as a transition section, resulting in a non-uniform flow field at the pump inlet. Therefore, the characteristics of the pump should be investigated under non-uniform flow to determine its influence on the pump. In this study, the pressure pulsation characteristics were examined in the time and frequency domains, and the sources of low-frequency and high-amplitude signals were analyzed using wavelet coherence analysis and numerical simulation. From computational fluid dynamics (CFD) results, non-uniform inflow has a great effect on the flow structures in the pump's inlet. The pressure pulsation in the pump at the rated flow increased by 78–128.7% under the non-uniform inflow condition in comparison with that observed under the uniform inflow condition. Furthermore, a low-frequency signal with a high amplitude was observed, whose energy increased significantly under non-uniform flow. The wavelet coherence and CFD analysis verified that the source of this signal was the low-frequency pulsating vortex under the steam generator.

Aleksandr P. Sorokin, Yuliya A. Kuzina, Radomir Sh. Ashadullin et al.

It is shown that, as the result of developing alkali liquid metal coolants, including sodium, eutectic sodium-potassium alloy, lithium and cesium, the scientific basis has been established for their application in nuclear power. The paper presents data from investigations of thermophysical, neutronic and physicochemical properties and characteristics of various alkali liquid metal coolants, the content of solid-phase and dissolved impurities in coolants, mass transport of impurities in circulation circuits with alkali liquid metal coolants, development of systems for removal of impurities, and control of the content of impurities in alkali liquid metal coolants. Alkali liquid metal coolants are considered as a part of a system that includes a structural material in contact with the coolant, and a gas space that compensates for the thermal expansion of the coolant. The state of the system is defined by the physicochemical properties of the system’s components. And the coolant and the structural materials also represent subsystems consisting of a base material, a coolant and impurities contained both in the material and in the coolant. It has been shown that each alkali liquid metal coolant has its own set of impurities that define its technology. It depends on the physicochemical properties of the solution of the structural material impurities and components in the coolant. Objectives have been formulated for investigating further alkali liquid metal coolants, as stemming from the need to improve the efficiency, environmental friendliness, reliability and safety, and for extending the life of nuclear power plants in operation or under design. Alkali liquid metals are promising candidate materials for being used in thermonuclear power not only as the coolant but also as the tritium breeding medium. These include, first of all, lithium and its eutectic alloy with lead (17 at. % of lithium). The possibility for using lithium or a lithium-lead alloy as a coolant in the blanket of the international thermonuclear power reactor is compared.

Walid Maalej, Yen Dieu Pham, Larissa Chazette

Requirements Engineering (RE) is the discipline for identifying, analyzing, as well as ensuring the implementation and delivery of user, technical, and societal requirements. Recently reported issues concerning the acceptance of Artificial Intelligence (AI) solutions after deployment, e.g. in the medical, automotive, or scientific domains, stress the importance of RE for designing and delivering Responsible AI systems. In this paper, we argue that RE should not only be carefully conducted but also tailored for Responsible AI. We outline related challenges for research and practice.

Min-Geon Choi, Martin Law, Shin-Kien Djeng et al.

In this study, the images of specific prompt gamma (PG)-rays of 719 keV emitted from proton–boron reactions were analyzed using single-photon emission computed tomography (SPECT). Quantitative evaluation of the images verified the detection of anatomical changes in tumors, one of the important factors in daily adaptive proton therapy (DAPT) and verified the possibility of application of the PG-ray images to DAPT. Six scenarios were considered based on various sizes and locations compared to the reference virtual tumor to observe the anatomical alterations in the virtual tumor. Subsequently, PG-rays SPECT images were acquired using the modified ordered subset expectation-maximization algorithm, and these were evaluated using quantitative analysis methods. The results confirmed that the pixel range and location of the highest value of the normalized pixel in the PG-rays SPECT image profile changed according to the size and location of the virtual tumor. Moreover, the alterations in the virtual tumor size and location in the PG-rays SPECT images were similar to the true size and location alterations set in the phantom. Based on the above results, the tumor anatomical alterations in DAPT could be adequately detected and verified through SPECT imaging using the 719 keV PG-rays acquired during treatment.