The current strategy for joining ITER divertor cooling pipes is to conduct semi-automated autogenous Tungsten Inert Gas (TIG) welding on thin-walled pipes using an inserted flat washer filler ring. In this approach, the positioning of the filler ring and the alignment of the pipe stubs so far can only be achieved manually. However, it has limitations for future maintenance because human interventions may be limited or completely prohibited in contaminated environments, requiring the need for remotely operated tools and systems. In addition, maintenance of cooling pipes will involve cutting and re-welding of the parts. However, components have limited lifespan for reuse. Additive manufacturing (AM) is an advanced technique that provides one potential way to overcome the limitations. This work investigates the use of the AM method to deposit material as an alternative approach to using filler rings, which a flange feature was firstly built on the pipe end using laser blown powder direct energy deposition (DED). Thereafter, semi-automated autogenous TIG welding was conducted on the AM modified pipe stubs. The results suggest that using the AM produced parts has achieved compliant pipe joins, implying possible improvements to maintenance strategies for future fusion power plants and experimental devices.
Abstract This paper proposes an approach that combines reduced-order models with machine learning in order to create physics-informed digital twins to predict high-dimensional output quantities of interest, such as neutron flux and power distributions in nuclear reactor cores. The digital twin is designed to solve forward problems given input parameters, as well as to solve inverse problems given some extra measurements. Offline, we use reduced-order modeling, namely, the proper orthogonal decomposition, to assemble physics-based computational models that are accurate enough for the fast predictive digital twin. The machine learning techniques, namely, k-nearest-neighbors and decision trees, are used to formulate the input-parameter-dependent coefficients of the reduced basis, after which the high-fidelity fields are able to be reconstructed. Online, we use the real-time input parameters to rapidly reconstruct the neutron field in the core based on the adapted physics-based digital twin. The effectiveness of the framework is illustrated through a real engineering problem in nuclear reactor physics—reactor core simulation in the life cycle of the HPR1000 governed by the two-group neutron diffusion equations affected by input parameters, i.e., burnup, control rod inserting step, power level, and temperature of the coolant—which shows potential applications for online monitoring purposes.
Peking University is implementing new superconducting magnets in a laser-driven proton accelerator, resulting in a lighter and more compact proton therapy facility. To efficiently transport protons with a wide energy spread, we propose a double-bend achromat design that rotates particles by 90 degrees and suppresses dispersion. Two focusing options are considered: integrating quadrupole magnets within the dipole magnets to create a hybrid field, or separating the quadrupole for independent focusing and bending. We first delve into the related lattice design, followed by an in-depth analysis of coil selection for each option. The magnetic field of the coil is indeed calculated using a combination of the Biot–Savart law and the Multi-Level Fast Multipole Method (MLFMM). We assess field quality and feasibility using TraceWin and zgoubi simulations in fieldmap, accounting for dipole-induced dispersion and quadrupole-induced chromatic effect. Through the analysis of superconducting magnets and beam dynamics, and by considering the transmission requirements of laser-plasma-accelerated protons, we have indeed developed a beam transport scheme. This scheme is anticipated to integrate laser-accelerated protons into a compact proton therapy facility, and it will eventually be implemented.
Rotating machinery is a kind of significant equipment that widely used in nuclear power plants (NPPs). The harsh operating environment and long-term continuous operation of the rotating machinery can cause various faults due to wear, vibration et al., that threatens the safety of the NPPs. Intelligent fault diagnosis techniques can timely discover the abnormality of the rotating machinery, that received extensively attention in recent years. A fault diagnosis method for NPPs rotating machinery based on MoCo siamese neural network is proposed to address the issues of high noise, small sample, and low accuracy in fault diagnosis under actual operating conditions. The wavelet transform is used to denoise the sensor signals of rotating machinery and extract time-frequency features. The training samples are encoded by the siamese neural network method. The momentum contrast (MoCo) method is used to update the encoder of the siamese neural network. The cosine similarity is used to measure the similarity of sample coding features. The dataset of rotating machinery from Machinery Failure Prevention Technology (MFPT) is adopted to validate the effectiveness and accuracy of the MoCo siamese neural network method. The results shows that the proposed fault diagnosis method has strong noise resistance capability and can accurately diagnose rotating machinery in small sample conditions, demonstrating the potential application value in the fault diagnosis of NPPs rotating machinery.
Ashis Kumar Mandal, Md Nadim, Chanchal K. Roy
et al.
Research in software engineering is essential for improving development practices, leading to reliable and secure software. Leveraging the principles of quantum physics, quantum computing has emerged as a new computational paradigm that offers significant advantages over classical computing. As quantum computing progresses rapidly, its potential applications across various fields are becoming apparent. In software engineering, many tasks involve complex computations where quantum computers can greatly speed up the development process, leading to faster and more efficient solutions. With the growing use of quantum-based applications in different fields, quantum software engineering (QSE) has emerged as a discipline focused on designing, developing, and optimizing quantum software for diverse applications. This paper aims to review the role of quantum computing in software engineering research and the latest developments in QSE. To our knowledge, this is the first comprehensive review on this topic. We begin by introducing quantum computing, exploring its fundamental concepts, and discussing its potential applications in software engineering. We also examine various QSE techniques that expedite software development. Finally, we discuss the opportunities and challenges in quantum-driven software engineering and QSE. Our study reveals that quantum machine learning (QML) and quantum optimization have substantial potential to address classical software engineering tasks, though this area is still limited. Current QSE tools and techniques lack robustness and maturity, indicating a need for more focus. One of the main challenges is that quantum computing has yet to reach its full potential.
Abstract In this paper, a dynamic prediction scheme that combines the data assimilation method and dynamic mode decomposition (DMD) is brought out for the prediction of the whole-core power distribution under xenon oscillations within the HRP1000 reactor. The DMD is used to predict the power values over the nodes where in-core detectors exist, and predicted power is then extended to the whole core using data assimilation methodologies, e.g. the inverse distance–based data assimilation method. In the data assimilation stage, the selection of the background physical field and the regularization factor under different noise levels is investigated. A series of numerical experiments, based on the HPR1000 proof of feasibility of the coupling scheme, is conducted under low noise levels or low prediction step sizes. Finally, the optimal application conditions and the prediction performance of the coupling scheme in different noise levels are analyzed for practical engineering usage.
ABSTRACT For decades, the United Kingdom has maintained a stockpile of approximately 225 nuclear warheads—up to 120 of which are available for delivery by four Vanguard-class nuclear-powered ballistic missile submarines. The stockpile is now increasing. The United Kingdom is currently building a new class of Dreadnaught-class submarines and developing a new nuclear warhead. In addition, it is expected that the United Kingdom will eventually increase the size of its arsenal and that Royal Air Force (RAF) Lakenheath will regain a United States Air Force nuclear mission in the coming years. The Nuclear Notebook is researched and written by the staff of the Federation of American Scientists’ Nuclear Information Project: director Hans M. Kristensen, associate director Matt Korda, and senior research associates Eliana Johns and Mackenzie Knight. To see all previous Nuclear Notebook columns in the Bulletin of the Atomic Scientists dating back to 1987, go to https://thebulletin.org/nuclear-notebook/.
This paper explores the intricate relationship between man and nature in Ernest Hemingway’s The Old Man and the Sea through the lens of deep ecology. It challenges the traditional anthropocentric interpretation of the novella, proposing that the protagonist Santiago’s struggle is not merely a tale of human triumph over nature but a journey towards understanding and coexisting with the natural world. By applying the principles of deep ecology, the study reveals how Santiago’s evolving relationship with the marlin and other sea elements reflects a broader ecological consciousness. The analysis also draws parallels between Santiago’s experience and the Biblical narrative of Jonah, suggesting that Santiago’s success is not solely due to his physical endurance but also the cosmic forces that aid him. This paper ultimately rethinks the themes of struggle and victory in the novella, emphasising the need for a harmonious relationship between humanity and the environment.
Garlic is a versatile vegetable commonly grown in subtropical and highland agroecosystems, which is utilized for its culinary, medicinal, and spice properties. The use of garlic as a medicinal aid can be traced back to ancient times. The health benefits of garlic production are attributed to its antiviral, antibacterial, and antifungal properties. The use of garlic is prevalent in both traditional and modern healthcare systems, where it is used to treat a wide range of conditions. Numerous studies have reported the therapeutic properties of garlic, and its effectiveness has been demonstrated in clinical trials. The growing global interest in health and wellness, the widespread use of garlic as a spice, and its potential economic, social, and health benefits have contributed to a surge in its demand worldwide. This review aims to provide a comprehensive overview of the scientific literature on the morphological descriptions of garlic and its nutritional and health significance.
Future fusion reactors like ITER and DEMO will have all-tungsten (W) walls and long pulses. These features will make wall conditioning more difficult than in most of the existing devices. The W Environment Steady-state Tokamak (WEST) is one of the few long pulse (364 s) fusion devices with actively cooled W plasma-facing components in the world. WEST is a unique test bed to study impurity migration and plasma density control via reactor relevant wall conditioning techniques. The phase II of WEST operations began in 2022, after the installation of a new lower divertor, now entirely equipped with actively cooled, ITER grade, W monoblocks. After pump down, we baked WEST between 90 °C and 170 °C for ∼2 weeks. After 82.5 h at 90 °C and 33 h at 170 °C, vacuum conditions were stable with a vessel pressure of 6x10-5 Pa and mass spectra dominated by H2 molecules. While at 170 °C, we performed ∼40 h of D2 glow discharge cleaning (GDC) and ∼5 h of glow discharge boronization (GDB), using a 15 %-85 % B2D6-He mix and a total boron mass of ∼12 g. This was the very first GDB at such high temperature for WEST. The whole wall conditioning sequence led to a ∼10 times reduction of the H2O signal as well as to a ∼3 times reduction of the O2 signal, according to mass spectra. Once back to 70 °C, the vessel pressure was 5.5x10-6 Pa and plasma restart was seamless with ∼30 s cumulated over the very first 5 pulses and an Ohmic radiated power fraction Frad = 0.6, showing successful conditioning of the new ITER grade divertor. The effect of the first, ‘hot’ GDB faded with a characteristic cumulative injected energy of 2.45 GJ and saturation towards Frad ∼0.8. After 1.4 h and 7.5 GJ of cumulative plasma time and injected energy, we carried out a second GDB, this time at 70 °C. This ‘cold’ GDB initially led to a much lower Ohmic Frad = 0.3–0.4 but the effect lasted ∼7 times less, with a characteristic cumulative injected energy of 0.37 GJ. At the end of the campaign, we cumulated ∼3h and ∼30 GJ through repetitive, minute long pulses without any boronization. Throughout this 4-weeks-long experiment, Frad in the 4 MW heating phase evolved only marginally (from 0.5 to 0.55). This increase is mostly due to the build-up of re/co-deposited layers on both lower divertor targets.
ThO2 is a promising fuel for next-generation nuclear reactors. As a critical quantity measuring its radiation tolerance, the dependence of the threshold displacement energy on temperature and crystal orientation in ThO2 is unclear and established using comprehensive molecular dynamics simulations in this work. For both Th and O primary knock-on atoms (PKAs), the thresholds, denoted as EdTh and EdO, respectively, are calculated using two different interatomic potentials. Similar temperature and orientation dependence are observed, albeit with some quantitative differences. While on average over all orientations, higher energy is required for Th PKAs than O PKAs to displace atoms, the polar-averaged EdTh is significantly lower than that for EdO. Further, EdTh and EdO show different crystal orientation dependence and temperature dependence. Notably, the cubic symmetry in the fluorite structure is followed by EdTh, but does not hold for EdO because of the existence of two sublattices. The much higher average EdO than EdTh and their different temperature dependence are interpreted by the distinct recombination rates of Th and O Frenkel pairs in thermal spikes, resulting from the substantially lower migration barriers of O vacancies and interstitials. The recombination of O vacancies and interstitials, both of which are charged, is further enhanced by the Coulomb interaction at small Frenkel pair separations. The new findings are discussed for their generality in fluorite-structured oxides by comparing the results in ThO2 and UO2.
Gallium oxide, a wide band gap semiconductor, is a focus material in the semiconductor field at present. Many mature processes have been developed for n-type doping of gallium oxide. However, the conventional doping process has not achieved its p-type doping on bulk crystals, which hinders its application. Proton irradiation transmutation doping is considered to be a more likely p-type doping method than thermal diffusion method and ion implantation method. Proton irradiation transmutation doping is realized by using the transmutation products produced by the nuclear reaction between high-energy protons and target materials. Proton irradiation transmutation doping can put doping atoms at lattice sites. It can also produce more uniform impurity distribution in target materials. What is more, proton irradiation transmutation can produce many elements in gallium oxide crystals. The co-doping effect of many different elements can not be considered as the superposition of single doping effect. Currently, it is considered that two element co-doping has the effect of reducing ionization energy. Therefore, it is hopeful to realize p-type doping of gallium oxide by Coulomb coupling effect of many doping elements imported by proton irradiation transmutation. In this paper, the transmutation doping of gallium oxide irradiated by 100 MeV protons was simulated and analyzed by using the Monte Carlo software FLUKA of nuclear reaction. The simulation conditions were set according to the beam output capacity of the high-current proton cyclotron of China Institute of Atomic Energy. In the analysis, there are 17 kinds of elements and about 80 kinds of nuclides that have significant influence on gallium oxide doping. Over half of nuclides are radionuclides. Simulation calculation was mainly about the activity and transmutation element concentration of gallium oxide after proton irradiation. The results show that the activation activity decreases by about four orders of magnitude after 100 cooling days, and the element concentration of transmutation products tends to be stable. Within the depth range of 1.50 cm of gallium oxide, the specific activity of the target material does not change obviously with the depth. The analysis of element concentrations of transmutation products with different doping types shows that proton irradiation transmutation can generate net p-type doping. The net p-type doping concentration is different at different depths of the target material. It is the largest at the depth of 0.60-0.90 cm, which can reach 4.26×1014 cm−3 per 1016 cm−2 proton fluence. Compared with the doping of 40 MeV proton irradiation and fast neutron irradiation, 100 MeV proton irradiation transmutation doping efficiency is higher.
Despite being developed more than four decades ago based on expert judgment, the THERP time-reliability correlation (TRC) remains widely employed for calculating diagnosis human error probabilities in human reliability analysis for nuclear power plant risk assessment. However, with numerous advancements in nuclear plant equipment and operations, as well as the emergence of plants featuring advanced interfaces, there's a growing need to validate the THERP TRC. The objective of this study is to establish a TRC for the diagnosis human error probability in a modern reference nuclear power plant equipped with up-to-date human–machine interfaces and compare it with the median of the THERP TRC. To achieve this goal, we devised a method to gather event diagnosis times from a simulator and developed procedures to derive diagnosis TRCs using this data. Our findings indicate that while the median of the THERP TRC offers a conservative diagnosis human error probability for up to 25 min, it becomes overly optimistic beyond this threshold.
Methodology for suppressing or recovering the distorted spectra, which may occur due to mutual non-uniformity and nonlinear response when a multi-detector is simultaneously operated for gamma spectroscopy, is presented with respect to its applicability to stabilization of spectra having the non-identical feature using modified full spectrum reallocation method. The modified full-spectrum reallocation method is extended to provide multiple coefficients that describe the gain drift for multi-division of the spectrum and they were incorporated into an optimization process utilizing a random sampling algorithm. Significant performance improvements were observed with the use of multiple coefficients for solving partial peak dislocation. In this study, our achievements to confirm the stabilization of spectrum having differences in moments and modify the full spectrum reallocation method provide the feasibility of the method and ways to minimize the implication of the non-linear responses normally associated with inherent characteristics of the detector system. We believe that this study will not only simplify the calibration process by using an identical response curve but will also contribute to simplifying data pre-processing for various studies as all spectra can be stabilized with identical channel widths and numbers.
The development of high-Z (high atomic number) radiation shielding materials is vital in order to protect personnel who work with harmful gamma radiation sources. At the same time, the emission of external bremsstrahlung (EB) radiation in those shielding materials when the radiation source emits beta particles as well as gamma radiation is also of prime concern.The production of EB in films of lead monoxide (PbO) loaded polycarbonate (PC) composite at eleven different filler levels (FLs) varying, in terms of weight fraction, from 0.0 % up to 10.0 % were investigated experimentally by using beta particles from strontium-90/yttrium-90 (90Sr/90Y) radioactive source. A nonlinear relation is observed between EB intensity and target thickness. The effective atomic numbers of the prepared PbO-filled PC composite films (at different FLs) were determined via EB measurements, followed by calculations, and the values obtained were compared with the modified atomic numbers which were determined for the same composite films (at different FLs) using the Markowicz and Van Grieken equation, and it was found that they are in good agreement. Finally, the atomic number dependence of EB in these composite films (PbO-filled PC composites) has been studied. It is obtained that the intensity of EB spectra depends on the square of the atomic number of the target material.
BackgroundFLiBe is commonly used as the coolant and carrier salt in liquid molten salt reactors (MSRs). Its certain moderating properties and thermal neutron scattering attributes affect the neutronic performance of the MSR, and this in turn influences the physical design and safe operation of the reactor. Consequently, studying FLiBe's thermal neutron scattering data is essential for MSRs.PurposeThis study aims to analyze the influence of of FLiBe thermal neutron scattering on neutronic performances of a 65-MW MSR.MethodsFirst, according to the requirements, a core model of a 65-MW MSR was established by using the general Monte Carlo procedure. Then, the neutronics performance of the MSR was calculated by considering the scattering cross-section of the free gas model and FLiBe thermal neutron scattering data (e.g., the neutron spectrum, effective multiplication factor, and nuclide reactivity rate). Finally, the changes in the influence of FLiBe thermal neutron scattering effect on neutronic properties under different energy spectra were compared.ResultsThe computation results show that, by considering the thermal scattering effect of FLiBe molten salt, the neutron energy spectrum in the core of the MSR becomes harder, 235U fission rate decreases, the keff value of the reactor decreases, but the density coefficient in the temperature reaction coefficient of the fuel keeps almost unchanged, and the Doppler coefficient decreases by 0.28×10-5 K-1. With the hardening of the energy spectrum, the variation in the 235U fission rate reduction decreases, and the decrease in keff caused by thermal neutron scattering changs from 9.2×10-4 to 2×10-4.ConclusionsTherefore, it is necessary to incorporate FliBe's thermal neutron scattering data into the physical calculations for the MSR core.
The aim of the study is the activity concentration measurements of organic and inorganic 14C in the discharges of JSC “Institute of Nuclear Materials” (INM). In INM the research water-water reactor “IVV-2M” is operating. Collecting of 14C species was performed using a 14C sampler with a chromium oxide and platinum catalysts at different temperatures: 400, 550 and 700 °C. The measurements of 14C activity were performed using a liquid scintillation counter. The share of organic 14C in emissions ranged from 0.30 to 0.84 and depends on the temperature of the catalyst, core structure and reactor operating mode.