131I is a typical fission product in nuclear reactors. It has a strong affinity for the human thyroid gland and is an important nuclide of concern in radiation protection under both normal and accident conditions of reactors. Accurate measurement of its radioactivity is of great significance. The main measurement method involves collecting 131I in aerosols using an activated carbon adsorption device and then analyzing it with a γ spectrometer. This study proposes a bidirectional ratio method to obtain the γ detection efficiency through integrating the depth distribution coefficient of 131I in activated carbon. Compared with the traditional methods of preparing standard uniform volume sources or using destructive analysis, this experimental method is more reasonable and reliable. In addition, to verify the reliability of this method, experimental verification of the proportional coefficient of bidirectional measurement was conducted, and experimental work on the correlation analysis between sampling flow rate and distribution coefficient was provided. The experiments show that the detection efficiency of the iodine cartridge source with a real depth distribution coefficient obtained by the volume source integration method incorporating a probability function can quickly and conveniently obtain the γ detection efficiency of non-uniformly distributed iodine cartridge sources, providing a feasible approach for accurately measuring the radioactive activity of the fission product 131I in the environment.
Recent DIII-D experiments on Small Angle Slot (SAS) divertors have confirmed that a combination of divertor closure and target shaping can enhance cooling across the divertor target and increase energy dissipation, but with significant dependence on BT (toroidal magnetic field) direction. In these novel divertors, the roles of closure, target shaping, drifts, and scale lengths are all interconnected in optimizing dissipation, with the separatrix electron density neSEP being the key parameter associated with the level of dissipation/detachment. After modifying the original flat-targeted graphite SAS to include a V shape with a tungsten coating on the outer side of the divertor (SAS-VW), matched series of discharges were run to compare to detailed SOLPS-ITER modeling. Experimentally, when run as designed with the outer strike point at the slot vertex, SAS-VW requires nearly identical neSEP for detachment as the original SAS, with little difference in dissipation for the new geometry. This is in contrast to (1) earlier modeling predictions that a small change of the SAS geometry to a V shape should enhance dissipation at the same neSEP for magnetic configurations having better H-mode access (ion B × ∇B drift directed into the divertor), and (2) despite the achievement of significantly higher (2-7x) neutral pressures and compression in the SAS-VW slot. Comparisons of experimental density scans to the most recent SOLPS-ITER modeling with ExB drifts show reasonable agreement for dissipation/detachment onset when using separatrix density as the independent parameter. In order to help understand the discrepancy in modeled vs actual performance for the new configuration, additional measurements varying gas injection location and impurity injection were undertaken. In-slot D2 gas fueling is more effective (5–22 %) in promoting detachment, in accord with modeling. In-slot impurity injection (N2 or Ne) can yield 30 % lower core Zeff and 15 % less confinement degradation after detachment compared to main chamber puffing, as well as relatively lower tungsten leakage from the divertor. Modeling can also reproduce the improved detachment seen as the strike point moves inboard of the slot vertex.While we can explain the effects of the most important parameters causing energy dissipation in these slot divertors, it remains that many aspects of their behavior cannot be accurately modeled using state-of-art codes such as SOLPS-ITER. This is of concern for future model-driven designs utilizing similar V-shaped geometries.
Interim storage of Used Nuclear Fuel (UNF) is increasingly important due to saturated fuel pools at Nuclear Power Plants (NPPs). Safe UNF storage requires a detailed assessment of dry cask systems, focusing on thermal, mechanical, and corrosion aspects, which are yet to be fully studied for Korean systems. This study examines the thermal performance of Korean dry cask storage, called KORAD-21 under three cases: normal, direct fire, and indirect fire exposure. Additionally, it considers beyond-design-basis conditions and the impact of radiative heat transfer in the thermal model. The first case represents normal operation while the second and third cases involve fire exposure, modeled as direct and indirect fire. Direct fire involves contact with the cask surface, with 700 °C, 800 °C, 900 °C, and 1000 °C fire for 5–50 min. All cask components stayed below safety limits except at 1000 °C for 50 min, indicating a beyond-design-basis accident. Nonetheless, these results align with U.S. Nuclear Regulatory Commission (NRC) guidelines. Similarly, for indirect fire using diesel and kerosene at radii of 0.5 m, 1 m, and 1.5 m, peak temperatures remained within safety limits. Including radiative heat transfer in the thermal model is crucial for consistent and accurate results.
To enhance the mechanical strength of Li4SiO4 and reduce its sensitivity to carbon dioxide and water, advanced tritium breeder core–shell Li2TiO3-Li4SiO4 was designed and fabricated by graphite bed method. The 1:1 phase ratio between Li2TiO3 and Li4SiO4 was confirmed by X-ray diffraction (XRD) and Rietveld refinement. Scanning electron microscopy (SEM) revealed that submicron-sized Li2TiO3 grains aggregated at the grain boundaries of Li4SiO4. Micro-computed tomography (Micro-CT) distinctly illustrated the shell-structure and the three-dimensional distribution of internal pores, aligning with the original design requirements and expectations. Neutron irradiation and out-of-pile tritium release experiments were conducted to evaluate the tritium release performance. Temperature-programmed desorption tritium release spectra exhibited two distinct release peaks, occurring at approximately 312 and 478 °C. The corresponding desorption activation energies were calculated using varying heating rates, yielding values of 0.63 eV and 1.64 eV, respectively. Isothermal desorption experiments indicated that complete release of residual tritium can be achieved at temperatures exceeding 400 °C. The tritium release rate-controlling process was found to be primarily diffusion of tritium through the crystal, with an effective diffusivity of 3.73 × 10-6exp(−1.35 eV/kT) m2/s.
Refactoring is the process of restructuring existing code without changing its external behavior while improving its internal structure. Refactoring engines are integral components of modern Integrated Development Environments (IDEs) and can automate or semi-automate this process to enhance code readability, reduce complexity, and improve the maintainability of software products. Similar to traditional software systems such as compilers, refactoring engines may also contain bugs that can lead to unexpected behaviors. In this paper, we propose a novel approach called RETESTER, a LLM-based framework for automated refactoring engine testing. Specifically, by using input program structure templates extracted from historical bug reports and input program characteristics that are error-prone, we design chain-of-thought (CoT) prompts to perform refactoring-preserving transformations. The generated variants are then tested on the latest version of refactoring engines using differential testing. We evaluate RETESTER on two most popular modern refactoring engines (i.e., ECLIPSE, and INTELLIJ IDEA). It successfully revealed 18 new bugs in the latest version of those refactoring engines. By the time we submit our paper, seven of them were confirmed by their developers, and three were fixed.
Jameel-Un Nabi, Mahmut Boyukata, Asim Ullah
et al.
In this study, we investigate the role of nuclear deformation on the calculated electron capture cross section (ECC) of even-even chromium (Cr) isotopes. We first determined the nuclear structure properties of these nuclei within the interacting boson model-1 (IBM-1). The energy spectra and E2 transition probabilities were calculated by fitting the parameters in the model formalism. The analysis of the potential energy surface was also performed to predict the geometric shape of the Cr nuclei by plotting their contour plot in the plane of (beta, gamma) deformation parameters. Later, we calculated the ECC within the proton-neutron quasiparticle random phase approximation (pn-QRPA) model. In particular, we studied how the calculated ECC changed with different values of the nuclear deformation parameter. The calculated Gamow-Teller (GT) strength distributions were widely spread among the daughter states. The total GT strength decreased with increasing value of the beta parameter. The computed ECC values, however, increased with increasing beta values of the Cr isotopes.
This work investigated the most suitable type of degrader (Cu, Al or Nb) and its thickness, taking into consideration the salient aspects of concrete activation for high-purity 89Zr production by 89Y(p,n)89Zr nuclear reaction. The MCNP and FISPACT codes were used to determine the optimal degrader thickness and the radioactivity of shielding concrete by neutron activation, respectively. The results showed that the optimal thickness of the beam degraders was 1.16, 3.19, and 1.33 mm for Cu, Al, and Nb, respectively. The neutron production rate per proton and the energy and angular distributions of neutrons varied depending on the type of degrader. Considering the radioactivity of the target-room concrete and the amount of radioactive waste expected to be generated, the use of a 1.33-mm-thick Nb degrader for 89Zr production was determined to be the best choice.
In this study, a novel extended Pham model is offered and examined. This model can fit positive, negative, and approximately symmetric data. In addition, it features four alternative hazard rate shapes, namely increasing, decreasing, bathtub, and upside-down bathtub shapes. The new model's main properties, such as quantiles, moments, and mean deviations, are derived. To evaluate the estimation of distribution parameters, two approaches are studied. From a classical standpoint, the maximum likelihood technique is used to determine the point and approximate confidence intervals of all unknown parameters. The Bayesian estimation method, on the other hand, is considered via the Markov chain Monte Carlo technique for obtaining Bayes point estimates alongside Bayes credible intervals. We present various Monte Carlo simulation studies to investigate the efficacy of maximum likelihood and Bayes estimation findings for the model's parameters. Numerical investigations showed that the offered Bayes estimates outperformed those derived using the conventional method. We also analyzed two sets of real data taken from the medical sector; the first represents survival rates for cancer patients who received a combination of radiotherapy and chemotherapy, and the second consists of remission times for bladder cancer patients. These clinical scenarios reveal that the new model outperforms other important competing models based on specific statistical criteria. Ultimately, for both clinical data applications, the proposed extended Pham distribution is the best choice compared to the traditional Pham and the other well-known eight lifetime models.
Medical physics. Medical radiology. Nuclear medicine, Nuclear engineering. Atomic power
Data-driven fault diagnosis techniques are significant for the stable operation of nuclear power plants (NPPs). However, in practical applications, the fault diagnosis of NPPs usually faces imbalance data problems with small fault samples and much redundant data which results in low model training efficiency and poor generalization performance. Thus, this paper proposes a convolutional variational autoencoding gradient-penalty Wasserstein generative adversarial network with random forest (CVGR) to reduce the impact of imbalanced samples on fault diagnosis. Firstly, a feature selection method based on the random forest is used to identify the most relevant measurements and reduce the impact of redundant data on fault diagnosis. Then, variational autoencoding is introduced into gradient-penalty Wasserstein generative adversarial to effectively extract original sample features and generate high-quality samples with high rationality and diversity. In addition, the convolutional neural network is used to extract the features of mixed samples to realize intelligent fault diagnosis. Finally, several experiments based on the Fuqing Unit 2 full-scope simulator under different operating conditions are used to validate the performance of the CVGR in data enhancement and intelligent fault diagnosis. The results show that the proposed method can effectively mitigate the imbalance data problem, which gives insights into intelligent fault diagnosis of NPPs.
Young-Jin Kim, Chi Bum Bahn, Seung Heon Baek
et al.
Crevice corrosion is a localized attack of metal that occurs in occluded areas of materials as a result of a degradation of the oxide passivity on the metal surface in contact with stagnant environments. Materials suffer crevice corrosion when generally the crevice opening gap is so narrow that the migration or diffusion of ionic species into the crevice can be restricted and consequently results in the production of aggressive crevice solutions and differential aeration conditions over time. Among several factors affecting the crevice corrosion, differential aeration causing oxygen depletion associated with the geometry of components, acidification, and accumulation of aggressive species (e.g., Cl−, SO4−2, NO3−) in the crevice solution become main aspects of the mechanism of the crevice corrosion. Thus, controlling such factors is most critically necessary to either prevents or terminates the crevice corrosion. This paper covers electrochemical aspects of the crevice corrosion, roles of critical factors affecting the crevice corrosion, and electrochemical processes of impurity species in the crevice in high temperature water. A better and clear understanding of mechanisms of the crevice corrosion is important to develop the protection and mitigation technology against the crevice corrosion in order for maintaining the integrity and longevity of structural components at various industries
Surface temperature measurement is critical for the safety and proper operation of nuclear fusion reactors such as tokamaks, which operate at high temperature [100–3600 °C] in the presence of complex and unknown surface reflectance properties, causing a reflected flux that disturbs measurement interpretations. This paper describes a numerical approach based on machine learning techniques to estimate the surface temperature of in-vessel components from infrared images, despite the presence of reflections and the unknown emissivity of materials. Our contributions are two-fold: for the first time in the infrared domain, we generate a huge dataset of simulated images thanks to a novel GPU implementation of a Monte Carlo infrared ray tracer. This implementation offers the great advantage of enabling the generation of a very large amount of synthetic images for different plasma scenarios. Hence the second contribution of this paper: we propose an infrared inverse lighting model, based on a Convolutional Neural Network (CNN) trained with the images generated by our ray tracer. The proposed approach is applied on a numerical prototype of W Environment Steady state Tokamak (WEST), including complex simulated thermal scenes. Using synthetic test data, and without providing the surface optical properties, the mean temperature error predicted by the CNN on ITER-like wide angle view of WEST is evaluated to 9% with standard plasma scenarios and 22% in case of exotic thermal scenes.
Artificial intelligence (AI) permeates all fields of life, which resulted in new challenges in requirements engineering for artificial intelligence (RE4AI), e.g., the difficulty in specifying and validating requirements for AI or considering new quality requirements due to emerging ethical implications. It is currently unclear if existing RE methods are sufficient or if new ones are needed to address these challenges. Therefore, our goal is to provide a comprehensive overview of RE4AI to researchers and practitioners. What has been achieved so far, i.e., what practices are available, and what research gaps and challenges still need to be addressed? To achieve this, we conducted a systematic mapping study combining query string search and extensive snowballing. The extracted data was aggregated, and results were synthesized using thematic analysis. Our selection process led to the inclusion of 126 primary studies. Existing RE4AI research focuses mainly on requirements analysis and elicitation, with most practices applied in these areas. Furthermore, we identified requirements specification, explainability, and the gap between machine learning engineers and end-users as the most prevalent challenges, along with a few others. Additionally, we proposed seven potential research directions to address these challenges. Practitioners can use our results to identify and select suitable RE methods for working on their AI-based systems, while researchers can build on the identified gaps and research directions to push the field forward.
The purpose of this study is to perform radiation monitoring by acquiring gamma images and real-time optical images for 99mTc vial source using charge couple device (CCD) cameras equipped with the proposed compact gamma camera. The compact gamma camera measures 86 × 65 × 78.5 mm3 and weighs 934 g. It is equipped with a metal 3D printed diverging collimator manufactured in a 45° field of view (FOV) to detect the location of the source. The circuit's system uses system-on-chip (SoC) and field-programmable-gate-array (FPGA) to establish a good connection between hardware and software. In detection modules, the photodetector (multi-pixel photon counters) is tiled at 8 × 8 to expand the activation area and improve sensitivity. The gadolinium aluminium gallium garnet (GAGG) measuring 0.5 × 0.5 × 3.5 mm3 was arranged in 38 × 38 arrays. Intrinsic and extrinsic performance tests such as energy spectrum, uniformity, and system sensitivity for other radioisotopes, and sensitivity evaluation at edges within FOV were conducted. The compact gamma camera can be mounted on unmanned equipment such as drones and robots that require miniaturization and light weight, so a wide range of applications in various fields are possible.
BackgroundPack cementation aluminizing technology is a common method for preparing tritium barrier coatings, and its relative parameters during the preparation process have an important influence on the microstructure of the aluminide layer and the tritium barrier properties of the in-situ oxidized Al2O3 coating.PurposeThis study aims to investigate the effects of pack aluminizing conditions on the microstructure of the Fe-Al layer and analyze the related kinetic analysis of the aluminizing process.MethodsFirst of all, a pack aluminizing process activated by 1 wt% AlCl3 was used to fabricate aluminide coatings on the substrate of 316L stainless steel in the 923 K to 1 173 K range. Then, scanning electron microscope (SEM), energy dispersive spectrometer (EDS), and X-ray diffraction (XRD) were employed to characterize the cross-sectional microstructure and composition of the aluminized layer. Finally, the effects of aluminizing temperature and time on the microstructure and composition of the aluminized layer were analyzed, and the kinetic parameters of the formation of the Fe-Al layer and the relationship between aluminizing time and the thickness of the aluminized layer were further obtained.Results & ConclusionsThe experimental results show that the main phases of the aluminized layer are Fe2Al5 and FeAl with a certain amount of FeAl(Cr,Ni) precipitates. The high aluminizing temperature would accelerate the growth of aluminized layer and lead to the formation of a thick intermediate layer between the substrate and outer aluminized layer above 1 023 K. Simultaneously, extending the aluminizing time could increase the thickness of the Fe-Al layer, but has no effect on the phase composition. The relation between aluminizing temperature and the growth velocity of the Fe-Al layer is in accord with Arrhenius' equation, and the relative activation energy of the aluminizing process is about 79.23 kJ·mol-1. During the process of pack aluminizing, the relationship between the aluminizing time and the Fe-Al coating thickness is h=14.585t1/2+19.514.
India is known around the world for its diverse civilizations and mystical rituals. Scholars and philosophers of the time formed a century-old tradition in the depths of this culture. Despite a long history of being viewed as unscientific, scientists and doctors are now aware of the benefits of traditional Indian health care. Many investigations on traditional medicine and its apparently magical qualities in the treatment of terminal diseases are currently being done. Home remedies are used all around the world, but they are recognized as science in India only. Two traditional Indian medicinal traditions: Ayurveda and Siddha are progressively gaining traction in the global healthcare business. In this article, some of India’s most odd and effective medicinal practices, as well as the benefits of each therapy will be reviewed. Throughout history, traditional medicines were the only source of primary healthcare, and they made a substantial contribution. Knowledge of how to use medicinal plants to treat various ailments was highly valued by ancient cultures. Until the mid-nineteenth century, plants were the principal therapeutic agents used by humans, and they continue to play an important role in pharmaceutical formulations. Traditional medicine is used by around 80 percent of people in undeveloped countries for their primary health care needs because of its low prices, effectiveness, frequently restricted availability of modern medicine, and cultural and religious preferences. Plant research in the traditional system of medicine is becoming increasingly significant in the development of global healthcare and conservation efforts. Traditional medicine systems are being used to uncover biologically active chemicals that are useful to the pharmaceutical industry. To this end, as much information possible is presented about these areas in this article. There are a number of geographically specific traditional health behaviors and are well reviewed in this paper.
Large scale laser facilities are needed to advance the energy frontier in high energy physics and accelerator physics. Laser plasma accelerators are core to advanced accelerator concepts aimed at reaching TeV electron electron colliders. In these facilities, intense laser pulses drive plasmas and are used to accelerate electrons to high energies in remarkably short distances. A laser plasma accelerator could in principle reach high energies with an accelerating length that is 1000 times shorter than in conventional RF based accelerators. Notionally, laser driven particle beam energies could scale beyond state of the art conventional accelerators. LPAs have produced multi GeV electron beams in about 20 cm with relative energy spread of about 2 percent, supported by highly developed laser technology. This validates key elements of the US DOE strategy for such accelerators to enable future colliders but extending best results to date to a TeV collider will require lasers with higher average power. While the per pulse energies envisioned for laser driven colliders are achievable with current lasers, low laser repetition rates limit potential collider luminosity. Applications will require rates of kHz to tens of kHz at Joules of energy and high efficiency, and a collider would require about 100 such stages, a leap from current Hz class LPAs. This represents a challenging 1000 fold increase in laser repetition rates beyond current state of the art. This whitepaper describes current research and outlook for candidate laser systems as well as the accompanying broadband and high damage threshold optics needed for driving future advanced accelerators.