BackgroundElectron beam injectors are the core components that determine the performance of free electron laser terahertz sources (FEL-THz). Radio frequency (RF) accelerator-based injectors can generate high-quality electron beams required to drive high-power THz radiation.PurposeThis study aims to design and commission a compact Free Electron Laser for Terahertz (FEL-THz) injector using an Independently Tunable Cell (ITC) structure, which balances high quality, cost-effectiveness, and compactness.MethodsThe collaborative FEL-THz system developed by Huazhong University of Science and Technology and the University of Science and Technology of China, was taken as research object. Initially, optimization concepts and design results based on the ITC structure were introduced. Thereafter, the system stabilization, beam diagnostics and system optimization measures were detailed for beam commissioning and operation. Relevant schemes and research validation were completed through beam dynamics simulations and online experiments.ResultsThe experimental results demonstrate that the optimized ITC injector achieves an electron beam energy of approximately 13.7 MeV with an energy spread of 0.41% and a transverse emittance of 8.8 mm mrad, meeting high-power and miniaturization requirements.ConclusionThe simulation and experimental results both indicate that, through optimization design combined with indirect diagnostic techniques, the ITC injector can meet the demands for both high power and miniaturization of FEL-THz. This configuration holds promising potential for advancing the miniaturization of high-power FEL-THz facilities. Furthermore, the application of indirect diagnostic techniques can also compensate for the insufficient diagnostic methods during the commissioning process, laying the groundwork for further promotion of the ITC injector.

BackgroundWith the extensive application of nuclear technology in medical field, the demand for radiation protection materials has been increasing. Traditional lead-based protective materials suffer from disadvantages such as heavy weight and biological toxicity, making the development of lightweight, lead-free and flexible X-ray protective materials a research priority.PurposeThis study aims to investigate the X-ray shielding mechanism and develop high-performance flexible protective materials suitable for medical diagnostic X-ray tubes operating within voltages below 150 kV.MethodsFirstly, the mass attenuation coefficients of different elements were calculated using XCOM program, revealing complementary K-edge absorption effects among tungsten (W), bismuth (Bi), and gadolinium (Gd) elements across different energy ranges. Secondly, Monte Carlo simulations were employed to predict the shielding performance of W, Bi, and Gd element combinations for X-ray tubes operating under 120 kV tube voltage with 2.7 mm Al filtration. Finally, flexible protective materials comprising W+Bi-based composite layered with Gd-based materials were prepared and experimentally tested.ResultsExperimental test results show that the optimized composite material achieves excellent shielding performance with shielding efficiency of 82.98%, mass attenuation coefficient of 5.86 cm2·g-1, linear attenuation coefficient of 9.16 cm-1 and half value layer of 0.08 cm. The effective atomic number (Zeff) analysis confirms enhanced absorption in the 50~90 keV range, which corresponds to the typical energy range of medical diagnostic X-rays.ConclusionsResults of this study demonstrate that the material design strategy based on complementary K-edge absorption effects can effectively improve the performance of flexible X-ray protective materials to shield both bremsstrahlung and characteristic radiation in the X-ray spectrum, providing valuable insights for developing next-generation lightweight, lead-free, and flexible X-ray protective materials for medical applications.

BackgroundThe detection of trace uranium in water is essential for mitigating health risks associated with uranium exposure. Electrochemical detection presents a promising and efficient approach for the rapid, real-time monitoring of trace uranyl ions (UO?2?) in aqueous environments.PurposeThis study aims to utilize the high specific surface area and the hybridization ability of the surface orbitals of antimonene (AM), a two-dimensional material, to load oligonucleotides on the surface of AM by self-assembly method, and to be used as a specific uranyl ion probe for the electrochemical detection of trace uranium in water.MethodsFirst of all, test samples consisted of Uranyl ion (UO22+), Oligonucleotide, AM, etc., were prepared according to strict processing steps. Then, atomic force microscopy (AFM) and ultraviolet absorption spectroscopy (UVAS) were employed to observe and confirm the successful loading of oligonucleotides on the antimonene surface. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) scans were applied to testing that AM-loaded oligonucleotides were less internally resistive and more electrochemically active than individual oligonucleotides or AM. The effects of electrode modification density, temperature, pH, and enrichment time on the detection performance of uranyl ions were further explored using differential pulse voltammetry (DPV) tests. Finally, the sensitivity, specificity, and stability of the electrochemical sensors based on AM-loaded oligonucleotide probes were evaluated.ResultsTest results show that the detection conditions are optimized using the DPV method, and the optimal conditions are found to be a modifier concentration of 0.8 mg?mL-1, an electrolyte pH of 3.0, a temperature of 30 ℃, and an incubation time of 12 min. Under the optimized conditions, the linear range is 1.48×10-8~1.07×10-7 mol?L-1, and the detection limit is 2.99×10-10 mol?L-1, along with good reproducibility, selectivity, and reliability for real-water detection.ConclusionsA novel strategy for constructing high-performance electrochemical sensors for uranyl ion detection using oligonucleotides proposed in this study presents an innovative probe material design scheme to enable the development of simple, efficient, and flexible electrochemical uranyl sensors for practical applications.

BackgroundThe distribution coefficient (Kd) of radionuclides on bentonite is one of the key parameters in the safety assessment of geological repositories for high-level radioactive waste.PurposeThis study aims to reliably predict the Kd values of various radioactive cations in bentonite based on machine learning (ML) models.MethodsBased on the Japan Atomic Energy Agency's adsorption database (JAEA-SDB), 1 240 sets of Kd data of 10 nuclides (Am, Bi, Cm, Cs, Eu, Ni, Pb, Po, Ra, U) in bentonite were collected, and 9 input factors were selected to construct six ML models including random forest (RF) and support vector regression (SVR). The robustness of the ML models was evaluated by Monte Carlo cross-validation (MCCV).ResultsThe validation results indicate that the RF model is the most effective in predicting Kd, achieving a determination coefficient (R2) of 0.902 9 on the training set and 0.728 6 on the test set. Moreover, the RF model accurately reproduce the probability density distribution characteristics of Kd, and pH, initial concentration, ionic strength, and temperature are the main factors affecting Kd.ConclusionResults of this study demonstrate that ML methods, especially the RF model, can rapidly and reliably predict the Kd of multiple radionuclides on bentonite under complex conditions, offering a promising new approach for the safety assessment of radioactive waste disposal repositories.

BackgroundAchieving precise identification of neutrons/gammas in space is beneficial for studying space radiation fields. Traditional identification methods are significantly affected by data noise, making it challenging to distinguish neutrons/gammas under the high-noise conditions of spaceborne detectors.PurposeThis study aims to propose a deep learning algorithm that combines Scattering Convolution Networks with MobileNetV4 (MNv4) and Kolmogorov–Arnold Networks (KAN) to improve neutron/gamma discrimination performance and the noise robustness of this method.MethodsFirstly, a ?50 mm×50 mm NaI(Tl):6Li crystals and H6410 photomultiplier tubes were employed to collect data on neutron beams of 2 500 keV and 5 000 keV from the National Defense Technology Industrial Ionizing Radiation Calibration Station at China Institute of Atomic Energy (CIAE). Then, the 2 500 keV data were divided into test set 2 and training set, while the 5 000 keV data served as test set 1. After classifying the dataset using the charge comparison method, the scattering convolution networks (SCN) was used for denoising and dimensionality reduction, reducing 1 800 sample points to 113. Particle identification was then performed using MNv4 or KAN model. Finally, simulated signals with noise levels of 10%~50% were applied to investigating the algorithm's noise resistance and tested different signal-to-noise ratios with falling edge trigger leves of -4 mV, -8 mV, and -12 mV to verify the algorithm's robustness.ResultsThe experiment results show that MNv4 and KAN achieve recognition accuracies of 99.7% and 98.6% on the two test sets, respectively, compared to the comparison method, which improves the Figure of Merit (FOM) from 1.82 to 4.07 and 4.40. At a 15% noise level, MNv4 and KAN achieve neutron identification accuracies of 99.7% for 2 500 keV and 5 000 keV energies whilst the identification accuracies of above two algorithms are maintained above 99% with a signal-to-noise ratio (SNR) of 9.13 dB at a 40% noise level.ConclusionsCombining SCN with deep learning algorithms like MNv4 or KAN provides dimensionality reduction and noise resistance. Compared to the charge comparison method, this approach improves the Figure of Merit (FOM) and enables neutron/gamma discrimination even at high noise levels, demonstrating good robustness.

BackgroundFuel assembly is one of the key components of a nuclear reactor that significantly impacts the thermal-hydraulic performance of the pressurized water reactor. The helical tri-lobe fuel (HTF) design has a better heat transfer performance compared with the mature rod-type fuel, hence has drawn much attention and deserves to further illustrate the enhanced heat transfer mechanism of helical structure.PurposeThis study aims to employ numerical simulation to examine the single-phase flow and heat transfer properties within HTF assemblies, investigating the influence of structural parameters on flow and heat transfer.MethodsFirstly, a 7 HTF elements arranged in a triangular lattice was taken as analysis object in this study. The models of the HTF elements with various structural parameters were constructed, including different helical pitches, gap distances and ratio of lobe root arc to lobe tip arc radius (R2/R1). Then, the Integrated Computer Engineering and Manufacturing (ICEM) was adopted to generate a high-quality hexahedral structured mesh, achieving high mesh quality to accurately calculate the complex flow dynamics within the helical fuel flow field. Mesh independence check was conducted to confirm the satisfactoriness of the mesh scheme. Subsequently, ANSYS Fluent 2021R1 was adopted as the calculation platform, with the shear stress transport (SST) k-ω turbulence model and wall symmetry model being selected. The calculation model was set up with boundary conditions of a velocity inlet, pressure outlet, and uniformly heated wall surfaces. Finally, the essential thermal parameters, such as secondary flow velocities, vorticity of the cross-section, temperatures, and heat transfer coefficients of helical fuel flow field with different spiral shapes during the flow and heat transfer processes, were extracted from simulation output to elucidate the precise influence of these structural parameters on the flow and heat transfer characteristics.ResultsSimulation results show that the helical structure of the HTF significantly augments the lateral mixing flow of the coolant and therefore intensifies the heat convection. The secondary flow intensity near the cladding surface area of the HTF is enhanced by reducing the helical pitch, and the heat transfer capacity of the HTF is improved. Meanwhile, with the decreasing of the helical pitch, the flow resistance of the coolant channel increases. However, a helical pitch exceeding 240 mm markedly amplifies fluid temperature non-uniformity and cladding surface temperature variations. Reducing the minimum distance between fuel elements can enhance the heat transfer capacity, while having little influence on the non-uniformity of fluid and cladding surface temperature. The increase of the R2/R1 of the HTF strengthens the heat transfer capacity, weakens the temperature concentration in the concave arc and increases flow resistance of the coolant channel.ConclusionResults of his study provide insights into optimizing fuel assembly design for enhanced thermal-hydraulic performance and reactor safety.

BackgroundIn a levitated magnetic dipole confinement device, the magnetic field excited by the Tilt-Slide-Rotate (TSR) or the Resonant Line Field (RLF) coils can disrupt the topology of the background magnetic field, thereby affecting particle confinement. Due to the magnetic field generated by the TSR coil disrupting the structure of the closed magnetic field lines of the background dipole field, alpha particles injected close to the TSR coil side experience rapid loss.PurposeThis study aims to investigate the effect of magnetic disturbances generated by TSR coils and RLF coils on the confinement of alpha particles generated by DD-3He catalyzed nuclear reactions in a background magnetic dipole field.MethodsFirstly, a collision loss model based on the parameters of the China Astro-Torus No.1 (CAT-1) device was established. Secondly, an interchange mode stable background magnetic field was obtained by the Dipole Equilibrium Grad-Shafranov Solver (DEGS). Thirdly, the magnetic field disturbance was generated by the TSR coil and calculated using a line segment approximation method. And the poloidal magnetic field disturbance produced by the RLF effect was generated by adding a toroidal magnetic field with the same direction or two opposite directions in the background magnetic dipole field. Finally, the orbits of alpha particles in a magnetic field were simulated using the particle testing method.ResultsSimulation results of the magnetic field with a low poloidal mode number by superimposing a toroidal magnetic field on the background magnetic dipole field show that the mode n=0 poloidal disturbance magnetic field maintains a higher confinement particle fraction than that of n=1 mode within 10 μs, and after the flight time of alpha particles exceeds 10 μs, the confined particle fraction in the n=0 mode rapidly decreases.ConclusionsThe magnetic field disturbances can cause rapid loss of alpha particles along an open magnetic field line, reducing the loss during high-energy alpha particle relaxation by controlling the operating current of the TSR coil and the RLF effect.

BackgroundAngle-resolved photoemission spectroscopy (ARPES) based on synchrotron radiation requires tunable photon energies to perform three-dimensional electronic structure analysis, covering both surface states (20~200 eV) and bulk phases (>200 eV). However, single-period undulator cannot cover the entire required photon energy range due to limitations in magnetic field period and intensity.PurposeThis study aims to characterize the energy spectral performance of a double elliptically polarized undulator (DEPU) designed to expand the photon energy coverage for comprehensive electronic structure studies.MethodsFirstly, a DEPU system consisting of a low-energy insertion device (LEID) with 148 mm period length and a high-energy insertion device (HEID) with 58 mm period length was installed at beamline BL09U of Shanghai Synchrotron Radiation Facility (SSRF). Then, the spectral characteristics were measured using ionization chambers with gas absorption spectra of argon, nitrogen, and neon for energy calibration across different energy ranges. Finally, the gap-energy correspondence relationships were systematically determined by measuring fundamental peak positions at various magnetic gap settings using photodiodes, and photon flux measurements were conducted with appropriately sized white slits to maintain 4σ apertures.ResultsMeasurement results show that the LEID effectively covers the energy range of 22~250 eV through fundamental harmonics with gap variations, achieving photon flux above 1012 ph·s-1 at energies below 100 eV. The HEID fundamental harmonics cover 250~1 700 eV efficiently, while third harmonics extend the coverage to 1 700~2 000 eV, maintaining flux levels above 1012 ph·s-1 up to 800 eV. Energy calibration measurements show deviations of -0.14 eV to -5.3 eV compared to literature values, confirming reliable energy positioning across the entire range.ConclusionThe DEPU successfully achieves comprehensive photon energy coverage from 20 eV to 2 000 eV in the EUV to soft X-ray domain, with measured flux levels consistent with theoretical simulations. This dual-period design enables depth-resolved electronic structure research by providing both surface-sensitive low-energy photons and bulk-sensitive high-energy photons, demonstrating its effectiveness for advanced materials characterization including topological quantum materials and unconventional electronic systems.

BackgroundNuclear fuel rods operate under extreme service environments in reactor systems, hence precise inspection of cladding tube and end plug welds represents a critical nuclear safety safeguard. Traditional detection methods face significant challenges including the scarcity of high-quality training datasets due to low real defect occurrence rates and high X-ray imaging equipment costs, alongside existing models' inability to meet real-time detection requirements.PurposeThis study aims to develop an intelligent weld defect detection algorithm based on imbalanced convolution feature extraction that achieves both high detection accuracy and real-time performance for fuel rod weld defect identification.MethodsA novel defect detection model, named as YOLOv8n-WIOU-Fasternet, was designed through comprehensive architectural modifications. Firstly, a distance-aware attention mechanism was integrated into the bounding box regression loss function, incorporating a two-level distance penalty mechanism to focus on ordinary-quality anchor boxes while mitigating adverse gradients from low-quality anchors. Secondly, distribution focal loss (DFL) was incorporated to refine edge-level position estimation, enabling more precise boundary localization through cross-entropy optimization of probability distributions around target labels. Meanwhile, by collecting digital radiography (DR) images of 500 fuel rods, a batch of samples containing abnormal defects such as porosity, gas expansion, incomplete penetration, tungsten inclusion, and blockage were prepared. The area near the end plug weld was selected as the region of interest (ROI), and open-source image annotation tool Labellmg was applied to manual annotation of the defect area to obtain 720 defect images. By systematically expanding the dataset, samples with "pseudo defects" were generated, and a total of 7 200 DR images of fuel rods containing different types of defects were constructed. Among them, the number of different types of defects such as pores, tungsten inclusions, and incomplete penetration was the same in the training set, and were divided into training and validation sets in an 8:2 ratio. An additional 72 fuel rod defect DR images that did not participate in the training and validation process were collected as an independent test set to evaluate and experimentally validate the performance of the defect detection model. Finally, traditional convolutional modules were replaced by a newly designed partial convolution (PConv) structure that selectively applies convolution to a subset of input channels while retaining others, followed by pointwise convolution for spatial information fusion and maintaining representational completeness.ResultsThe experimental validation results demonstrate that the proposed YOLOv8n-WIOU-Fasternet model achieves false negative and false positive rates both below 5%, representing significant performance improvements across multiple metrics and substantial reductions compared to baseline models. The maximum F1 score reaches 0.947 at a confidence threshold of 0.285, with corresponding false positive and false negative rates of 3.1% and 3.5%, respectively. The average precision (AP) performance significantly surpasses both traditional feature extraction methods and the original YOLOv8 model across various IoU thresholds.ConclusionsThe proposed model successfully achieves an optimal balance between detection accuracy and computational efficiency through its innovative architectural design. The integration of distance-aware attention mechanisms and partial convolution structures reduces computational overhead while maintaining superior detection performance. This comprehensive approach provides a robust and practical solution for automated fuel rod defect detection in real-world nuclear fuel manufacturing applications, meeting both precision requirements and real-time processing constraints essential for industrial deployment.

BackgroundDuring measurement of the multi-sphere spectrometer, solutions of the current unfolding methods depend on the prior information. However, during some special circumstances, i.e. experimental validation of the deep penetration problem calculation method, the unfolding process needs to be independent of the prior information, which is essential to validate the computational method for deep-penetration.PurposeThis study aims to propose an unfolding method that is independent of the prior information and adaptive to the uncertainties and illness of the unfolding problems.MethodsThe iterative regularization unfolding method is based on Krylov subspace method. The Lanczos bidiagnolization was employed to calculate orthogonal basis of the Krylov subspaces, and the Tikhonov regularization was applied to suppressing the uncertainties contained in the measured data. Then, the regularization parameter was determined by the Generalized Cross Validation (GCV) principle to constrain the uncertainties and illness of the unfolding problem. Finally, multi-sphere spectrometer measurement of 241Am-Be neutron spectrum was used to verify this established method, and the unfolded spectrums were compared with that of the ISO standard solution.ResultsThe unfolded results with the proposed method agree well with the reference spectrum. Relative error of the unfolded results using the proposed method is 16%, while relative errors of the unfolded results using the GRAVEL and ML-EM methods are 103% and 107%, respectively.ConclusionsComparing with the current unfolding methods, the proposed method can effectively avoid the "semi-convergence" behavior and achieve better accuracies while large fluctuations contained in the measured counting are suppressed of the ill-conditioned problem.

Radiopharmaceuticals are playing an increasingly important role in the field of tumor diagnosis and treatment, with one of the core being the efficient and stable binding of radioactive isotopes with targeted molecules by chelating agents, and possessing high stability and good pharmacokinetic properties in vivo. This article systematically reviews the research progress of chelating agent labeling chemistry for classic and novel radioactive metal nuclides, with a focus on exploring the applicable chelating agents, labeling strategies, and in vivo application performance of key nuclides such as 68Ga, 177Lu, 90Y, and 225Ac. By analyzing the thermodynamic stability, labeling conditions (pH, temperature, time), and in vivo kinetic inertness of radioactive nuclide chelating agent complexes, the influence of chelating agent structure on the targeting, stability, and efficacy of radiopharmaceuticals are revealed, providing theoretical and technical references for the development and clinical translation of radiopharmaceuticals.

BackgroundNuclear graphite is utilized as a moderator and structural material in molten salt reactors, where the graphite is exposed to elevated temperatures and substantial fluxes of fast neutron irradiation over extended periods. The consequence of fast neutron irradiation on nuclear graphite is the production of a large number of point defects, which undergo a series of processes including annihilation, diffusion and agglomeration, resulting in the formation of large dislocation structures at elevated temperatures. It is evident that high-temperature neutron irradiation exerts a profound influence on the microstructure of graphite, consequently altering its macroscopic properties.PurposeThis study aims to reveal the defect evolution and microstructural changes of nuclear graphite under irradiation.MethodsFirstly, NG-CT-50 nuclear graphite, a microfine grained nuclear graphite candidate for Thorium Molten Salt Reactor, was selected as the research object. Then, in-situ electron irradiation experiments on NG-CT-50 nuclear graphite were conducted at the range from room temperature to 750 ℃ using an electron beam of 200 keV and observed by Transmission Electron Microscope (TEM) simultaneously, and the dynamic changes in the microstructure of the graphite and the evolution of defects were observed by High Resolution Transmission Electron Microscopy (HRTEM). Finally, the HRTEM images were noise filtered by Winer and Fourier filtering for better basal plane images.ResultsObservation results show that irradiation temperature plays a significant role in the evolution of the microstructure of graphite. High temperatures facilitate the annihilation of point defects induced by irradiation and the movement and recombination of irradiation-induced partial dislocations. Instead of irradiation-induced 'ruck and tuck' defects or fullerene-like structures reported in the literature, a large number of dislocation loops are in-situ observed, a phenomenon consistent with the classical theory of graphite irradiation defects. The evolution of defects at high temperatures can be described as the formation of interstitial or vacancy loops, the growth and decomposition of dislocation loops, the interlayer migration or glide of partial dislocations, and the interaction or recombination of partial dislocations with other defects.ConclusionsThis study provides a theoretical basis for predicting the high-temperature irradiation performance of graphite and for the optimal design of irradiation-resistant graphite.

BackgroundReversible Solid Oxide Cells (R-SOCs) hold significant potential for renewable energy storage and utilization, but the application of traditional cobalt-based perovskite air electrode materials is limited due to their high thermal expansion coefficients and structural instability.PurposeThis study aims to design and fabricate novel high-efficiency air electrodes to improve the operational efficiency and stability of fuel cells.MethodsBased on traditional double perovskite oxide PrBa0.8Ca0.2Co2O6-δ (PBCC), a novel B-site high-entropy perovskite oxide, i.e., PrBa0.8Ca0.2Fe0.4Co0.4Ni0.4Cu0.4Y0.4O6-δ (PBC-FCNCY), was proposed to achieve a substantial reduction in cobalt content via a multi-element doping strategy while preserving superior electrochemical performance. Subsequently, X-ray Diffraction (XRD), Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS) were employed to characterize the performance of PBC-FCNCY.ResultsCharacterization results confirm that the high-entropy structure optimizes the crystal structure and microstructure of the material. Electrochemical tests results show that PBC-FCNCY air electrode achieves a peak power density of 1 105 mW·cm-2 in fuel cell mode and a current density of ?1 418 mA·cm-2 at 1.3 V in electrolysis cell mode at 700 °C, both outperforming PBCC air electrode. Furthermore, it operates stably for over 110 h in fuel cell mode and over 85 h in fuel cell/electrolysis cell cycling mode.ConclusionsThe novel B-site high-entropy air electrode for R-SOCs proposed in this study has characteristics of enhanced activity and prolonged durability, demonstrating its practical application potential in R-SOCs.

BackgroundPrinted circuit plate heat exchanger (PCHE) has the characteristics of high efficiency and compact heat transfer, but the analysis method of PCHE flow and heat transfer based on finite volume method (FVM) is inefficient and difficult to carry out large-scale optimization calculation.PurposeThis study aims to improve the analysis and optimization efficiency of three-dimensional models by constructing a fusion field reduction model for PCHE low and heat transfer.MethodsFirstly, the trapezoidal PCHE was taken as the research object, supercritical CO2 as the working fluid for the hot channel, and water as the working fluid for the cold channel. Then, the proper orthogonal decomposition (POD), truncated singular value decomposition (tSVD), and gaussian process regression (GPR) were combined to construct a reduced-order model by Latin hypercube sampling and a small amount of sample data generated by Fluent software. Thereafter, the reduced-order model was applied to the prediction of flow and heat transfer characteristics and overall performance of PCHE under new working conditions.ResultsThe prediction results show that the fusion field reduction model efficiently decomposes the high rank matrix and accurately predict the multi-physics field distribution of trapezoidal PCHE. For the temperature field and velocity field of PCHE, the root mean square error of the new working condition in the sample space is 1.5×10-3, and the root mean square error of the new working condition outside the sample space is 6.2×10-3, and the calculation efficiency is improved by 270 times. However, the prediction effect of the fusion field reduction model on the overall performance of PCHE is poor.ConclusionsThe reduced-order model of the fusion field has certain reference significance for the future optimization analysis work.

BackgroundSodium boiling is a critical transient phenomenon prior to severe accidents in sodium-cooled fast reactors. Accurate prediction of the two-phase state and thermodynamic parameters of the coolant during sodium boiling is essential for sodium-cooled fast reactors accident analysis.PurposeThis study aims to develop a core thermal-hydraulic model for the sodium-cooled fast reactor integrated analysis program ISAA-Na (Integrated Severe Accident Analysis code) on the basis of the multi-bubble liquid slug assumption.MethodsIn the multi-bubble slug model developed for ISAA-Na, bubbles were classified as small bubbles (not exceeding the minimum grid size) and corresponding large bubbles, with the liquid between them forming a slug. Separate sets of three conservation equations (mass, momentum, energy) were established and solved for both the bubbles (according to their type) and the liquid slug. Based on this model setup, ISAA-Na was used to model and calculate the loss-of-flow experiment in the high burnup irradiation core of CABRI-BI1 (C?ur à Haut B?rnup Irradiation). Finally, simulation results of various analysis codes were compared with that of experimental results.ResultsComparison results show that ISAA-Na provides more accurate predictions of coolant temperature and pressure prior to boiling compared to other codes such as SAS4A, ASTEC-Na, and SIMMER. Specifically, in the fission zone, ISAA-Na predicts a maximum coolant temperature difference of approximately 15 K during steady state and about 20 K prior to transient boiling, which align well with experimental observations. However, after the onset of boiling, overestimations of bubble growth rate and two-phase interface movement are observed due to the lack of fuel melting and cladding failure models.ConclusionsOverall performance of ISAA-Na demonstrated in this study indicates that the application of the multi-bubble liquid slug boiling model in ISAA-Na for the analysis of the CABRI-BI1 experiment is deemed reasonable and reliable.

BackgroundCF (Chinese Fuel) series fuel assemblies are the core components of nuclear power independently developed by China National Nuclear Corporation (CNNC), which together with the drive mechanism, constitute an important part of a large pressurized water reactor which is related to the stability and safety of nuclear reactor operation. Development of any fuel assembly and related equipment must undergo friction and rod drop test to verify its structural integrity and the property. The traditional friction and rod drop performance test can only be carried out with small eccentricity to obtain the test data such as friction force and rod drop curve. It can't be achieved to analyze and study the performance with multiple eccentricities, especially the larger eccentricity. And there are no more studies on comparative mechanical analysis of the friction force of the driving mechanism through full displacement and in the two media of water and air.PurposeThis study aims to analyze the friction and rod drop performance of the drive line's moving parts of the self-developed CF2 fuel assembly under water and air working conditions with different eccentricity.MethodsA 1:1 simulated CF2 fuel assembly was used in the test with an independently-developed rotatable top cap. The integration of multiple eccentricity was initially implemented for scientific and accurate regulation. The method to study the performance of the driving mechanism was optimized. The friction force and rod drop performance data were obtained through the experiments of the driving mechanism in water and air through full displacement and under different eccentric conditions.ResultsExperimental results show that the friction force of control rod drop in the air at the lowest and highest positions is 26.5 N and 32.1 N, respectively when the eccentricity is 4.67 mm, whilst the two force values in the air at the lowest and highest position is 37.1 N and 39.2 N, respectively when the eccentricity is 9.4 mm. The friction force control rod drop in the motionless water at the lowest position and the highest position is 54.8 N and 39.5 N, respectively when the eccentricity is 4.67 mm whilst the two force values in the water are 62.8 N and 44.1 N, respectively when the eccentricity is 9.4 mm. As the control rod is gradually raised, the friction force in the air increases much more than that in static water. The maximum value in the air occurs at the highest position, while the maximum value in static water occurs at the lowest position. By comparing and analyzing the rod drop performance and parameters like velocity, displacement and vibration, it can be seen that with the continuous increase of the eccentricity, the friction during rod operation also increases correspondingly, and the maximum speed during rod drop gradually decreases. The data shows that the impact of the various eccentricities on the buffer time is small and the value can be basically consistent. The minimum rod drop time occurs when the eccentricity is 0 mm. The time for control rod reaching to the buffer port is 1.049 s, and the time reaching to the bottom is 1.477 s.ConclusionsThe numerical comparison of friction force between in the air and static water through full displacement and under multiple eccentricities has been carried out, the fuel assembly and control rod run well, the friction does not exceed the limit value, and no jamming of the rod occurs under the maximum eccentric condition. It can verify the rationality of the design of CF2 fuel assembly, providing an important test basis for the design, safety evaluation and software development of this series fuel assemblies.

BackgroundMegaPower is a heat pipe reactor designed for decentralized energy markets, such as remote areas and military bases. Its startup process involves complex multi-physics coupling calculations. Traditional high-resolution simulations often face high computational costs.PurposeThis study aims to develop and validate a fast reduced-order model based on the Proper Orthogonal Decomposition-Radial Basis Function (POD-RBF) method to efficiently simulate the startup process of the MegaPower heat pipe reactor.MethodsFirstly, a high-resolution 1/6 core model was constructed to capture the essential features of MegaPower, and OpenMC was employed to model the 1/6 core model, maintaining the symmetry and main structural characteristics of the reactor geometrically. Then the neutron transport calculations were carried out by using OpenMC, and FEniCSx was used for thermal-hydraulic and stress analysis. Subsequently, the POD-RBF method was integrated into the model to reduce computational cost while maintaining accuracy. Finally, the dynamic behavior of power, temperature, and reactivity during the startup process was analyzed and compared against high-resolution simulation results.ResultsThe simulation results indicate that the POD-RBF method achieves accurate predictions with an average power distribution error of 0.77% and a maximum error of 3.04%, and the entire startup process simulation time is reduced from 74 d to just 7.5 h, achieving an efficiency improvement of approximately 99.6%. Reactivity prediction results show that an average error below 50 pcm and a maximum error not exceeding 100 pcm are achieved. The power ramp rate during the adjustment phase reaches approximately 0.53% FP/s, with the reactor achieving nominal power smoothly and maintaining stable power and reactivity dynamics. Furthermore, the POD-RBF method significantly enhances computational efficiency, reducing the time per time step from 800 s to 3 s.ConclusionsThe results of this study verify the efficiency and accuracy of the POD-RBF method for simulating transient multi-physics coupling problems, providing reliable computational support for the design and safety assessment of heat pipe reactors and offers a new methodology for addressing complex multi-physics problems efficiently.

BackgroundEstablishing a lunar base is the first step for human space exploration, and providing stable and reliable energy for the base is one of the most critical priorities. Compared to solar energy, nuclear power offers advantages such as high power output, low mass-to-power ratio, long operational lifespan, and all-weather power supply, making it an ideal energy solution for lunar surface bases.PurposeThis study aims to design a lunar surface heat pipe molten-salt reactor with a 20-a lifetime to meet the 100 kWe electrical power requirement, capable of generating power immediately after landing on the lunar surface without additional shielding.MethodsFirst of all, the structure and main parameters of Lunar surface Heat Pipe Molten Salt Reactor (LHPMSR) were determined according to design requirement. Then, the neutron physics and shielding analysis were conducted using SCALE 6.1 to obtain the radial distribution of neutron flux, power distribution, variation of keff during reactor's lifetime and radiation dose distribution, and select the Al2O3 as the reflective layer material where the reactivity control was achieved by controlling the rotation of the drum. After calculating the viscous limit, sonic limit, entrainment limit, boiling limit, and capillary limit of the heat pipe, an analysis of its heat transfer limits was conducted. Finally, the heat pipe thermal transfer was simulated through thermal resistance network methodology, and thermal-hydraulic analysis was performed using coupled Computational Fluid Dynamics (CFD) approach to obtain temperature distributions of reactor core and the heat pipe, as well as the molten salt velocity distribution.ResultsAnalytical results indicate that the three-zone core configuration effectively achieves power flattening and full-power operation for 20 a is maintained without requiring additional shielding or refueling. Meanwhile, the heat pipe thermal transfer capacity remains below critical heat flux limits, meeting design specifications.ConclusionsThe overall design satisfies the preliminary construction requirements for lunar bases and provides valuable references for molten salt reactor designs on planetary surfaces.

BackgroundOrganic-inorganic hybrid perovskite wafers have demonstrated significant potential for large-area X-ray detection applications. However, current perovskite wafers exhibit poor optical transparency and suboptimal crystal quality, which severely limit the performance and stability of X-ray detectors. Self-powered perovskite X-ray detectors have attracted increasing attention due to their advantages of low power consumption, portability, and excellent adaptability.PurposeThis study aims to develop high-performance self-powered X-ray detectors by fabricating transparent MAPbBr3/MAPbCl3 heterojunction wafers through hot-pressing technology, and investigate their self-driven detection mechanisms.MethodsFirstly, MAPbBr3 and MAPbCl3 single crystals were grown using the improved inverse temperature crystallization (ITC) method and subsequently grounded into uniform powders with average particle sizes of 0.38 μm and 0.57 μm, respectively. Then, a gradient temperature-controlled bidirectional hot-pressing process was developed, where the powders were placed on opposite sides of a cylindrical mold and subjected to crystallization-induced pressing at 297 MPa while gradually heating from 25 °C to 60 °C for 10 h. Finally, comprehensive characterization techniques including X-ray diffractometer (XRD), scanning electron microscope (SEM), ultraviolet visible (UV-vis) spectroscopy, and ultraviolet photoelectron spectroscopy (UPS) were employed to analyze the crystal structure, morphology, optical properties, and energy band alignment of the fabricated heterojunction wafers.ResultsThe hot-pressing technique successfully produces MAPbBr3/MAPbCl3 heterojunction wafers with excellent optical transparency and clear interfaces. The Au-MAPbBr3/MAPbCl3-Au structured X-ray detector exhibits a sensitivity of 782.26 μC·Gyair-1·cm-2 and an ultra-low detection limit of 57 nGyair·s-1 at 0 V bias, representing superior performance compared to single-component detectors. Under 10 V bias, the sensitivity further increases to 7 785.32 μC·Gyair-1·cm-2, which is 4.33 and 6.09 times higher than MAPbBr3 and MAPbCl3 wafer detectors, respectively. The device maintains stable performance after cumulative absorption of 3 675 μGyair of X-ray radiation.ConclusionsThe enhanced performance of the heterojunction X-ray detectors is primarily attributed to the built-in electric field formed by the PN heterojunction, which effectively suppresses dark-state carrier recombination and enhances carrier transport under X-ray irradiation. The advancement achieved in this study significantly expands the potential of perovskite-based detectors for low-power, large-area detection applications and provides a new direction for developing high-performance self-powered X-ray detection technology.