The primary objective of this study is to reveal the corrosion failure mechanism of typical accident-tolerant fuel (ATF) Cr-coated claddings under deviated water chemistry conditions in the primary loop of pressurized water reactors (PWRs). Given the critical role of Cr coatings in enhancing the corrosion resistance of fuel claddings, understanding their dissolution behavior under varying high-temperature and high-pressure water environments is essential for ensuring the long-term safety and reliability of nuclear power plants. Pure metallic Cr was selected as the research object in this work, as it serves as the key component of the protective coating and its corrosion behavior directly reflects the performance of the entire Cr-coated cladding system. To achieve the research goal, a series of corrosion dissolution experiments was conducted under different temperatures and dissolved oxygen (DO) concentration conditions. A high-temperature and high-pressure water micro-flow corrosion loop with a Ti inner lining was employed to simulate the actual operating environment of the PWR primary loop. This experimental apparatus ensures the stability of temperature, pressure, and water chemistry parameters throughout the experiment, which is crucial for obtaining accurate and reproducible corrosion data. The electrical conductivity at the outlet of the loop was monitored in real-time to continuously track the dissolution process of Cr. Additionally, inductively coupled plasma mass spectrometry (ICP-MS) was used to analyze the concentration of Cr ions in the solution, providing a reliable method to verify the dissolution rate data obtained from the electrical conductivity monitoring. For the data analysis and model establishment, the Arrhenius equation and Butler-Volmer (B-V) equation were integrated to develop a mixed potential model describing the corrosion dissolution behavior of Cr in high-temperature and high-pressure water. This mixed potential model takes into account both the electrochemical reactions and the temperature-dependent kinetic processes, enabling a comprehensive understanding of the corrosion mechanism. To further improve the accuracy of the model, a genetic algorithm was applied to optimize the model parameters, and the optimized model was then used to fit the experimental data. Through this process, a Cr dissolution kinetic model that considers the coupled effects of temperature and DO concentration was successfully constructed. The research results show that there is a positive correlation between the Cr dissolution rate and temperature. Specifically, when the temperature exceeds 150 ℃, the dissolution rate of Cr increases significantly with the increase in temperature, demonstrating a strong temperature dependence. This phenomenon can be attributed to the accelerated electrochemical reaction kinetics and the increased mobility of ions at higher temperatures, which promote the dissolution of the Cr surface. Regarding the effect of DO, the presence of DO significantly promotes the corrosion dissolution process of Cr. In the deaerated environment, the dissolution of metallic Cr is barely detectable, indicating that oxygen plays a critical role in initiating and accelerating the corrosion reaction. When the DO concentration exceeds 300 ppb, a notable increase in the Cr dissolution rate is observed, and the dissolution rate continues to increase with the further increase in DO concentration. This result suggests that the DO concentration is a key factor controlling the corrosion rate of Cr in the PWR primary loop environment, and effective oxygen control is essential for mitigating the corrosion failure of Cr-coated claddings. The kinetic prediction model of Cr dissolution successfully described the coupling effect of temperature and DO, enabling a quantitative evaluation of the corrosion failure of metallic Cr under deviated water chemistry conditions.
Accurate evaluation of hydrogen(H2)production yield in high α-radioactive solutions is crucial for ensuring the long-term storage safety of high-level radioactive liquid waste.The production of hydrogen from water radiolysis,induced by ionizing radiation,can lead to a dangerous buildup of gas pressure within storage tanks,presenting a significant risk of hydrogen explosion.In this study,a robust Monte Carlo simulation framework was developed to construct a comprehensive radiation absorbed dose model for aqueous solutions containing 89 representative radionuclides,and model the solutions in storage tanks of varying sizes and accurately calculate the contributions of α,β,and γ radiation as well as their three-dimensional spatial distributions.This model further integrates pure water radiolysis reaction kinetics to establish a hydrogen production model.The coupling of Monte Carlo simulations with radiolysis reaction kinetics provides a more accurate and detailed prediction of hydrogen production in the presence of radiation.The results from this combined model show that hydrogen concentration overall increases over time,exhibiting a small peak in the initial stage due to the interaction between hydroxyl radicals(·OH)and H2 as well as their precursors.The concentration of hydrogen peroxide(H2O2)and oxygen(O2)initially rises,followed by a decrease,and eventually stabilizes at equilibrium.Increasing the size of the storage tank leads to higher contribution ratios of β and γ radiation doses,influencing the non-monotonic variation of H2 concentration,with a reduced peak value observed.This is largely associated with the increased G(·OH)values,which represent the yield of·OH generated by β and γ radiation.The concentration of O2 exhibits a monotonic increase,which is primarily driven by the enhanced reactions between·OH and hydroperoxyl radicals(HO2·),leading to O2 production.Furthermore,the H2O2 concentration initially increases due to the elevated levels of·OH radicals but decreases later due to the accelerated consumption of H2O2 through reactions with·OH and solvated electrons(e-aq),both of which play critical roles in the aqueous radiolysis process.The findings of this study provide a deeper understanding of the complex interactions between radiation types,dose distributions,and the radiolytic kinetics governing hydrogen production in high-level radioactive waste storage tanks.By overcoming the limitations of traditional empirical models,this work establishes a more accurate theoretical framework for predicting the risks of hydrogen explosions in such storage systems,therefore,offers valuable insights into the safety management of high-level radioactive waste,laying the groundwork for more reliable predictions and effective mitigation strategies in the future.
Starting from the neutron transport equation,the diffusion equation is firstly derived via the P1 approximation,and subsequently the neutron diffusion equation is obtained through the diffusion approximation.Compared with the diffusion equation,the P1 equation directly retains the complete first-order anisotropic scattering and eliminates the diffusion approximation.Existing research indicates that for cases involving strong anisotropic scattering,the computational accuracy achieved using the P1 equation is significantly higher than that obtained with the diffusion equation,without significantly increasing computation time.Therefore,to accurately solve this equation within the coarse-mesh nodal method framework,this paper referred to the variational nodal method for anisotropic scattering PN equation,to derive the second-order even-parity form of the steady-state multigroup P1 equation.Then,a theoretical model of the variational nodal method for solving the P1 equation was constructed,which included functional formulation based on the Galerkin variational principle,Ritz discretization using three-dimensional orthogonal basis functions for the flux within nodes and for the current on surfaces,and variational derivation to yield the spatially discretized P1 equation.Furthermore,based on an existing variational nodal method code for the diffusion equation,a variational nodal code for the P1 equation,named NECP-VioletP1,was developed.The modifications included enhancing the cross-section input module to handle first-order scattering matrices,implementing new routines to calculate specific response matrices,and integrating the first-order scattering source term into the iterative solution scheme.And its'verification and analysis were conducted through quantitative comparison with the finite difference code for solving the P1 equation,set up for several benchmark cases including 2D single-assembly with different fuel enrichments and poison rod configurations,2×2 assemblies with increasing heterogeneity,and 2D mini-core problem with a light water reflector.The results show that the maximum deviation of the effective multiplication factor(keff)calculated by this code from that of the finite difference code with refined-mesh is-12 pcm,and the maximum relative deviation of the fission rate distribution is-0.76%,with the largest errors predictably occurring at high-gradient regions like fuel-reflector interfaces.A comparative analysis on the mini-core problem highlights the significant advantage of the P1 method over the diffusion method.Furthermore,spatial convergence studies indicate that a 5th-order flux expansion and 2nd-order current expansion within the variational nodal method achieve sufficient accuracy with computational efficiency superior to mesh refinement in the finite difference method(FDM).This study successfully establishes a robust and accurate variational nodal method for solving the P1 equation.The developed NECP-VioletP1 code proves to be a highly effective solver,offering a superior accuracy compared to traditional diffusion theory.It provides a reliable core solver for advanced,high-fidelity core physics analysis based on the P1 theory.
Thin-walled pipelines, with their significant economic advantages, mainly due to the lightweight characteristics and lower manufacturing costs brought about by reduced material usage, coupled with excellent performance, including superior corrosion resistance and high strength to weight ratio, have been widely used in diversified industrial scenarios such as chemical processing plants, oil and gas transportation systems, and power generation facilities. These structures are particularly favored in large-scale infrastructure projects where material efficiency and operational economy are paramount. However, under severe operating conditions, such as rapid temperature variations, high-pressure corrosive environments, or high-frequency mechanical vibrations, the cross-sectional loads of thin-walled pipelines are prone to significant fluctuations and complex dynamic responses. These loading variations substantially increase the risk of structural integrity compromises through local buckling phenomena, plastic deformation mechanisms, or stress-corrosion cracking failures, particularly at critical sections like weld joints and support attachments. Consequently, the accurate extraction, precise analysis, and systematic optimization of cross-sectional loads in thin-walled pipelines have become essential research objectives—not only for enhancing their load-bearing capacity through improved design methodologies but also for developing proactive maintenance strategies to prevent fatigue-induced failures and catastrophic fractures. Such advanced monitoring capabilities are crucial for ensuring the long-term structural reliability and operational safety of pipeline systems, especially in critical infrastructure applications where failure consequences are severe. Current industrial practices primarily rely on periodic manual inspections or simplified analytical models, which often fail to capture the full complexity of real-time loading conditions and their evolution throughout the operational lifecycle. In this paper, an innovative methodology for extracting cross-sectional loads in thin-walled pipelines based on distributed strain measurement data was proposed. The comprehensive approach involved installing optimized sensor networks along the pipeline surface to capture strain variations, calculating equivalent stress values through constitutive material relationships, and subsequently back-calculating the multi-axial loads acting on critical cross-sections through advanced inverse analysis algorithms. This integrated measurement-to-load transformation enabled continuous real-time monitoring of cross-sectional force conditions, including axial forces, bending moments, torsional loads, and shear forces, with high temporal resolution and accuracy. The methodological framework incorporated compensation mechanisms for temperature effects, material non-linearity, and boundary condition uncertainties to ensure robust performance under varying operational conditions. The rationality and accuracy of the proposed methodology were rigorously validated through comprehensive comparative analysis using advanced finite element software simulations. A series of numerical experiments were conducted on various pipeline configurations under different loading scenarios, with systematic comparisons between the reconstructed loads and the applied reference values. Additional experimental validation was performed using laboratory-scale test rigs instrumented with high-precision strain gauges and load cells. The proposed theoretical method can effectively reconstruct cross-sectional loads at any arbitrary location of thin-walled pipelines, with low mean absolute errors across all load components, demonstrating performance that significantly outperforms conventional monitoring approaches. The method shows particular advantages in identifying combined loading conditions and detecting localized stress concentrations that traditional methods often miss.
In recent years,machine learning algorithms have been extensively and successfully applied across multiple domains within nuclear physics,particularly demonstrating remarkable effectiveness in conducting trend analysis for the integral validation of nuclear data.The current domestic methodology for sensitivity-based trend analysis predominantly relies on manual procedures where specialists first identify a reference experimental sequence corresponding to a sensitive nuclide-reaction channel combination,then proceed to screen various experimental characteristic parameters including energy spectrum indices through expert judgment and empirical knowledge.This traditional approach aims to discover potential correlations between observed deviations in keff calculations and the sensitivities associated with particular nuclide-reaction channels.However,this conventional methodology exhibits considerable limitations in both efficiency and comprehensiveness,as the manual screening process proves inherently inefficient and fundamentally incapable of exhaustively exploring the vast combinatorial space of all possible correlations among diverse experimental features and nuclear data sensitivities.This significant challenge in efficiently performing thorough sensitivity-based trend analysis for criticality benchmark testing has consequently emerged as the primary obstacle confronting large-scale criticality benchmark validation initiatives.To resolve this pressing issue,our research implements sophisticated association rule analysis utilizing the well-established Apriori algorithm to systematically identify and extract frequent itemsets representing specific nuclide-reaction channel sensitivity combinations from the comprehensively organized benchmark experimental feature information database ENDITS-EXP.These systematically identified frequent itemsets subsequently underwent rigorous statistical verification procedures to determine whether significant linear regression trends exist between the calculated keff deviations and the corresponding nuclide-channel sensitivity coefficients,with detailed trend analysis graphs generated to visually represent these identified relationships.Through this innovative application of advanced data mining technology,an automated framework for conducting sensitivity-based criticality benchmarking trend analysis was successfully established and demonstrated,achieving substantial improvements in analytical efficiency while simultaneously refining the investigative granularity to enable more detailed and systematic examination of nuclear data performance across varied experimental conditions.This transformation from manual expert-dependent screening processes toward automated pattern discovery and correlation identification represents a crucial advancement in nuclear data validation methodology,potentially leading to more reliable nuclear data libraries and enhanced safety assessments in practical reactor physics applications.The systematic implementation of association rule mining for exploring complex sensitivity trends not only optimizes the overall analytical workflow but also reveals previously unrecognized correlations between nuclear data uncertainties and computational biases,thereby generating valuable insights for future nuclear data evaluation and refinement efforts while establishing a robust foundation for managing increasingly large and complex benchmark datasets.
During severe accident progression in boiling water reactors (BWRs), reactor pressure vessel failure leads to the release of corium into the deep water pool of the containment pedestal, inevitably triggering fuel-coolant interactions (FCI) that form debris beds—a process threatening containment integrity. The characteristics of the resulting debris bed, including its porosity, morphology, and particle size distribution, critically determine the coolability of the molten material and the potential for steam explosions, thereby directly influencing the effectiveness of severe accident mitigation strategies. To reproduce prototypic debris bed formation phenomena under economically and safely feasible conditions, metallic simulants including tin (Sn), tin-bismuth alloy (Sn-Bi), zinc (Zn), and tin-iron alloy (Fe-Sn) were selected as representatives of actual corium compositions (Zr/Fe mixtures). The fragmentation processes of melt jets, droplet breakup, and debris sedimentation/agglomeration were comprehensively recorded using high-speed videography. The simulant materials were selected based on a simplified scaling analysis considering both hydrodynamic similarity (Froude number) and thermal similarity (modified Stefan number and Abe’s heat transfer regime maps), ensuring that the experimental observations are relevant to prototypical reactor conditions. Precise measurements were obtained for debris bed characteristics including geometric configuration, porosity distribution, as well as morphological parameters and particle size distribution of fragments. The experimental results reveal significant material-dependent behaviors: 1) Steam explosion is observed exclusively in the Sn experiments, attributed to its high thermal conductivity combined with high superheat, which maintains the melt in a fully liquid state with excellent fluidity, enabling violent film boiling collapse and instantaneous heat transfer; 2) The Fe-Sn alloy experiments produce uniquely dense debris beds with extensive agglomeration and low porosity, in stark contrast to the high-porosity (＞90%) honeycomb structures formed by low-melting-point simulants (Sn, Zn, Sn-Bi); 3) Despite having comparable superheat levels, Fe-Sn exhibitsno steam explosion, instead undergoing mild film boiling that generated “externally solidified, internally liquid” particles that subsequently bonded upon settling. Analysis of the Fe-Sn results indicates that its intermediate superheat and stable film boiling regime lead to progressive surface solidification while maintaining a liquid core, with particle collision at the pool bottom rupturing the solid shells and allowing internal melt to weld adjacent particles together, forming dense agglomerates. This mechanism provides critical insights for prototypic reactor conditions, suggesting that the Zr/Fe components in actual corium may form similar dense, low-porosity layers that impede coolant penetration and threaten long-term coolability. The work provides crucial experimental data for enhancing the multicomponent corium debris bed database, offering significant scientific value for understanding the mechanisms by which melt material composition influences debris bed formation, fragmentation behavior, and steam explosion potential. These findings contribute to the development of more accurate severe accident models and inform the optimization of mitigation strategies for both BWRs and pressurized water reactors (PWRs) during the ex-vessel phase of severe accidents.
In the poison design scheme of dispersed particle fuel, there are situations in which TRISO fuel particles and BISO poison particles are mixed and dispersed into the SiC matrix. The common equivalent homogenization method based on the disadvantage factors has difficulty in handling the conditions where multiple types of particles coexist, while the stochastic medium neutron transport method has difficulty in dealing with large-scale calculation problems. To establish the double heterogeneity processing capability for multiple particle mixing in the fuel compact and achieve high-fidelity neutronics simulation of the whole core loaded with dispersed particle fuel, this study adds a dispersed particle fuel processing module to the deterministic high-fidelity program NECP-X. The part of resonance calculation is based on the global-local coupling calculation framework. First, one-dimensional (1D) equivalent models of plate or rod fuel elements were established through the conservation of the Dancoff factor. Then, in the equivalent model, the ultrafine group method was used to obtain the effective self-shielding cross-sections. Among them, the collision probabilities inside and between the particles and the matrix were obtained through the Hébert model. The part of transport calculation is based on the 2D/1D coupling transport method. In the radial direction, the Sanchez-Pomraning (S-P) method was incorporated into the 2D MOC (method of characteristic) calculation to account for randomly distributed particles and obtain the radial flux distribution at the particle and matrix locations. In the axial direction, the pin-based homogenization was adopted, and the particle structure was considered in the flux-weighted calculation of the homogenized cross-sections. Then, the axial flux distribution was obtained through 1D SN calculation. Similarly, the particle structure must be considered in the calculation of the homogenization parameters in the coarse-mesh finite difference method. In addition, the iterative format of the equivalent homogenized cross-sections was modified to ensure its convergence when the particle packing fractions are greater than 0.5. Taking the Monte Carlo program with explicit particle modeling as reference, calculations were carried out for rod-type fuel pin and plate-type reactor core problems. In the rod-type single pin problem, the bias of cross-sections are less than 1.8%, and the bias of infinite multiplication factors （kinf） are less than 200 pcm. In the plate-type full core problem, the bias of effective multiplication factors （keff） are less than 260 pcm, and the RSE of power is within 1%. The calculation results show that the method in this paper can obtain high-precision results such as resonance self-shielding cross-sections, keff, and power distributions. Therefore, the numerical simulation method established in this study can be used for high-fidelity neutronics calculation of the entire reactor with dispersed particle fuel.
Flow measurement is critical for the safe operation of lead-cooled fast reactors (LFR), where liquid lithium-lead (LiPb) alloy acts as the primary coolant due to its superior thermal and physical properties. However, the harsh working conditions of liquid LiPb, including high temperature, electrical conductivity, corrosiveness, and intense radiation, render conventional flowmeters inapplicable. Although permanent magnet flowmeter (PMF) shows potential for liquid metal measurement, their application in LFR LiPb systems remains insufficient, with electrode shape and corrosion resistance posing key challenges to accuracy and sensitivity. This study aims to design a high-performance PMF for LiPb flow measurement, investigate electrode shape effects, and optimize structures to enhance sensitivity and reduce high flow rate accuracy degradation. To achieve these goals, a PMF with through-type electrodes was developed to ensure direct LiPb contact and minimize signal attenuation. Molybdenum was selected as the electrode material for its electrochemical stability in LiPb, while high-purity alumina ceramic insulation rings prevented stray current leakage. The PMF incorporated SmCo permanent magnets, a conductive fluid pipe (outer diameter 32 mm, wall thickness 4.5 mm), heat insulation layers, and cooling plates to maintain magnetic stability and suppress thermoelectric interference. Eight electrode shapes were designed: one cylindrical, three frustum-shaped (varying end areas), and four conical (zero end area, varying tail lengths). Three-dimensional finite element simulations were conducted using the magnetohydrodynamics (MHD) module. Mesh sensitivity analysis identified Mesh 4 (48 585 elements) as optimal for accuracy and efficiency. Simulations were performed at 500 ℃ with a flow rate range of 0.1-1.0 m3/h, adopting a laminar flow model and second-order discretization. The control variable method isolated the effects of electrode end area and tail length on performance. Simulation results confirm that the SmCo magnet assembly provides a well-distributed magnetic field, with a maximum flux density of 0.367 36 T at the pipe center. Electrode shape does not significantly affect flow velocity distribution, ensuring measurement deviations stem from electromagnetic effects alone. All electrodes transmit a complete electromotive force (EMF) signals with millivolt-level output. For electrodes of equal tail length, potential difference and sensitivity decrease with increasing end area—conical electrode 1 (zero end area, 2.5 mm tail length) outperforms frustum and cylindrical counterparts. Among conical electrodes, shorter tail lengths enhance performance. Conical electrode 1 maintains the highest sensitivity (degradation rate 0.85%) compared to the cylindrical electrode (1.13%) at high flow rates, as its shape minimizes electric field energy loss at the electrode end. This study concludes that electrode shape is a decisive factor in PMF performance. For through-type electrodes with identical insertion depth and length, smaller end areas and shorter tail lengths significantly improve sensitivity and reduce high flow rate accuracy loss, with conical electrodes offering optimal performance. The designed PMF has molybdenum electrodes, alumina insulation, and thermal protection, effectively addresses LiPb’s corrosion and high-temperature challenges. These findings fill the research gap in LFR LiPb flow measurement and provide a theoretical basis for electromagnetic flowmeter optimization. The proposed design and strategy can be extended to other liquid metal measurement scenarios, advancing high-precision flow measurement for advanced nuclear energy systems.
As a fourth-generation nuclear reactor,the sodium-cooled fast reactor(SFR)is a crucial reactor type for China to realize its closed-cycle nuclear energy strategy.When a sodium-water reaction(SWR)accident occurs in SFR,high-pressure steam enters the sodium loop and reacts with liquid sodium.The two-phase reaction rate model for sodium and water vapor is of great significance for predicting sodium-water accidents and optimizing the treatment of waste sodium.Based on the temperature-dependent liquid film morphology differences observed in previous visual experiments on liquid sodium-water vapor interactions,in this study the Buckingham-Lennard-Jones mixed potential method was employed to investigate the interaction mechanism between molten sodium hydroxide(NaOH)liquid films and water vapor within the temperature range of 600-900 K via molecular dynamics(MD)simulations.Firstly,the applicability of the potential was verified by calculating density and viscosity,then the surface tension was calculated using the stress tensor method,final the intermolecular interactions was analyzed by combining the results of the radial distribution function(RDF)and average molecular coordination number.The results indicate that water molecules form weak hydrogen bonds with hydroxide ions and coordination structures with sodium ions under high-temperature conditions.In the molten sodium hydroxide free surface system,water molecules are mainly distributed on the surface rather than being uniformly distributed due to electrostatic forces.When water molecules are abundant in the environment,they form coordination bonds with sodium ions on the surface of the molten material,gradually converting the electrostatic interactions between ions in the surface layer of the liquid film into water molecule-ion interactions.This process reduces the internal forces within molten sodium hydroxide,thereby decreasing its surface tension.In addition,the diffusion coefficient of water molecules in molten sodium hydroxide was fitted using mean squared displacement(MSD)data at different temperatures.The results indicate that the diffusion coefficient of water vapor in sodium hydroxide increases with rising temperature,which is consistent with the Arrhenius distribution.The calculated diffusion activation energy of water molecules is 31.7 kJ/mol.Compared with the diffusion behavior of water molecules in pure water or aqueous solutions,water molecules in molten sodium hydroxide exhibit a higher diffusion activation energy,indicating that the diffusion process is significantly inhibited.This research provides theoretical support for the study of high-precision liquid sodium-steam two-phase reaction models and holds theoretical significance for the analysis and prevention of sodium-water accidents in sodium-cooled fast reactors.
The sodium-cooled fast reactors(SFRs)represent a significant option among Generation Ⅳreactors,offering potential benefits such as nuclear fuel breeding,improved uranium utilization,and the transmutation of high-level radioactive waste.In SFRs,sodium voiding decreases neutron absorption and hardens the neutron energy spectrum,resulting in positive reactivity.At the same time,the increased neutron mean free path leads to greater neutron leakage,which contributes negative reactivity.The net sodium void effect can be controlled by balancing these competing mechanisms.Consequently,axially heterogeneous core designs play a crucial role in influencing neutron leakage and are key to mitigating positive sodium void reactivity.Furthermore,sustainable SFR development must address challenges related to nuclear fuel fabrication and waste management,requiring flexible breeding capabilities at various stages.The breeding ratio directly impacts fuel utilization efficiency and neutron economy,making its optimization essential for the long-term viability of these reactors.In SFRs,a trade-off exists between controlling sodium void worth and adjusting the breeding ratio,both of which are critical objectives.This study develops an optimization method coupling neutron transport calculations with a genetic algorithm to design axially heterogeneous core configurations,applied to a 1 000 MWth metal-fueled SFR.The sodium void worth and breeding ratio were selected as target parameters for optimization.The NSGA-Ⅱ algorithm,implemented via Python's Geatpy library,was employed to encode the geometric parameters of the core fuel zone.A neutronics-genetic algorithm framework was established to explore the design space,evaluating core physics performance based on breeding ratio and sodium void worth.The genetic algorithm iteratively searched for Pareto-optimal solutions within the MET-1000 benchmark core geometry,aiming to regulate sodium void effects while enabling flexible tuning of breeding performance.The Pareto front,representing optimal solutions where no objective can be improved without compromising another,was successfully derived with rapid convergence.Quantitative analysis of the Pareto front elucidated the inherent trade-off between sodium void worth and breeding ratio.Axial heterogeneity enabled modulation of sodium void worth(-119.7-2144.1 pcm)and breeding ratio(1.14-1.42).Spatial analysis reveals that the reduction in sodium void worth primarily results from increased neutron leakage near the sodium plenum,necessitating the positioning of fissile zones closer to these regions.Breeding performance is regulated through the axial arrangement of fertile and fissile zones.However,higher breeding ratios require increased fuel enrichment,which negatively impacts the doubling time.Compared to the MET-3000,MET-1000 exhibits narrower breeding ratio optimization ranges due to core size limitations,necessitating further design refinements to enhance breeding capability.
Direct contact condensation is a highly efficient and compact heat transfer technology, widely applied in boiling water reactors and small modular reactors for nuclear reactor safety, especially in suppression containments and emergency coolant systems. During accident scenarios like loss-of-coolant accidents (LOCAs), high-temperature and high-pressure steam mixed with non-condensable gases is rapidly discharged into the suppression pool via vertical discharge pipes. This process triggers intense pressure oscillations, which threaten the structural integrity of the containment system, pipe connections, and safety valves. To clarify the underlying physical mechanism and improve prediction accuracy for practical engineering design, a calculation model for steam-air bubble condensation pressure oscillation was established based on bubble dynamics equations. This model specifically incorporates the effects of non-condensable gases on interface heat transfer coefficient and mass transfer resistance, as well as the coupling interaction between bubbles. These factors often overlooked in existing models but critical in nuclear engineering applications. Experimental validation was conducted using a visualized water tank with a discharge nozzle. The nozzle has an inner diameter of 12 mm and an immersion depth of 900 mm. Tests were performed under typical nuclear power plant operating conditions: steam mass fluxes ranging from 70 to 120 kg/(m2·s), liquid subcooling degrees of 40-70 K, and air mass fractions of 10%. High-speed cameras and pressure sensors were used to record bubble morphology and pressure variation data. The results demonstrate that the proposed model reliably predicts bubble formation, growth, coalescence behaviors and pressure oscillation characteristics. The maximum relative errors for bubble equivalent diameter, pressure oscillation frequency, and amplitude are 20%, 13.9%, and 1.9%, respectively. Its prediction performance outperforms existing models that ignore non-condensable gas effects. Further parametric analysis reveals that pressure oscillations are synergistically influenced by steam mass flux and steam-air composition, while liquid subcooling has a negligible effect on oscillation frequency. At a low mass flux of 70 kg/(m2·s), increasing the air mass fraction reduces the dominant oscillation frequency and enhances pressure intensity by slowing bubble condensation and increasing bubble residence time. At a high mass flux of 110 kg/(m2·s), the dominant frequency and pressure intensity first increase with air mass fraction due to enhanced bubble coalescence, then decrease when the air mass fraction exceeds 35% as condensation resistance becomes the dominant factor. This study provides a theoretical tool for the safe design, operation optimization, and risk assessment of suppression pools and containment pressure relief systems in nuclear power plants, supporting the improvement of nuclear reactor safety under accident conditions and reducing the risk of equipment fatigue damage.
The control rod assemblies perform the indispensable and critical function of power regulation and emergency shutdown in nuclear reactors, forming a fundamental safety barrier. The reliability of their free fall behavior, often referred to as the “drop time” directly impacts overall reactor safety and operational integrity. A typical control rod assembly consists of a central spider coupling and 24 individual neutron-absorbing control rods. The free fall process is defined as the assembly starting from an initial zero velocity, descending under the primary influence of gravity within a confined guide tube, and culminating in the contact between the lower end surface of the connector rod and the limit stop. However, accurately predicting this dynamic behavior presents significant theoretical and practical challenges. The operating environment within a reactor core is exceptionally complex, characterized by extreme conditions such as high temperature, high pressure, intense radiation fields, and pervasive flow-induced vibrations. These factors profoundly affect the assembly’s motion. Furthermore, the descent is governed by strongly coupled multi-physics phenomena. These include repeated collisions and friction between the control rod assembly and the surrounding guide channels, complex vibrational effects arising from the system’s inherent structural flexibility, and the significant, transient coupling effects with the surrounding fluid’s resistance. The intricate interplay of these factors dramatically increases the difficulty of creating accurate theoretical models using conventional analytical approaches. To address these limitations, a novel, high-fidelity and fluid-rigid-flexible coupled multibody dynamics simulation method was developed and implemented. This research focused specifically on a typical control rod assembly, establishing a comprehensive simulation model for its free fall behavior that explicitly integrates both transient fluid load effects and nonlinear mechanical contact interactions. For the fluid dynamics part, an advanced computational fluid dynamics (CFD) software was utilized to simulate the complex surrounding flow field, pressure distribution, and associated hydrodynamic forces acting on the moving assembly. This involved modeling the narrow annular gaps and the resulting viscous effects. Simultaneously, the detailed mechanical system, including the spider arms, individual rods, and their interactions with the guide channels, was modeled using a multibody dynamics (MBD) software. This model accurately captured contact forces, friction, and structural flexibility. A critical aspect of this approach was the implementation of a robust co-simulation strategy. This technique enabled real-time data exchange between the CFD and MBD solvers at each time step, thereby faithfully capturing the two-way coupled interactions between the fluid and the structure. The results demonstrate that our proposed coupled method provides a substantially more accurate and physically realistic simulation of the control rod assembly’s dynamic response under these challenging, complex boundary conditions. It successfully captures transient events like bouncing and jamming that are difficult to predict with decoupled models. Consequently, it achieves a more precise and reliable prediction of the total drop time, a key safety parameter. This work offers valuable, high-fidelity theoretical support for enhanced nuclear reactor safety analysis and provides critical, data-driven insights for the structural optimization of control rod drive mechanisms and guide tube designs. The developed methodology also establishes a reliable reference framework for peers investigating similar complex fluid-structure interaction problems in other tightly constrained engineering environments.
In multiple processes of natural uranium conversion,gas-solid fluidized bed reactors are involved,and the particles therein are all high-density particles.At present,there is a lack of systematic mechanistic research on the fluidization behavior of such high-density particles,which thus requires focused investigation.A fluidization model based on the Lagrangian method,namely the DDPM(dense discrete phase model),was constructed,and the robustness of the model was verified by comparing with experimental data from cold-model fluidization tests using real materials.Flow snapshots of gas and solid phases at different time were obtained,and the pressure fluctuations in the bed were studied using statistical analysis,spectral analysis,and orthogonal experimental design methods.The results show that bubbling occurs in the bed,and vortices of the gas phase appear at the bubble positions.After the fluidization behavior is fully developed,the particle concentration is low near the distributor,while particles mostly aggregate in the middle and upper regions of the bed.The flow channels between particles are smaller in these regions,making bubbles more likely to form.During the fluidization process,slugging and channeling are obvious,which affect the sufficient contact between gas and solid phases.The expansion rate is low,and fluidization dead zones occasionally appear,indicating that the fluidization state of UO2 particles is poor.A bubbling fluidized bed is formed in the bed,and the deviation degree is much greater than 0,suggesting uneven fluidization behavior.No obvious single peak is found,which indicates the absence of periodic bubble generation.Instead,multiple small peaks exist in the range of 0.2-10 Hz,and the main frequency of the bed corresponds to this frequency interval.In addition,based on Kolmogorov's-5/3 law,the gas-phase flow did not reach turbulence.The continuous wavelet transform(CWT)shows a continuous coherent structure band below 20 Hz,indicating that the main frequency of the bed is concentrated in this frequency range and forms a peak band,which is consistent with the results of the multiscale analysis(MSA).After the bed fully developed,a coherent structure band along the frequency direction appears,suggesting the generation of larger bubbles.An L16(215)orthogonal interaction table was established.Through analysis of variance(ANOVA),it is found that full cone angle(α)and the coupling parameter(Rfb×dp)has a significant impact on fluidization quality,while superficial gas velocity(U)has a certain impact.Other parameters and coupling parameters have little effect on fluidization quality.
As an important component of nuclear reactors,the pressurizer plays a crucial role in controlling the pressure of the reactor coolant system during normal operation,transient conditions,and accident scenarios.Currently,steam-type pressurizers are commonly used in pressurized water reactors(PWRs)both domestically and internationally.Its working principle relies on phase equilibrium and the compressibility of saturated steam for pressure control.Compared to steam-type pressurizers,nitrogen pressurizers,which utilize a mixture of nitrogen and steam or a high volume fraction of nitrogen for pressure stabilization,offer advantages such as compact size,flexible arrangement,and rapid response.Therefore,some compact small PWRs adopt nitrogen pressurizers for pressure control of the coolant system.Nitrogen,as a non-condensable gas,exhibits significant differences in physical properties compared to steam.It is necessary to conduct experimental research on the thermal response characteristics of nitrogen pressurization systems under high pressure.This paper focuses on the experimental investigation of the thermal response characteristics of a pure nitrogen-water nitrogen pressurization system under high pressure.The experimental setup includes a water tank,a surge line,and a nitrogen pressurizer.During the experiment,the water tank was heated or cooled to simulate the temperature rise and fall processes of the reactor.The numerical simulation analysis utilizes the LOCUST 1.0.2 thermal-hydraulic system analysis program,referencing the experimental circuit diagram to establish a one-dimensional nitrogen pressurization system calculation model.The modeled components include the surge line and the pressurizer,both of which are represented as tubular components.The inlet of the surge line is connected to a time-dependent control volume,with the input boundary conditions being the temperature of the water tank and the flow rate at the inlet of the surge line.The results indicate that,compared with the heating rates of+20,+40 and+60℃/h,the higher the heating rate,the faster the response of parameters such as pressure in the nitrogen pressurizer,and the smaller the difference in the response rate of the pressurizer under different heating rates.For the heating condition,when the temperature measurement point of the pressurizer is submerged in water,a sudden temperature rise occurs,with the maximum temperature increase being 9%.For the cooling condition,when the temperature measurement point of the pressurizer is exposed to the nitrogen space,a sudden temperature drop occurs,with the maximum temperature decrease being 3%.Compared with the calculated values of LOCUST 1.0.2 and the experimental values,the relative deviation of the pressure value of the pressurizer is 2.8%,which is within the acceptable range.
Sandstone-type uranium deposits are recognized as the main type for uranium exploration and mining in China, owing to their large reserves and ease of extraction. However, some of the sandstone-type uranium deposits are covered by thick overburden layers and buried at relatively great depths, which make the conventional methods difficult to obtain effective measurement results. In this context, soil thermoluminescence (TL) and optically stimulated luminescence (OSL) measurement methods, which both belong to the category of cumulative radon measurement, have shown good applicability in sandstone-type uranium exploration, because these methods have the advantages of long accumulation time of uranium ore body radiation information and low interference from environmental factors. Nevertheless, there are two limitations in the soil OSL measurement process: The first is the relatively complex soil chemical treatment procedure, which is difficult to satisfy the requirements for the large number of samples in uranium exploration; The second is the relatively low radiation response of quartz, which causes the OSL measurement to be insufficient in identifying weak anomaly information, and is unable to satisfy the precision requirements of exploration. In order to resolve these limitations, this study conducted a series of experiment to address the above issues. Accordingly, the distribution characteristics of the soil OSL signal and its corresponding mineral sources were firstly analyzed. Subsequently, the minerals for the OSL signal measurement were selected based on the intensity of the stable OSL signal under different soil chemical treatment procedures, and the measurement process was optimized. The experimental results indicate that the main source of soil OSL signals under different soil chemical treatment procedures is the 100-300 ℃ TL signal from quartz and feldspar minerals, with carbonate rocks contributing only a minor portion of the OSL signal. Furthermore, organic matter within the soil can reduce the intensity of OSL signal. The soil OSL signal intensity increases initially and then decreases under different soil chemical treatment stages. The soil OSL signal intensity is highest when the soil contains only quartz and feldspar. Therefore, the identification capability of weak anomaly information in the sandstone-type uranium deposits can be enhanced by selecting quartz-feldspar admixture minerals as measurement samples. Based on the above results, the optimized method was applied to the exploration of a certain sandstone-type uranium deposit in Inner Mongolia after simplifying the soil pretreatment processes. The results show that, compared with the measurements of soil instantaneous radon and ground γ-ray spectrum, only simple data processing is required by the optimized method to delineate the favorable metallogenic zones along the exploration profile. This study can provide crucial technical references for the application of the soil OSL exploration method in the deep exploration of sandstone-type uranium deposits.
As a strategic pillar of low-carbon energy systems,nuclear power's sustainable development fundamentally depends on operational safety.Catastrophic accidents at Three Mile Island,Chernobyl,and Fukushima have demonstrated the severe threats posed by reactor core damage events.These events involve complex multi-physics phenomena,including core melt progression,molten corium relocation,containment failure mechanisms,and radionuclide release.Given the prohibitive challenges,and often impossibility,of experimentally replicating such extreme conditions,highly reliable severe accident(SA)analysis tools become essential.These tools are vital for deciphering accident sequences,optimizing mitigation strategies,and ultimately ensuring reactor safety.Currently,a critical vulnerability exists in China's engineering capabilities for SA analysis,which remains significantly dependent on foreign commercial software.The imposition of post-trade war technology embargoes on these crucial codes has severely constrained China's domestic nuclear autonomy and hindered the international market expansion envisioned under its"go global"strategy.To address this technological gap and bolster national safety research while supporting indigenous pressurized water reactor(PWR)development,Xi'an Jiaotong University has developed CAP(containment analysis program under severe accidents).CAP serves as an integrated analysis code specifically designed to simulate the response of PWR containment structures during both thermal-hydraulic transients and severe accident scenarios.Its computational architecture integrates and couples a robust thermal-hydraulic module with specialized SA physical models critical for containment behavior prediction.These core SA physical models encompass phenomena such as radionuclide transport,molten corium-concrete interaction(MCCI),direct containment heating(DCH),and other key physical processes relevant to PWR containment experiencing severe accidents.To verify CAP's accuracy and validity under severe accident conditions,representative international experimental benchmarks(NUPEC M-8-1,AHMED,CCI-4,and IET-1)were simulated.The calculated results from CAP were systematically compared against the available experimental data.These verification studies demonstrate that the CAP program's calculations align well with the experimental results.This validation confirms that CAP can effectively simulate essential severe accident phenomena within the containment environment,encompassing thermal-hydraulic transients,radionuclide migration behavior,molten core-concrete interactions,and direct containment heating events.CAP thus presents a domestically developed solution that directly addresses the pressing technological vulnerability in severe accident analysis.Its deployment contributes significantly to nuclear safety research and strengthens China's independent nuclear power capabilities.
Accurate calculations of nuclear binding energies in theory is a long-standing problem in nuclear physics,as it provides critical insights the effective interactions and structures of atomic nuclei.Currently,there are severe limitations in theory due to the exponential growth of the Hilbert space with increasing nucleon number,i.e.,curse of the dimension.There are some effort to mitigate this problem by using the state-of-art methods,such as the machine learning and quantum computing.Recent advances in quantum computing have opened new avenues for addressing these challenges,enabling the direct simulation of nuclear many-body systems on quantum hardware.In this work,a detailed study on the calculation of nuclear binding energies using the full quantum eigensolver(FQE)algorithm,implemented on a real quantum processor,i.e.Quafu,was presented.Two nuclear systems(2H and 6He)were investigated.The deuteron,as the simplest bound nucleus with just one proton and one neutron,serves as an ideal benchmark for testing quantum algorithms,FQE.6He,a light,two-valence neutron nucleus,was used for estimating the ability of the Quafu quantum cloud platform and its"Baihua"quantum chip.Our results demonstrate that for the deuteron,the FQE algorithm on the"Baihua"quantum processor achieves a higher level of accuracy compared to previously reported results obtained using the variational quantum eigensolver(VQE)on the IBM_QX5 and IBM_19Q platforms,as discussed in Dumitrescu's article.For 6He,the FQE-calculated binding energy shows accuracy comparable to recent VQE-based calculations reported in Yoshida's article.These findings highlight the feasibility of performing precise nuclear structure calculations on near-term quantum devices and underscore the potential of the FQE approach for future applications in nuclear physics.Overall,this study extends the scope of quantum computing in nuclear physics by demonstrating that the FQE algorithm can serve as a practical and accurate tool for computing binding energies on real quantum hardware.The results provide a benchmark for future developments in quantum simulations of nuclei and suggest promising directions for scaling these methods to larger nuclear systems,ultimately contributing to a deeper understanding of nuclear structure and dynamics.
Mesophase pitch-based C/C composites,which offer advantages such as low density,high thermal conductivity,high specific modulus,and low coefficient of thermal expansion,are candidate materials for heat radiator fins in space heat-pipe reactors.Since space heat-pipe reactor design requires joining C/C composites to metal thermal components,brazing Cu to C/C composites has become a critical technical pathway for manufacturing high-performance fins.As the reinforcement phase and thermal conduction pathway in composites,fiber orientation significantly influences material properties,imparting pronounced anisotropy to characteristics such as thermal conductivity,coefficient of thermal expansion,and tensile strength.Thus,variations in fiber orientation within composites will inevitably affect joint performance.To address this objective,this study employed highly stable commercial AgCuTi filler metal to braze C/C composites with different fiber orientations to Cu metal.The microstructure,room temperature shear strength,fracture morphology,and thermal conduction properties of the brazed joints were systematically investigated.The results indicate that joints with fibers oriented perpendicular to the brazing surface(C/C⊥-Cu)exhibit the best performance.Under the condition of 880 ℃ and without applied pressure,the room temperature shear strength reached 33.19 MPa(peak strength of 41.65 MPa),and the thermal diffusivity measured 154.539 mm2/s.In contrast,joints with fibers parallel to the brazing surface(C/C//-Cu)demonstrate inferior performance,with a significantly lower room temperature shear strength of only 14.71 MPa and a reduced thermal diffusivity of 84.581 mm2/s.Microstructural and fractographic analysis reveals that the brazed joints formed under this process can effectively absorb external loads due to the presence of highly plastic and dense Ag-based and Cu-based solid solutions.Concurrently,a continuous TiC layer formed on the C/C composite side ensures stable heterogeneous bonding between the metal and the C/C composite.The C/C⊥-Cu joint exhibits significantly superior strength to the C/C//-Cu joint.This difference stems from their distinct failure mechanisms:When subjected to shear stress perpendicular to the fiber orientation,the C/C⊥-Cu joint experiences crack propagation primarily within the TiC layer at the joint interface,as the fibers themselves possess higher shear resistance than the joint region.In contrast,the C/C//-Cu joint fails differently under stress parallel to the fiber direction.Cracks tend to initiate and propagate along interlaminar regions or between fiber bundles within the composite material.For 1D or 2D composites,interlaminar shear strength is typically lower than in-plane shear strength,making the C/C⊥-Cu joint more resistant to shear failure.Furthermore,braze filler infiltration provides additional pinning effects that enhance joint strength.The C/C⊥-Cu configuration facilitates better braze penetration,contributing to its higher shear strength.The C/C⊥-Cu joint exhibits both ideal mechanical properties and thermal conductivity,showing promise for use in brazing heat radiator fins for space heat-pipe reactors.
This research addresses the critical challenge of corrosion failure in fuel cladding and structural materials exposed to extreme high-temperature environments(500-600℃)within lead-bismuth cooled fast reactor(LFR).To mitigate degradation mechanisms including selective dissolution,oxidation,and liquid metal embrittlement,an innovative NbMoVCrAl high-entropy alloy coating was designed and fabricated via magnetron sputtering on HT9 ferritic/martensitic steel substrates.The coating exhibits a homogeneous single-phase BCC solid solution structure,confirmed by X-ray diffraction(XRD),scanning electron microscope(SEM)and energy dispersive X-ray spectrometry(EDS)analysis.Systematic investigations were conducted to evaluate its corrosion behavior and protective mechanisms under oxygen-controlled conditions(2×10-6%-3×10-6%)representative of LFR operational scenarios.The NbMoVCrAl coating(nominal composition:Nb-22%,Mo-22%,V-22%,Cr-22%,Al-12%)was deposited using a high-purity alloy target(99.99%)under optimized sputtering parameters:base pressure of 2.0×10-3 Pa,substrate bias voltage of-100 V,chamber pressure of 0.53 Pa,substrate temperature of 350℃,and deposition duration of 3 h.Post-deposition characterization reveals a dense,crack-free microstructure with uniform elemental distribution and a thickness of 8.71 μm.Corrosion tests were performed in static lead-bismuth eutectic(LBE)at 500,550,and 600℃for 1 000 h,with oxygen concentrations precisely regulated via Ar-5%H2/Ar-2%O2 gas mixtures.Preferential oxidation of Al generates a continuous,adherent α-Al2O3 layer that effectively suppresses LBE penetration.Cross-sectional SEM/EDS confirms corrosion depths of less than 1 μm at all temperatures,attributed to the oxide layer's thermodynamic stability and rapid self-healing capability.In stark contrast,uncoated HT9 steel suffers severe corrosion(depth:14.80±0.41 μm at 550℃)due to non-protective Fe3O4,Fe-Cr spinel formation,and Cr depletion at the oxide-substrate interface.In the aforementioned LBE environment,increasing temperature will accelerate the thickening of the oxide layer,surface Cr depletion,and peeling of uncoated HT9 steel;For the NbMoVCrAl coated HT9 steel sample,the NbMoVCrAl coating maintains a stable BCC solid solution structure at 600℃.Compared with the HT9 steel sample,the high-entropy alloy coating has good resistance to LBE corrosion,with a corrosion depth of less than 1 μm and an corrosion rate 1-2 orders of magnitude lower than HT9 steel.It has great potential for practical applications in engineering.
The application of high burnup fuel in commercial nuclear reactors is primarily driven by compelling economic imperatives.In the competitive landscape of nuclear power generation,increasing fuel burnup can significantly extend the operational cycle of reactor cores,reduce the frequency of refueling outages,and minimize the volume of spent nuclear fuel requiring long-term storage and disposal.These benefits collectively translate into substantial cost savings for nuclear power plants,enhancing their economic viability and competitiveness relative to other energy sources.However,as fuel burnup levels rise continuously,the fuel assemblies,particularly the uranium dioxide fuel pellets,undergo progressive performance degradation due to prolonged exposure to intense neutron irradiation,high temperatures,and mechanical stresses within the reactor core.This degradation manifests in various forms,with fuel pellet fragmentation and axial relocation emerging as two of the most critical issues that compromise fuel integrity.Fuel pellet axial relocation exerts multiple adverse effects on reactor safety,especially concerning accident prevention and mitigation.A key consequence is the formation of localized hotspots in the ballooned regions of the fuel cladding.When fragmented fuel pellets migrate axially and accumulate in specific areas of the cladding,they disrupt the uniform heat transfer between the fuel and the coolant.This uneven heat distribution leads to localized overheating of the cladding,which not only accelerates cladding corrosion and creep but also elevates the risk of cladding rupture under accident conditions such as loss-of-coolant accidents(LOCAs)or reactivity-initiated accidents(RIAs).Such a scenario would severely undermine the reactor's safety barriers and trigger radioactive material release,posing significant threats to both the environment and public health.To address this critical technical challenge,in this study,an axial relocation model was developed for high burnup fuel pellets based on the LOCUST code,a specialized tool widely utilized for fuel performance analysis in nuclear engineering applications.The development process was guided by fundamental theories of fuel mechanics,heat transfer,and irradiation-induced material behavior,ensuring the model's ability to capture the complex physical mechanisms underlying pellet relocation.Subsequently,rigorous verification of the model was conducted by comparing its predictions against analytical solutions derived from established theoretical frameworks.This verification step confirmed the model's accuracy in replicating key physical phenomena under idealized conditions.To further enhance the model's credibility and practical applicability,comprehensive validation was performed using data from the FR2 reactor test,which are renowned for providing high-quality,well-documented datasets on fuel performance under various operating conditions.The comparison between the simulation results generated by the LOCUST code's axial relocation model and the experimental data demonstrated excellent agreement across multiple key parameters,including pellet relocation distance,cladding temperature distribution,and hotspot characteristics.These verification and validation results collectively indicate that the axial relocation model developed in this study exhibits robust predictive capabilities,making it a valuable tool for assessing the safety of high burnup fuel in commercial nuclear reactors and supporting the optimal design and operation of next-generation nuclear fuel systems.
