Reactor Pressure Vessel Research Articles

Research progress on thermal aging of reactor pressure vessel steel

Nuclear energy is highly valued in many countries for its reliability, cleanliness and cost-effectiveness. Ensuring the safe development and utilization of nuclear energy has become crucial for addressing the global energy shortage and mitigating climate change. The reactor pressure vessel (RPV) is exposed to a high-temperature, high-corrosion and high-radiation environment, the RPV materials have a significant impact on the stability and safety of a nuclear power station. In this paper, the effects of long-term high-temperature hot aging on microstructure and mechanical properties of RPV steel, as well as the research progress in embrittlement mechanism and service life prediction, are reviewed. At the same time, the existing problems and further research directions of RPV steel are pointed out.

The Use of the Stopping and Range of Ions in Matter Code for Calculation of Damage in Three Different Types of Steel

In recent years, nuclear power plants have been built worldwide. This amount large of power is better than other energy sources for the environment, it does not have a greenhouse gas. A pressurized water reactor (PWR) is a type of light water reactor to generate electricity and it needed enriched Uranium and large cost. The purpose of this work was to investigate three different types of steel for PWR reactor vessels such as SA30400, SA302B and SA355B-1 steel. The result shows that SA355B-1 performs better than the other. On the other hand, phonons, ionization and collision events show very little damage to all materials.

Simulation Study on Defect Damage Behavior of Fe under Irradiation Environment

Abstract As a commonly used structural material in nuclear power plants, Reactor pressure vessel (RPV) steel is subjected to high-energy neutron irradiation from the reactor core for a long time, and the service environment is harsh. The accumulation of point defects (interstitial atoms and vacancies) generated by irradiation over a long period can seriously affect the microstructure of the material. The macroscopic properties of the material changed until the material failed, which threatened the safety and operation stability of nuclear power plants. This paper used the method of molecular dynamics to simulate the cascade collision process of Fe in the irradiation environment. The relationship between different factors and radiation damage defects was studied. Firstly, the quantity of the Frenkel pairs increases rapidly in the irradiation environment, and then recombination occurs after reaching the peak, which makes the quantity of the Frenkel pairs decrease rapidly. Finally, the quantity of Frenkel pairs is in a stable trend. When PKA energy and temperature increase, the higher the quantity of Frenkel pairs at the peak is, the higher the recombination rate of defects is. Meanwhile, the larger the cluster size of interstitial atoms and vacancies is, the greater the corresponding quantity of clusters is. As PKA energy increases, the quantity of residual Frenkel pairs at stability increases, while the number of residual Frenkel pairs at stability decreases with temperature. This is attributed to the intense thermal motion of molecules at high temperatures, resulting in the quantity of Frenkel pairs decreasing at the stable stage. Therefore, by simulating the irradiation damage process of Fe, the prediction of material irradiation damage under a neutron irradiation environment is provided, and the service life of materials can be provided with theoretical guidance.

The numerical simulation investigates the influence of agitator parameters on particle suspension characteristics

This study investigates the effect of different agitator parameters in a baffleless stirred reactor on solid particle suspension during quaternary ammonium chitosan synthesis. Computational Fluid Dynamics (CFD) simulations investigate different agitator configurations, including blade diameter, rotational speed, and bottom clearance, to optimize chitosan particle distribution. Reducing the bottom clearance reduces particle accumulation, but can create stagnant zones that may disrupt fluid flow. Increasing the rotational speed improves particle distribution until a saturation point is reached. Increasing paddle diameter improves axial fluid circulation. Optimal settings for the vane size of a 180 mm reactor vessel are identified as 0.45 times the diameter, with a speed of 350 rpm, and a bottom clearance of 0.25 times the diameter. These simulations provide critical insight into the suspension of solid particles in baffleless stirred reactors and provide valuable guidance for optimizing stirrer parameters.

Assessment of Uncertainty in the Calculation of Neutron Fluence on the VVER-440 Reactor Pressure Vessel Due to Uncertainties in Neutron–Nuclear Interaction Cross-Sections

Assessment of Uncertainty in the Calculation of Neutron Fluence on the VVER-440 Reactor Pressure Vessel Due to Uncertainties in Neutron–Nuclear Interaction Cross-Sections

Effect of Tank Diameter on Solid Suspension in Industrial Reactor Vessels

Effect of Tank Diameter on Solid Suspension in Industrial Reactor Vessels

A simple new approach for mapping an ultrasonic tank for sonochemistry

The most used piece of equipment for sonochemistry is the ultrasonic cleaning bath. However, what is sometimes forgotten by scientists new to sonochemistry is the vital importance of the shape and positioning of any reaction vessel in the bath to obtain the most efficient and reproducible results. In experiments using an ultrasonic bath, a glass vessel (reactor) is inserted into the water contained in the bath. The water acts as the coupling medium for the transfer of acoustic energy from the transducer to the vessel (termed indirect sonication). The position of the reaction vessel above the base of the US bath can change the energy transmitted into it over a wide range of values (in our system between 100–500 J). We have carried out a study of the vertical distribution of the ultrasound field in a common type of ultrasound bath, comparing conventional sonochemistry dosimeters with a new and very simple approach using the Ultrasonic Capillary Effect (UCE) which can be performed in any laboratory. The technique involves the use of a capillary tube, to locate the vertical positions of acoustic pressure maxima above a single transducer on the base of the bath. The results are compared with those obtained using calorimetry, iodimetry, a cavitometer and the perforation of aluminium foil. The results show that the optimum position for the reaction vessel can be located very simply using UCE.

Probabilistic fracture mechanics analyses of a reactor pressure vessel using the irradiation embrittlement evaluation based on the Bayesian nonparametric method

In the structural integrity assessment of an embrittled reactor pressure vessel (RPV) based on probabilistic fracture mechanics (PFM), it is crucial to consider both of the mean value and the uncertainty of the embrittlement prediction. Typically, the embrittlement prediction uncertainty is given by a normal distribution, and its standard deviation is determined from the residuals of the measured and predicted values of all data used to develop the embrittlement prediction method. Therefore, the same uncertainty is assumed regardless of neutron fluence and the available data. To overcome this issue, the Japan Atomic Energy Agency recently developed the embrittlement prediction method based on machine learning and Bayesian statistics, i.e., the Bayesian nonparametric (BNP) method, and introduced it to the PFM analysis code. The BNP method can predict the probability distribution according to data scarcity and provide more reasonable uncertainty because it estimates significant uncertainties where the scatter of actual measured data is large and the number of data is small. In this study, PFM analysis for a Japanese model RPV in a pressurized water reactor is conducted using the PFM analysis of structural components in aging light water reactors, where the embrittlement probability distribution calculated using the BNP method is used. Furthermore, the effects of different embrittlement prediction methods and uncertainties on the failure frequency of RPVs are investigated in the PFM analyses, and the results are presented.

Analysis of Shift in Nil-Ductility Transition Reference Temperature for RPV Steels Due to Irradiation Embrittlement Using Probability Distributions and Gamma Process

Reactor pressure vessel (RPV) steels are highly susceptible to irradiation embrittlement due to prolonged exposure to high temperature, high pressure, and intense neutron irradiation. This leads to the shift in nil-ductility transition reference temperature—∆RTNDT. The change in ∆RTNDT follows a certain distribution pattern and is impacted by factors including chemical composition, neutron fluence, and irradiation temperature. Existing empirical procedures can estimate ∆RTNDT based on fitting extensive irradiation embrittlement data, but their reliability has not been thoroughly investigated. Probability statistical distributions and the Gamma stochastic process were performed to model material property degradation in RPV steels from a pressurized water reactor due to irradiation embrittlement, with the probability models considered being normal, Weibull, and lognormal distributions. Comparisons with existing empirical procedures showed that the Weibull distribution model and the Gamma stochastic model demonstrate good reliability in predicting ∆RTNDT for RPV steels. This provides a valuable reference for studying irradiation embrittlement in RPV materials.

Experimental and modeling study on irradiation effect of A508-Ⅲ steel

Irradiation can induce microscopic defects in reactor pressure vessel (RPV) steel, resulting in macroscopic hardening and embrittlement. This paper proposes a micro‑meso-macroscale calculation framework for the mechanical properties of irradiated RPV steel based on experimental and numerical investigations. The mean size and number density of Fe-ion-irradiation-induced dislocation loops were measured using transmission electron microscopy (TEM). These parameters were described by a power-function relationship with the irradiation dose at various temperatures and were used as input parameters for the crystal plasticity finite element model (CPFEM). Nano-indentation tests of A508-Ⅲ steel under different irradiation conditions were successfully simulated. In addition, microstructural characterization and molecular dynamics (MD) simulations revealed the phenomenon of dislocation pinning and the sweeping of irradiation defects during dislocation migration, implying that the dislocation-loop interactions could be responsible for the formation of dislocation channels and curved dislocation lines. Furthermore, increase in yield stress and the ductile-brittle transition temperature (DBTT) at various temperatures were investigated. Results indicated that yield stress, DBTT, and the degree of irradiation hardening and embrittlement increased with the irradiation dose and decreased with irradiation temperature. Finally, the adjusted reference temperature (ART), a significant design parameter for nuclear reactors, was calculated and evaluated using the multiscale framework. The framework can serve as a reference text for extending the life of nuclear reactors.

Application of reinforcement learning to deduce nuclear power plant severe accident scenario

Severe accident scenarios for nuclear power plants are determined through probabilistic safety analysis (PSA). In this process, it is possible to identify the failure sequence of specific components, but assessing the impact of component failure time on the severity of accident remains a challenge. In this study, a novel approach is presented that utilizes machine learning methodologies such as reinforcement learning (RL) to complement traditional PSA. The proposed process was validated by comparing whether the most severe accident scenarios obtained through critical accident simulations can be reproduced by a RL, since this is a novel use of machine learning techniques. The comparison shows feasibility of exploring critical accident scenarios using RL. To implement the reinforcement learning methodology based on the existing system code, supervised learning model that can predict the remaining time of reactor vessel failure was implemented in this study. Based on this prediction model and data from existing catastrophic accident simulation, RL was implemented. The results obtained from RL were subsequently validated with the results of severe accident code simulation. In summary, new methodology for applying machine learning techniques to the nuclear accident analysis process was presented, and the feasibility and potential of the proposed methodology were discussed.

Numerical simulation of in-vessel steam explosion for China third-generation PWR

In this study, in order to evaluate the Reactor Pressure Vessel (RPV) integrity under in-vessel steam explosion loads for China third-generation Pressurized Water Reactor (PWR), 2D and 3D numerical simulation of in-vessel steam explosion is conducted using MC3D code. The sensitivity analyses for in-vessel steam explosion are performed, including break area, water temperature, water level, melt temperature, and break height. The results show that the premixing stage cannot cause RPV failure and the possibility of the steam explosion blowing the RPV upper head off is almost non-existent. When the break area increases, the maximum pressure and impulse of the RPV inner wall increase obviously first and then generally decrease slightly. With the increase of water temperature, the maximum pressure and impulse first increase and then decrease. When the water level is higher, the maximum pressure variation is small. When the water level is very low, the maximum pressure decreases. The maximum impulse generally decreases with the decrease of the water level. When the melt temperature exceeds 2850 K, the steam explosion is not sensitive to the melt temperature. With the increase of the break height, the maximum pressure and maximum impulse first increase and then decrease. Furthermore, based on the results of sensitivity analysis, two cases of conservative conditions are selected, and the RPV integrity under in-vessel steam explosion loads for China third-generation PWR is considered. The result shows that the integrity of the RPV can be maintained under the in-vessel steam explosion loads for China third-generation PWR with a large margin. These studies provide some reference to improve the severe accident management strategy in China.

Radiation survey for Taiwan research reactor vessel

This study comprehensive evaluates radiation distribution and waste characterization during the decommissioning of the TRR Reactor Vessel. Multiple radiation surveys provide valuable data on dose rates at various positions within the vessel, utilizing thermoluminescent dosimeters (TLDs) and ionization chamber detectors for a comprehensive understanding of the radiation environment. Radionuclide analyses of experiment tubes and the Bio-shield enhance insights into radioactive activation, identifying Co-60 as the primary radionuclide. This information is crucial for proper management and disposal of radioactive waste during decommissioning. Overall, these surveys, radionuclide analyses, and estimations significantly contribute to the safe and efficient decommissioning of the TRR Reactor Vessel, aiding in identifying radiation hotspots, understanding radioactive activation, and developing effective waste management strategies and TRR internal components dismantling plan.

Validation of the added mass effect in the narrow gaps of nuclear reactor pressure vessels

Nuclear reactor pressure vessels (RPVs) must be robust to external environmental excitations such as seismic loads. Precise numerical models that predict the dynamic responses to external loads are crucial for evaluating the safety of RPVs. Notably, in RPVs submerged in reactor coolant, it is necessary to examine the added mass effect of the fluid via fluid-structure interaction (FSI) analysis, employing either an analytical approach or a numerical analysis. The present study focuses on modeling and analyzing the added mass effect in the narrow gaps associated with the dense structural layout in the reactor. In this context, this paper validates analytical and numerical models that accurately describe the added mass effect for two cases: (i) simple concentric cylinders with a narrow gap filled with fluid and (ii) a complex small-scale RPV with narrow gaps also filled with fluid. Initially, the analytical model, employing Lagrange's equation of motion and velocity potential, and the numerical model, utilizing FE modeling in acoustic FSI through ANSYS, were validated through experimental modal testing for the added mass effect in the narrow gap between simple concentric cylinders. The analytical model for the concentric cylinders indicates that the added mass diverges to infinity as the gap approaches zero, which should be examined carefully. Through experiments for the concentric cylinders, the analytical and FEM-based added mass effects were validated with a natural frequency error of 3 %. Subsequently, based on the results for the concentric cylinders, a complex numerical model of the small-scale reactor with complex boundary conditions was developed and cross-validated through corresponding experimental modal testing of the small-scale RPV. The added mass model for the narrow gaps in the RPV was validated by substantial agreement of eight representative modes, as demonstrated by a 5 % natural frequency error.

Numerical simulation on in-vessel molten corium behavior with external vessel cooling using smoothed particle hydrodynamics

The in-vessel retention through external reactor vessel cooling (IVR-ERVC) strategy is a key management strategy for early termination of a nuclear severe accident that can threaten the integrity of the reactor vessel. To simulate the physical phenomena of the molten corium, the smoothed particle hydrodynamic (SPH) method is utilized in this study. The SPH method is a Lagrangian computational fluid dynamic (CFD) method that can simulate multi-fluid stratification, turbulence, natural circulation, radiative heat transfer, thermal ablation, and crust formation. To address the external vessel cooling, it is coupled with a conventional 1-D nuclear system analysis method. The 1-D system analysis code can calculate the two-phase natural circulation of cooling water and the convective heat transfer on the external reactor vessel wall. These two simulation codes exchange the temperature and heat flux of the reactor vessel outer wall. This study numerically simulated the IVR-ERVC strategy for a Korean high-power reactor and compared it with the traditional lumped parameter method (LPM). Unlike LPM, this study provides localized detailed data about the thermal hydraulic behavior of molten corium and visualization of phenomena in the IVR-ERVC strategy. This enhances our understanding of the phenomena in IVR-ERVC strategy and introduces new perspectives.

Application of Modern Approaches to the Numerical Modeling of the Stress-Strain State for the Strength Assessment of Complex Units of the NPP Primary Circuit Equipment. Part 3. Application of Submodeling Technique and Extended Finite Element Method for Calculation of the Reactor Pressure Vessel Nozzle Zone

Application of Modern Approaches to the Numerical Modeling of the Stress-Strain State for the Strength Assessment of Complex Units of the NPP Primary Circuit Equipment. Part 3. Application of Submodeling Technique and Extended Finite Element Method for Calculation of the Reactor Pressure Vessel Nozzle Zone

Evaluation of RPV closure head penetration integrity considering fitting and residual stresses

To ensure the structure integrity of the Reactor Pressure Vessel (RPV), the main challenge is the embrittlement of beltline material. However, the stress is more complex for the regions of Closure Head Penetration (CHP). Feedback of leakage at the CHP has been found during in-service inspection. Although the detailed mechanical evaluation of the RPV head and the CHP has been carried out by many international institutions, there are limited studies to concern structure integrity of CHP tube. The systematic analysis of the influence of material strength matching, assemble stress, the Welding Residual (WR) stress and work pressure load on the fracture is also limited. In this paper, the systematic influence of these factors is analyzed, and the distribution characteristics of Stress Intensity Factor (SIF) and the crack propagation characteristics are studied. The 2D model and accurate 3D model are carried out using the finite element method. The results show that the WR stress on the outer surface of the CHP and the area adjacent to the weld is larger than the yield strength of the material. There is a gap between the RPV and the upper part of the CHP. The attenuation rate of the WR stress in the outlet direction of RPV is lower than that in the inlet direction, so cracks are more likely to occur in the out of direction. The influence of WR stress on the circumferential stress distribution and fracture parameters in the wall thickness direction of CHP is bigger than the influence of assemble load and design condition load. However, the overall stress of CHP is low. The SIF values along the crack front have an asymmetric distribution, and the SIF value is very small. As the fatigue crack propagation life is much longer than the assumed limit in the design lifetime, the risk of fracture and crack fatigue propagation caused by mechanical stress is low.

A patent retrieval method and system based on double classification

As one of the most prominent carriers of knowledge, patents can provide masses of cross-domain knowledge to support the innovative design process of products. However, there is a major problem faced by most patent-aided innovation design systems, that is, identifying and providing patents related to design requirements from a multitude of cross-domain patents. To address this problem, a patent retrieval method based on double classification is proposed in this study, and a corresponding patent-aided innovative design prototype system is also developed. Firstly, the functional attributes are extracted from design requirements and expanded to different fields based on functional bases, by which the primary patent sets are constructed via classifying cross-domain patents. Secondly, technical features are mined from the primary patent sets with the topic model, which is used to classify the primary patent sets in turn and construct the secondary patent sets, hence, corresponding patents can be obtained to solve the design problems. Finally, a patent-aided prototype system is developed based on the proposed method. On the basis of the system, the hole plug of irradiated samples of nuclear reactor pressure vessel has undergone innovative design, which verifies the feasibility and practicability of both the method and system.

Direct FE2 multiscale modeling of hydrogen-induced cracking in reactor pressure vessels

Leveraging on a recently developed multiscale simulation method, we propose a pioneering strategy for the multiscale analysis of hydrogen-induced cracking in reactor pressure vessels that considers micro-voids, their influences on hydrogen diffusion as well as the operating pressure of the vessel. In the finite element analysis, the nodal lattice hydrogen concentration and displacements are exchanged bi-directionally between the macroscale and microscale within a monolithic solution procedure. During the analysis, the voids are shown to cause non-uniform lattice hydrogen diffusion and the trapping effect, resulting in inter-void hydrogen accumulation, is demonstrated. Based on the hydrogen concentration on the void surfaces, the void hydrogen pressure was calculated for the hydrogen-induced cracking analysis. It was found that both internal shearing and necking failure modes exhibited micro-structure dependence. The internal shearing mode caused oriented through-wall propagation of cracks in the vessel pressure while the internal necking mode promoted void nucleation in the reactor pressure vessel. As a result, during the early stages of void evolution, the oriented internal shearing of the dispersed small voids showed a high possibility to induce through-wall failure of the reactor pressure vessel.

CFD Applications to Pressurized Thermal Shock-Related Phenomena

In pressurized water reactor accident scenarios, the injection of water from the emergency core cooling system (ECCS) (ECC injection) might induce a pressurized thermal shock (PTS), affecting the reactor pressure vessel (RPV) integrity. Therefore, PTS is a vital research issue in reactor safety, and its analysis is essential for evaluating the integrity of RPVs, which determines the reactor life. The PTS analysis comprises a coupled analysis between thermal–hydraulic and structural analyses. The thermal–hydraulic approach is particularly crucial, and reliable computational fluid dynamic (CFD) simulations should play a vital role in the future because predicting the temperature gradient of the RPV wall requires data on the transient temperature distribution of the downcomer (DC). Since one-dimensional codes cannot predict the complex three-dimensional flow features during ECC injection, PTS is one reactor safety issue where CFD simulation can benefit from complement evaluations with thermal–hydraulic system analysis codes. This study reviewed from the viewpoint of the turbulence models most affecting PTS analysis based on papers published since 2010 on single- and two-phase flow CFD simulation for the experiment on PTS performed in the Rossendorf coolant mixing model (ROCOM), transient two-phase flow (TOPFLOW), upper plenum test facility (UPTF), and large-scale test facility (LSTF). The results revealed that in single-phase flow CFD simulation, where knowledge and experience are sufficient, various turbulence models have been considered, and many analyses using large eddy simulation (LES) have been reported. For two-phase flow analysis of air–water conditions, interface capturing/tracking methods were used in addition to two-fluid models. The standard k–ε and shear stress transport (SST) k–ω models were still in the validated phase, and various turbulence models have yet to be fully validated. In the two-phase flow analysis of steam–water conditions, many studies have used two-fluid models and Reynolds-averaged Navier-Stoke (RANS), and NEPTUNE_CFD, in particular, has been reported to show excellent prediction performance based on years of accumulated validation.