Progress in Nuclear Energy最新文献

Safety, efficiency and economic benefits cannot be ignored in the development of nuclear energy. As a type of widely used fuel in nuclear reactors, solid fuel has limited potential, long investment return cycle of new nuclear reactors and great construction resistance. Addressing these challenges, two effective approaches involve the utilization of new fuel cladding materials, specifically Accident Tolerant Fuel (ATF), and the incorporation of novel fuel pellet structures to improve economic viability and safety. In this paper, an ATF of U₃Si₂-FeCrAl system with annular structure is analyzed based on a fuel behavior analysis code CAMPUS-ANNULAR. The assessment encompasses fuel performance under typical normal operating conditions and accident scenarios such as Loss of Coolant Accident (LOCA) and Reactivity Initiated Accident (RIA). By employing the solid fuel performance analysis code CAMPUS, a comparative work is conducted to evaluate the performance of the solid U₃Si₂-FeCrAl system under both normal and accident conditions. Results indicate that, during normal operation, the annular U₃Si₂-FeCrAl system with equivalent power density reduces peaking fuel temperatures by about 70 K–150 K in comparison to the solid U₃Si₂-FeCrAl system. This reduction enhances the temperature margin under accident conditions, subsequently lowering the risk of fuel meltdown. However, the annular U₃Si₂-FeCrAl system increases the risk of Pellet Cladding Mechanical Interaction (PCMI) failure under RIA condition.

This study aims to enhance the fuel cycle and fissile breeding performance of a sodium-cooled fast breeder reactor (FBR) by utilizing minor actinides (MAs) as a means of reactivity control alongside partially-inserted control rods. Choosing the PFBR-500 as the reference design, four core models, designated as Cases A, B, C, and D, utilizing various proportions of minor actinides (MAs) were built and simulated using OpenMC. The MA concentrations were optimized to compensate for the withdrawal of control rods and ensure the same initial reactivity for all cores. Burnup analysis over 365 EFPDs revealed a significant increase in cycle length and burnup for the modified cores along with a modest rise in breeding ratio. Notably, Case C, employing 3.45 wt.% MAs in the 88 inner-core fuel subassemblies achieved an extra 62.25 EFPDs cycle length, a 33.74% rise in single-cycle burnup, and a 3.86% increase in breeding gain compared to the reference. Loading MAs into the inner-core region proved to be more effective in enhancing both fertile-to-fissile conversion (thus extending the cycle length and fuel burnup) and transmutation than utilizing MAs throughout the core due to greater neutron flux at the core center. While Case D utilizing 2.2 wt.% MAs both in the inner and outer core fuel subassemblies had the highest overall MA loading, it demonstrated lower increments in cycle length, burnup, and breeding gain compared to Case C. Case C also exhibited the highest overall destruction rate (approximately 24%/y) for Np and Am isotopes, and successfully transmuted around 24.08 kg ²³⁷Np, 9.33 kg ²⁴¹Am and 3.82 kg ²⁴³Am over the course of a single year. The addition of MAs also achieved a slight flattening of the axial and radial flux profile and a decrease in the flux peaking factor. However, it slightly lowered the beta-effective, Doppler constant, and control rod assembly worth, and shifted the coolant void reactivity worth to the positive side.

Nuclear power plants (NPPs) are becoming increasingly interesting for future energy supply. Nowadays, most of the modern NPPs, such as Generation III+ and Small Modular Reactors (SMRs), offer an even higher safety standard than their predecessors, often relying on passive systems. Due to the continuous improvement of design and safety solutions in the nuclear field, it is essential to simultaneously increase modelling capabilities. This can be achieved by the advancement of modelling tools and by increasing the experience of the analyst. This work focuses on code validation to potentially allow users to gain modelling experience and to provide insights for further code development. Due to the complexity of severe accidents, it may prove to be challenging to model passive systems under such conditions, thus the validation is especially important for numerical codes, such as MELCOR.

Codes used for the simulation of severe accidents are simplified in order to be capable of capturing all occurring phenomena in a realistic computational time frame. Thus, it is not trivial if these codes are capable of modelling the combination of passive safety systems within the new integrated features present in many NPP designs. For this reason, this work aims to investigate how such assessments should be performed as well as to consider the severe accidents code MELCOR with respect to the simulation of a passive isolation condenser at the large-scale experimental facility PANDA with and without the presence of non-condensable gases.

Our work summarises the present ideas with regards to validation and verification of nuclear codes and highlights the fact that the severe accident code MELCOR is capable of simulating passive safety systems, such as the passive isolation condenser. Improvements can be made when modelling condensation in the presence of non-condensable gases and thus suggestions were made for the improved modelling.

In the event of a loss-of-coolant accident at a nuclear power plant, a large amount of steam enters the main pump, causing the pump's pressurization to deteriorate or even fail. To reveal the deterioration mechanism of the pump performance, the gas-liquid distribution characteristics in the centrifugal pump were studied by using structured grids and the Eulerian-Eulerian model. Based on the dimensional analysis method, a predictive correlation for bubble size was established, which included factors such as inlet gas volume fraction (IGVF), rotational speed, liquid flow rate, and impeller geometric parameters. When the predictive correlation is applied to the numerical simulation, the numerical two-phase pressurization agrees well with that obtained from the experiment. As the IGVF increases, the gas begins to accumulate at the impeller inlet under the effect of the pressure gradient force. Due to the large increase in liquid velocity, the gas begins to accumulate from the middle of the diffuser flow channel. The area occupied by the gas pocket in the impeller loses its pressurization capability. The pressure vortex formed at the inlet of the channel causes the diffuser to lose its pressurization capacity. An increase in rotational speed and a decrease in liquid flow rate can effectively prevent the formation and development of gas pockets in the impeller.

Transients are events that cause nuclear power plants (NPPs) to transition from a normal state to an abnormal state, which can lead to severe accidents if not properly handled. Transient identification is crucial for NPPs’ safety and operation. In this paper, we propose a novel multimodal text-time series learning framework(MTTL), the first work to apply a large language model for transient identification. The MTTL consists of self-supervised learning pre-training and zero-shot classification for transient identification. During pre-training, the framework utilizes a large language model(LLM) and a time-series(TS) encoder to fully exploit the rich multimodal information available in NPPs, i.e., to obtain the embeddings of both text data and TS data. The LLM is used to capture the transient knowledge of the NPPs by learning from the text data, and the TS encoder is used to capture the temporal dependencies of the transients by encoding the TS data. Both the LLM and the TS encoder have a linear projection head to map the embeddings into a common space. The similarity between the embeddings of the text and TS data is calculated to minimize the contrastive learning loss and obtain a pre-trained model with rich transient knowledge. During the zero-shot classification, the framework utilizes a pre-trained model to effectively identify real-world NPP transients where the data is different from the pre-trained simulated data. The proposed framework is evaluated on the High-Temperature Reactor-Pebblebed Modules (HTR-PM) plant, and the results demonstrate that the MTTL outperforms several baseline methods, including Transformer, LSTM, and CNN1D. The better zero-shot transient identification capability makes it possible to perform better in real-world NPPs.

Liquid entrainment phenomenon can occur in the T-junction formed by the vertical ADS-4 pipeline and the hot pipe section during SBLOCA process in AP1000 reactor. At present, most of the studies on the liquid entrainment phenomenon in T-junction with large branch pipe concentrate on the atmospheric pressure condition, which is difficult to accurately reflect the real state of the accident process. The liquid entrainment experiments were carried out at 0.1–0.4 MPa on ADETEL facility. The results show that there will be obvious reverse flow phenomenon in the branch at 0.1 MPa and the phenomenon disappears gradually with the increase of pressure. Furthermore, the occurrence of intermittent two-phase slug flow in the horizontal tube was observed at lower pressures. As pressure increases, the entrainment process will become more continuous and stable, with a concomitant reduction in intermittency. The steady-state entrainment liquid level and the onset of entrainment liquid level both decrease with increasing pressure, indicating that increasing pressure can facilitate the liquid entrainment amount. The existing correlations cannot accurately estimate the entrainment amount during SBLOCA in nuclear reactor with a deviation of more than +100% between the predictions and experimental data.

There is significant interest in off-site modular factory construction for nuclear power. The IAEA defines Small Modular Reactors as “factory shop built and transported to site” and lists over 30 water cooled, 14 high temperature, 10 fast neutron, 10 molten salt, and 8 micro reactors in development worldwide. Off-site modular construction is a new development and offers more reliability in the construction and nuclear industries. A tool to help designers navigate the plethora of increased options and design challenges that modular design presents has therefore been identified as possibly increasing the efficiency and effectiveness of the design process, especially in the concept design phase. This study found that the method can create a starting point for design engineers to iterate and improve designs, significantly reduce design time in finding improved solutions, and improve performance and reduce costs associated with pipe length and network flows around the plant.

This research delves into the integration and control of a Thermal Energy Storage (TES) system with a Small Modular Reactor (SMR), specifically the NuScale VOYGR SMR module in RELAP5-3D. The research methodology centered on modeling the NuScale VOYGR SMR, a light water pressurized water reactor (LWR) with a power output capacity of 77 MWe per module. The reactor and plant details were sourced from NuScale's final safety analysis report and supplemented by information from the NuScale website. The SMR plays a crucial role in energy generation, and to manage and dispatch the produced energy effectively, a robust storage system is essential. The proposed solution to this challenge is the implementation of the TES system. The selected TES for this research is a two-tank system. The study also employed Model Predictive Control (MPC) to optimize the operation of the TES system in conjunction with the SMR. Various simulations, including accident scenarios, were conducted to assess the system's response and performance. The research leveraged real energy demand data from the California Independent System Operator (CAISO) database and scaled it to reflect the power generation of a single SMR. The findings suggest that while integrating a TES system with an SMR can enhance the performance compared to a standalone SMR, certain scenarios might exacerbate the total power mismatch. The study provides insights into the potential of integrating TES systems with nuclear reactors and the challenges and considerations involved.

In this study, the gamma ray attenuation characteristics for CuAlNi shape memory alloys with different proportions of Sn doping was investigated. We determined the mass attenuation coefficient (μ/ρ) of CuAlNiSn alloys both experimentally and theoretically within an energy range of 59.5–1332.5 keV. The experimental measurements were made using a high purity Germanium detector (HPGe) and theoretical calculations were made using WinXCOM program. To evaluate the gamma radiation shielding abilities of the alloy samples, the obtained (μ/ρ) values were used to determine the gamma protection parameters μ, HVL, TVL, MFP, and Z_eff. In addition, the radiation protection efficiency (RPE) parameter was determined using gamma ray intensities in the absence and presence of the attenuator. Further analysis of the samples was conducted using a Rigaku Miniflex 600 model computer-controlled X-ray diffractometer (CuKα & λ = 1.5405 A0). The crystallographic structure of the alloys before and after irradiation was investigated. Other analysis which include EDX analysis (to investigate the chemical content) and SEM analysis (to investigate the microstructure) were conducted. According to result outcomes, gamma ray radiation did not affect the shape memory properties of structure. Another interesting observation is that, the radiation attenuation properties increase with increasing Sn concentration. Finally, we discovered that the CuAlNiSn4 alloy (which has the highest doping rate) provides good protection especially at low energy levels.

Release rate estimation is crucial for the consequence assessment and emergency decision-making in nuclear accidents. However, inevitable model biases can lead to significant deviations. This study proposes an Adaptive Center Constraint for joint release rate estimation and model correction (ACC joint) for improved robustness and accuracy. It uses a tailored cost function to determine the optimal center constraint, which can automatically adapt to different cases. It was validated against four wind tunnel experiments, which simulated complex dispersion scenarios with densely built-up and highly heterogeneous terrains. The ACC joint method was compared with the Tikhonov and joint correction. The results indicate that the proposed method significantly improves the accuracy of release rate estimation. Compared to the joint correction method, the mean relative error is reduced by 38.6% and 31.4% in the all-measurement and independent validation, respectively. Furthermore, sensitivity analysis reveals that the ACC joint method provides lower mean relative error with different numbers of measurements and shows ultimate stability in all scenarios. It also suggests that measurement sites should be positioned in downwind high-concentration areas and the foot of mountainous areas for reliable estimation. The results from different cost functions verify the scalability of the proposed method, providing potential applications to other complex scenarios.