Search Results (20)

The article presents a comparative thermodynamic and economic analysis of nuclear power plants using high-temperature gas-cooled reactors (HTGRs) and small modular pressurized water reactors (SMRs). HTGRs, with their ability to achieve steam temperatures exceeding 650 °C, offer significantly higher electricity generation efficiency (approximately 52%) compared to SMRs and traditional PWRs, which achieve around 32%. The study underscores the importance of economic efficiency in investment decisions, noting that while SMRs are still in the conceptual phase, their future construction is uncertain, with realistic deployment expected by the late 2030s or early 2040s. The analysis highlights the superior thermodynamic performance of HTGRs due to their hierarchical dual-cycle gas–steam technology, compared to the single-cycle Clausius–Rankine process used in SMRs and PWRs. The paper contributes new insights into the comparative advantages and challenges of these nuclear technologies, particularly emphasizing the advanced safety features of HTGRs and the inherent design challenges associated with scaling down PWR technology for SMRs. Full article

Nuclear power plant (NPP) fault diagnosis is critical to ensure the safe, stable and economic operation of nuclear facilities. Existing deep learning-based NPP fault diagnosis methods primarily extract features from the temporal and spatial domain. Given recent advances in frequency-domain learning and lightweight models for time-series modeling, this paper proposes a frequency-domain learning-based fault diagnosis method for multi-modular high-temperature gas-cooled reactor (mHTGR) modules. It extracts temporal and spatial frequency-domain features using a lightweight complex-valued neural network (CVNN), which are then applied for fault classification and severity estimation. Under typical fault detection tasks for an mHTGR, comparative experiments verify that the proposed method outperforms existing methods that utilize long short-term memory (LSTM) and graph neural networks (GNNs) for spatiotemporal feature extraction in terms of classification accuracy, mean squared error (MSE) loss, and inference time. Full article

Timely detection of anomalies in nuclear power plants (NPPs) is essential for operational safety, especially under conditions where process signals deviate gradually or abruptly from nominal patterns. Traditional detection methods often struggle to adapt under transient conditions or in the absence of well-labeled fault data. To address this challenge, we propose KD-ADWIN, an adaptive concept drift-detection framework designed for unsupervised anomaly detection in dynamic industrial environments. The method integrates three core components: a Kalman-based prediction module to extract smoothed signal trends, a multi-channel detection strategy combining statistical and derivative-based drift indicators, and an adaptive thresholding mechanism that tunes detection sensitivity based on local signal variability. Evaluations on a synthetic dataset show that KD-ADWIN accurately detects both abrupt and gradual drifts, outperforming classical baselines. Further validation using full-scope simulation data from a modular high-temperature gas-cooled reactor (MHTGR) demonstrates its effectiveness in identifying concept drifts under realistic actuator and sensor fault conditions. Full article

As a model predictive control (MPC) technique, dynamic matrix control (DMC) has gained widespread industrial adoption due to its straightforward model construction and clear physical interpretation. However, its effectiveness relies on the accuracy of the predictive model, where measurement inaccuracies or excessive noise in step-response coefficients may significantly degrade control performance. This study enhances robustness of DMC by implementing finite impulse response (FIR) filters on measured step-response coefficients while providing theoretical proof of its stability. The improved algorithm is applied to cold helium temperature control of the modular High-Temperature Gas-Cooled Reactor (mHTGR). A cascade control structure is adopted, where the inner loop uses a PID controller to ensure system stability, while the outer loop uses DMC to adjust the setpoint of the hot helium temperature, thereby controlling the cold helium temperature. Numerical simulation results demonstrate significant improvements in temperature control performance and enhanced robustness of the modified DMC method. Full article

The global push for clean hydrogen production has identified nuclear energy, particularly high-temperature gas-cooled reactors (HTGRs), as a promising solution due to their ability to provide high-temperature heat. This study conducted a techno-economic analysis of hydrogen production in Saudi Arabia using the pebble bed modular reactor (HTR-PM), focusing on two methods: high-temperature steam electrolysis (HTSE) and the sulfur–iodine (SI) thermochemical cycle. The Hydrogen Economic Evaluation Program (HEEP) was used to assess the economic viability of both methods, considering key production factors such as the discount rate, nuclear power plant (NPP) capital cost, and hydrogen plant efficiency. The results show that the SI cycle achieves a lower levelized cost of hydrogen (LCOH) at USD 1.22/kg H₂ compared to HTSE at USD 1.47/kg H₂, primarily due to higher thermal efficiency. Nonetheless, HTSE offers simpler system integration. Sensitivity analysis reveals that variations in the discount rate and NPP capital costs significantly impact both production methods, while hydrogen plant efficiency is crucial in determining overall economics. The findings contribute to the broader discourse on sustainable hydrogen production technologies by highlighting the potential of nuclear-driven methods to meet global decarbonization goals. The paper concludes that the HTR-PM offers a viable pathway for large-scale hydrogen production in Saudi Arabia, aligning with the Vision 2030 objectives. Full article

The development of the Modular High-Temperature Gas-Cooled Reactor is a significant milestone in advanced nuclear reactor technology. One of the concerns for the reactor’s safe operation is the effects of a loss-of-flow accident (LOFA) where the coolant circulators are tripped, and forced coolant flow through the core is lost. Depending on the steam generator placement, loop or intracore natural circulation develops to help transfer heat from the core to the reactor cavity, cooling system. This paper investigates the fundamental physical phenomena associated with intracore coolant natural circulation flow in a one-sixth Computational Fluid Dynamics (CFD) model of the Oregon State University High Temperature Test Facility (OSU HTTF) following a loss-of-flow accident transient. This study employs conjugate heat transfer and steady-state flow along with an SST k-ω turbulence model to characterize the phenomenon of core channel-to-channel natural convection. Previous studies have revealed the importance of complex flow distribution in the inlet and outlet plenums with the potential to generate hot coolant jets. For this reason, complete upper and lower plenum volumes are included in the analyzed computational domain. CFD results also include parametric studies performed for a mesh sensitivity analysis, generated using the STAR-CCM+ software. The resulting channel axial velocities and flow directions support the test facility scaling analysis and similarity group distortions calculation. Full article

Small nuclear power plants can provide a stable, carbon-free energy supply to civil infrastructure and industrial enterprises in remote regions isolated from unified energy systems. More than 70 projects of small modular reactors are currently being developed by IAEA member countries; several low-power power units are already supplying thermal and electrical energy to consumers. One of the main limitations standing in the way of widespread dissemination of this technology is the high specific capital cost of a low-power nuclear power plant; therefore, new scientific and technical solutions are needed in this industry. Increasing the thermodynamic efficiency of power cycles of small modular reactors can become a driver for reducing the cost of supplied electrical energy. This paper presents the results of a comprehensive thermodynamic analysis of existing and promising power cycles for small modular reactors. In addition to traditional steam power cycles, cycles using non-traditional working fluids, including carbon dioxide, freons, and helium cycles, are considered. Optimal sets of thermodynamic parameters were determined to ensure maximum net efficiency of electricity production. For water-cooled reactor plants, a maximum efficiency of 33.5% at an initial temperature of 300 °C could be achieved using a steam turbine cycle. It was revealed that for reactor plants with liquid metal and liquid salt coolant in the range of initial temperatures above 550–700 °C, the maximum thermal efficiency was provided by the Brayton recompression cycle with a carbon dioxide coolant: the net electrical efficiency exceeded the level of steam turbine plants, with intermediate superheating of the steam, and could reach a value of 49.4% at 600 °C. This makes the use of these cycles promising for low-power nuclear power plants with a high initial temperature. In small gas-cooled reactor plants with a helium coolant, the use of a binary cycle consisting of a helium Brayton cycle and a steam-powered Rankine cycle provided an efficiency of 44.3% at an initial helium temperature of 700 °C and 52.9% at 1000 °C. This was higher than in the Brayton cycle with a recuperator, with a minimum temperature difference in the heat exchanger of 20 °C: the efficiency was 40.2% and 52%, respectively. Also, the transition to power cycles with non-traditional working fluids will lead to a change in the operating conditions of turbomachines and heat exchangers. Full article

This study quantitatively analysed the influence of cooling water parameters on the performance of a modular high-temperature gas-cooled reactor (MHTGR) nuclear power plant (NPP). The secondary circuit system and cold-end system were modelled using EBSILON software, version 16.0. The influence of cooling water inlet temperature and mass flow rate on the thermal performance of the secondary circuit system was analysed over the full power range with the goal of optimising net power. Under 100% rated condition, for each 1 °C increase in cooling water inlet temperature between 10 and 33 °C, the net power and cycle efficiency decreased by 0.67 MW and 0.14%, respectively, whereas the heat consumption rate increased by 28.72 kJ/(kW·h). The optimal cooling water mass flow rates corresponding to cooling water inlet temperatures of 16 °C and 33 °C were obtained. The optimal cooling water mass flow rate decreased nonlinearly with decreasing power levels. At a cooling water inlet temperature of 33 °C, an increase in cooling water mass flow rate from the designed value (7697.61 kg/s) to the optimal value (10,922.14 kg/s) resulted in a 1.03 MW increase in net power. These findings provide guidelines for MHTGR NPP operation optimisation and economic improvement, especially under high-temperature weather conditions. Full article

For multi-modular nuclear power plants under the scheme of multiple nuclear steam supply system (NSSS) modules driving a single steam turbine, the NSSS modules are coupled tightly with each other by the common turbine, giving more complex normal operation with respect to the single-modular plants. To limit the operation cost of multi-modular plants, one operator is assigned to monitor and control two or more modules, whose feasibility should be verified. Combined with the characteristics of multi-module control rooms and multi-module running tasks, this paper designs a comprehensive situation awareness measurement method that combines SART, NASA-TLX (NASA Task Load Index), and eye movement tracking methods. The SART, NASA-TLX, and gaze entropy are adopted to measure the operators’ SA, and a series of accident handling experiments are performed on a full-scale simulator to gain enough data for analysis. The operators’ eye trajectories on the human–machine interface (HMI) during the experiments are all recorded for calculating the gaze entropy. Both the SART and NASA-TLX scales are filled by the operators after finishing the experiments. The experiment results show that the difference in operators’ workload and SA amongst all the experimental scenarios is limited, even between the toughest and tenderest scenarios, indicating the feasibility of one operator driving two NSSS modules simultaneously. Full article

The world’s first high-temperature gas-cooled reactor pebble-bed module (HTR-PM) nuclear power plant adopts an innovative reactor type and a modular structure design. Parameter estimation and model calibration are of great significance prior to the implementation of model-based control and optimization. This paper focuses on identifying the thermal hydraulic parameters of HTR-PM over the global operating domain. The process technology and model mechanism of HTR-PM are reviewed. A parameter submodel named global parameter mapping is presented to quantify the relationship between an unknown model parameter and different operating conditions in a data-driven manner. The ideal construction of such a mapping requires reliable estimates, a well-poised sample set and an appropriate global surrogate. An adaptive model calibration scheme is designed to tackle these three issues correspondingly. First, a systematic parameter estimation approach is developed to ensure reliable estimates via heuristic subset selection consisting of estimability analysis and reliability evaluation. To capture the parameter behavior among the multiple experimental conditions and meanwhile reduce the operating cost, an adaptive experimental design is employed to guide condition testing. Experimental conditions are sequentially determined by comprehensively considering the criteria of sampling density, local nonlinearity and parameter uncertainty. Support vector regression is introduced as the global surrogate due to its capability of small-sample learning. Finally, the effectiveness of the model calibration scheme and its application performance in HTR-PM are validated by the simulation results. Full article

The lack of fresh water in the world has become a growing concern. As an open-source incremental technology for water resources, desalination has become an important method to solve the global water crisis. Based on the inherent safety, versatility, modularity, and advantages of high-temperature gas-cooled reactors, the Saudi Arabia desalination project is the relying background. This paper proposes a complete solution for the high-temperature gas-cooled reactor power and water coproduction project by selecting a combination of process-proven multi-effect distillation (MED) and reverse osmosis (RO). In the scheme, a tertiary circuit is designed for the isolation of radioactive entities. An innovative comparative analysis of the engineering investment and production costs of different desalination technologies, such as MED and RO, and a comparison of the investment estimates of the “thermal” and “membrane” methods for the production of 10,000 tonnes of fresh water per day are performed. The feasibility and energy efficiency of the multi-effect distillation–reverse osmosis (MED-RO) scheme are presented, demonstrating the feasibility and practicality of the above approach. Full article

This study describes a life cycle assessment (LCA) of a fourth generation (4G) nuclear power plant. A high temperature helium cooled reactor and gas turbine technology with modular helium reactor (GT-MHR) is used in this study as an example. This is currently one the safest design of a nuclear power plant. The study also takes into account impact of accidents and incidents (AI) which happened around the world at nuclear power generation facilities. The adopted method for the study is a hybrid LCA analysis. The analysis of each phase of the life cycle was done on the basis of process chain analysis (PCA). Where detailed data were not available, the Input/Output (I/O) databases was employed. The obtained results show that greenhouse gases (GHG) emissions and energy intensity per unit of electricity production are relatively low. In fact, these are even lower than emissions from a number of renewable energy sources. The results show considerably different greenhouse gases (GHG) emissions and energy intensity per unit of electricity production when effects of AI are taken into account. Full article

The modular high temperature gas-cooled reactor (MHTGR) based nuclear steam supplying system (NSSS) is constituted by an MHTGR, a once-through steam generator (OTSG) and can generate superheated steam for industrial heat or electric power generation. The wide range closed-loop stability is achieved by the recently proposed coordinated control law, in which the neutron flux and the temperatures of both main steam and primary coolant are chosen as controlled variables, and the flowrates of both primary and secondary loop and the control rod speed are chosen as manipulated variables. However, the thermal power is only controlled in open loop manner and hence could be further optimized through feedback. Motivated by this, a dynamic matrix control (DMC) is proposed for optimizing the thermal power of MHTGR based NSSS. A simple step-response model with the thermal power response data is utilized in designing the DMC. The design objective of DMC is to optimize the deviation of the thermal power from its reference under its rate constraint. Then, by the virtue of strong stability of existing control law and optimization ability of DMC, a cascade control structure is implemented for the thermal power optimization, with the coordinated control law in the inner loop and DMC in the outer loop. Numerical simulation results show the satisfactory improvement of thermal power response. This cascade control structure inherits the advantages of both proportional-integral-differential (PID) control and DMC, by which the zeros offset and the short settling time of thermal power are realized. Full article

Fault diagnosis is crucial for the operation of energy systems such as nuclear plants, and heavily relies on various types of sensors for temperature, pressure, concentration, etc. Due to the redundancy of sensors in each energy system, the sensor selection scheme can deeply influence the diagnostic efficiency. In this paper, a Boolean network (BN) with its linear representation is proposed for describing the fault propagation among sensors. Both the sufficient condition of fault detectability and that of fault discriminability are given. Then, a sensor selection method for fault detection and discrimination is proposed. Finally, the theoretic result is applied to realize the diagnosis oriented sensor selection for a nuclear steam supply system based on a modular high temperature gas-cooled reactor (MHTGR). The computation and simulation results verify the correctness of the theoretical results. Full article

The modular high temperature gas-cooled reactor (MHTGR) is a typical small modular reactor (SMR) that offers simpler, standardized and safer modular design by being factory built, requiring smaller initial capital investment, and having a shorter construction period. Thanks to its small size, the MHTGRs could be beneficial in providing electric power to remote areas that are deficient in transmission or distribution and in generating local power for large population centers. Based on the multi-modular operation scheme, the inherent safety feature of the MHTGRs can be applicable to large nuclear plants of any desired power rating. The MHTGR-based nuclear steam supplying system (NSSS) is constituted by an MHTGR, a side-by-side arranged helical-coil once-through steam generator (OTSG) and some connecting pipes. Due to the side-by-side arrangement, there is a tight coupling effect between the MHTGR and OTSG. Moreover, there always exists the parameter perturbation of the NSSSs. Thus, it is meaningful to study the model-free coordinated control of MHTGR-based NSSSs for safe, stable, robust and efficient operation. In this paper, a new model-free coordinated control strategy that regulates the nuclear power, MHTGR outlet helium temperature and OTSG outlet overheated steam temperature by properly adjusting the control rod position, helium flowrate and feed-water flowrate is established for the MHTGR-based NSSSs. Sufficient conditions for the globally asymptotic closed-loop stability is given. Finally, numerical simulation results in the cases of large range power decrease and increase illustrate the satisfactory performance of this newly-developed model-free coordinated NSSS control law. Full article