Core Inlet Temperature Research Articles

State feedback control of HPR1000 average coolant temperature based on dominant pole

Control of nuclear power plant is still based on the traditional PID control system, which is difficult to obtain high control quality in the process of a wide range of load changes. To effectively use the measurable information of the system and consider the constraints, state feedback control based on the dominant pole method is proposed for the average coolant temperature control of HPR1000. The control system is divided into two parts: one part is a feedback branch, which realizes the state feedback by using the measurable system state quantity including the core inlet temperature, the core outlet temperature and the reactor power, and at the same time introduces the integral link to reduce the steady-state error; the other part is a feedforward branch, which uses the nominal load change to make feedforward compensation to improve the control performance of load tracking. At the same time, Particle Swarm Optimization (PSO) method is used to optimize the controller parameters, and the dominant pole meeting the requirements is obtained. The control performance under different working conditions is verified on the HPR1000 model. The test results show that the state feedback control can effectively improve the setpoint tracking ability and anti-disturbance ability.

Photovoltaic/thermal (PV/T) solar collectors employing phase-change nano-capsules as spectral filters: Coupled, decoupled, and partially-coupled configurations

The ineffective utilization of solar radiation poses negative impacts on the performance of photovoltaic (PV) cells in terms of their efficiency and durability. For the first time, this study numerically introduces a comparative performance analysis between multiple PV/T configurations (thermally decoupled, coupled, and partially coupled) that employ nano-encapsulated phase-change material (nano-ePCM) dispersions. The dispersions act as multi-functional fluids that can optically filter incident radiation to fit the spectral response of Si PV cells, and serve as both heat carriers and storage media to effectively cool PV cells. The water-dispersed ePCM particles are made of silica shells and paraffin cores. The numerical model developed for the proposed configurations mainly comprises of three mathematical models (thermal, optical, and electrical) that are coupled together to simulate the performance of the novel systems. To ensure that the presented results are of high accuracy and credibility, the optical, electrical, and thermal models were rigorously validated against published data. Performance of the three PV/T configurations was comparatively analyzed upon varying the PCM core material, mass flowrate, channel depth, inlet and ambient temperatures, and wind speed. The utilized dispersion exhibited a 73.8% spectral match with Si PV cells, thus hinting at the effective spectral filtration capabilities of the designed fluid. When compared to similar PV/T configurations from different literatures, total exergy efficiency enhancements of 43.2%, 76.8%, and 2.6% were evident for the coupled, decoupled, and partially coupled systems, respectively. In addition, results have shown that the thermally decoupled system outperforms the coupled and partially coupled systems in terms of thermal performance but exhibits the poorest performance when superior electrical performance is desired.

Numerical Analysis of Liquid Potassium Flow and Heat Transfer in a Core for Space Nuclear Reactor Based on Entransy Dissipation Theory

AbstractThe research on the flow and heat transfer of alkali metals is an important technical means to strengthen the heat transfer of the core. In this paper, the 15 cooling channels with different structures are established. Under Re = 2.85 × 104–2.17 × 105, several operating parameters, such as core inlet temperature (T = 350 K, 390 K, 450 K, 550 K, 850 K), fuel rod pitch ratio (P = 1.2, 1.4, 1.6, 1.8, 2.0), and channel shape (triangle and square) on the heat transfer performance are numerically simulated. At the same time, this work introduces an evaluation criterion, entransy dissipation, to measure the irreversibility of the heat transfer process. The results show that the triangular channel has a stronger heat transfer capacity than the square. And the increase of the rod diameter ratio is a positive means to enhance the heat transfer. Among the studied channels, Model “I” (triangle channel, P = 2.0) has the best heat transfer performance. The above results have some guiding value to realize core heat transfer enhancement by adjusting fuel rod arrangement.

Validation of Feedback Reactivity Evaluation Models for Plant Dynamics Analysis Code During Unprotected Loss of Heat Sink Event in Sodium-Cooled Fast Reactors

Abstract Feedback reactivity caused by core deformation is one of the inherent safety features in a sodium-cooled fast reactor (SFR). To validate the evaluation models of the reactivity feedback equipped in the in-house plant dynamics analysis code, named Super-COPD, we have been conducting the benchmark analyses for the unprotected loss of heat sink (ULOHS) tests of balance of plant (BOP)-302R and BOP-301 as one of the representative issues in Experimental Breeder Reactor-II (EBR-II), a pool-type experimental SFR in the United States. During the transient of the ULOHS tests, the reactor power decreased to the decay heat level due to the negative reactivity caused by the radial expansion of the core. Developing the evaluation models of the reactivity feedback is essential for predicting the plant behavior in unprotected events, such as ULOHS events, and the numerical analyses modeling the feedback reactivity were conducted. By comparing the numerical results and the experimental data, the increment temperature profiles of the core inlet and the decreasing reactor power profile calculated by Super-COPD were comparable with experimental data. The applicability of the evaluation models for the reactivity feedback was indicated during the ULOHS event. In addition, through the sensitivity analyses on the cold pool model, it was found that the modification of the plenum model of the cold pool to take into account the thermal stratification was required to improve the core inlet temperature profile.

Study of the mixing characteristics of a multibypass combustor of a turbine-based combined cycle

When the multimode and multibypass turbine-based combined cycle (TBCC) engine performs mode transition, it involves switching between multiple bypasses. During the transition process, the flow field of the combustor is adjusted rapidly, and the mixing performance is affected. However, superior mixing is the premise of the superior combustion performance of the combustor. In this paper, the mixing characteristics of the TBCC triple-bypass combustor during the mode transition process are studied by numerical simulation. Different structural and aerodynamic parameters, including equivalent expansion angle (5.5°, 9.2°, 12.8°), lobe mixer width (20, 25, 30 mm), bypass ratio (0.44, 0.56, 0.66) and inlet temperature, were studied to discuss the trending of flow field, vorticity field, temperature field, and oxygen content distribution. The results show that the performance of triple-bypass combustor is worse than that of double-bypass combustor under the condition of turbo core inlet Mach number 0.3. The total pressure loss is increased by 0.3% and the thermal mixing efficiency is decreased by 12.4%. The increase in the equivalent expansion angle reduces the mixing efficiency (12.5%) and improves the total pressure recovery coefficient (1%). However, increases in lobe width, bypass ratio, and ram inlet temperature increased mixing characteristics but increased flow losses. The increase in turbo bypass inlet temperature (300–500 K) improved the total pressure recovery coefficient by 0.17% and the thermal mixing efficiency by 7.0%. Conversely, the increase of the turbo core inlet temperature (800–1200 K) not only reduces the total pressure recovery coefficient, but also reduces the mixing performance. In addition, the studies show that the mixing performance of the lobe mixer is mainly affected by the velocity difference between the primary and secondary flow. Besides the streamwise vortex and normal vortex, the normal vortex dissipation rate controlled by the velocity difference is also one of the factors affecting the mixing performance.

Application of machine learning algorithm in the prediction of fuel rod temperature performance

In order to predict the fuel rod temperature performance effectively, we establish a series of machine learning models based on <italic>k</italic>-nearest neighbor, decision tree and AdaBoost algorithms. The input parameters and calculation results of fuel rod performance analysis software JASMINE and data feature engineering are used as the training and test data for the machine learning models. The models are trained by the training data set which includes the characteristic parameters such as pellet and cladding type, axial height, local power, cladding corrosion thickness and core inlet temperature. After training, the models use the test data to predict the cladding outside surface temperature and pellet center temperature. The prediction results show that the model based on AdaBoost algorithm has the best prediction performances, and the mean square errors of cladding outside surface temperature and pellet center temperature are 0.605 ℃ and 8.347 ℃, respectively, and the average absolute errors are 0.273 ℃ and 3.814 ℃, respectively. Comparing the predicted values with the target values, the maximum deviation of Adaboost algorithm for the cladding outside surface temperature is 3 ℃, and the most of the prediction deviation of the pellet center temperature is less than 10 ℃, indicating that the model based on AdaBoost algorithm has the high prediction accuracy for the temperature performance of fuel rods.

Studi Karakteristik Termohidrolik Pada Kanal Pendingin Teras Reaktor SMART Menggunakan CFD Ansys Fluent

The Small Modular Reactor (SMR) type nuclear power plant is currently growing very rapidly by offering various kinds of safety features, both active and passive. One of the SMRs currently to be built and operated is the SMART (System-integrated Modular Advanced Reactor) reactor. The SMART reactor is designed to use conventional PWR fuel types but operates at a lower flow rate and core inlet temperature than conventional PWR. The existence of this basic difference needs to be a separate note for us in evaluating the safety of the SMART Reactor, especially for the thermohydraulic aspect. The thermohydraulic characteristics have been carried out previously using the MATRA code, however, the temperature distribution in the cooling sub channel is still unknown. Therefore, the purpose of this study is to calculate the temperature distribution in the cooling sub-channel on SMART. The program used in this study is CFD ANSYS. Ansys Fluent 2021 R1 Computational Fluid Dynamic (CFD) computer code was used to simulate coolant flow and heat transfer from fuel to coolant. The cooling sub channel was modeled consisting of four fuels with a diameter of 0.95 cm and a pitch of 1.26 cm in a rectangular arrangement surrounded by light water coolant. Based on the calculation, there is an increase in the average temperature of the coolant between the input and output sides of the coolant sub channel of 60 ℃, which is greater than the SMART reactor design. The fuel center and fuel cladding temperatures were calculated at 1100 ℃ and 350 ℃, respectively. This difference is caused by the modeling assumptions which is still far from the actual design. The model was assumed to consist of pure fuel and ignores the actual variations in fuel and fuel assembly. Keywords: SMART Reactor, CFD, Ansys Fluent, Thermal Hydraulic

Design Study of Small Modular Reactor Class Super Fast Reactor Core for In-Vessel Retention

Abstract The small modular reactor (SMR) class core design concept of once-through supercritical light water-cooled reactor (SCWR) with fast neutron spectrum (super fast reactor (FR)) is being developed at Waseda University. For the 300 MWel class design, complete core meltdown may need to be considered in case of a severe accident. This study proposes the new in-vessel retention (IVR) concept of the SMR class super FR (super FR-IVR), which can avoid recriticality even if the whole core relocates to the lower plenum of the reactor pressure vessel (RPV). The core characteristics with a given set of design specifications and criteria are evaluated based on fully coupled neutronics and thermal-hydraulics core burnup calculations. The debris criticality is evaluated based on Monte Carlo based method to consider the RPV lower plenum and debris configurations. The relationships between the 300 MWel class core design with the inner vessel diameter of 2.32 m and the IVR design are revealed. By reducing the operation cycle length from 720 days to 360 days and increasing the core inlet temperature from 280 °C to 370 °C, the required IVR submergence level could be reduced from 2.18 m to 1.38 m, assuming that the debris bed (melt pool) is homogeneous. However, when fully stratified debris configurations are assumed, the required disperser height and the corresponding IVR submergence level may increase to about 2.70 m.

Influence of spray drying parameters on the physicochemical characteristics of microencapsulated orange (Citrus sinensis L.) essential oil

The study evaluated the factors affecting the microencapsulation of Citrus sinensis L. essential oil (CSEO) by spray drying method with maltodextrin as raw material. These investigated parameters including concentration of maltodextrin (20–35% w/w), concentration of CSEO (1.0–2.5% w/w), inlet temperature (120–180°C) and feed flow rate (120–240 mL/h) were thoroughly analyzed. As the result, the spray drying parameters such as wall material concentration (30% w/w), core material concentration (1.5% w/w), inlet temperature (140 °C), and feed flow rate (120 mL/h) were identified to be effective parameters process on various indexes of microparticles for indexes of microparticles. This suitable condition gave the spray-dried powder with low moisture content (3.01%), high drying yield 90.05%, high values of MEE (89.94%), high MEY (76.09%) index, and low SO content (10.06%). After microencapsulation, the chemical compositions of essential oil were still maintained without any significant compromise in product qualities.

Optimization of multi-group energy structures for diffusion analyses of sodium-cooled fast reactors assisted by simulated annealing – Part II: Methodology application

Part I of this study introduced a novel methodology for the optimization of energy group structures to be used in diffusion calculations of Sodium cooled Fast Reactors. The goal of the optimization is to speed up calculations, particularly in transient analyses, while maintaining an acceptable accuracy of the results.The proposed methodology is based by either direct or simulated annealing search techniques. The capabilities of the method were preliminarily demonstrated on a single core state of the Superphénix reactor by using the DYN3D nodal diffusion code.The scope of Part II is the further demonstration of the methodology efficiency through its application to more challenging “real-life” cases. In this respect, a static Superphénix neutronic benchmark comprising 13 different core states and a transient test initiated by an increase of the core inlet temperature at the Phénix reactor are considered.For both Superphénix and Phénix reactor cores, 2- to 12-group optimal condensed energy group structures are identified using the 24-group structure as a starting point. The obtained optimal structures are thus employed in DYN3D and compared to the reference 24-group DYN3D solutions.The outcomes show that also for a broader range of core configurations and under transient conditions the optimal energy group structures allow for significant acceleration of the DYN3D performance with practically negligible degradation of the solution accuracy.

Artificial neural network for predicting nuclear power plant dynamic behaviors

A Nuclear Power Plant (NPP) is a complex dynamic system-of-systems with highly nonlinear behaviors. In order to control the plant operation under both normal and abnormal conditions, the different systems in NPPs (e.g., the reactor core components, primary and secondary coolant systems) are usually monitored continuously, resulting in very large amounts of data. This situation makes it possible to integrate relevant qualitative and quantitative knowledge with artificial intelligence techniques to provide faster and more accurate behavior predictions, leading to more rapid decisions, based on actual NPP operation data. Data-driven models (DDM) rely on artificial intelligence to learn autonomously based on patterns in data, and they represent alternatives to physics-based models that typically require significant computational resources and might not fully represent the actual operation conditions of an NPP. In this study, a feed-forward backpropagation artificial neural network (ANN) model was trained to simulate the interaction between the reactor core and the primary and secondary coolant systems in a pressurized water reactor. The transients used for model training included perturbations in reactivity, steam valve coefficient, reactor core inlet temperature, and steam generator inlet temperature. Uncertainties of the plant physical parameters and operating conditions were also incorporated in these transients. Eight training functions were adopted during the training stage to develop the most efficient network. The developed ANN model predictions were subsequently tested successfully considering different new transients. Overall, through prompt prediction of NPP behavior under different transients, the study aims at demonstrating the potential of artificial intelligence to empower rapid emergency response planning and risk mitigation strategies.

Comparison of back propagation network and radial basis function network in Departure from Nucleate Boiling Ratio (DNBR) calculation

Abstract Since estimating the minimum departure from nucleate boiling ratio (MDNBR) requires complex calculations, an alternative method has always been considered. One of these methods is neural network. In this study, the Back Propagation Neural network (BPN) and Radial Basis Function Neural network (RBFN) are introduced and compared in order to estimate MDNBR of the VVER-1000 light water reactor. In these networks, the MDNBR were predicted with the inputs including core mass flux, core inlet temperature, pressure, reactor power level and position of the control rods. To obtain the data required to design these neural networks, an externally coupledcode was developed and its ability to estimate the thermo-hydraulic parameters of the VVER-1000 reactor was compared with other numerical solutions of this benchmark and the Final Safety Analysis Report (FSAR). After ensuring the accuracy of this coupled-code, MDNBR was calculated for 272 different conditions of reactor operating, and it was used to design BPN and RBFN. Comparison of these two neural networks revealed that when the output SMEs of the two systems were approximately the same, the training process in RBFN was much faster than in BPN and the maximum network error in RBFN was less than in BPN.

Research on thermal hydraulic characteristics of integrated reactor in natural circulation operation under ocean motions

The modified one-dimensional thermal hydraulic program RELAP5/MOD3.3 was developed to simulate the natural circulation characteristics of an integrated reactor. The ocean motions were realized by adding additional acceleration in the source term of momentum equation. The pressure drop and heat transfer correlations of helically coiled tubes were adopted. The effect of natural circulation characteristics on integrated reactor was studied under rolling, heaving and inclined motions. Simulation results show that the core inlet temperature has no significant change under those three ocean conditions. The average fluctuation value of core mass flow rate is less than the steady-state value and decreases with the increasing rolling angle under the rolling motion. Besides, critical period was observed. In the heaving motion, the average fluctuation value of core mass flow rate is equal to the steady-state value which is different from the rolling motion. The steam equilibrium quality changes slightly in different heaving acceleration. In the inclined condition, the core mass flow rate is decreased with the increasing inclined angle and excessive inclined angle will cause the steam unsuperheated and this may affect the performance of the turbine.

Study on thermal hydraulic characteristics under startup of SCWR

To investigate the startup characteristics of the supercritical pressure water-cooled reactor (SCWR) system, a complete startup system model of the SCWR was established with the analysis code SCTRAN, based on the high-performance light water reactor (HPLWR) steam cycle and SCWR circulation startup loop. The correctness of the model was verified in comparison with the steady-state parameters of the steam cycle of the HPLWR. A sliding pressure startup procedure with a circulation loop that employs a control system was analyzed, and the transient performances of the core, steam drum, turbine, reheaters, steam extraction and heaters at each stage were obtained. The calculation results showed that the startup sequence and startup thermal parameters could fully meet the expectations: the system starts up stably and the core remains in the single phase; the inlet steam of the turbine stays superheated; the core inlet temperature can reach 280 °C after the adoption of the high-pressure and low-pressure heaters; and the inlet pressure of the high-pressure turbine can be kept constant. During the startup process, the maximum cladding surface temperature (MCST) remains below the limit of 650 °C, suggesting that the entire startup procedure is safe and reliable.

Comparison of back propagation network and radial basis function network in Departure from Nucleate Boiling Ratio (DNBR) calculation

Abstract Since estimating the minimum departure from nucleate boiling ratio (MDNBR) requires complex calculations, an alternative method has always been considered. One of these methods is neural network. In this study, the Back Propagation Neural network (BPN) and Radial Basis Function Neural network (RBFN) are introduced and compared in order to estimate MDNBR of the VVER-1000 light water reactor. In these networks, the MDNBR were predicted with the inputs including core mass flux, core inlet temperature, pressure, reactor power level and position of the control rods. To obtain the data required to design these neural networks, an externally coupledcode was developed and its ability to estimate the thermo-hydraulic parameters of the VVER-1000 reactor was compared with other numerical solutions of this benchmark and the Final Safety Analysis Report (FSAR). After ensuring the accuracy of this coupled-code, MDNBR was calculated for 272 different conditions of reactor operating, and it was used to design BPN and RBFN. Comparison of these two neural networks revealed that when the output SMEs of the two systems were approximately the same, the training process in RBFN was much faster than in BPN and the maximum network error in RBFN was less than in BPN.

Study on Startup Control Characteristics for CSR1000

The analysis of the startup system and startup characteristics are one important part of SCWRs design. In order to realize the analysis of the whole startup system, this paper proposes the new wall heat transfer model, based on the supercritical transient analysis code named SCTRAN. Then, the paper presents a control strategy for the startup process, including the control of coolant flow rate, core inlet temperature, system pressure, core thermal power, and steam drum water level. Different control schemes are set up according to different control objectives of the startup phases. Based on the CSR1000, an analytical model including the circulation loop and the once-through direct cycle loop is established, and four startup processes with control systems are put forward. The calculation results show that the thermal parameters of the circulation loop and the once-through direct cycle loop meet the expectation, and the maximum cladding surface temperature does not exceed the limit temperature 650℃. The feasibility of the startup scheme and the security of the startup process are verified.

Closed loop configuration in the axial flux tilt control of a PWR

Two closed loop configurations for the axial flux tilt control practice are compared in terms of certain controllability measures. To this end, the core of a PWR is taken into account. The Morari resiliency index and the Condition Number are adopted as reliable controllability measures examined for the open loop plant to evaluate the selected input/output pairs. In one scenario, boron injection is accompanied by the control rod as common means for the concurrent regulation of the core power and the pertaining axial offset. In the other case however, the boron mechanism is replaced for another regulating rod which implies the mechanical shim strategy proposed in more recent designs (e.g. IRIS or APR). A two-region modeling of the reactor core is resorted in both cases and the resultant TITO model is controlled by a Davison tuned PI regulator. Simulations indicate that the chemical shim configuration better meets the attempted controllability indices and thereby predicates a more resilient closed loop control practice. A step input perturbation is effected on the core inlet temperature to further verify this result.

Effect of reactor operator intervention during unprotected LOFA in a typical MTR

Abstract The main objective for reactor engineering and inherent safety features is to keep the nuclear fuel in a thermally safe condition with enough safety margins during all operational states (normal-abnormal and accidental states). In this work, an accident analysis of the unprotected loss of flow transient in a typical material test reactor is presented. The effect of reactor operator intervention during the accident in case of manually triggering the shutdown system at different flow coast down ratios is studied. Flow trip scenarios are compared for flow trip ratios of 14, 15, 20, 30, 40, 50 and 60 %. The calculations were performed with the nuclear reactor analysis code PARET. The reactor stability region is described in terms of initial reactor power, core inlet temperature, and power peaking factor.

EFFECTS OF COOLING SCHEMES ON THE PERFORMANCE OF SPACE CLOSED BRAYTON CYCLE

Closed Brayton cycle can efficiently convert the fission energy of the reactor into electricity, which is an ideal energy conversion system for long life, high-power and compact space reactor. In order to ensure the safe and reliable operation of turbines, compressors and generators, the space closed Brayton cycle intends to cool bearings and generators by working fluid, such as He-Xe mixture. So the cooling will inevitably affect the cycle efficiency. In this paper, three different cooling schemes for bearings and generators were proposed for the space closed Brayton cycle. They are: (1) bypassing some gas from the compressor outlet to cool bearings and generators and joining the mainstream before the reactor inlet, (2) bypassing some gas from the compressor outlet to cool bearings and generators and joining the mainstream after the reactor outlet, and (3) setting an independent cooling loop. The influence of bleeding gas flow rate on the key components was analyzed, and the three schemes were compared. The results show that the temperature difference at hot end of recuperator, molar specific power of reactor, turbine inlet temperature and molar specific work of schemes (1) and (2) decrease with increase of bleeding ratio. The scheme (3) is not effected by bleeding ratio. For a given bleeding ratio, the increasing of compression ratio will promote the space Brayton cycle efficiency of the scheme (1) and (2) at first, then the efficiency reaches its maximum value, with further increasing of compression ratio, the efficiency will reduce. But further increasing of bleeding ratio will reduce the temperature difference at hot end of recuperator, the cycle efficiency and compression ratio can not reach the maximum when the bleeding ratio increases. Therefore, there are optimal bleeding ratio, maximum cycle efficiency and corresponding compression ratio. And the maximum cycle efficiency of scheme (1) and (2) increases first and then decreases with the increase of bleeding ratio. The scheme (1) has the highest efficiency of power generation, 21.63%, because the bypass can reduce the core heat absorption and the turbine inlet temperature is the highest. The scheme (3) has the lowest efficiency which is 19.78% with the highest molar specific power which is 0.8832kJ∙mol-1 , and this scheme can reduce the core inlet temperature and the power of recuperator. The analysis provides a reference for the cooling design of the space closed Brayton cycle in the future.

Neutron noise analysis of simulated mechanical and thermal-hydraulic perturbations in a PWR core

KWU pre-Konvoi PWRs (SIEMENS design) are commonly exhibiting high neutron noise levels which can lead to costly operational issues (i.e. activation of SCRAM system, operation of unrated core power, etc.). The frequency region of interest of neutron noise is below 1 Hz, which is the typical frequency range of thermal-hydraulic phenomena. This feature seems to indicate that, coolant flow and temperature oscillations can have a key impact on neutron noise phenomena. Moreover, an increasing neutron noise trend (in term of normalized root mean square) was recently observed in many KWU-PWRs. This increasing trend has been speculated to be correlated with the introduction of a new fuel design type in the KWU-PWRs. This fact indicates that there should be some correlation between neutron noise spectral characteristics and fuel assemblies’ performance. In order to advance in understanding this phenomenon, the transient nodal code SIMULATE-3K (S3K) has been used to simulate mechanical vibrations of fuel assemblies and thermal-hydraulic fluctuations of the core inlet flow and temperature. The simulated neutron detectors responses are analysed with noise analysis techniques and compared to real plant data. This analysis indicates that the cross-feedback between the mechanical and thermal-hydraulic disturbances complicate the identification of the origin of the perturbation source. The simulated results indicate that the neutron noise spectral characteristics can be associated separately to different causes. In this sense, the results of this work seem to indicate that the spectral features of the neutron noise are a consequence of both mechanical perturbations and thermal-hydraulic fluctuations.