Pebble-bed High Temperature Gas-cooled Reactor Research Articles

A System Predictive Maintenance Framework for Advanced Reactors Using a Data-Driven Digital Twin

Advanced reactor designers are looking to maximize the system capacity factor to make advanced reactors more economically competitive and meet the projected energy demand. To achieve this goal, we propose a Dynamic Operation and Maintenance Optimization (DyOMO) framework to perform system-level predictive maintenance (PdM) using a dynamic Bayesian network and component-specific PdM using deep neural networks. At the system level, DyOMO detects the presence of anomalous phenomena, determines the most influential degradation mode, and estimates the remaining useful life (RUL) distribution for the system. At the component level, DyOMO summarizes the health state of key system components, determines the presence of an anomaly using a feedforward neural network, and predicts component RUL using a Bayesian neural network. To evaluate the overall performance of DyOMO, normal operations of a Pebble-Bed High-Temperature Gas-cooled Reactor (PB-HTGR) were simulated with realistic component degradation for the steam turbine and steam generator. Across the 20 independent reactor life simulations, it was found that maintenance was always performed before any safety limits were violated and before a component failed. Specifically, the system-level PdM suggested maintenance on the steam generator once the steam pressure approached its safety limit, and the component-specific PdM suggested maintenance on the steam turbine once the turbine blade hardness degraded. The results indicate that through the continuous monitoring of the system and individual components, the DyOMO framework improves safety and increases the availability of the reactor when compared to traditional maintenance philosophies.

Numerical study of the particle-scale heat transfer in the HTR-PM pebble bed based on GPU-DEM

An essential aspect of the design of a pebble bed high-temperature gas-cooled reactor (HTGR) is the consideration of heat transfer. A particle-scale heat transfer model was developed based on the previous GPU-DEM numerical model. This model includes the heat conduction of the particles in contact, the radiative heat transfer among particles, and unidirectional convection heat transfer in the flow field. The comparison of the predicted results with the results of the TF-PBEC experiment demonstrates the accuracy of the conduction and radiation modules within the current model. Based on the current model and the porous media model, a numerical study of the natural convection heat transfer in the High-Temperature gas-cooled Reactor-Pebble-bed Module (HTR-PM) after reactor shutdown is performed. This paper systematically introduces the model design, pebble bed generation, flow field calculation, and heat transfer simulation. The results indicate that natural convection contributes to removing residual heat in the reactor core, and a higher pressure leads to better convection heat transfer. At extremely low Reynolds numbers (Re < 10), convection heat transfer is comparable to conduction and radiation, while for pressurized pebble beds (Re = 50–500), convection heat transfer dominates. Furthermore, the influence of different models used to calculate the Nusselt number of the results is compared and analyzed. For most cases, the differences in the temperature distribution of the pebble bed obtained from the different correlations are minor. However, the impact of porosity on the local Nusselt number cannot be ignored in the extremely low Reynolds numbers flows. Overall, the particle-scale heat transfer model can provide more effective reference information for the design and construction of an HTGR.

Reinforcement Learning-Based Control Sequence Optimization for Advanced Reactors

The last decade has seen the development and application of data-driven methods taking off in nuclear engineering research, aiming to improve the safety and reliability of nuclear power. This work focuses on developing a reinforcement learning-based control sequence optimization framework for advanced nuclear systems, which not only aims to enhance flexible operations, promoting the economics of advanced nuclear technology, but also prioritizing safety during normal operation. At its core, the framework allows the sequence of operational actions to be learned and optimized by an agent to facilitate smooth transitions between the modes of operations (i.e., load-following), while ensuring that all safety significant system parameters remain within their respective limits. To generate dynamic system responses, facilitate control strategy development, and demonstrate the effectiveness of the framework, a simulation environment of a pebble-bed high-temperature gas-cooled reactor was utilized. The soft actor-critic algorithm was adopted to train a reinforcement learning agent, which can generate control sequences to maneuver plant power output in the range between 100% and 50% of the nameplate power through sufficient training. It was shown in the performance validation that the agent successfully generated control actions that maintained electrical output within a tight tolerance of 0.5% from the demand while satisfying all safety constraints. During the mode transition, the agent can maintain the reactor outlet temperature within ±1.5 °C and steam pressure within 0.1 MPa of their setpoints, respectively, by dynamically adjusting control rod positions, control valve openings, and pump speeds. The results demonstrate the effectiveness of the optimization framework and the feasibility of reinforcement learning in designing control strategies for advanced reactor systems.

An inversion model for burnup history of spent fuels in pebble bed HTGR based on optimization algorithm

The measurement of transuranic isotopes in spent nuclear fuel is a crucial technique for nuclear material accounting and nuclear non-proliferation. In a pebble bed high-temperature gas-cooled reactor, numerous fuel spheres circulate through the reactor core multiple times, making it unfeasible to document the power histories of individual fuel spheres. This complexity renders it impossible to employ traditional methods, such as solving the forward burnup equations used in conventional reactors, to calculate the transuranic isotopes.In this approach, optimization algorithms were coupled with the data obtained from the BUrnup Measurement System to establish a power history inversion model, which was used to solve for the power history of fuel spheres and subsequently calculate the transuranic isotopes.The paper also compared the pros and cons of coupling the inversion model with different optimization algorithms and evaluated models using various schemes of activity vector. This process helped determine the most suitable optimization algorithm and scheme of activity vector. Sensitivity analysis revealed that the established inversion model exhibited a degree of tolerance to noise in input data and the underlying physical model.

Equilibrium core modeling of a pebble bed reactor similar to the Xe-100 with SCALE

As the nuclear industry moves towards licensing and constructing advanced reactors, new attention has been focused on the advanced reactor designs that have past operational experience, such as pebble-bed high-temperature gas-cooled reactors (PB-HTGRs). Pebble-bed reactor designs have many advantages, such as their higher operating temperatures and online refueling capabilities. However, high-fidelity computational modeling of pebble-bed reactor designs, from reactor startup to operation at equilibrium, is more challenging compared to conventionally fueled reactors due to the continuous movement of the fuel pebbles through the reactor during operation. In previous work at Oak Ridge National Laboratory (ORNL), the SCALE Leap-In method for Cores at Equilibrium (SLICE) was developed around tools within the SCALE code system. This iterative method can effectively generate pebble-bed reactor zone-wise fuel inventories at equilibrium core operation within a reasonable computational time. The objective of this work was to further verify the ORNL SLICE method and to investigate the impact of considering temperature profiles during the application of the method. The SLICE method was applied to a modular high-temperature gas-cooled reactor design based upon publicly available design specifications of the Xe-100 pebble-bed reactor. Upon comparing the results from the SLICE method to published literature, the differences in the eigenvalue keffective were on the order of several hundred pcm (percent millirho). To investigate one possible cause of these differences, a study looking at the sensitivity of the full-core equilibrium keffective and discharge nuclide inventory to temperature was performed by developing equilibrium cores of two additional temperature profiles. From this temperature study, differences on the order of hundreds of pcm for the full-core equilibrium keffective, and up to 15% difference for the discharge inventories were found. These results indicated the strong dependence on temperature that needs to be considered for future work in equilibrium modeling of PB-HTGRs.

Investigating geometry adjustments for enhanced performance in a PeLUIt-10 MWt pebble bed HTGR with OTTO refueling scheme

This research investigates the impact of changes in reactor geometry to discover more optimal dimensional options for nuclear power plants with potential applications in remote areas of Indonesia. The reactor used is PeLUIt-10, a pebble bed High-Temperature Gas-cooled Reactor (HTGR) with a 10 MWt capacity and a “once-through-then-out” or OTTO fuel loading scheme. The neutronic and thermal–hydraulic performances of PeLUIt-10 were analyzed with its core size altered, first by modifying its height-to-diameter ratio (H/D ratio) and second by reducing its core volume. These analyses were performed using the Pebble Bed Reactor Neutron Diffusion (PEBBED) Code, a specialized tool to analyze HTGR reactor physics parameters, particularly Pebble Bed Reactors.. Neutronic parameters analyzed include total fuel flow, burnup, power peaking factor, and power density distribution. For thermal-hydraulics and safety, parameters include steady-state and transient fuel temperatures, especially in Depressurized Loss of Forced Cooling (DLOFC) accidents. Results show that the optimal design, maintaining a volume of 5 m3, is a reactor with a height of 159.57 cm and a diameter of 200 cm (H/D ratio of 0.8). The fuel can achieve a maximum burnup of 80.97 MWD/kg-HM at this size. Power density distribution at these dimension is better than another dimensions, with a relatively low power peaking value of 1.4. For safety parameters, the fuel temperature in transient conditions remains below the safety limit. Meanwhile, when the core volume is reduced, the minimum burnup target of 60 MWD/kg-HM at a reactor volume of 4.4 m3 with a diameter of 172 cm and height of 189.2 cm. Thus, for OTTO-cycle PeLUIt-10, altering H/D ratio is more beneficial.

Comprehensive analysis of ASTRA benchmark with MCU-HTR and Serpent codes

Key problems in the simulation of pebble-bed high-temperature gas-cooled reactors include approximations of TRISO fuel particles and pebble-bed models, choice of nuclear data libraries, and uncertainty in graphite impurity content. This study is focused on the investigation of these problems for the ASTRA critical facility simulation with MCU-HTR and Serpent Monte Carlo codes. This paper presents a comparative analysis of the ASTRA benchmark (IEU-COMP-THERM-008) through consistent code-to-code comparisons. Some studies were performed on the simplified models of the ASTRA facility. A special care was taken to develop similar models of the ASTRA facility for the calculations using MCU-HTR and Serpent. A good agreement in the multiplication factor (less than 160pcm) between the simulations of ASTRA critical configurations using MCU-HTR and Serpent with ENDF/B-VII.0 cross-section libraries was obtained. In addition, the reactivity impact of different graphite thermal scattering libraries included in ENDF/B-VIII.0 release on the calculated results for the ASTRA benchmark was examined. Graphite evaluations assuming 0, 10, and 30 % porosity were considered in Serpent simulations with ENDF/B-VIII.0 cross-section libraries. The spread of the calculated keff for the measured critical configurations having different core height was found to be approximately 200pcm for most selected models. Consequently, model’s ability to correctly capture the procedure of a reactor loading during startup was proven. However, a significant overestimation of the keff (1000–1500pcm) was observed when we used the equivalent boron content (EBC) in the reflectors graphite adjusted to reproduce the measured graphite absorption cross-section, the EBC in matrix graphite of 1 ppmwt., ENDFB/VIII.0 cross-sections, and 30 % or 10 % porous graphite thermal scattering libraries in the Serpent simulations.

The deterministic neutron transport calculation for the HTR-PM by the three-dimensional method of characteristics code ARCHER

Due to the strong geometric adaptability, the Three-Dimensional (3-D) Method Of Characteristics (MOC) is a promising candidate for 3-D whole-core high-fidelity neutron transport calculations. However, the 3-D MOC can hardly be applied to large-scale full core problems on account of the huge computational costs in memory and time. In the past, the 3-D MOC was mainly used in traditional Light Water Reactor (LWR) calculations, but rarely used for more complex core calculations. For pebble-bed High Temperature gas-cooled Reactors (HTRs), most 3-D MOC codes are out of ability to construct complex pebble beds, let alone efficient acceleration methods. The 3-D MOC code ARCHER can efficiently simulate the large-scale pebble-bed HTRs through using the Linear Source Approximation (LSA), the Coarse Mesh Finite Difference (CMFD) and the hybrid MPI-OpenMP parallel. In this work, the two-level CMFD acceleration and efficient preconditioners on Krylov subspace linear solvers are implemented in the ARCHER code in order to achieve better performance. In addition, the practical HTR-PM criticality problem is calculated by ARCHER, which is the world’s first high-fidelity neutron transport solution of large-scale pebble-bed HTRs by deterministic numerical method. It also shows that the 3-D MOC has great application potential in other complex reactors.

Optimum power determination and comparison of multi-pass and OTTO fuel management schemes of HTGR-based PeLUIt reactor

A co-generation reactor based on pebble-bed High-Temperature Gas-Cooled Reactor (HTGR) has been designed. This study focuses on designing a modular nuclear reactor based on pebble bed high-temperature reactor (Electric Power and Industrial Hot Steam Plant/Pembangkit Listrik dan Uap Panas Industri, abbreviated as PeLUIt), an upgrade from Indonesia’s 10 MW Experimental Power Reactor (Reaktor Daya Eksperimen, RDE). PeLUIt is proposed as a solution for electricity and co-generation application. The 5-pass and Once-Through-Then-Out (OTTO) refueling scheme for the PeLUIt has been analyzed. PEBBED was used for equilibrium core calculations, whereas COMBINE7 was used for spectrum calculations utilizing ENDF/B-VII.0 as nuclear data. Based on the results, it can be inferred that the PeLUIt co-generation reactor analysis with an optimal power of 40 MWt is produced by increasing fuel intake into the core while retaining core geometry and fuel design. In this study, burn-up levels for each refueling scheme are also analyzed, and the value for OTTO is lower than 5-pass refueling schemes. In addition, the Depressurized Loss of Forced Cooling (DLOFC) accident scenario for both types of refueling schemes was also analyzed. The result showed that the OTTO refueling scheme has a higher safety level than the 5-pass refueling scheme.

Horizontal Split-Table Conceptual Design to Support Advanced Reactor Validation Needs

To improve the nuclear data testing and validation of advanced reactors, such as pebble-bed high-temperature gas-cooled reactors, molten salt reactors, and heat pipe microreactors, a conceptual design for a novel critical assembly using a horizontal split table (HST) was developed jointly by Oak Ridge National Laboratory and Lawrence Livermore National Laboratory. The mechanical design is led by Lawrence Livermore National Laboratory, whereas the neutronics considerations are led by Oak Ridge National Laboratory. The characteristics of the designed HST and the benefits of performing such an experiment to the community are included. As a proof of concept, a proposed critical experiment using tristructural isotropic fuel particles and a graphite moderator/reflector is described, mimicking a pebble-bed-type advanced reactor based on the HTR-10. A critical configuration corresponding to a footprint of about 4.5 m2 was determined with SCALE/KENO-VI to fit the planned dimensions of the HST. The similarity of the pebble-bed design and the HTR-10 reactor application was assessed using SCALE/TSUNAMI, and a similarity coefficient, ck, of 0.9982 was obtained, proving that the concept will be useful for cold-critical validation and for nuclear data validation and assimilation of pebble-bed-type advanced reactors. In the proposed design, the materials with the highest keff sensitivity are graphite and uranium, which demonstrates that particular care must be given to carbon-related cross-section data. A cross-section library study was performed to test the influence of the different recent releases of the ENDF/B cross-section library on the concept’s keff. The effect of mechanical uncertainties between the fixed and moving tables was also assessed by calculating the reactivity change caused by vertical and horizontal gaps, as well as angular and torsion offsets between the two sides of the HST concept. As a last analysis step, the performed nuclear data assimilation of the hypothetical experiment showed that uncertainties can be reduced by several hundred pcm. The same analysis process is currently being used to create a molten salt advanced reactor–type HST concept based on the Molten Salt Reactor Experiment.

Uncertainty Propagation of Fission Product Yields from Uranium and Plutonium in Pebble-Bed HTGR Burnup Calculation

Quantifying fission product yield uncertainty contribution to reactor burnup calculation is an important aspect of pebble-bed High Temperature Gas-cooled Reactor (pebble-bed HTGR) uncertainty analysis. In this work, uncertainty propagation of fission product yield to pebble-bed HTGR burnup calculation is conducted. Uncertainty of fission product yields from four fissile isotopes, namely 233U, 235U, 239Pu and 241Pu, are considered. The stochastic sampling-based uncertainty analysis method is adopted and fission product yield covariance matrices are estimated from ENDF/B-VII.1. The covariance matrix for each fissile actinide is estimated based on the Bayesian method and fission product yields are assigned with log-normal distribution in the sampling process with the Latin Hypercube Sampling (LHS) method. Since the fission fraction from 239Pu plays an important role in fissions of fuels with high burnup value in pebble-bed HTGR, the fission product yield uncertainty contribution from 239Pu is highlighted in this work. The result shows that, in the burnup equilibrium state of pebble-bed HTGR, fission product yield uncertainty contributions from 235U and 239Pu to relative uncertainty of keff are 0.027% and 0.026%, respectively. The overall uncertainty contribution from four fissile isotopes (233U, 235U, 239Pu and 241Pu) to relative uncertainty of equilibrium core keff is 0.038%. Furthermore, fission product yield uncertainty has an important contribution to the nuclide density uncertainty of fission products. The most relative uncertainty, 10.82%, is observed in 109Ag contributed from the fission product yield uncertainty of 239Pu at the burnup equilibrium state. This indicates the uncertainty contribution from the fission product yield of 239Pu cannot be neglected in pebble-bed HTGR burnup uncertainty analysis.

Exergy study of hydrogen cogeneration and seawater desalination coupled to the HTR-PM nuclear reactor

This work presents a novel integration system of the high-temperature gas-cooled reactor-pebble bed module project to a hydrogen production process using the iodine-sulfur cycle in cogeneration with seawater desalination. The current approach includes a Rankine cycle, a sulfur-iodine thermochemical cycle for hydrogen production and a multi-stage flash desalination process. The use of a catalyst that allows the H2SO4 decomposition reaction to being carried out at temperatures compatible with the nuclear reactor project is considered. The residual heat from the acid decomposition reactions is used to desalinate seawater through the multi-stage flash process. A chemical process simulator is used to create a computational model that allows estimates of global and local efficiencies of the proposed flow diagram. Some operating parameters were sized, and their influence on the efficiency is also reported. The proposed model for the sulfur-iodine cycle can produce 0.41 kg/s of hydrogen with partial energy and exergetic efficiency of 37.35% and 38.64%. The desalination process can process 40.70 kg/s with energy and exergy efficiencies of 58.78% and 82.66%, respectively. The higher exergy destruction share is obtained in the heat exchangers (36.55%), chemical reactors (16.56%) and separators (12.80%). The global system showed efficiencies of 40.13% and 52.04%, respectively.

The progress on the 3D whole-core neutronics calculation of PANGU code

PANGU code is a modern computer code for the physics analysis of pebble-bed high temperature gas-cooled reactors (HTGRs). This paper presents the recent progress on the development of PANGU’s capability in three-dimensional (3D) whole-core neutronics calculations. Firstly, diffusion and SP3 solvers based on nodal Green function method (NGFM) have been developed for the 3D whole-core calculation. Secondly, the 3D discrete-ordinate (Sn) neutron transport solver with coarse mesh finite difference (CMFD) acceleration has been developed to provide reference solutions, as well as being used for pre-homogenization calculations. Thirdly, two methods have been proposed for treating the strong absorbers in the framework of 3D whole-core diffusion calculations. Finally, the performances of the newly developed methods and solvers are tested by typical numerical cases based on HTR-10.

ASSESSMENT OF RADIOLOGICAL IMPACTS FROM POSTULATED ACCIDENT CONDITIONS OF HTGR: A CASE STUDY IN SERPONG NUCLEAR AREA

High Temperature Gas-cooled Reactor (HTGR) design has an improved safety which depends on its TRISO coated fuel particles that are considered not to be damaged even in accident condition. However, the radiological impacts from accident condition in HTGR is still important to be assessed. This research is aimed to perform radiological impacts assessment of two postulated accidents of HTGR, which are depressurization and water ingress accident. As a case study, a 10-MWTh pebble-bed HTGR design named Reaktor Daya Eksperimental with the planned site located in Serpong Nuclear Area was chosen. The source terms from the accident conditions were estimated using mechanistic source term model and the dose consequences were calculated using PC-COSYMA. The input data for PC COSYMA, which are meteorological, population distribution, agricultural and local farm data, were compiled based on the site data of Serpong Nuclear Area. The radiological impacts were assessed based on individual and collective doses. The results showed that the highest dose will be received by the community within a radius of 250 m to the south from the reactor. It was also found that these accidents only cause minor radiological impacts which do not meet the criteria for any countermeasures (iodine thyroid blocking, sheltering, evacuation, food ban, decontamination, and relocation).

ARCHER - a new Three-Dimensional method of characteristics neutron transport code for Pebble-bed HTR with coarse mesh finite difference acceleration

A new deterministic code ARCHER using Three-Dimensional (3-D) Method of Characteristics (MOC) has been developed by Institute of Nuclear and new Energy Technology (INET), Tsinghua University, aiming to obtain high-fidelity transport solution of pebble-bed High Temperature gas-cooled Reactor (HTR) with explicit pebble-bed geometry. However, 3-D MOC usually suffers from the slow convergence rate without efficient acceleration methods. In this work, the Coarse Mesh Finite Difference (CMFD) based on regular mesh is implemented to accelerate 3-D MOC calculation, which is available for the problems with cylinder and cuboid geometry. The complex geometry of reactor core with randomly stacked spherical fuel elements and irregular helium flow area, as well as the topological relationships between fine Flat Source Region (FSR) mesh for MOC and coarse CMFD mesh, are the key but challenging tasks for high-fidelity transport solution. Constructive Solid Geometry (CSG) and Boolean operation are constructed to describe problem geometry, which has the ability to deal with complex topological relationships between meshes. In addition, tree grid structure is utilized to reduce the time complexity of ray tracing and obtain the grid mapping relationship between coarse mesh and fine mesh. Spatial domain decomposition parallel based on MPI is utilized to alleviate the memory pressure and pursue high computational performance. Ray parallel is further achieved through OpenMP with shared memory. Several problems have been used to verify the geometric modeling capability and computational performance of this new 3-D MOC code for pebble-bed HTR.

A multi-level nonlinear elimination-based JFNK method for multi-scale multi-physics coupling problem in pebble-bed HTR

In the pebble-bed high-temperature gas-cooled reactor, various physical phenomena occur at different spatial scales and are coupled together tightly in a nonlinear manner. More specifically, the local temperature profiles inside the fuel sphere and TRISO particle, which are essential in reactor design and safety analysis, are coupled with the global physical fields, such as the pebble bed temperature, helium temperature, as well as the fission heat source. Therefore, the multi-physics calculation combined with multi-scale model should be employed to describe the reactor behavior. The computational efficiency is the critical issue for the numerical solution of such global and local coupled systems. Jacobian-free Newton Krylov (JFNK) algorithm is an excellent candidate for multi-physics coupling issues due to its high convergence rate and superior computational performance, but it doesn’t consider the physical features at different scales. In this work, a multi-level nonlinear elimination is proposed within the JFNK framework to deal with the multi-scale coupled system in high-temperature gas-cooled reactor. The numerous local multi-scale temperature variables, including the fuel sphere and TRISO particle temperatures, are eliminated efficiently based on the Schur complement factorization due to its well sparse matrix structure. As a result, the number of unknowns is significantly reduced and the computational performance is improved. A steady-state pebble-bed HTR model is used in this work, and the numerical results show that multi-level nonlinear elimination-based JFNK method has high computational efficiency and numerical robustness, whose performance is 4 ∼ 6 times higher than that of the original JFNK algorithm.

Analysis of gamma spectra from burnup measurement in HTR-10

HTR-10, the 10 MW pebble-bed High Temperature Gas-cooled Reactor-Test Module designed by Tsinghua University, achieved its first criticality in 2000. One of the unique features of HTR-10 is the continuous fuel feeding achieved by its fuel cycle system, in which the fuel sphere is allowed to pass through the core several times before discharged out. During the fuel circulation, the on-line burnup measurement system is used to ensure fuel credit. Up to now, after nearly 21 years of operation, huge data including gamma spectra have been collected by this on-line burnup measurement system. In this paper, the gamma spectra data collected from Nov. 2005 to Mar. 2006 are analyzed to identify the radionuclides left in the irradiated fuel sphere after a long decay. The analysis includes energy identification, decay scheme confirmation, activity estimation and so on. This work shows that radionuclides and corresponding activities are preliminarily identified, which lays a base for R&D of new burnup measurement apparatus and the profiling of fuel irradiation history. That would help to increase accuracy for the nuclear material accounting and to improve the operation strategy of pebble bed high-temperature gas-cooled reactors.

An improved homogenization method for the treatment of strong absorbers in pebble-bed HTGR

In pebble-bed high temperature gas-cooled reactors (HTGRs), strong absorbers including control rods and absorber balls are placed in the reflector. The strong absorber regions need to be homogenized for the convenience of downstream whole-core neutronics diffusion calculation. Previously, a homogenization method based on the generalized equivalence theory (GET) was studied. This paper proposes an improved homogenization method by employing a more rigorous discontinuity factor (DF) model, for more accurate treatment of the strong absorbers in the HTGR reflector. The proposed method has been implemented in the PANGU code developed by Institute of Nuclear and New Energy Technology (INET), Tsinghua University. Numerical results suggest that the newly proposed homogenization method achieves good agreement with the heterogeneous Monte Carlo transport solution and experimental result.

Double Heterogeneity Neutronic Simulation of HTR-10 for First Criticality and Full Power Initial Core with TORT-TD code

In order to support the verification and validation of computational methods and codes for the safety assessment of pebble bed High-Temperature Gas-cooled Reactors (HTGRs), the calculation of first criticality and full power initial core of the high-temperature pebble bed reactor 10 MWt (HTR-10) has been defined as one of the problems specified for both code-to-code and code-to-experiment benchmarking with a focus on neutronics. HTR-10 Experimental facility serves as the source of information for the currently designed high-temperature gas-cooled nuclear reactor. It is also desired to verify the existing codes against the data obtained in the facility. In HTR-10, the core is filled with thousands of graphite and fuel pebbles. Fuel pebbles in the reactor consist of TRISO particles, which are embedded in the graphite matrix stochastically. The reactor core is also stochastically filled with pebbles. These two stochastic geometries comprise the so-called double heterogeneity of this type of reactor. In this paper, the first criticality and the power distribution in full power initial core calculations of HTR-10 are used to demonstrate treatment of this double heterogeneity using TORT-TD and Serpent for cross-section generation. HTR-10 has unique characteristics in terms of the randomness in geometry, as in all pebble bed reactors. In this technique, the core structure is modeled by TORT-TD, and Serpent is used to provide the cross-section in a double heterogeneity approach. Results obtained by TORT-TD calculations are compared with available data. It is observed that TORT-TD calculation yield sufficiently accurate results in terms of initial criticality and power distribution in full power initial core of the HTR-10 reactor.

The neutron streaming correction method in the homogenization of Pebble-bed HTGR reflector

In pebble-bed high temperature gas-cooled reactors (HTGRs), the outside graphite reflector generally contains void regions, including the boring channels for control rods, absorber balls and coolant flow. Deterministic reactor physics calculation of HTGR is usually based on regular geometries, which requires pre-homogenization to the materials with void regions. However, the volume-weighted homogenization to the HTGR reflector can greatly overestimate the keff, due to the neutron streaming effect in the reflector channels. This paper proposes a convenient method of correcting the neutron streaming effect in the HTGR reflector, by adjusting the homogenized transport cross sections based on preservation of the neutron transmission probabilities. The proposed method has been implemented in the PANGU code for pebble-bed HTGR physics analysis and fuel cycle simulations. Numerical results suggest that the proposed method can effectively reduce the discrepancy in the homogenization of the HTGR reflector.