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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Optimization Methodology of Pebble Bed HTGR Start-Up and Running-in Strategy

In recent years interest in advanced reactor technologies has increased significantly. However, the methods used for analysis of traditional nuclear reactors are insufficient to consider all the different and varied advanced reactor designs without further development. One promising advanced reactor design is the pebble bed reactor (PBR). PBRs possess unique operational and fuel cycle features that require the development of specific analysis methodologies to adequately design and analyze the systems. There is a need in PBR research for a capability to analyze and optimize the process of transitioning from the start-up reactor core to the equilibrium core (known as the “running-in” of the reactor). The start-up of a PBR and the transition to the equilibrium core is a complex, multi-physics challenge that has not yet been well researched and has many opportunities for design, analysis, and optimization of the process. In this research, a methodology is defined to consider the potential strategies in PBR start-up and run-in to the equilibrium core. Multiple candidate software are considered, and their pros and cons are discussed for the PBR-specific application in the methodology. A preliminary software selection for the physics engine is made, and initial verification of key modules is performed. Software to support optimization of the reactor run-in strategies through reduced order modeling (ROM) and machine learning are considered. Challenges for a full implementation of the methodology are discussed. Additional code selections and verification of models relevant to the application are needed before full demonstration of the methodology can be achieved and an optimal strategy determined.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Generating An Advanced Cross-section Library For HTGR Pebble Bed Depletion Calculations Using Reduced-Order Model Generation Techniques

For code development, Advanced Reactor Technologies - Gas Cooled Reactors Program (ART-GCR) rely on a collaboration with the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, but the cross sections generation and the methodology definition is part of this program area goals. Based on previous studies in FY23, the size of microscopic cross section libraries increases rapidly with the number of tabulations, requiring significant amount of memory and drastically slowing down the Griffin calculations when evaluating cross sections via the multivariate linear interpolation approach. Rising to these challenges, this work investigates constructing Reduced-order Models (ROMs) for the multi-group microscopic cross sections to accelerate the cross section evaluation in Griffin. A database of multigroup cross sections is first collected considering all possible parameters that a designer could change for optimization. Down-selection of the ROM techniques afterward shows Deep Neural Network (DNN) as the best candidate when jointly consider memory efficiency, predictive accuracy, computational cost, scalability, flexibility and ease of implementation of the algorithms in comparison to the multidimensional interpolation. This work develops a specific interface that enables the cross section predictions using pre-trained DNN models into Griffin leveraging the existing ROM capabilities. DNNs have been trained for all isotopes for use in Griffin. Preliminary Griffin testing shows that DNNs exhibit exceptional predictive accuracy and the use of DNNs provides orders of magnitude improvement in memory efficiency compared to conventional interpolation techniques. With such ROM techniques, it holds great promise to further increase the fidelity of the Pebble Bed Reactor (PBR) simulation by increasing the number of tabulations/state variables during cross section evaluation, while maintaining the computational cost affordable in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Deployment of the Finite Volume Method in Pronghorn for Gas and Salt cooled Pebble Bed Reactors

This report summarizes the activities related to ”Complete FHR and HTGR pebble bed simulator, including initial validation” funded by the NEAMS thermal-hydraulics focus area. The activity revolves around the coarse-mesh thermal-hydraulics code Pronghorn and its application to gas and salt cooled Pebble bed reactor (PBR). The main difference between gas and salt cooled PBR from a thermal-hydraulics perspective is the fluid. To address the difference in fluid behavior, two separate approaches are implemented in the MOOSE Navier Stokes module: 1) a Boussinesq approximation and 2) a fully compressible formulation. The developed finite volume method capabilities are used for improving pre-existing gas-cooled and salt-cooled pebble-bed reactor models. A steady-state, multiphysics gas-cooled pebble-bed reactor model is created that couples the equilibrium core depletion capability developed in previous work, and the finite volume method capability developed for this report. The salt-cooled pebble-bed reactor model is upgraded to use the incompressible finite volume method capability and then extended to three spatial dimensions. Finally, several verification-and-validation exercises performed with Pronghorn are documented using the verification-and-validation report of the MooseDoc system. The goal of this effort to document the verification-and-validation level of Pronghorn and improve stakeholder confidence in the results obtained with Pronghorn.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

XE-100 modeling and simulation for neutronic analysis in MCNP6.2

XE-100 is a generation IV helium-cooled, graphite-moderated, pebble-bed reactor (HTGR). As part of the pathway toward a conceptually designing and licensing this reactor, an independent Monte Carlo model was created in MCNP6.2, and several distinct neutronic analyses were then performed. The double heterogeneity of TRISO fuel within graphite pebbles introduces unique modeling challenges related to particle and pebble clipping. The results show that for neutron and photon heating of ex-core components such as the reflector, RCSS, core barrel (CB), the model that contains clipping produces higher heating values. It is therefore concluded that removing clipping via compression of the particles and pebbles within the model distributes the neutrons and gammas preferentially toward the core center, and reduces the heating that is experienced toward the reactor periphery. Thus, the most conservative model for ex-core heating contains particle and pebble clipping. Also presented are results on the impact of chamfers that exist on the corners of graphite reflector blocks. As these chamfers could potentially create streaming paths, the neutron and gamma flux from the core to the CB were analyzed. It was determined that the chamfers do not significantly impact the neutron or gamma signatures on the CB, in that the shape of the neutron and photon flux on a detector imposed on the CB shows no preferential streaming path. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A White Paper: Disposition Options for a High-Temperature Gas-Cooled Reactor

The high-temperature gas-cooled reactor (HTGR) is a uranium-fueled, graphite-moderated, gas-cooled nuclear reactor design concept capable of producing very high core outlet temperatures. Both types of HTGR have the tristructural isotropic (TRISO) fuel kernel at the heart of the fuel design. For the prismatic block-type HTGR, the TRISO particles are overcoated with a resinated graphitic matrix and pressed into fuel compacts, which are then heat treated and placed in the fuel channels of the prismatic-block-shaped fuel assemblies. For the pebble-bed-type HTGR, the TRISO particles are dispersed in a graphitic-matrix sphere, which is the basic unit for the reactor core. Despite having very different fuel designs, both types of HTGR are graphite-moderated, gas-cooled, thermal reactors using many of the same materials. As a result, both prismatic-block-type and pebble-bed-type HTGRs have similar radioactive waste streams, all of which require safe and secure storage and eventual disposition. Modern HTGR designs are based on a long and rich operating history of several different graphite-moderated, gas-cooled, thermal reactors. Several of these reactors have been shut down, the fuel has been placed in safe storage, and they have undergone some degree of decommissioning. As such, there is significant experience in the management of the spent nuclear fuel (SNF) and radioactive wastes associated with operating these reactors. This white paper will, (1) identify the definitions and regulations that apply to the safe and secure management, storage, and disposal of radioactive waste; and (2) identify the key radioactive waste streams from HTGRs and their characteristics. Idaho National Laboratory (INL) has significant experience in the management of SNF from HTGR predecessors. This experience should form the basis for the management and disposition efforts of the radioactive waste from any new HTGR-type small modular reactor, or microreactor intended for deployment at the INL site.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

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 k effective 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 k effective 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 k effective , and up to 15% difference for the discharge inventories were found. In conclusion, these results indicated the strong dependence on temperature that needs to be considered for future work in equilibrium modeling of PB-HTGRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Deterministic High-Fidelity Neutronics Simulation of Pebble Bed Reactors Using Pebble Tracking Transport

The pebble tracking transport (PTT) algorithm offers a high-fidelity deterministic approach for neutron transport for pebble bed reactors (PBRs). This approach requires the mesh for the active-core region to consist exclusively of tetrahedral elements, where each node in the pebble-packing region represents a pebble centroid. This paper investigates the application of PTT for full-scale PBRs, considering both the isothermal and the temperature-dependent core conditions. Macroscopic cross sections are generated using Serpent 2 full-core eigenvalue simulations where pebbles are grouped into disjoint subsets using machine learning. To minimize the need for individual cross-section sets for each pebble in the core, K-means clustering is used to group pebbles by temperature and neutronic environment parameters. Here, we compare the multiplication factor and power rate distributions between PTT simulations using the Griffin reactor physics software and reference solutions from Serpent 2. Our analysis shows that a full-core, high-fidelity PTT calculation produces accurate results with minimal local (pebblewise) errors. Additionally, timing results indicate that PTT simulations converge rapidly on modern supercomputing platforms.

Griffin↗
DOE OSTI2025

Temperature sensitivity of the equilibrium neutronics and accident analysis of the HTR-10

Pebble-Bed High-Temperature Gas-cooled Reactors (PB-HTGR) are moderated by the graphite in the fuel pebbles and the graphite reflector surrounding the pebble-bed. Because graphite is by far the most abundant material in PB-HTGRs and the primary moderator, accurate modeling of the graphite material, including density, impurities, and temperatures, is crucial for accurate computational modeling and simulation of these reactors. While main characteristics of the graphite components are often known, the local temperature is less well known and often averaged over all components. Here, this work studies the impact of considering accurate temperature profiles in the graphite material on the generation of a small PB-HTGR model at the state of equilibrium operation and on short-term accident progression. The fuel compositions for the PB-HTGR were determined using a jump-in equilibrium modeling method, the Axial Radial Zone Equilibrium Modeling (AR-ZEM) method. In contrast to previous work, the AR-ZEM method was used considering thermal-hydraulic feedback from the MELCOR code to determine temperatures of the fuel pebbles and the surrounding graphite reflector. The consideration of an axial and radial temperature profile in the core and reflector, as opposed to uniform material temperatures, had an impact of almost 1,300 pcm on the equilibrium core eigenvalue and caused significant differences in the discharged plutonium fuel inventory with up to 4.9% and 11.0% for Pu-239 and Pu-242, respectively. To assess the impact on short-term accident progression, two Anticipated Transient Without SCRAM (ATWS) events, a Pressurized Loss of Forced Coolant (PLOFC) and a Control Rod Withdrawal (CRW) with loss of flow, were simulated with MELCOR. The use of temperature profiles in the equilibrium core models did not reveal a significant impact on the temperature, power, or reactivity responses during the transients. In conclusion, a need for consideration of accurate temperature profiles, in particular for the graphite reflector, was found for the generation of equilibrium PB-HTGRs core models using jump-in methods, but detailed temperature profiles may not be necessary when performing conservative transient analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Graphite waste classification and disposal cost estimation for high temperature gas and salt reactors

As high-temperature reactor designs progress to demonstration, managing the radioactive wastes from these systems presents unique challenges. This work explores the irradiated graphite source term produced by three reactor designs: The Modular High Temperature Gas reactor (MHTGR), a pebble-bed High Temperature Gas Reactor (pb-HTGR), and a Fluoride-cooled High-temperature Reactor (FHR). We predicted a C-14 concentration of 4.3 Ci/m 3 for the MHTGR, 1.2 Ci/m 3 for the pebble bed HTGR, and 2.5 Ci/m 3 for the gFHR after 20 years of operation. The final C-14 concentration highly depended on the graphite nitrogen impurity, a major precursor for C-14. The C-14 concentration in all reactor types exceeded the 0.8 Ci/m3 threshold, resulting in a Class C waste classification. The costs associated with accepting the graphite after 20 years in a low-level waste disposal facility were projected to be 255 dollars per kWe for the MHTGR, 248 dollars per kWe for the pb-HTGR, and 56.8 dollars per kWe for the FHR.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling↗
DOE OSTI2022

Modeling of a Generic Pebble Bed High-temperature Gas-cooled Reactor (PB-HTGR) with SAM

This report presents the modeling of the core of a generic pebble-bed reactor (PBR) at the system level using the System Analysis Module (SAM) code. This work is an extension of a previous work by the authors (Ooi et al. (2021)) that used the so-called 2-D ring model approach to model the PBMR-400. With the new approach, the pebble bed of the reactor is modeled with multiple PBCoreChannel components with spherical heat structures which allows the code to calculate thermal fluid parameters with built-in closure relations. The new core-channel approach is an improvement to the 2-D ring model approach as it does not introduce geometric distortions to the model and thus reduces the uncertainties of the predictions. In addition to thermal fluid simulations, point kinetics (PKE) are included to the model. Simulations are performed under a steady-state normal operation condition and a load-following transient scenario. This particular transient scenario is chosen as it tests both the thermal fluid and neutronics aspects of the model. The predicted results from both the steady-state and transient scenarios are compared with the results by Stew- art et al. (2021) who performed similar simulations with a Griffin-Pronghorn coupled tool. Despite the differences between the codes, with SAM being a system-analysis code and Pronghorn being a porous-medium code, both sets of results compare favorably. The over- all profiles and trends of the predicted temperatures and reactivities from the SAM and Griffin/Pronghorn simulations are similar, with some differences in their predicted values. The first part of the report covers the significance of a relatively fast-running approach that is capable of modeling the pebble bed reactor at the system-level while simultaneously capturing the radial thermal behavior of the core. Then, the modeling approach used in this work is discussed in details. Lastly, the results and comparisons with the Griffin/Pronghorn simulation are presented.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Development of a Data Platform for High-Temperature Gas-cooled Reactor (HTGR) Nuclear Energy University Program (NEUP) Thermal-Fluid Experiments

Since the U.S. Department of Energy (DOE)’s Office of Nuclear Energy (NE) initiated the Nuclear Energy University Program (NEUP) in 2009, a total of 30 NEUP projects focused on High-Temperature Gas-cooled Reactor (HTGR) thermal-fluid experiments were funded up to fiscal year (FY) 2021. This represents a total DOE investment of approximately $23M over the 12-year period, covering thermal fluid phenomena important to both pebble bed and prismatic HTGR designs. The NEUP projects have produced a large amount of high-quality experimental and computational data that were published in final project reports, journal articles, dissertations, and conference proceedings, but in most cases the actual data sets and supporting information such as facility and instrumentation descriptions were not publicly disseminated to the HTGR community. To the authors’ best knowledge, a data platform that organizes and summarizes these NEUP-funded projects for HTGR research does not currently exist. To improve access to this HTGR validation data and optimize the return on the significant investment made by DOE, the Advanced Reactor Technologies (ART) Gas-Cooled Reactor (GCR) program started a survey of completed and ongoing HTGR NEUP projects with the aim of developing a public-access data platform that can be used to retrieve computational fluid dynamics (CFD) and system code validation data and guide future NEUP investments. This paper summarizes the status of the current ART-GCR database, provides an overview of the NEUP-funded HTGR-related research projects from FY2009 to FY2021 and identify validation knowledge gaps still existing in HTGR thermal-fluid research.

42 ENGINEERING↗
DOE OSTI2022

A framework to implement human reliability analysis during early design stages of advanced reactors

Nuclear power plants require human actions throughout their lifecycle from design, construction, operation, and decommissioning. However, for advanced reactors (e.g., Generation IV), the reliance on human intervention in safety-related actions is expected to be reduced or completely replaced by automated actions. The Probabilistic Risk Assessment (PRA) Standard for Advanced Non-LWR Nuclear Power Plants requires that the impacts of all operator actions are captured and incorporated in the risk of the modeled plant. Moreover, the Modernization of Technical Requirements for Licensing Advanced Reactors requires human reliability analysis (HRA) to be included throughout all design and PRA development stages. However, due to the lack of details during the early design stages, HRA is often postponed until the design is mature enough. Conducting HRA in later design stages, though it may be adequate in capturing pre-, at-, and post-initiators comes short of informing the design itself in the iterative design lifecycle. Hence, this paper presents a framework to include HRA during the design's early stages, pre-conceptual or conceptual. The proposed framework provides a process for the removal of operator actions that do not contribute to the risk and the identification of all key operator actions that are critical to the safety of the design. The results of this framework are then used to inform the design of those safety-related operator actions to update the design further. Then, using information from the updated design, this framework can be reapplied to investigate the impact of the design update on human reliability. The PRA model of the X-energy's pre-conceptual Xe-100 high-temperature gas-cooled pebble-bed reactor (HTGR-PB) design is used to demonstrate the approach. In the pre-conceptual Xe-100 PRA model, also called Phase 0 PRA model, human actions were considered an integral part of analyzing the plant response to different initiating events. Hence, in this paper, all possible human actions in the Xe-100 PRA model are identified, analyzed, and removed to emulate a design relying only on the available automated control systems. The preliminary results of this assessment show how safe the Xe-100 design is even without crediting any human actions. The results also list necessary sequences in which operator actions are critical to the risk profile of the design.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

PSA 2025 Presentation: "Modeling and Sensitivity Analysis of a Generation IV Pebble Bed Reactor Using MELCOR 2.2"

Accompanying the advancement of reactor technologies is the need for computational modeling and simulation to predict their behavior under normal operating conditions and accident scenarios. New Generation IV reactor designs which employ non-conventional fuel have a particular need for modeling the behavior and release of radionuclides and other material from the fuel. In this work, MELCOR version 2.2, a system-level safety and accident scenario code developed by Sandia National Laboratories, was used to model a 200-MWth pebble bed modular reactor and calculate the inventories of circulating and deposited graphite, metal dust, and elemental components released from the fuel elements. A base case modeling the reactor under standard operating conditions was calculated using MELCOR and the inventories were extrapolated to 30 years of operation time using a logarithmic regression fit. A sensitivity analysis was also performed in which several key parameters for the base case model were modified to explore the effect of these changes on the inventories calculated by MELCOR. A set of transient scenario simulations for a depressurized loss of forced cooling (DLOFC) accident were also performed. The results of the sensitivity analysis and transient simulations are reported and discussed in relation to the modeling techniques used for this study.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

HTGR Simulation Methods & International Collaborations

ART-GCR “Methods” activity is split between Experimental Validation data from the ANL NSTF and OSU HTTF (next three presentations). HTGR core simulation (this presentation). International collaboration within OECD Generation-IV (Gen-IV) and USA/Japan bi-lateral agreements (this presentation) HTGR Simulation Methods No new NE-52 funding for HTGR Methods support in FY20; ~$200K FY19 carry-over funds only. Consists of international code-to-code benchmarks (IAEA CRP on HTGR UAM and OECD/NEA MHTGR-350) and refinement of a few-group Pebble Bed Reactor (PBR) cross section (XS) generation methodology. Funding will be requested in FY21 to produce the final reports for the two benchmarks and continue the development of the PBR XS generation methodology. Additional (non-ART) HTGR-related support work at INL NEAMS: HTR-Application work package at INL Create a benchmark for the pebble shuffling and depletion algorithms being developed for NEAMS Griffin code. iFOA award with X-Energy: Develop independent Monte Carlo model of Xe-100 design. Independent design confirmatory analysis of Xe-100 design using NEAMS tools Griffin and Pronghorn. Support X-Energy design team to use their own legacy design tools (VSOP99 and MGT). Support NEAMS Griffin and Pronghorn development team for the iFOA needs (received $50K additional funding for required development).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

High-Temperature Gas-Cooled Pebble-Bed Reactors Running In And Transient Modeling Capabilities Demonstration

This study presents a comprehensive benchmarking and verification effort of several thermal-hydraulic and multiphysics capabilities for high-temperature gas-cooled reactor (HTGR) applications. The first part of this effort focuses on the running-in verification of Griffin's multiphysics capabilities, specifically for simulating the evolution of Pebble Bed reactor cores from startup to equilibrium. In the absence of validation data, code-to-code comparisons are conducted with Kugelpy, showing good agreement for key quantities like maximum power density and fresh core k-eigenvalue predictions. However, discrepancies in equilibrium core predictions suggest potential issues with cross sections, underscoring the need for further refinement and evaluation. The HTTF system analysis code benchmark involves RELAP5-3D, SAM, and GAMMA+ to assess their predictive capabilities for HTTF behavior under both normal operation and pressurized conduction cooldown (PCC) transient conditions. While there is good agreement in predicting major parameters such as coolant temperature, solid temperature, and flow distribution, discrepancies in transient behavior highlight differences in modeling approaches, nodalizations, and heat transfer models. The HTTF lower plenum CFD benchmark employs nekRS to simulate flow mixing phenomena, successfully capturing relevant flow physics and demonstrating mesh independence in complex geometries. Preliminary results suggest a relatively uniform temperature field but significant unsteadiness in the flow, requiring time-averaging analyses. The GPBR200 system analysis code benchmark uses SAM's core channel and porous media models, incorporating an RCCS loop for decay heat removal. During steady-state and transient conditions, including protected de-pressurized and pressurized loss of forced cooling (DLOFC and PLOFC), both models show good agreement in predicting temperature profiles and key parameters. Notably, while the core channel model underpredicts convective heat transfer effects, both models maintain temperatures well below the TRISO fuel safety limit. These benchmarking efforts collectively enhance the predictive capabilities of the tools used in HTGR design and safety analysis, guiding developments to improve their accuracy and applicability.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Reduced Order Models Generation for HTGRs Pebble Shuffling Procedure Optimization Studies

This report provides an initial study for producing reduced-order models (ROMs) of pebble-bed high temperature gas reactor (HTGR) models for the purposes of design optimization. As an initial study, this work is meant to be exploratory---identifying useful workflows and methods for ROM generation---and not meant to be a catch-all analysis of HTGR ROM generation and usage for optimization. This report summarizes three tasks performed in Fiscal Year 2022: 1) the creation of HTGR model, 2) the sensitivity analysis of model design parameters, and 3) an introduction to ROM generation techniques. The representative HTGR model created in this work is a multiphysics equilibrium-core using the BlueCRAB (comprehensive reactor analysis bundle) reactor analysis application, coupling four physical phenomena: neutronics, streamline depletion, porous flow thermal hydraulics, and pebble heat conduction. Part of the model creation was identifying some design parameters and quantities of interest that are relevant in an optimization analysis and adjustable in the model. The sensitivity analysis utilized a polynomial chaos expansion methodology to compute global sensitivity metrics. This analysis showed that thermal hydraulics parameters and quantities of interest had a relatively small impact on simulation results. Finally, the ROM generation work involved exploring three different ROM methodologies: polynomial regression, a Gaussian process, and artificial neural networks. Using a cross-validation technique to characterize ROM performance, the Gaussian process and single-layer artificial neural networks showed the most promising results. Overall, this study was insightful and the lessons learned will be invaluable for the eventual development of an HTGR design optimization workflow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Status Report on FY2022 Model Development within the Integrated Energy Systems HYBRID Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of a pebble bed high temperature gas reactor (HTGR), liquid air energy storage (LAES), and compressed air energy storage (CAES) in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to flexibly operate in ways consistent with IES operation expectations. When these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗