Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Pebble”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

High Fidelity CFD Simulations Supporting the KP-FHR

Kairos Power, LLC, is developing its version of the Fluoride-cooled High-temperature Reactor, the KP-FHR. The design uses a pebble bed core with fluoride salt as a coolant. The pebbles used in the KP-FHR have a diameter of 4 cm, with a shell fuel region where TRISO particles are embedded. A Pebble bed core design is adopted by several Gen IV reactors, They boast many benefits, such as fuel integrity, highly efficient heat transfer, and passive safety. However, it is challenging to accurately predict temperature and flow inside a pebble bed. Traditional approaches use the porous media model, which regards the pebble bed as a continuous medium, but with different temperature fields representing different levels, such as the fluid temperature, pebble surface temperature, and pebble center temperature. Empirical heat transfer correlations are adopted to calculate the heat transfer coefficient between different phases. However, empirical correlations are usually validated with experimental data, which usually lacks detail inside the pebble bed. The available experimental data is also generally at a high Reynolds number, which falls outside of the conditions of KP-FHR. Explicit computational fluid dynamics (CFD) simulations of randomly packed pebble beds have only become feasible recently. This is thanks to the rapid development of computational power and scalable algorithms. In this work, we used the Spectral Element Method (SEM) CFD code NekRS to simulate the randomly packed pebble bed in a cylindrical container. NekRS, which is the GPU variant of Nek5000, but refactored to utilize the computational power of GPUs using the OCCA library to run on hybrid architecture high performance computing systems. It was initially developed with the libParamunal library, but truncated and tuned for large-scale turbulence simulation. As a result, the SEM reaches higher precision with the same degrees of freedom by using a high-order Lagrange polynomial basis distributed on Gauss-Lobatto-Legendre quadrature inside each element, compared to lower-order methods, such the Finite Volume Method and Finite Element Method. The report is divided into five parts. We start with a general discussion of the pebble bed reactor, along with a specific investigation into the KP-FHR. The second part presents the numerical methodology. In the third part, we study a modular pebble bed with 1741 pebbles in a container of 7 pebble-diameter radius. Beyond LES simulations done by NekRS, we also leveraged the thermal radiation model in OpenFOAM to study heat transfer under no-forced-flow scenarios. Then, in the fourth part we simulated a pebble bed similar to the size of the Hermes Test Reactor. The total number of pebbles is in these simulations is 34,374. The container radius is 14 pebble-diameters. Finally, the report concludes in part five, with a discussion of future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1999

Diagnostic Clast-Texture Criteria for Recognition of Impact Deposits

It is difficult to find definitive evidence for impact in the geological record because there are many endogenous geological processes that can produce diamictites similar to those generated by impact ejecta. The classic impact criteria of shock fabrics in certain minerals, and iridium layers, for example, may be either difficult to find, or long-since erased from the impact site (shock fabrics also anneal with time). It is important to be able to recognize impact-generated materials in order to understand earth's crustal development and biological evolution. In future exploration of Mars and other solar-system bodies, recognition of impact materials will be important for elucidating planetary evolution, planetary volatile inventories, and exobiological issues. The cobble depicted is typical of many that have been found in diamictite deposits in Belize generated by the Chicxulub K-T impact event. The pebbles are roughly-hewn in general shape with smoothed corners and edges. Surfaces are almost uniformly frosted (on both protuberances and hollows), but some asperities are glazed. Optical microscopy and thin-section petrographic microscopy reveal the frosting to be only a few microns thick, with a well-defined granular structure; grains are the same size as those composing the bulk of the limestone, but their clearer appearance may represent annealing. One or two adjacent pebble faces are often decorated with striated gouges and closely-spaced hemispherical depressions representing indentation hollows produced by well-rounded impacting clasts of up to 0.5 cm in diameter. Some of the impactors are still embedded in the cobble surface. Non-destructive x-ray diffraction techniques showed the impactors to be of the same mineralogy as the target cobble. We believe this unusual glazing and frosting to be related to the impact event, but this must be reconciled with its survival for over 60 my. since it is composed of one of the most alterable substances, CaCO3. We focus, however, on the non-fractured rounded pebbles that appear to have impacted the larger cobble as a swarm of clasts, probably encountered during ballistic flight. It cannot be defined whether the cobble swept through the pebble cloud, or the pebbles rained upon a slowermoving cobble. Two interesting questions arise: (1) Where did large numbers of such well rounded pebbles come from in the ejecta curtain?, and (2) How did they embed themselves in a nominally brittle rock without suffering damage? Are the well-rounded pebbles crystalline (devitrified) melt spherules? Further investigations are in progress. If the cobble was cold and brittle, impact of well-rounded pebbles would have produced Hertzian fracture patterns (a) in the virtually elastically isotropic cobble target. For penetration depths of about 0.5 of the impactor diameter, the pebbles would require a relative impact velocity sufficient to cause pebble fragmentation and crushing, and the development of a complex Hertzian-Boussinesq fracture field (b) involving deep fracturing and lateral surface spalling (impact velocities > 50 m/s). The existing relationship could only evolve by the impact of cold, hard pebbles into a soft, plastic cobble surface (c). For limestone to have been plastic, it must have been at elevated temperature, but to prevent calcification of the material, the ambient pressure must also have been elevated. This would be possible either in the impact's gas plume, or within the confines of a thin aerodynamically-produced shock bow generated by supersonic ballistic motion of the cobble. In the latter case, it is implied that the cobble swept through the pebbles rather than vice-versa. Although there are high T-P conditions associated with volcanism, such textures have not been reported on volcaniclastic materials, nor from other high T-P environments; e.g., metamorphic (as far as the authors are aware). We propose that this very easily recognizable embedding and indentation surface texture can be used as a diagnostic criterion for the recognition of impact ejecta. The term "peening texture" is suggested, because it is absolutely analogous to the plastic-deformation induced, metal-surface textures generated by ball-bearing bombardment used in engineering metallurgy to work-harden metal surfaces. Additional information is contained in the original (Figures).

Marshall, J. R.↗
DOE OSTI2024

Renewable low-Z wall for fusion reactors with built-in tritium recovery (Final Technical Report)

This project pursued development of a novel renewable plasma-facing wall technology for fusion reactors. The technology is based on a slurry which can be easily delivered by delivery tubes to the reactor wall. The slurry dries at the hot reactor wall into pebble rods which are extruded out into the hot plasma, where the pebbles break off and fall along the reactor wall and can be recovered by gravity and re-used. The falling pebbles carry away heat and tritium and also protect the wall against large scale erosion or redeposition of material. The research focused on carbon-based pebble rods and demonstrated that pebble rods could be produced from slurry with tolerable levels of outgassing on a reactor-relevant timescale (< 5 minutes). Steady-state handling of reactor relevant (up to 50 MW/m 2 ) normal-incidence heat loads was demonstrated. Pebble release velocities were found to be sufficiently small (< 1 m/s) to allow recovery below the vacuum chamber. Tunability of the pebble rod breaking rate was demonstrated by changing the fill fraction of the interpebble matrix which binds the pebbles together. This work could benefit the public by helping move forward the design of commercially viable fusion energy reactors. Designing a first wall for magnetic fusion reactors which can handle the huge heat loads present and also avoid buildup of tritium-containing deposits is extremely challenging and requires novel approaches like the one being investigated here.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Initial study on cross-section generation requirements for a PBR equilibrium core

A Serpent model of the equilibrium core HTR-PM small modular nuclear reactor in China, was developed for use in cross-section preparation studies in order to guide methods development for the Griffin reactor multiphysics application. The model includes detailed isotopics for 10 distinct pebble burnup groups in 126 core zones with unique fuel and moderator temperatures obtained from a coupled neutronics-thermal-fluids equilibrium core calculation using Griffin-Pronghorn. A sensitivity study of the fuel and moderator temperatures for various core regions was performed with the MOOSE stochastic tools. The results show that the uncertainties are, not unexpectedly, dominated by the value of the fluid temperature and that the power level, heat transfer coefficient and effective conduction to neighboring pebbles and fluid constitute, at best, second order effects. The temperature uncertainty range varies from 28 K to 57 K between the core entry and exit planes, respectively, but these values are probably higher. We still have to quantify the significance of these uncertainties in the preparation of cross-sections in future work. In addition, we verified that the effective pebble approximation used in the PEBBED and V.S.O.P. computer codes works well for the preparation of region averaged cross-sections. Nevertheless, there are some discrepancies in the cross-sections when compared to the multi-pebble model, which could affect the prediction of peak values and the depletion calculation. We conclude that is highly desirable for future studies with Griffin to be able to handle both the 'effective' pebble approximation and the multi-pebble approach for various pebble burnup groups. This enables Griffin users with the flexibility to perform higher-fidelity studies. Finally, we initiated the preparation of cross-sections for various core regions from the full core Serpent reference model. We quantified the differences in 26 group cross-sections from infinite domain models versus the full core approach. These reference cross-sections will serve to verify the double heterogeneity, self-shielding, and spectrum-correction methods in Griffin. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Pronghorn: A Porous Media Thermal-Hydraulics Core Simulator and its Validation with the SANA Experiments

Pebble bed High Temperature Reactors (HTRs) are characterized by many advantageous design features, such as excellent passive heat removal in accidents, large margins to fuel failure, and online refueling potential. However, a significant challenge in the core modeling of pebble bed reactors is the complex fuel-coolant structure. This paper presents a new porous media simulation code, Pronghorn, that aims to alleviate modeling challenges for pebble bed reactors by providing a fast-running, medium- fidelity core simulator. Pronghorn is intended to accelerate the design and analysis cycle for pebble bed and prismatic HTRs by permitting fast scoping studies and providing boundary conditions for systems-level analysis. Pronghorn is built on the Multiphysics Object-Oriented Simulation Environment (MOOSE) using modern software practices and a thorough testing framework. This paper describes the physical models used in Pronghorn and demonstrates Pronghorn’s capability for modeling gas-cooled pebble bed HTRs by presenting simulation results obtained for the German SANA pebble bed decay heat experiments. Within the limitations of the porous media approximation and existing available closure relationships, Pronghorn predicts the SANA experimental pebble temperatures well, expanding the code’s validation base. A brief code-to-code comparison shows a similar level of accuracy with other porous media simulation tools; this enhances Pronghorn’s advantages of an arbitrary equation of state, unstructured mesh capabilities, compressible flow models, high coupling potential to MOOSE fuels performance and systems-level thermal-hydraulics codes, and modern software design.

42 ENGINEERING↗
DOE OSTI2022

Initial study on cross section generation requirements for a PBR equilibrium core

A Serpent model of the HTR-PM equilibrium core was developed for use in cross section prepa-ration studies in order to guide methods development for the Griffin reactor multiphysics applica-tion. The model includes detailed isotopics for 10 distinct pebble burnup groups in 126 core zoneswith unique fuel and moderator temperatures obtained from a coupled neutronics-thermal-fluidsequilibrium core calculation using Griffin-Pronghorn. A sensitivity study of the fuel and mod-erator temperatures for various core regions was performed with the MOOSE stochastic tools.The results show that the uncertainties are, not unexpectedly, dominated by the value of the fluidtemperature and that the power level, heat transfer coefficient and effective conduction to neigh-boring pebbles and fluid constitute, at best, second order effects. The temperature uncertaintyrange varies from 28 K to 57 K at the core entry and exit planes, respectively, but these val-ues are probably higher. We still have to quantify the significance of these uncertainties in thepreparation of cross sections, which will be postponed for future work. In addition, we verifythat the single effective pebble approach works well for the preparation of region averaged crosssections in the infinite domain approximation. Nevertheless, there are significant discrepanciesin the cross sections when compared to the multi-pebble model. This could affect the predictionof peak values and in the depletion calculation. We conclude that is highly desirable for futurestudies with Griffin to be able to handle both the ?effective? pebble approximation and the multi-pebble approach for the various pebble burnup groups. This enables Griffin users the flexibilityto perform higher-fidelity studies. Finally, we initiate the preparation of cross sections for variouscore regions from the full core Serpent reference model. We quantify the differences in 26 groupcross sections from infinite domain models. These reference cross sections will serve to validatethe double heterogeneity, self-shielding, and spectrum-correction methods in Griffin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Evaluation of PBR Spent Fuel Criticality and Dose Rate Compliance for Storage and Transportation

Spent tri-structural isotropic (TRISO)–based fuels have a strong track record in storage and transportation without documented incidents. This work seeks to reduce uncertainty to aid in more informed spent fuel management of TRISO-based fuels by modeling both fresh and spent pebble bed reactor (PBR) fuel and comparing the results to the regulatory standards from 10 CFR 71. SCALE was used for all modeling due to it having fast and accurate methods for handling PBR fuel modeling, as well as having an efficient method for shielding calculations in monaco with automated variance reduction using importance calculations (MAVRIC), which utilizes the consistent adjoint-driven importance sampling (CADIS) and the forward-weighted consistent adjoint-driven importance sampling (FW-CADIS) methods. KENO-VI was used for all criticality calculations, TSUNAMI was used for uncertainty quantification on k-effective, TRITON and the Oak Ridge isotope generation code (ORIGEN) were both used for depletion of the fuel, and MAVRIC was used for shielding calculations. For criticality assessments, this study focused on the requirement that the value of the neutron multiplication factor, k-effective (k-eff), would not exceed a peak value of 0.95, including uncertainty, with 95% confidence. Criticality was initially examined by modeling fresh fuel from three different designs—HTR-10 fuel, PBMR-400 fuel, and demonstration fuel representative of a TRISO-fueled modern high-temperature gas reactor (HTGR) design, henceforth referred to as Demo HTGR—and placing them into various sized containers with conditions described in 10 CFR 71 to quantify the peak k-eff state. When the peak value of 0.95 k-eff was exceeded, mitigation methods were examined in those scenarios. Burnup credit, pebble displacement in areas of strong neutron multiplication, and random pebble replacement using pebbles of various compositions and replacement fractions were examined. In summary, the criticality of PBR fuels can be well accounted for by restricting container size, taking credit for burnup, or by displacing/replacing pebbles. Uncertainty of the k-eff due to nuclear data uncertainties was recorded at ~0.6644%Δk/k, or roughly 664% mil (pcm). The nuclear data–induced uncertainty was relatively small and should not require significant modification in the design to be accounted for. Revisions to the evaluated nuclear data file values have been shown to have a larger impact than nuclear data–induced uncertainty. For dose rate aspects, U.S. Nuclear Regulatory Commission regulations require a maximum dose rate of 10 millirem per hour (mrem/h) at 2 meters. In examining the dose rate behavior of spent PBR fuel, the representative Demo HTGR fuel was modeled exclusively due to it possessing the highest target burnup of the examined fuels. Equilibrium cycle modeling methods were used to produce a higher-fidelity discharge isotopic composition than simple assumptions, such as reflected pebbles. The discharge composition was used as a source term in the fixed-source transport shielding calculations, and dose rates were calculated at 2 m for the shortest possible cooling time. The low concentration of fuel material led to dose rates that were in line with regulatory limits, despite the high burnup when compared to traditional light water reactor fuels. In conclusion, the methods employed in this study would require more work to further verify and validate and are limited to the criticality and dose rate analyses performed.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Verification of Triso Fuel Burnup Using Machine Learning Algorithms

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134 Cs, 137 Cs, 154 Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

VERIFICATION OF TRISO FUEL BURNUP USING MACHINE LEARNING ALGORITHMS

Pebble Bed Reactors are fueled with fuel pebbles that are circulated multiple times through the reactor vessel before discharge. During the normal operation of a PBR, ejected pebbles are returned to the reactor or discharged depending on the fuel burnup and physical condition of the pebbles. The burnup measurement is usually based on detected radiation signatures of fission products accumulated in the pebble fuel over burnup. Previous research has shown that height of photopeaks of fission products, such as 134Cs, 137Cs, 154Eu, etc., can be used independently or in combination to infer or predict the level of burnup in the fuel. However, it remains challenging to measure such complex sources due to self-shielding effects, strong radiation background and intervening materials. Another operational challenge is the required high throughput of burnup measurement, which necessitates limited measurement time and thus impacts quality of measured gamma-ray spectra. Hence, advanced spectral analysis methods are needed to analyze the noisy gamma spectra and predict the burnup values. We propose to use machine learning (ML) method to interpret gamma-ray spectra and predict the burnup values of the pebbles. ML has achieved widespread success and adoption across a few domains that require pattern recognition and analysis in varied data types. In this work, we apply three proven ML approaches - multilayer perceptrons, convolutional neural networks, and transformers - to the task of predicting fuel burnup from measured gamma spectra, and compile a dataset of simulated spectra for training and validation of the ML models. In this paper, we will discuss the network architecture of these three ML approaches and compare the performance of the simplest of these (MLP) to a standard linear regression.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2025

Comprehensive defect evaluation of advanced nuclear fuels using high-resolution acoustic signals and optimized sensor separation

Graphite pebble composite structures based on TRistructural-ISOtropic (TRISO) particles are being developed as core nuclear fuels in advanced power reactors, promising safe operation at increased temperatures. Ensuring the structural integrity of these nuclear fuels requires comprehensive and accurate non-destructive evaluation (NDE) techniques to characterize defects and damage in the pebbles. However, traditional acoustic evaluation methods face limitations in defect characterization due to the highly attenuative, and geometrically and compositionally complex nature of these structures. This study proposes an improved acoustic NDE technique for accurate detection and classification of anticipated relevant defects and damage in graphite pebbles using high-resolution acoustic signals and optimized transmit-receive sensor networks. The proposed approach utilizes a triangular three-sensor network as the base unit, comprising three transmit-receive sensors. The sensor separation distance, as well as acoustic excitation center frequency, pulse-width, and bandwidth are optimized to enhance spatial resolution and improve signal-to-noise ratio, enabling effective characterization of the smallest size and widest range of defects in pebbles. Furthermore, the use of the triangular sensor configuration instead of a more conventional transmit-receive sensor pair expands the inspection region from a one-dimensional linear path to a two-dimensional area, increasing spatial coverage. To mitigate challenges associated with processing of complex acoustic signals arising from high-frequency, high-bandwidth excitation in these structures, a machine-learning-based signal processing algorithm is integrated with the sensor network. In the machine-learning-based algorithm, multi-domain features are extracted from the acoustic signals to capture intricate signal characteristics, significantly improving defect identification and classification compared to traditional approaches. The proposed acoustic NDE technique offers considerable promise for practical and reliable defect/damage diagnostics of advanced nuclear pebble fuels.

42 ENGINEERING↗
DOE OSTI2024

SLICE

For most of their lifetime, pebble-bed reactors (PBRs) operate at an equilibrium state in which the core is filled with fuel pebbles at various levels of burnup. A fuel pebble travels multiple times in so-called passes through the reactor before it reaches its target discharge burnup and is replaced with a fresh fuel pebble. Given the stochastic nature of the fuel pebble travel paths and consequently the individual fuel pebble histories, it is not possible with standard methods developed for traditional reactor concepts to calculate the fuel inventory in the reactor core. An iterative approach, the SCALE Leap-In method for Cores at Equilibrium (SLICE), was developed to generate region-average fuel inventory for a PBR. The SLICE code enables automatic generation of input files for the SCALE code system (https://www.ornl.gov/scale), management of the SCALE result files, and analysis of results.

Bostelmann, Friederike [Oak Ridge National Laborat↗