Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Kernel”

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 739 records · Page 41

ECP Report: Update on Proxy Applications and Vendor Interactions

The ExaLearn miniGAN team (Ellis and Rajamanickam) have released miniGAN, a generative adversarial network(GAN) proxy application, through the ECP proxy application suite. miniGAN is the first machine learning proxy application in the suite (note: the ECP CANDLE project did previously release some benchmarks) and models the performance for training generator and discriminator networks. The GAN's generator and discriminator generate plausible 2D/3D maps and identify fake maps, respectively. miniGAN aims to be a proxy application for related applications in cosmology (CosmoFlow, ExaGAN) and wind energy (ExaWind). miniGAN has been developed so that optimized mathematical kernels (e.g., kernels provided by Kokkos Kernels) can be plugged into to the proxy application to explore potential performance improvements. miniGAN has been released as open source software and is available through the ECP proxy application website (https://proxyapps.exascaleproject.ordecp-proxy-appssuite/) and on GitHub (https://github.com/SandiaMLMiniApps/miniGAN). As part of this release, a generator is provided to generate a data set (series of images) that are inputs to the proxy application.

97 MATHEMATICS AND COMPUTING↗

Destructive PIE and Safety Testing of Six AGR-2 UO 2 Capsule 3 Compacts

The Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s second irradiation experiment (AGR-2) was irradiated in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) from June 2010 to October 2013 (Collin 2014). The fuel compacts in this experiment held either tristructural isotropic (TRISO)-coated spherical kernels of uranium oxide (UO2) or TRISO-coated kernels containing both uranium carbide and uranium oxide phases (UCO). There were six separately monitored and controlled capsules in the AGR-2 test train. Capsule 3 held twelve compacts containing UO2-TRISO particles fabricated by BWX Technologies Nuclear Operations Group. The AGR-2 TRISO particles were fabricated in a pilot-scale fluidized-bed chemical vapor deposition (FB-CVD) furnace with a coating chamber inner diameter of 150 mm (Phillips, Barnes, and Hunn 2010), which was a change from the first irradiation experiment (AGR-1) particles that had been coated in a lab-scale FB-CVD coating system with a chamber inner diameter of 50 mm (Lowden 2006). The TRISO particles were overcoated with resinated graphite flake at Oak Ridge National Laboratory (ORNL), and the overcoated particles were pressed into one-inch-long, half-inch-diameter cylinders (Hunn, Montgomery, and Pappano 2010). Each cylindrical compact held an average of 1,543 TRISO particles with 9.6% enriched UO2 kernels that had a nominal diameter of 500 μm (Hunn, Savage, and Silva 2012). Capsule 3 compacts were irradiated to average calculated burnups of 9.01–10.69% fissions per initial metal atom (FIMA), and the average calculated fluences of fast neutrons with energies E n > 0.18 MeV were 3.05–3.53×10 25 n/m 2 (Sterbentz 2014). The calculated time-average, volume-average Capsule 3 compact temperatures were 996–1,062°C. However, Capsule 3 compact temperatures varied several hundred degrees across each compact, and the timeaverage minimum (TA min ) and time-average maximum (TA max ) temperatures were between 889–999°C and 1,072–1,105°C, respectively (Hawkes 2014). After irradiation, the AGR-2 test train was transferred from ATR to the INL Materials and Fuels Complex for inspection and disassembly (Ploger, Demkowicz, and Harp 2015). The initial inspection included dimensional metrology of the compacts and graphite fuel holders. Like all the AGR-2 compacts, the compacts in Capsule 3 shrank slightly during irradiation, as expected, with an average length reduction of 1.07–1.24% and an average diameter reduction of 0.13–0.41%. Post-irradiation examination (PIE) of the capsule components was completed to measure select fission products ( 90 Sr, 110m Ag, 134 Cs, 137 Cs, 144 Ce, and 154 Eu) outside the compacts (Stempien and Demkowicz 2020). This involved gamma counting of the graphite and graphoil spacers at the top and bottom of each capsule, acid leaching for radiochemical analysis of fission products on the metallic capsule components, and burn-leach analysis of the graphite holders. The total amount of 110mAg measured on the Capsule 3 components was 13% of the calculated capsule inventory. This was significantly lower than the amount of 110m Ag measured on the three UCO capsule components, which ranged from 32–70%. The lower 110m Ag release in Capsule 3 was likely due to lower peak temperatures compared with the UCO fuel capsules (Hawkes 2014). Measured inventories of the other select fission products were also lower in Capsule 3.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Performance Assessment of AFQMC Implementation (ECP Milestone 5.2 Report)

The auxiliary field quantum Monte Carlo algorithm in QMCPACK was ported to run on AMD GPUs using HIP. Initial performance measurements on early access hardware indicate a 4x slowdown compared to NVIDIA V100s. The slowdown was determined to be a result of suboptimal ROCM libraries for small matrix sizes coupled with some poorly performing hipified CUDA kernels. Through a preliminary analysis of HIP kernel performance we determined a strategy for pro ling and tuning kernels. We request that ROCM libraries are optimized for smaller problem sizes particularly for batched operations.

97 MATHEMATICS AND COMPUTING↗

Selection and Characterization of Surrogate Material for Developing Zr Barrier Coatings for Uranium Nitride Particles

In support of UC 1-x N x fuel kernels (~ 800 micrometer diameter) development work ongoing at Oak Ridge national laboratory (ORNL), where the fuel kernels will be embedded inside a possible zirconium based matrix, Argonne National Laboratory (ANL) is contributing to help develop a robust metal diffusion barrier coating. Zirconium nitride (ZrN) and Zirconium oxide (ZrO2) were selected as possible diffusion barrier candidates, and the atomic layer deposition (ALD) has been chosen as a candidate technology to deposit the film. Development of such a barrier coating with the ALD process entails significant number of trials to study relevant parameters. Therefore, to prevent needless wastage, instead of coating directly over fuel kernels, a surrogate candidate with similar dimensions and physical properties were been selected and coated to develop the diffusion barrier coating.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Quantitative Performance Assessment of Proxy Apps and Parents (Report for ECP Proxy App Project Milestone ADCD-504-28)

The ECP Proxy Application Project has an annual milestone to assess the state of ECP proxy applications and their role in the overall ECP ecosystem. Our FY22 March/April milestone (ADCD- 504-28) proposed to: Assess the fidelity of proxy applications compared to their respective parents in terms of kernel and I/O behavior, and predictability. Similarity techniques will be applied for quantitative comparison of proxy/parent kernel behavior. MACSio evaluation will continue and support for OpenPMD backends will be explored. The execution time predictability of proxy apps with respect to their parents will be explored through a carefully designed scaling study and code comparisons. Note that in this FY, we also have quantitative assessment milestones that are due in September and are, therefore, not included in the description above or in this report. Another report on these deliverables will be generated and submitted upon completion of these milestones. To satisfy this milestone, the following specific tasks were completed: Study the ability of MACSio to represent I/O workloads of adaptive mesh codes. Re-define the performance counter groups for contemporary Intel and IBM platforms to better match specific hardware components and to better align across platforms (make cross-platform comparison more accurate). Perform cosine similarity study based on the new performance counter groups on the Intel and IBM P9 platforms. Perform detailed analysis of performance counter data to accurately average and align the data to maintain phases across all executions and develop methods to reduce the set of collected performance counters used in cosine similarity analysis. Apply a quantitative similarity comparison between proxy and parent CPU kernels. Perform scaling studies to understand the accuracy of predictability of the parent performance using its respective proxy application. This report presents highlights of these efforts.

97 MATHEMATICS AND COMPUTING↗

Using Likwid and Byfl to Benchmark Hardware Performance

This paper outlines a benchmarking study conducted during my internship at LANL, focusing on CPU (Computer Processing Unit) and program performance assessment. The primary goal was to gather memory access data using three methods across five polybench kernels The data gathered would then be used to compare and contrast to one another and calculate operational intensity for performance comparisons. Benchmarking tools like Byfl and Likwid were employed, with Byfl offering hardware-independent data through LLVM compiler communication and Likwid directly interacting with computer hardware. The study considered various benchmarking factors, including optimization levels, Big O notation ((n)), CPU diversity and specific kernel equations. Big O notation was utilized to simplify code complexity, with detailed breakdwons of operations and memory components for each polybench application. Specific O(n) equations enabled nuanced kernel compariosns, facilitating the identification of performance variations. CPU efficiency assessments were conducted using Likwid tests on two CPUs. The central focus on code optimization aimed at achieving higher speeds and reduced memory usage through streamlined code. Future work propsoes creating a roofline model, synthesizing benchmarking data into a comprehensive data graph to assist in optimizing code and improving hardware performance. The potential impact on the laboratory or national mission was underscored, emphasizing the importance of optimizing applications and hardware to conserve resources and accelerate program execution. The specific relevance to LANL’s operations in math-intensive fields such as Nuclear Fission, Space Exploration, and Nanotechnology highlights the necessity of efficient benchmarking for resource conservation and proram speed. Overall, this study contributes to the understanding of CPU and program performance, providing insights for future optimization efforts in a laboratory setting

97 MATHEMATICS AND COMPUTING↗

Concepts for Actinide Recovery from TRISO Used Nuclear Fuel

The work described in this report has developed a preliminary conceptual flowsheet based on limited published literature for the head-end of a TRISO oxycarbide UNF reprocessing plant. The essential function of the head-end is to prepare the UNF for subsequent separation of actinides. The main steps of the conceptual TRISO UNF head-end reprocessing flowsheet are: 1. Fragmentation of the graphite moderator to expose the fuel particles. 2. Separation of fuel particles from fragmented graphite moderator by sieving and fluidization. 3. Fragmentation of the fuel particles to expose the fuel kernel. 4. Dissolution of the fuel kernel in nitric acid. Noteworthy at this step is the formation of organic acids (mainly oxalic and mellitic acids) from the carbon associated with the fuel and TRISO coatings. These acids can interfere with actinide separations and solvent extraction hydraulic performance and carbon dioxide gas generation. 5. Clarification of the dissolved fuel solution to separate the coating fragments. 6. Dissolver off-gas treatment with specific emphasis on managing generation of carbon dioxide gas containing carbon-14. The quantity of carbon dioxide is projected to be 100 to 1000 times greater than that arising from dissolving LWR UNF. Pre or post treatment of the exposed fuel kernels could be undertaken to mitigate the formation of organic acids but there still exists a significant off-gas treatment challenge. The literature on reprocessing uranium nitride UNF was reviewed but a flowsheet was not specifically developed since its scope and uncertainties are expected to be encompassed by the oxycarbide flowsheet. Overall, the predominant feature of processing TRISO UNF is carbon management to reduce waste volume and mitigate the formation of carbon dioxide and organic acids. This report recommends broad areas of research that will help to further define the head-end flowsheet.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Methodology for Determination of Cellulosic Glucans and Hemicellulose Content in a Fuel Ethanol Production Facility (CRADA Final Report)

Develop a single methodology for determination of the total cellulosic glucan, including both cellulose and beta-glucans, along with hemicellulose content in corn kernel fiber which could be utilized by the dry grind corn ethanol production industry to determine the cellulosic converted fraction of the corn kernel fiber. The work will build upon a methodology already described in literature but will specifically focus on a more complete determination of the structural polysaccharides in corn kernel fiber to make it more applicable to the corn ethanol industry.

09 BIOMASS FUELS↗

Modeling the Ex-core Detector Response into a Production Option in MPACT

In the past few years, the Consortium for Advanced Simulation of Light Water Reactors (CASL) has overseen a successful activity to extend the radiation transport capability from the reactor in-core geometry to the ex-core geometry by coupling the deterministic neutronics code MPACT, with the Monte Carlo code Shift. However, transient problems such as RIAs require an efficient prediction of the ex-core detector response to determine the timeframe for a reactor trip. Therefore, in addition to the high-fidelity MPACT-Shift coupled calculation, separate efforts have been made to explore simplified methods for ex-core detector response with MPACT standalone calculation. In a previous milestone L3_RTM.MCH.P17.06, several simplified methods for ex-core detector response were developed in MPACT. In particular, the double kernel method is based on the default MPACT core geometry, so extensive modeling or transport calculation with full reflector and ex-core details are not needed in this method. Since the 1-D diffusion and neutron streaming kernels are used for extended ex-core calculations, the extra computational efforts are very small. The work implemented in the current milestone provides a fully integrated option for MPACT to approximately calculate the ex-core detector response using the double kernel method. To overcome the difficulty of obtaining the consistent diffusion coefficients (these were obtained through separate CMFD calculation and edits), the 1-D diffusion solver is replaced by a 1-D Sn transport solver to compute the neutron flux at the vessel outer surface. The new VERA inputs for ex-core detector are processed in MPACT. The detector signals are linked to the SCRAM logic as an option to trip the core during transient calculation. Two sets of 3-D quarter core problems are run with MPACT standalone and VeraShift to verify the radial and axial effects on detector response by varying the moderator density and control rod position. For the cases with moderator density changes, the detector responses from MPACT are within 2 sigma error of VeraShift. For the cases at different control rod positions, the axial offsets computed from MPACT are within 2% error of VeraShift results.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy scaling advantages of resistive memory crossbar based computation and its application to sparse coding

In this study, the exponential increase in data over the last decade presents a significant challenge to analytics efforts that seek to process and interpret such data for various applications. Neural-inspired computing approaches are being developed in order to leverage the computational properties of the analog, low-power data processing observed in biological systems. Analog resistive memory crossbars can perform a parallel read or a vector-matrix multiplication as well as a parallel write or a rank-1 update with high computational efficiency. For an N × N crossbar, these two kernels can be O(N) more energy efficient than a conventional digital memory-based architecture. If the read operation is noise limited, the energy to read a column can be independent of the crossbar size (O(1)). These two kernels form the basis of many neuromorphic algorithms such as image, text, and speech recognition. For instance, these kernels can be applied to a neural sparse coding algorithm to give an O(N) reduction in energy for the entire algorithm when run with finite precision. Sparse coding is a rich problem with a host of applications including computer vision, object tracking, and more generally unsupervised learning.

97 MATHEMATICS AND COMPUTING↗

Proteomic Analysis of Pecan ( Carya illinoinensis ) Nut Development

Pecan (Carya illinoinensis) nuts are an economically valuable crop native to the United States and Mexico. A proteomic summary from two pecan cultivars at multiple time points was used to compare protein accumulation during pecan kernel development. Patterns of soluble protein accumulation were elucidated using qualitative gel-free and label-free mass-spectrometric proteomic analyses and quantitative (label-free) 2-D gel electrophoresis. Two-dimensional (2-D) gel electrophoresis distinguished a total of 1267 protein spots and shotgun proteomics identified 556 proteins. Rapid overall protein accumulation occurred in mid-September during the transition to the dough stage as the cotyledons enlarge within the kernel. Pecan allergens Car i 1 and Car i 2 were first observed to accumulate during the dough stage in late September. While overall protein accumulation increased, the presence of histones diminished during development. Twelve protein spots accumulated differentially based on 2-D gel analysis in the weeklong interval between the dough stage and the transition into a mature kernel, while eleven protein spots were differentially accumulated between the two cultivars. These results provide a foundation for more focused proteomic analyses of pecans that may be used in the future to identify proteins that are important for desirable traits, such as reduced allergen content, improved polyphenol or lipid content, increased tolerance to salinity, biotic stress, seed hardiness, and seed viability.

2D-gel↗

Exploring the Brighter-fatter Effect with the Hyper Suprime-Cam

The brighter-fatter effect has been postulated to arise due to the build up of a transverse electric field, produced as photocharges accumulate in the pixels’ potential wells. We investigate the brighter-fatter effect in the Hyper Suprime-Cam by examining flat fields and moments of stars. We observe deviations from the expected linear relation in the photon transfer curve (PTC), luminosity-dependent correlations between pixels in flat-field images, and a luminosity-dependent point-spread function (PSF) in stellar observations. Under the key assumptions of translation invariance and Maxwell’s equations in the quasi-static limit, we give a first-principles proof that the effect can be parameterized by a translationally invariant scalar kernel. We describe how this kernel can be estimated from flat fields and discuss how this kernel has been used to remove the brighter-fatter distortions in Hyper Suprime-Cam images. We find that our correction restores the expected linear relation in the PTCs and significantly reduces, but does not completely remove, the luminosity dependence of the PSF over a wide range of magnitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

Numerical Investigation of Spark Ignition Events in Lean and Dilute Methane/Air Mixtures using a Detailed Energy Deposition Model

It is beneficial but challenging to operate spark-ignition engines under highly lean and dilute conditions. The unstable ignition behavior can result in downgraded combustion performance in engine cylinders. Numerical approach is serving as a promising tool to identify the ignition requirements by providing insight into the complex physical/chemical phenomena. An effort to simulate the early stage of flame kernel initiation in lean and dilute fuel/air mixture has been made and discussed in this paper. The simulations are set to validate against laboratory results of spark ignition behavior in a constant volume combustion vessel. In order to present a practical as well as comprehensive ignition model, the simulations are performed by taking into consideration the discharge circuit analysis, the detailed reaction mechanism, and local heat transfer between the flame kernel and spark plug. The energy profile and the energy source geometry are investigated in detail to represent the physics of electrical discharge. It was observed in the experiments that a sufficiently high ambient pressure is necessary for a successful ignition event in the lean and dilute mixture when the spark plug gap size and primary energy input are held constant. By adopting realistic energy levels, this detailed energy deposition model showed the capability to reasonably present such ignition behavior transition. The unique combination of energy deposition profile and geometry reveals the complexity of electrical discharge during the spark ignition event. The response of the combustible gas to the energy deposition showed dependency on the volumetric energy density, energy source’s surface area, temperature gradient at the energy source boundary, as well as the heat transfer condition local to the flame kernel.

Zhang, Anqi↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

Macroscopic impacts of cloud and precipitation processes on maritime shallow convection as simulated by a large eddy simulation model with bin microphysics

This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision–coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg -1 . Simulations with collision–coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts model results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.

54 ENVIRONMENTAL SCIENCES↗

Preparation of UC0.07-0.10N0.90-0.93 spheres for TRISO coated fuel particles

The U.S. Department of Energy is considering a new nuclear fuel, which should be much more impervious during a loss of coolant accident. The fuel would consist of tristructural isotropic coated particles with dense uranium nitride (UN) kernels. The objectives of this effort are to make uranium oxide microspheres with adequately dispersed carbon nanoparticles and to convert these microspheres into UN kernels. Recent improvements to internal gelation process were successfully applied to the production of uranium gel spheres with different concentrations of carbon black. After the spheres were washed, a simple, two-step heat profile was used to produce kernels with a chemical composition of UC0.07 0.10N0.90 0.93. The first step involved heating the microspheres to 2023 K in a vacuum, and in the second step, the microspheres were held at 1873 K for 6 hrs in nitrogen.

internal gelation↗

Results from the DOE Advanced Gas Reactor Fuel Development and Qualification Program

Modular HTGR designs were developed to provide natural safety, which prevents core damage under all design basis accidents and presently envisioned severe accidents. The principle that guides their design concepts is to passively maintain core temperatures below fission product release thresholds under all accident scenarios. This level of fuel performance and fission product retention reduces the radioactive source term by many orders of magnitude and allows potential elimination of the need for evacuation and sheltering beyond a small exclusion area. This level, however, is predicated on exceptionally high fuel fabrication quality and performance under normal operation and accident conditions. Germany produced and demonstrated high quality fuel for their pebble bed HTGRs in the 1980s, but no U.S. manufactured fuel had exhibited equivalent performance prior to the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program. The design goal of the modular HTGRs is to allow elimination of an exclusion zone and an emergency planning zone outside the plant boundary fence, typically interpreted as being about 400 meters from the reactor. To achieve this, the reactor design concepts require a level of fuel integrity that is better than that claimed for all prior US manufactured TRISO fuel, by a few orders of magnitude. The improved performance level is about a factor of three better than qualified for German TRISO fuel in the 1980’s. At the start of the AGR program, without a reactor design concept selected, the AGR fuel program selected to qualify fuel to an operating envelope that would bound both pebble bed and prismatic options. This resulted in needing a fuel form that could survive at peak fuel temperatures of 1250°C on a time-averaged basis and high burnups in the range of 150 to 200 GWd/MTHM (metric tons of heavy metal) or 16.4 to 21.8% fissions per initial metal atom (FIMA). Although Germany has demonstrated excellent performance of TRISO-coated UO2 particle fuel up to about 10% FIMA and 1150°C, UO2 fuel is known to have limitations because of CO formation and kernel migration at the high burnups, power densities, temperatures, and temperature gradients that may be encountered in the prismatic modular HTGRs. With uranium oxycarbide (UCO) fuel, the kernel composition is engineered to prevent CO formation and kernel migration, which are key threats to fuel integrity at higher burnups, temperatures, and temperature gradients. Furthermore, the recent poor fuel performance of UO2 TRISO fuel pebbles measured in Chinese irradiation testing in Russia and in German pebbles irradiated at 1250°C, and historic data on poorer fuel performance in safety testing of German pebbles that experienced burnups in excess of 10% FIMA [1] have each raised concern about the use of UO2 TRISO above 10% FIMA and 1150°C and the degree of margin available in the fuel system. This continues to be an active area of study internationally.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Managing a Real-Time Embedded Linux Platform with Buildroot

Developers of real-time embedded software often need to build the operating system, kernel, tools and supporting applications from source to work with the differences in their hardware configuration. The first attempts to introduce Linux-based real-time embedded systems into the Fermilab accelerator controls system used this approach but it was found to be time-consuming, difficult to maintain and difficult to adapt to different hardware configurations. Buildroot is an open source build system with a menu-driven configuration tool (similar to the Linux kernel build system) that automates this process. A customized Buildroot [1] system has been developed for use in the Fermilab accelerator controls system that includes several hardware configuration profiles (including Intel, ARM and PowerPC) and packages for Fermilab support software. A bootable image file is produced containing the Linux kernel, shell and supporting software suite that varies from 3 to 20 megabytes large – ideal for network booting. The result is a platform that is easier to maintain and deploy in diverse hardware configurations

Diamond, J.↗