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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.

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Scalable Risk Assessment of Rare Events in Power Systems With Uncertain Wind Generation and Loads

Risk assessment of rare events has become increasingly important in power system planning and operation with the increasing integration of renewable energy and the presence of system uncertainties. However, quantifying the risk posed by rare events via the traditional method, i.e., Monte Carlo sampling (MCS), incurs substantial computational expense stemming from the vast ensemble of power flow simulations. To accelerate the assessment, this paper proposes a Deep Neural Network (DNN)-kernelized vector-valued Gaussian Process (VVGP) approach with excellent computational efficiency while maintaining high accuracy. Consequently, serving as a surrogate model for the power flow solver, the DNN-kernelized VVGP enables significantly faster but accurate risk assessment compared to the power flow solver. The developed surrogate model evaluates low-order N - k events that contain more than 90% instances by adeptly capturing the topological features while the high-order N - k events are assessed via a power flow solver, thereby striking a balance between computational efficiency and uncertainty quantification accuracy. Moreover, the model incorporates a Support Vector Machine (SVM) classifier to resample concerning low-probability tail events to counteract the biases potentially introduced during the DNN-kernelized VVGP evaluations. Simulations conducted on the modified IEEE 24-bus, 118-bus, and European 1354-bus systems demonstrate that the proposed method maintains the accuracy benchmark set by MCS while significantly reducing computational demands in large-scale power systems as compared to other state-of-the-art methods.

17 WIND ENERGY↗
DOE OSTI2022

Computational Fluid Dynamics Modeling of Low Temperature Ignition Processes From a Nanosecond Pulsed Discharge at Quiescent Conditions

Recent interest in nonequilibrium plasma discharges as sources of ignition for the automotive industry has not yet been accompanied by the availability of dedicated models to perform this task in computational fluid dynamics (CFD) engine simulations. The need for a low-temperature plasma (LTP) ignition model has motivated much work in simulating these discharges from first principles. Most ignition models assume that an equilibrium plasma comprises the bulk of discharge kernels. LTP discharges, however, exhibit highly nonequilibrium behavior. In this work, a method to determine a consistent initialization of LTP discharge kernels for use in engine CFD codes like CONVERGE is proposed. The method utilizes first principles discharge simulations. Such an LTP kernel is introduced in a flammable mixture of air and fuel, and the subsequent plasma expansion and ignition simulation is carried out using a reacting flow solver with detailed chemistry. Finally, the proposed numerical approach is shown to produce results that agree with experimental observations regarding the ignitability of methane-air and ethylene-air mixtures by LTP discharges.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Numerical Investigation of Ammonia/n-Heptane Dual-Fuel Spray Flames Using Large Eddy Simulations

Diesel engines are extensively used in heavy-duty transportation, power generation, and marine vehicles due to their superior thermal efficiency and extended high-load operability compared to spark ignition (SI) engines. However, combustion in diesel engines is generally characterized by locally rich fuel–air mixtures and high combustion temperatures, causing significant amounts of soot and NO x emissions from these engines. Utilizing carbon-free alternative fuels and enhancing fuel efficiency represent promising strategies to mitigate greenhouse gas (GHG) and other emissions in the heavy-duty transportation sector. In this context, ammonia (NH 3 ), as a hydrogen carrier, has received significant attention as a viable substitute for hydrocarbon fuels due to its carbon-free composition, relatively high energy density, and well-established infrastructure. Many previous studies have considered combustion and emission characteristics of ammonia-hydrocarbon fuel blends in engines and simplified flames. But, detailed investigations on the effects of ammonia on the performance of hydrocarbon fuels under engine conditions are lacking. In the present study, we perform large eddy simulations (LES) of the ignition and flame processes in a constant-volume combustion reactor, where n-heptane is injected in an ammonia/air ambient mixture in a diesel-like environment. A detailed and validated reaction mechanism containing 302 species and 1981 reactions is employed. The Engine Combustion Network Spray H experimental data is used to validate the spray model under both non-reacting and reacting conditions. Dual-fuel combustion is simulated using the well-stirred reactor (WSR) approach. Results are presented for two spray cases: (1) single fuel (SF) with n-heptane injected into a mixture of air and combustion products and (2) dual-fuel (DF) with the injection of n-heptane in a mixture of air, ammonia, and combustion products. It is observed that the presence of ammonia has a significant effect on the ignition and flame development processes. With ammonia addition, both the first- and second-stage ignition delay times increase, but the effect of ammonia on the second-stage ignition is significantly more prominent. In addition, the ignition kernel size and growth rate decrease noticeably. For SF spray, the main ignition is characterized by multiple ignition kernels near the spray tip, whereas for DF spray, a single relatively small ignition kernel forms and grows slowly in the downstream direction. The flame development and the final quasi-steady flame structure are also modified due to ammonia. Here, the outcome of this research would enable a better understanding of ammonia–diesel dual-fuel spray flame behavior and guide the development of associated engine combustion strategies.

ammonia↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2020

A massively parallel and scalable multi-CPU material point method

Harnessing the power of modern multi-GPU architectures, we present a massively parallel simulation system based on the Material Point Method (MPM) for simulating physical behaviors of materials undergoing complex topological changes, self-collision, and large deformations. Our system makes three critical contributions. First, we introduce a new particle data structure that promotes coalesced memory access patterns on the GPU and eliminates the need for complex atomic operations on the memory hierarchy when writing particle data to the grid. Second, we propose a kernel fusion approach using a new Grid-to-Particles-to-Grid (G2P2G) scheme, which efficiently reduces GPU kernel launches, improves latency, and significantly reduces the amount of global memory needed to store particle data. Finally, we introduce optimized algorithmic designs that allow for efficient sparse grids in a shared memory context, enabling us to best utilize modern multi-GPU computational platforms for hybrid Lagrangian-Eulerian computational patterns. We demonstrate the effectiveness of our method with extensive benchmarks, evaluations, and dynamic simulations with elastoplasticity, granular media, and fluid dynamics. In comparisons against an open-source and heavily optimized CPU-based MPM codebase [Fang et al. 2019] on an elastic sphere colliding scene with particle counts ranging from 5 to 40 million, our GPU MPM achieves over 100x per-time-step speedup on a workstation with an Intel 8086K CPU and a single Quadro P6000 GPU, exposing exciting possibilities for future MPM simulations in computer graphics and computational science. Moreover, compared to the state-of-the-art GPU MPM method [Hu et al. 2019a], we not only achieve 2x acceleration on a single GPU but our kernel fusion strategy and Array-of-Structs-of-Array (AoSoA) data structure design also generalizes to multi-GPU systems. Our multi-GPU MPM exhibits near-perfect weak and strong scaling with 4 GPUs, enabling performant and large-scale simulations on a 10243 grid with close to 100 million particles with less than 4 minutes per frame on a single 4-GPU workstation and 134 million particles with less than 1 minute per frame on an 8-GPU workstation.

Wang, Xinlei↗
DOE OSTI2022

Lifting and Dropping VMs to Dynamically Transition Between Time- and Space-sharing for Large-Scale HPC Systems

As HPC environments increasingly integrate with edge based systems, system architectures will need to handle a broader class of workloads and scheduling requirements. One result of this shift will be the need to simultaneously support bulk-synchronous parallel (BSP) and on-demand service based applications on the same infrastructure. This in turn will require that future resource management approaches utilize both space-shared as well as time-shared resource scheduling strategies. In this work we introduce the concept of "VM-lifting'' (and its inverse "VM-Dropping'') which allows dynamically switching an HPC workload between space-shared and time-shared scheduling regimes. Our work targets co-kernel based HPC system software environments, in which multiple specialized OS kernels execute natively on dedicated physical resource partitions inside a single compute node. With VM-lifting, a native co-kernel can be migrated at runtime to and from locally hosted Virtual Machine Environments due to changing scheduling requirements of the node. This allows an HPC node to be dynamically (re-)configured as either a time-shared Infrastructure-as-a-Service (IaaS) resource or a dedicated space shared resource based on the current workload demands. We have implemented this approach in the context of the Hobbes Exascale System Software stack and have demonstrated that a node can be reconfigured with minimal impact on the running applications.

Gordon, Nick↗
DOE OSTI2022

EPMA-Based Mass Balance Method for Quantitative Fission Product Distribution Comparison between TRISO Particles

Two irradiated AGR-2 TRISO particles were chosen to demonstrate a recently developed mass balance technique in which EPMA-generated concentration data was used to determine fission product mass on a layer-by-layer basis in TRISO particles. EPMA-calculated fission product masses for most fission products in the two particles were within +/- 20% of their ORIGEN-modelled masses. Results show that Sr, Ba, and Eu accumulate preferentially in the carbon-rich kernel periphery on the particles’ side that lacks a gap between the buffer and IPyC. In addition, the more mobile elements--Cs, Sr, and Pd, accumulate in greater quantity in the outer layers of particle AGR2-223-RS34 compared to particle AGR2-223-RS06, which has relatively more of those elements’ mass located in the kernel and kernel periphery, suggesting enhanced fission product transport in particle AGR2-223-RS34. This model can be used better understand and test fission product transport in TRISO particles.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Pre-Ionization Controlled Laser Plasma Formation for Ignition Applications (Final Scientific/Technical Report)

This report consists of three grand funded papers. Abstracts for each follow. 1) In this work, we present experimental and modeling studies of air pre-ionization using ultraviolet (UV) laser pulses and its effect on laser breakdown of an overlapped near-infrared (NIR) pulse. Experimental studies are conducted with a 266 nm beam (fourth harmonic of Nd:YAG) for UV pre-ionization and an overlapped 1064 nm NIR beam (fundamental of Nd:YAG), both having pulse duration of 10 ns. Results show that the UV beam produces a pre-ionized volume which assists in breakdown of the NIR beam, leading to reduction in NIR breakdown threshold by factor of >2. Numerical modeling is performed to examine the ionization and breakdown of both beams. The modeled breakdown threshold of the NIR, including assist by pre-ionization, is in reasonable agreement with the experimental results. 2) The present contribution compares the energy absorption, optical emission, temperature, and fluid dynamics of ultraviolet (UV) λ = 266 nm and near infrared (NIR) λ = 1064 nm nanosecond laser induced plasmas in ambient air. For UV pulses at the conditions studied, energy absorption by the plasmas increases relatively gradually with laser pulse energy starting at delivered energy of E~8 mJ. Corresponding measurements of plasma luminosity show that the absorption of UV radiation does not necessarily result in visible plasma emission. For the NIR induced plasmas, the energy absorption profile is far more abrupt and begins at ~55 mJ. In contrast with UV, the absorption of NIR radiation is always accompanied by intense optical emission. The temperatures of both types of plasma have been measured with Rayleigh scattering thermometry (at times after the Thomson signal sufficiently diminishes). The UV plasmas can attain a wider range of temperatures, including lower temperatures, depending on the pulse energy (e.g., T ~400–2000K for E ~7–35 mJ at Δt = 10 μs after the pulse) while the NIR plasmas show only hotter temperatures (e.g., T ~ 12 000 K for E = 75 mJ at Δt = 10 μs after the pulse) as is consistent with the literature. Differences in the fluid dynamics for UV versus NIR pulses are shown with Schlieren imaging. In this work, the contrast in the UV and NIR plasma threshold behavior is attributed to differing roles of avalanche ionization and multiphoton ionization as is also illustrated by a simple numerical model. 3) The present contribution examines the impact of plasma dynamics and plasma-driven fluid dynamics on the flame growth of laser ignited mixtures and shows that a new dual-pulse scheme can be used to control the kernel formation process in ways that extend the lean ignition limit. We perform a comparative study between (conventional) single-pulse laser ignition (λ = 1064 nm) and a novel dual-pulse method based on combining an ultraviolet (UV) pre-ionization pulse (λ = 266 nm) with an overlapped near-infrared (NIR) energy addition pulse (λ = 1064 nm). We employ OH* chemiluminescence to visualize the evolution of the early flame kernel. For single-pulse laser ignition at lean conditions, the flame kernel separates through third lobe detachment, corresponding to high strain rates that extinguish the flame. In this work, we investigate the capabilities of the dual-pulse to control the plasma-driven fluid dynamics by adjusting the axial offset of the two focal points. In particular, we find there exists a beam waist offset whereby the resulting vorticity suppresses formation of the third lobe, consequently reducing flame stretch. With this approach, we demonstrate that the dual-pulse method enables reduced flame speeds (at early times), an extended lean limit, increased combustion efficiency, and decreased laser energy requirements.

Mechanical engineering↗
DOE OSTI2020

Safety Testing and Destructive Examination of AGR-2 UO 2 Compact 3-1-1

Post-irradiation examination and elevated-temperature safety testing are being performed on compacts from the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program’s second irradiation experiment (AGR-2). The compacts in the AGR-2 irradiation experiment held either tristructural isotropic (TRISO)-coated particles containing uranium oxide fuel kernels (UO 2 ) or TRISO-coated particles containing fuel kernels with both uranium carbide and uranium oxide phases (UCO). In UO 2 TRISO particles, oxygen released by uranium fission can react with the surrounding carbon in the buffer layer to form carbon monoxide (CO). Excess CO can lead to various irradiation performance issues under certain operating conditions, such as pressure-induced fracture, kernel migration, and silicon carbide (SiC) corrosion. In UCO TRISO particles, CO formation is reduced because the chemical potential for oxidation of uranium carbide is lower than for oxidation of carbon.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

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↗
DOE OSTI2020

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↗
DOE OSTI2020

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↗
DOE OSTI2021

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↗
DOE OSTI2022

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↗
DOE OSTI2024

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↗
DOE OSTI2024

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↗
DOE OSTI2025

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↗
DOE OSTI2023

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↗