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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Simulation of Mechanical Fractionation of Chopped Whole-Plant Corn (WPC) Using Discrete Element Method (DEM)

Fractionating whole-plant corn (WPC) in a single-pass harvesting system requires studies on the WPC-to-equipment interaction for improved property control, as well as mechanical and air-driven separation processes compared to the traditional multi-pass grain and stover harvesting system. The discrete element method (DEM) technique has the potential to simulate WPC mechanical fractionation and support simulation-based design of WPC separation processes. In this study, methods to develop DEM particle models of WPC (kernel, cob, stalk, and husk) and their material properties for simulating mass fractionation using the ASABE standard mechanical shaker were proposed. Measurement was done on the axial dimensions (major, intermediate, and minor) and mass of each WPC type (mean sample size is 56), sampled from single-pass harvesting. Applying gaussian multivariate regression and bootstrapping re-sampling techniques, a DEM particle approximate to each WPC was developed. Sensitivity analysis of the DEM Young‘s modulus, Poisson‘s ratio, and interaction parameters of coefficient of restitution, coefficient of rolling friction, and coefficient of static friction on mass fraction was performed after 156 ASABE sieve-shaking DEM simulation runs, generated using Latin Hypercube Design (LHD) design of experiment (DOE) from 19 DEM material parameters. DEM simulation using Hertz-Mindlin with flexible bond contact laws and DOE optimized material properties successfully reproduced the mass fractions retained in ASABE sieves at 9.8% mean relative error and a coefficient of determination of R2 = 0.87. Here, the DEM methodology developed for mechanical WPC mass fractionation could be deployed to perform virtual design of feedstock handling equipment and performance analysis of mechanical fraction systems.

09 BIOMASS FUELS↗
DOE OSTI2023

Integrated Quantum-Classical Protocol for the Realistic Description of Solvated Multinuclear Mixed-Valence Transition-Metal Complexes and Their Solvatochromic Properties

Linear cyanide-bridged polymetallic complexes, which undergo photoinduced metal-to-metal charge transfer, represent prototypical systems for studying long-range electron-transfer reactions and understanding the role played by specific solute–solvent interactions in modulating the excited-state dynamics. Here, to tackle this problem, while achieving a statistically meaningful description of the solvent and of its relaxation, one needs a computational approach capable of handling large polynuclear transition-metal complexes, both in their ground and excited states, as well as the ability to follow their dynamics in several environments up to nanosecond time scales. Here, we present a mixed quantum classical approach, which combines large-scale molecular dynamics (MD) simulations based on an accurate quantum mechanically derived force field (QMD-FF) and self-consistent QMD polarized point charges, with IR and UV–vis spectral calculations to model the solvation dynamics and optical properties of a cyano-bridged trinuclear mixed-valence compound (trans-[(NC) 5 Fe III (μ-CN)Ru II (pyridine) 4 (μ-NC)Fe III (CN) 5 ] 4– ). We demonstrate the reliability of the QMD-FF/MD approach in sampling the solute conformational space and capturing the local solute–solvent interactions by comparing the results with higher-level quantum mechanics/molecular mechanics (QM/MM) MD reference data. The IR spectra calculated along the classical MD trajectories in different solvents correctly predict the red shift of the CN stretching band in the aprotic medium (acetonitrile) and the subtle differences measured in water and methanol, respectively. By explicitly including the solvent molecules around the cyanide ligands and calculating the thermal averaged absorption spectra using time-dependent density functional theory calculations within the Tamm–Dancoff approximation, the experimental solvatochromic shift is quantitatively reproduced going from water to methanol, while it is overestimated for acetonitrile. This discrepancy can likely be traced back to the lack of important dispersion interactions between the solvent cyano groups and the pyridine substituents in our micro solvation model. The proposed protocol is applied to the ground state in water, methanol, and acetonitrile and can be flexibly generalized to study excited-state nonequilibrium solvation dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Simulating low-energy neutrino interactions with MARLEY

Monte Carlo event generators are a critical tool for the interpretation of data obtained by neutrino experiments. Several modern event generators are available which are well-suited to the GeV energy scale used in studies of accelerator neutrinos. However, theoretical modeling differences make their immediate application to lower energies difficult. In this paper, I present a new event generator, MARLEY, which is designed to better address the simulation needs of the low-energy (tens of MeV and below) neutrino community. The code is written in C++14 with an optional interface to the popular ROOT data analysis framework. The current release of MARLEY (version 1.2.0) emphasizes simulations of the reaction 40 Ar ( ν e , e − ) 40 K ⁎ but is extensible to other channels with suitable user input. This paper provides detailed documentation of MARLEY's implementation and usage, including guidance on how generated events may be analyzed and how MARLEY may be interfaced with external codes such as Geant4. Further information about MARLEY is available on the official website at http://www.marleygen.org. Program title:MARLEY 1.2.0 CPC Library link to program files:https://doi.org/10.17632/4v7zxnc8j3.1 Developer's respository link:http://github.com/MARLEY-MC/marley Code Ocean capsule:https://codeocean.com/capsule/9868179 Licensing provisions: GNU General Public License 3.0 Programming language: C++14 External routines/libraries used: GNU Scientific Library [1,2] (required), ROOT [3,4] (optional) Nature of problem: Simulation of neutrino-nucleus scattering events at energies of tens-of-MeV and below Solution method: Initial two-to-two scattering kinematics are sampled using the allowed approximation differential cross section and tables of precomputed nuclear matrix elements. Subsequent de-excitations of the remnant nucleus are simulated using a Monte Carlo implementation of the Hauser-Feshbach statistical model and tabulated γ-ray decay schemes for discrete nuclear levels. Additional comments including restrictions and unusual features: Input data are provided with the code that are suitable for producing simulations of the charged-current reaction 40 Ar ( ν e , e − ) 40 K ⁎ , coherent elastic neutrino-nucleus scattering on spin-zero target nuclei, and neutrino-electron elastic scattering on any atomic target. Preparation of new reaction input files (whose format is documented in Appendix B) would enable other reaction channels and nuclear targets to be handled by the existing code framework. Although there is no maximum neutrino energy enforced by the code itself, realistic neutrino-nucleus scattering events may be generated up to roughly 50 MeV. Above this energy, the effects of forbidden nuclear transitions, which are neglected in the current treatment of the cross sections (see section 2.1), become increasingly important.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Liquefaction of pelleted corn cobs

Liquid slurries at high loadings (pumpable slurries) are critical to handle the streams between the unit operations in a biorefinery. Their liquefaction potential was initially tested with a small-scale method using 3FPU Ctec-2 /g dry biomass, and results were confirmed in 1L bioreactors experiments. Liquid slurries of cobs were observed in small scale tests (based on visual appearance, and reducing sugars released). Results were confirmed in 1L bioreactors under similar experimental conditions. Yield stress value in bioreactor was 34 ± 6Pa at 96 h, and glucan and xylan conversion to glucose and xylose, respectively, were 41 and 21%. In addition, work has been initiated with liquefaction of other pelleted corn stover fractions: Husk/Leaf (A),Husk (B), Stems (D) and controls (whole corn stover; F and G). Compositional analysis of the pellets showed glucan content (%) in the samples ranged from 31.9 to 36.1, xylan from 19.1 to 20.9, total lignin 13.1 to 18.8,and total ash 1.73 to 10.19. The moisture content ranged from 6.21 to 11.66%. Given these similar characteristics, we also examined liquefaction of these other samples, and they also showed that liquid slurries are possible. Work is continuing to define favourable conditions for liquid slurries formation.

Cruz, Antonio↗
DOE OSTI2026

Alpha-Imaging Detector System Development for Large Area Monitoring

Effective management and disposal of legacy nuclear waste are essential for ensuring safe work environments and minimizing environmental impacts. Monitoring airborne actinide contamination is particularly critical due to the high internal dose potential of alpha-emitting radionuclides. Traditional continuous air monitoring systems (CAMs) used in the industry are limited in the volume of air they can sample, potentially leading to inaccurate radiation detection over large areas. For example, in 2018, elevated levels of airborne Plutonium-239 were detected beyond the controlled areas of the Hanford Plutonium Finishing Plant, highlighting the potential risks to both plant workers and nearby residents. To address these challenges, high-efficiency particulate absorbing (HEPA) air purifiers can enhance air flow by up to 1.5 orders of magnitude, thereby increasing monitoring efficiency and providing a cost-effective solution for large-area surveillance. To quantify the activities of alpha-emitting radionuclides on HEPA filters, the Savannah River National Laboratory is developing an advanced alpha-imaging detection system. This system includes scintillating materials combined with a digital scientific camera. A significant concern in operating such a large-area airborne monitoring system is the handling of HEPA filters, which may be contaminated with radioactive particles. To mitigate these hazards, it is crucial to ensure that any contamination is securely fixed onto the filters. Efforts have been made to optimize the sensitivity of scintillator-epoxy composites and apply them to HEPA filters. These materials were characterized using fluoroscence spectroscopy. These techniques confirmed the purity of the raw materials, the dispersion of scintillators in the epoxy matrix, and the stability of their optical and structural properties post-modification. The optimal scintillator-epoxy composite was selected for use on alpha-spiked HEPA filters to evaluate the efficiency of the sprayer. HEPA filters, embedded with alpha particles collected by an air purifier deployed in an airborne radiation area, have been tested to assess detection efficiency. Future work will focus on employing multiple imaging sensors simultaneously to enhance sensitivity across different regions of the HEPA filter.

Pham, Phuong [Savannah River National Laboratory (↗
DOE OSTI2021

Examining Nuisance Aerosol Detections in Light of the Origin of the Screening Process (November 2021)

The evolution of philosophy and computations in the International Data Center (IDC) related to aerosol samples have had profound impacts on the number of recorded detections in the network since routine operations began in 2000. Key decisions from policymakers have been the list of triggering radionuclides, the scheme for categorizing these into interest levels 1-5, and an algorithm for determining when an anthropogenic isotope is seen so often that it is no longer interesting, known as the Exponential Weighted Moving Average (EWMA). These are described in the Operations Manual of the IDC. Key parameters that are controlled by the IDC but for which the IDC receives occasional input from policymakers include the constants in EWMA and the peak significance threshold for individual gamma rays, the latter of which directly leads to determination of the presence or absence of a radionuclide in a sample. There are also changes in computations which the IDC makes and informs policy makers about, such as changes in how background is computed, which could also affect the ease of detecting a peak – real or false. Rather than focus on the quantitative changes due to computation changes, this work records some thinking on how isotopes and peak significance levels were chosen, and the resulting detections seen over 18 years during the buildup of the International Monitoring System (IMS). These detections are considered on a global scale to try to determine the relative impact on monitoring, and in some cases, the nature of their existence. Repeated detections of 131I and 133I are the most troublesome, but they are not so frequent to be a major problem for the Verification Regime. These detections could probably be handled adequately using scientific methods currently under development for xenon backgrounds. It is also somewhat problematic that top-level analysis of aerosol backgrounds has not been reported previous to this. The steep increase in the rate of detections after 2016 are a concern, either in the actual backgrounds or from changes in the calculations methods used to generate the Reviewed Radionuclide Report (RRR.) Final conclusions of the authors are that the computational stability of the RRR is very important. With computational stability, changes can be usefully analyzed as being due to changes in radioactivity in Earth’s atmosphere This report is a distillation into text of a talk given in the Radionuclide Experts Group (RNEG) in Vienna during Working Group B (WGB) in February of 2019. This report does not directly contain any IDC data, only summaries by year, or by isotope, or by location. No specific IDC detection by time, location, or isotope is included.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Error statistics and scalability of quantum error mitigation formulas

Quantum computing promises advantages over classical computing in many problems. Nevertheless, noise in quantum devices prevents most quantum algorithms from achieving the quantum advantage. Quantum error mitigation provides a variety of protocols to handle such noise using minimal qubit resources. While some of those protocols have been implemented in experiments for a few qubits, it remains unclear whether error mitigation will be effective in quantum circuits with tens to hundreds of qubits. In this paper, we apply statistics principles to quantum error mitigation and analyse the scaling behaviour of its intrinsic error. We find that the error increases linearly O(ϵN) with the gate number N before mitigation and sublinearly O(ϵ'N γ ) after mitigation, where γ ≈ 0.5, ϵ is the error rate of a quantum gate, and ϵ' is a protocol-dependent factor. The $\sqrt{N}$ scaling is a consequence of the law of large numbers, and it indicates that error mitigation can suppress the error by a larger factor in larger circuits. We propose the importance Clifford sampling as a key technique for error mitigation in large circuits to obtain this result.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗
DOE OSTI2025

High fidelity blade-resolved and actuator line data from a 16 turbine wind farm simulation using ExaWind

This data was generated with the ExaWind code suite (https://github.com/Exawind) as a demonstration of a large, 16 turbine wind farm simulation, calculated using two different levels of fidelity. The lower level of fidelity approach uses an actuator line approach to represent the turbines, and was simulated with AMR-Wind (https://github.com/Exawind/amr-wind/) as the background flow solver, coupled to OpenFAST (https://github.com/OpenFAST/openfast). The higher level of fidelity simulation uses a blade-resolved approach, and is done using AMR-Wind, Nalu-Wind (https://github.com/Exawind/nalu-wind), OpenFAST, and TIOGA (https://github.com/Exawind/tioga). In the blade-resolved simulation, ExaWind couples together a background flow solver, AMR-Wind, and a near-body solver, Nalu-Wind, through an overset technique from the TIOGA application. OpenFAST handles the structural dynamics of the turbine blades and towers, which informs the fluid-structure interaction of the wind turbines with the flow solvers. In the actuator line simulation, a mesh of 295M elements was used for a 5km x 5km domain, and it was simulated using 256 nodes (2048 GPU's) on the Oak Ridge Leadership Computing Facility Frontier supercomputer. For the blade-resolved simulation, 1.5B element mesh was used in the AMR-Wind background 5km x 5km domain, and 16M elements were used for each turbine in the Nalu-Wind domains, for a total of 1.7B elements. This was simulated using 384 nodes on Frontier, with each node using 56 cores for Nalu-Wind and 8 GPU cores. The data in this archive includes the turbine outputs from OpenFAST, 2D sampling planes from AMR-Wind, and full-field solution files from AMR-Wind and Nalu-Wind.

17 WIND ENERGY↗
DOE OSTI2023

Phase Behavior of the Ternary NaCl-PuCl 3 -Pu Molten Salt

There is a gap in our understanding of the behavior of fused and molten fuel salts containing unavoidable contamination, such as those due to fabrication, handling, or storage. Therefore, this work used calorimetry to investigate the change in liquidus temperature of PuCl 3 , having an unknown purity and that had been in storage for several decades. Further research was performed by additions of NaCl, making several compositions within the binary system, and summarizing the resulting changes, if any, to the phase diagram. The melting temperature of the PuCl 3 was determined to be 746.5°C, approximately 20°C lower than literature reported values, most likely due to an excess of Pu metal in the PuCl 3 either due to the presence of metallic plutonium remaining from incomplete chlorination or due to the solubility of Pu in PuCl 3 . From the melting temperature, it was determined that the PuCl 3 contained between 5.9 to 6.2mol% Pu metal. Analysis of the NaCl-PuCl 3 samples showed that using the Pu rich PuCl 3 resulted in significant changes to the NaCl-PuCl 3 phase diagram. Most notably an unreported phase transition occurring at approximately 406°C and a new eutectic composition of 52.7mol% NaCl–38.7mol% PuCl 3 –2.5mol% Pu which melted at 449.3°C. Additionally, an increase in the liquidus temperatures was seen for NaCl rich compositions while lower liquidus temperatures were seen for PuCl 3 rich compositions. It can therefore be concluded that changes will occur in the NaCl-PuCl 3 binary system when using PuCl 3 with excess Pu metal. However, melting temperature analysis can provide valuable insight into the composition of the PuCl 3 and therefore the NaCl-PuCl 3 system.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Fast and Flexible Inference Framework for Continuum Reverberation Mapping Using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amounts of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long short-term memory summary network to reduce the high dimensionality of the light curve data and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with 10 3 –10 5 times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field CRM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

MOSCATO Development and Integration in Fiscal Year 2024

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy evolution for molten salt equipment. In FY24, significant developments were made to the code package, enhancing its capabilities in many aspects. The improvements and advancements can be summarized as follows: 1. Implementation of tritium transport capabilities and validation with experimental data: To enable modeling of tritium and other fission gases within MSRs, we implemented gas transport within MOSCATO via inclusion of couple mass transport equations within the salt and structural alloys. Comparisons to experimental data from literature showed good agreement with respect to tritium release rates. 2. Preliminary implementation of two-phase flow models in MOSCATO: To model tritium and other gases above their solubility limits, we implemented preliminary two-phase flow models within MOSCATO to account for bubble transport. The first model adopted was the Level-Set approach, which can handle the high void fraction regime, but with a requirement for high mesh resolution thus high computational expense. In this report, we present a verification of the Level-Set method using a simple benchmark case. We also performed a demonstration of the code as applied to an experimental case involving cover gas flow through salt in an experimental vessel. The second model adopted was the Eulerian-Eulerian dispersed flow model, which is computationally cheaper but limited to low void fraction regimes, such as bubbly flow. Validation and verification have not yet been performed for the Eulerian-Eulerian approach, but a preliminary implementation was completed. 3. Validation with static corrosion experiments: Static corrosion experimental data for stainless steel coupons within molten salts was used to further validate the corrosion model in MOSCATO. To do so, we leveraged the existing models in MOSCATO and simulated the sample mass loss and mass gain phenomena. Several ion species, including Cr 2+ , Fe 2+ and H + , were simulated in salt using the PNP solver, while Cr 0 and Fe 0 were simulated with a diffusion solver in stainless steel. The mass loss of the samples was compared with experimental data, and good agreement was achieved. These combined activities served to further expand the capabilities of MOSCATO and make it more generally applicable to the full range of phenomena that can control chemistry and corrosion in molten salt reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications

Introduction Reconstructing low-level particle tracks in neutrino physics can address some of the most fundamental questions about the universe. However, processing petabytes of raw data using deep learning techniques poses a challenging problem in the field of High Energy Physics (HEP). In the Exa.TrkX Project, an illustrative HEP application, preprocessed simulation data is fed into a state-of-art Graph Neural Network (GNN) model, accelerated by GPUs. However, limited GPU memory often leads to Out-of-Memory (OOM) exceptions during training, due to the large size of models and datasets. This problem is exacerbated when deploying models on High-Performance Computing (HPC) systems designed for large-scale applications. Methods We observe a high workload imbalance issue during GNN model training caused by the irregular sizes of input graph samples in HEP datasets, contributing to OOM exceptions. We aim to scale GNNs on HPC systems, by prioritizing workload balance in graph inputs while maintaining model accuracy. Our paper introduces diverse balancing strategies aimed at decreasing the maximum GPU memory footprint and avoiding the OOM exception, across various datasets. Results Our experiments showcase memory reduction of up to 32.14% compared to the baseline. We also demonstrate the proposed strategies can avoid OOM in application. Additionally, we create a distributed multi-GPU implementation using these samplers to demonstrate the scalability of these techniques on the HEP dataset. Discussion By assessing the performance of these strategies as data loading samplers across multiple datasets, we can gauge their effectiveness in both single-GPU and distributed environments. Our experiments, conducted on datasets of varying sizes and across multiple GPUs, broaden the applicability of our work to various GNN applications that handle input datasets with irregular graph sizes.

Lee, Claire Songhyun↗
DOE OSTI2021

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I–VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers’ views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Single Small-Scale Plutonium Redox Reaction System Yields Three Crystallographically-Characterizable Organoplutonium Complexes

Here, an approach to obtaining substantial amounts of data from a hazardous starting material that can only be obtained and handled in small quantities is demonstrated by the investigation of a single small-scale reaction of cyclooctatetraene, C 8 H 8 , with a solution obtained from the reduction of Cp' 3 Pu (Cp' = C 5 H 4 SiMe 3 ) with potassium graphite. This one reaction coupled with oxidation of a product has provided single-crystal X-ray structural data on three organoplutonium compounds as well as information on redox chemistry thereby demonstrating an efficient route to new reactivity and structural information on this highly radioactive element. The crystal structures were obtained from the reduction of C 8 H 8 by a putative Pu(II) complex, (Cp' 3 Pu II ) 1– , generated in situ, to form the Pu(III) cyclooctatetraenide complex, [K(crypt)][(C 8 H 8 ) 2 Pu III ], 1-Pu , and the tetra(cyclopentadienyl) Pu(III) complex, [K(crypt)][Cp' 4 Pu III ], 2-Pu . Oxidation of the sample of 1-Pu with Ag(I) afforded a third organoplutonium complex that has been structurally characterized for the first time, (C 8 H 8 ) 2 Pu IV , 3-Pu . Complexes 1-Pu and 3-Pu contain Pu sandwiched between parallel (C 8 H 8 ) 2– rings. The (Cp' 4 Pu III ) – anion in 2-Pu features three η 5 -Cp' rings and one η 1 -Cp' ring, which is a rare example of a formal Pu–C η 1 -bond. In addition, this study addresses the challenge of small-scale synthesis imparted by radiological and material availability of transuranium isotopes, in particular that of pure metal samples. A route to an anhydrous Pu(III) starting material from the more readily available Pu IV O 2 was developed to facilitate reproducible syntheses and allow complete spectroscopic analysis of 1-Pu and 2-Pu . Pu IV O 2 was converted to Pu III Br 3 (DME) 2 (DME = CH 3 OCH 2 CH 2 OCH 3 ) and subsequently Pu III Br 3 (THF) x , which was used to independently synthesize 1-Pu , 2-Pu , and 3-Pu .

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2020

VADER: A Tool for Criticality Safety Validation

The purpose of criticality safety is to prevent any inadvertent criticality from occurring during the handling or storage of fissile material. Calculations are frequently used to demonstrate that a sufficient subcritical margin exists. Validation is a key aspect of the evaluation process, establishing the suitability, accuracy, and associated uncertainty of the computational method and data to be used for the intended application. The validation process is performed by comparing the results of critical experiments with the calculated results from models of the experiments using the computational method to be validated. Laboratory critical experiments are controlled systems that achieve a k eff of approximately 1 in order to investigate the parameters at which such a critical condition is achieved. The validation parameters that are traditionally applied to safety analysis calculations are the bias and the bias uncertainty . The bias is the deviation of the average k eff of the validation suite from unity. The bias uncertainty accounts for the statistical uncertainty in the bias based on the standard deviation, sample size, and distribution of k eff values of the validation suite. The values of bias and bias uncertainty ensure that the systems predicted to be subcritical by the computational method will indeed be subcritical. The bias and bias uncertainty are often combined to determine an upper subcritical limit (USL) or computational margin that can then be applied to safety analysis calculations. Many methods have been developed by different organizations to calculate the bias and bias uncertainty for various types of criticality analyses. Each of these methods typically requires that the validity of various underpinning statistical assumptions be confirmed to demonstrate that the method is appropriate for the analysis of a given validation suite. An example of the validation decision making flow is shown in Fig.1. As shown in Fig. 1, the analyst performing the validation fits a trend line to the data and performs a test to determine if the trend was a statistically better representation of the data than if it were treated as an uncorrelated sample. If the trend line is a better representation of the data, then the analyst uses any one of a number of trending techniques to determine the bias and bias uncertainty. If a trend is not an appropriate representation of the data, then the analyst proceeds to perform a normality assessment for the data. If the normal assumption can be shown to be acceptable, then the analyst calculates the bias and bias uncertainty with the parametric technique. If the assumption of normality cannot be justified, then the nonparametric technique is used. Once the decision flow has been followed and the appropriate technique has been selected, the bias and bias uncertainty is typically combined with an administrative margin to determine a USL below which calculated values of k eff for safety analysis models can be considered subcritical. The calculations used in each decision are often performed with spreadsheets or with small programs available at various sites performing criticality analyses. Expertise in understanding and interpreting the results must be maintained to perform these calculations. This can often be an error-prone process. Oak Ridge National Laboratory (ORNL) is currently developing the Validation and Data Evaluation Resource (VADER) to simplify and automate the criticality safety validation process and to provide a software quality assurance pedigree to the calculational methods used. This paper discusses the use of the Fulcrum user interface with VADER, the anticipated initial capabilities of VADER to perform validation analyses, and the output from the code.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

CRADA Final Report: CRADA Number NFE-22-09330 with General Fusion

General Fusion is developing a magnetized target fusion (MTF) approach that involves compressing an initial magnetically confined plasma inside a cavity formed in liquid metal. This approach builds from concepts initially developed under the Linus program at the U.S. Naval Research Laboratory and combines it with advances from compact toroid experiment (CTX) and sustained spheromak plasma experiment (SSPX) in compact toroid plasmas and coaxial Marshall gun systems. Modeling the tokamak during compression is central to designing a successful MTF device. The plasma is formed by coaxial helicity injection in the General Fusion device. Immediately after formation, the plasma has a diverted tokamak configuration with a single null. As the wall moves inwards, the plasma is repelled from the conducting surface and driven inwards by currents induced by its magnetic field in the liquid metal wall. As the liquid metal closes (or bridges) the opening of the coaxial plasma injector, the magnetic field topology alters to remove the null. Due to this, the plasma moves from a diverted to a wall-limited configuration. The liquid metal liner continues to close in and change shape, reducing in radius by a factor of ten at the peak of plasma compression. A model of the MTF plasma must be able to handle this continually varying geometry, and to be predictive, it must faithfully include the real imperfections arising in the process. In this project, we pursued a Monte Carlo approach to closures for MHD by computing kinetic electron trajectories in an MHD plasma background from simulations of GF devices. This requires enhancing the capabilities of the KORC-T code for running large ensembles of kinetic trajectories by porting it to GPU architectures and enabling workflows for large ensembles on OLCF machines. With these capabilities, it is possible to produce a large library of kinetic calculations of electron orbits evolving in plasma configurations spanning the magnetic configurations and plasma density profiles, including non-axisymmetry, arising in the General Fusion’s existing PI3 spherical tokamak device. Using ensembles will capture particles passing a single point in space in a given magnetic configuration, and the entire dataset will cover a range of global magnetic field geometries. By sampling around many starting points, this dataset will capture the spatial dependence of the plasma parameters. From this large dataset, it is possible to produce a reduced model for the kinetic effects not captured in MHD.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Rapid Crystallization of Zeolites with Controllable Defects: Disentangling Fluoride Concentration and pH Using NH 4 F

Zeolite synthesis is typically conducted either under basic conditions or in neutral fluoride media using hydrofluoric acid (HF). While basic (OH − ) conditions generally result in faster zeolite crystallization, they can also increase the likelihood of framework defects and crystal intergrowths. In contrast, synthesis in neutral fluoride media tends to produce fewer defects because fluoride balances positive charges from structure-directing agents. However, this method often requires significantly longer crystallization times and involves the handling of dangerous HF. In the present study, we pursue the best of both synthesis conditions, rapid syntheses with controllable defect concentrations, by disentangling of mineralizing agent and chargebalancing agent using ammonium fluoride (NH 4 F) as an alternative to HF. We have investigated the use of NH 4 F in the syntheses of siliceous and aluminum-containing zeolite A (LTA, small pore), ZSM-5 (MFI, medium pore), and siliceous Beta(*BEA, large pore). The crystallization times of all four zeolites decreased substantially with an increasing NH 4 F concentration. Crystallization times were reduced from 24 to 4 h (Si-LTA), 96 to 36 h (Al-LTA), 240 to 6 h (ZSM-5), and 24 to 3 h (Si-*BEA). Additionally, increasing the NH 4 F concentration in the synthesis mixtures decreases the defect densities of siliceous zeolites. Raman spectroscopy, along with 29 Si MAS NMR, 19 F MAS NMR, 13 C MAS NMR, and fluorine elemental analysis of Si-LTA samples confirms that the reduction in charged defects (Si−O − ) is due to the higher incorporation of F − within the double four-membered ring (D4R) present in the LTA samples. We show that the accelerated crystallization is due to the role of F − in enhancing the silica mineralization rate (formation of silicon hexafluoride species) and stabilizing D4Rs under basic conditions. As a result, combining basic and fluoride-mediated synthesis could therefore be advantageous for faster zeolite production and improved control over structural properties for a wide variety of zeolite structures.

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