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At least 721 records · Page 40

Development of Microwave Resonant Cavity Transducer Recalibration Procedures

We are investigating a microwave resonant cavity transducer for flow sensing in the vessel of a high temperature fluid advanced reactor (AR), such as a molten salt cooled reactor (MSCR) or a sodium fast reactor (SFR). This transducer is a hollow metallic cylindrical cavity, with one of the flat walls of the cylinder flexible enough to undergo microscopic deflection due to dynamic fluid pressure. Membrane deflection leads to a shift in the microwave resonant frequency, which can be detected with a spectrum analyzer. We have performed a preliminary proof-of-principle test of flow sensing in high temperature liquid sodium in environment. The liquid sodium setup consists of a cylindrical vessel with a center feed line, where a transducer inserted through the top cap of the vessel measures velocity of the impinging liquid jet. For this test, we have developed a cylindrical resonator, which was machined from stainless steel 316 and electroplated with silver on the interior surfaces. Inner diameter of the cylindrical cavity is 22.2 mm, and the thin wall is approximately 200µm thick. The cavity was excited through a WR-42 waveguide through a subwavelength hole on the side of the wall of the cylinder in the TE 011 mode with resonant frequency f ≈ 17.8GHz. Sodium flow rate sensing study was performed in a liquid sodium vessel at 340°C temperature and ambient pressure. The flow rate was changed by varying sodium pump power, and a frequency shift of several hundred KHz was observed. From the measurements, we observed significant scatter in high temperature liquid sodium at low flow velocity values. Our hypothesis is that this is caused by temperature drift in the liquid, which results in thermal expansion of the cavity and a drift in the resonator frequency. In this report, we investigate temperature dependence of the resonant frequency through development of analytic models and preliminary analysis of experimental data. In addition, we develop a procedure for compensation for temperature drift during flow sensing.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Regulatory Testing of RPP-WTP HLW Glasses to Support Delisting Compliance, VSL-04R4780-1, Rev. 0 (Sep 2004)

The primary goal of the testing described in this report was to collect data to demonstrate compliance of the immobilized high-level waste (IHLW) glasses with delisting requirements. The collected data will be used to support a petition to delist the IHLW glasses destined for the national disposal facility. The Delisting Data Quality Objectives (DQO) (Cook and Blumenkranz 2003) identified a list of (16) inorganic constituents of potential concern (COPCs) and their associated limits for delisting. These COPCs can be divided into three groups, Cases 1, 2, and 3, based on their Toxicity Characteristic Leaching Procedure (TCLP) responses versus their respective delisting limits. To briefly summarize, Case 1 COPCs are those that, when loaded at their highest expected concentration in Waste Treatment Plant (WTP) glasses, are not expected to leach at their respective delisting limits when the glasses are exposed to the TCLP. Case 2 COPCs may reach the delisting limits in TCLP leachates of WTP glasses if loaded to concentrations near their maximum expected concentrations in glass. Finally, Case 3 COPCs are components that are likely to be present in concentrations sufficient to exceed their respective delisting limits in TCLP leachates of some possible glasses. The test objective was to show that, for (i) the expected range of inorganic contents in the waste feed to the Hanford WTP high level waste (HLW) vitrification facility, (ii) the expected range of glass product compositions, and (iii) the Case 1 and Case 2 COPCs identified by the DQO, the IHLW glasses meet all the relevant requirements for delisting. For Case 3 COPCs (i.e., Cd), the testing was to demonstrate the relationship between glass composition and TCLP cadmium (Cd) release, and then employ the results to develop TCLP-composition response models. During WTP operations, TCLP-composition models can be used to predict, within the required statistical uncertainties, TCLP responses of IHLW production glasses that are within the compositional region used to develop the model.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Lawrence Livermore National Laboratory Experimental Test Site 300 (S300): S300 Roadway Improvements - 817 Complex Soil Sampling and Analysis Plan (May 2023)

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Function Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Roadway Improvements Project at the 817 Complex (project). The purpose of the SAP was to describe the procedures for collection and analysis of environmental samples and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction in accordance with Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which was developed in accordance with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, and U.S. DOD 2000). The SAP was developed in accordance with the SSMP and based on preliminary design information provided to EFA by PMO.

54 ENVIRONMENTAL SCIENCES↗

Pilot-scale hydrotreating of catalytic fast pyrolysis biocrudes: process performance and product analysis

Catalytic fast pyrolysis (CFP) is a technology option for producing advanced biofuels from hydrocarbon-rich biocrude intermediates. The relatively high oxygen content of biocrudes compared to petroleum intermediates increases hydrogen consumption and the lower thermal stability accelerates catalyst deactivation and reactor fouling hindering the adaptation of hydrotreating technology for biocrude upgrading into biofuels. In this study, four chemically different biocrude feeds were upgraded in a pilot scale hydroprocessing unit at similar process conditions using a commercial hydrodeoxygenation (HDO) catalyst. The biocrude feeds and hydrotreated products were characterized using standard ASTM procedures and advanced analytical techniques (GCxGC-FID and GCxGC-MS). HDO catalyst activity was monitored by changes in physical properties and chemical composition of the upgraded products as a function of time on stream. Aliphatic acids, ketones, aldehydes, and furan derivatives were completely converted during the hydrotreating tests while the concentration of aromatics, aliphatic hydrocarbons and phenolics increased during the hydrotreating tests. The oxygen content, nitrogen content, specific gravity, viscosity and the heavy end of the boiling point range (determined by simulated distillation) of the upgraded products increased with increasing time on stream during hydrotreating. The deactivation rate was the lowest for the biocrude feed that contained the most aliphatic and aromatic hydrocarbons and was the highest for the biocrude feed that had the most anhydrosugars. Overall, the HDO deactivation rate correlates with the total amount of oxygen in the feed (17 wt% to 29 wt%, on a wet basis).

09 BIOMASS FUELS↗

Optimal reconstruction of baryon acoustic oscillations for DESI 2024

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 galaxy BAO analysis, we assess the sensitivity of the post-reconstruction BAO constraints to different choices in our analysis configuration, performing tests on blinded data from the first year of DESI observations (DR1), as well as on mocks that mimic the expected clustering and selection properties of the DESI DR1 target samples. Overall, we find that BAO constraints remain robust against multiple aspects in the reconstruction process, including the choice of smoothing scale, treatment of redshift-space distortions, fiber assignment incompleteness, and parameterizations of the BAO model. We also present a series of tests that DESI followed in order to assess the maturity of the end-to-end galaxy BAO pipeline before the unblinding of the large-scale structure catalogs.

79 ASTRONOMY AND ASTROPHYSICS↗

Magnetic phase diagram of a two-orbital model for bilayer nickelates with varying doping

Motivated by the recently discovered high-T c bilayer nickelate superconductor La 3⁢ Ni 2 ⁢O 7 , we comprehensively research a bilayer 2×2×2 cluster for different electronic densities n by using the Lanczos method. We also employ the random-phase approximation to quantify the first magnetic instability with increasing Hubbard coupling strength, also varying n. Based on the spin structure factor S(q), we have obtained a rich magnetic phase diagram in the plane defined by n and U/W, at fixed Hund coupling, where U is the Hubbard strength and W the bandwidth. We have observed numerous states, such as A-AFM, Stripes, G-AFM, and C-AFM. At half-filling, n=2 (two electrons per Ni site, corresponding to N=16 electrons), the canonical superexchange interaction leads to a robust G-AFM state (π,π,π) with antiferromagnetic couplings both in-plane and between layers. By increasing or decreasing electronic densities, ferromagnetic tendencies emerge from the “half-empty” and “half-full” mechanisms, leading to many other interesting magnetic tendencies. In addition, the spin-spin correlations become weaker both in the hole or electron doping regions compared with half-filling. At n=1.5 (or N=12), density corresponding to La 3 ⁢Ni 2 ⁢O 7 , we obtained the “Stripe 2” ground state (antiferromagnetic coupling in one in-plane direction, ferromagnetic coupling in the other, and antiferromagnetic coupling along the z axis) in the 2×2×2 cluster. In addition, we obtained a much stronger AFM coupling along the z axis than the magnetic coupling in the xy plane. The random-phase approximation calculations with varying n give very similar results as Lanczos, even though both techniques are based on quite different procedures. Additionally, a state with q/π=(0.6,0.6,1) close to the E-phase wavevector is found in our RPA calculations by slightly reducing the filling to n=1.25, possibly responsible for the E-phase SDW recently observed in experiments. In conclusion, our predictions can be tested by chemically doping La 3 ⁢Ni 2 ⁢O 7 .

36 MATERIALS SCIENCE↗

Realizability-preserving discontinuous Galerkin method for spectral two-moment radiation transport in special relativity

Here we present a realizability-preserving numerical method for solving a spectral two-moment model to simulate the transport of massless, neutral particles interacting with a steady background material moving with relativistic velocities. The model is obtained as the special relativistic limit of a four-momentum-conservative general relativistic two-moment model. Using a maximum-entropy closure, we solve for the Eulerian-frame energy and momentum. The proposed numerical method is designed to preserve moment realizability, which corresponds to moments defined by a nonnegative phase-space density. The realizability-preserving method is achieved with the following key components: (i) a discontinuous Galerkin phase-space discretization with specially constructed numerical fluxes in the spatial and energy dimensions; (ii) a strong stability-preserving implicit-explicit time-integration method; (iii) a realizability-preserving conserved to primitive moment solver; (iv) a realizability-preserving implicit collision solver; and (v) a realizability-enforcing limiter. Component (iii) is necessitated by the closure procedure, which closes higher order moments nonlinearly in terms of primitive moments. The nonlinear conserved to primitive and the implicit collision solves are formulated as fixed-point problems, which are solved with custom iterative solvers designed to preserve the realizability of each iterate. With a series of numerical tests, we demonstrate the accuracy and robustness of this discontinuous-Galerkin-implicit-explicit method.

79 ASTRONOMY AND ASTROPHYSICS↗

NuMI/LBNF Horn and Stripline Welding

Focusing horns for secondary particles are critical components for creating a stable beam of neutrinos. These components need to survive in a harsh environment and withstand high stresses. Extending the lifetime of the horns is critical as spare fabrication takes approximately two years and has many subcomponents with strict quality control. Two key aspects of the fabrication process include the inner conductor CNC TIG welding and the friction stir welding of the stripline pieces. The process for welding requires steps such as sample welding, x-ray imaging, and tensile pull tests. Having a perfect weld retains as much of the original strength of the base metal and reduces the risk of failure. As FNAL ramps up in power to 2.4MW, the lifetime of the horn and stripline will more heavily rely on continuing to have high quality welding procedures and thorough quality assurance.

Orea, Adrian↗

Lawrence Livermore National Laboratory Experimental Test Site 300 (Site 300): Site 300 Roadway Improvements - 836 Complex Soil Sampling and Analysis Plan (May 2023)

This Soil Sampling and Analysis Plan (SAP) was prepared by the Environmental Functional Area (EFA)/Technical Services Department (TSD) of the Environment, Safety & Health (ES&H) Directorate for the Project Management Office (PMO) for the proposed Roadway Improvements Project at the 836 Complex (project). The purpose of the SAP is to describe the procedures for collection and analysis of environmental samples and evaluation of analytical data (chemical and radiological) to determine management options of excavated soil during project construction. This SAP follows criteria established in Lawrence Livermore National Laboratory’s (LLNL) Soils Screening and Management Plan (SSMP) (LLNL 2022), which was formalized in accordance with U.S. Environmental Protection Agency (EPA) guidance for developing Data Quality Objectives for environmental data (EPA 2006) and the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM) guidance (U.S. NRC, U.S. EPA, U.S. DOE, and U.S. DOD 2000). The scope of this SAP is based on preliminary design information provided by PMO.

54 ENVIRONMENTAL SCIENCES↗

Development of Density Functional Tight-Binding Parameters Using Relative Energy Fitting and Particle Swarm Optimization

We provide a strategy to optimize density functional tight-binding (DFTB) parameterization for the calculation of the structures and properties of organic molecules consisting of hydrogen, carbon, nitrogen, and oxygen. We utilize an objective function based on similarity measurements and the Particle Swarm Optimization (PSO) method to find an optimal set of parameters. This objective function considers not only the common DFTB descriptors of binding energies and atomic forces but also incorporates relative energies of isomers into the fitting procedure for more chemistry-driven results. The quality in the description of the binding energies and atomic forces is measured based on the Ballester similarity index and relative energies through a similarity index induced by the Levenshtein edit distance to quantify the correct energetic order of isomers. Training and testing datasets were created to include all relevant chemical functional groups. Finally, the accuracy of this strategy is assessed, and its range of applicability is discussed by comparison against our previous parameterization. The improved performance of the new DFTB parameterization is validated with respect to the density functional theory large datasets QM-9 and ANI-1, where excellent agreement is found between the structures and properties available in these datasets, and the ones obtained with DFTB.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design by analysis rules for ASME Section III, Division 5, Class B components

The current rules for elevated temperature ASME Section III, Division 5, Class B components, other than piping, were basically adapted from the Design-by-Rule approach for Section VIII, Division 1 vessels. A goal of the proposed new rules is to explicitly account for the design life and cyclic service while recognizing the less-rigorous requirements commensurate with lesser safety consideration. Further goals are to maximize the use of modern computational technology, for example finite element analysis in conjunction with reference stress concepts, and to avoid the need for stress classification. This paper summarizes the work done to address these issues. A summary of the design-by-analysis for primary loads, strain limit evaluation, and creep-fatigue damage assessment is presented. The proposed design-by-analysis creep-fatigue damage calculation approach uses a new elastic follow-up-based Isochronous Stress Strain Curve stress relaxation procedure. A set of sample problems are selected to validate the proposed design-by-analysis rules for creep-fatigue damage assessment. The proposed Class B rules are evaluated against the Class A elastic design rules and the experimental data obtained from a family of a simplified model test-based key-feature test results. The proposed Class B creep-fatigue damage assessment methodology yields conservative design cycles estimates compared to the experimental results.

36 MATERIALS SCIENCE↗

Investigation of the Performance and Explainability Tradeoffs for Machine-Learning Models for Predictive Maintenance of Circulating Water Systems in Nuclear Power Plants

Predictive maintenance (PdM) has shown great potential for achieving substantial cost savings and enhancing the economic competitiveness of nuclear power plants (NPPs) in today's energy market. Among the different modeling approaches that exist, machine learning (ML) tools in particular have a demonstrated ability to handle high dimensional and multivariate data and to extract hidden relationships within data in industrial environments. While ML methods show great potential, their lack of explainability---especially for black-box models---is a major hurdle to their adoption. Moreover, considering the supposed trade-off between explainability and performance challenges, careful consideration must be made as to which of these quality aspects takes precedence in light of multiple modeling options, resource availability, and domain characteristics. The present work evaluates the performance of six ML models, each with a different degree of explainability, in classifying the conditions of circulating water pumps (CWPs) by utilizing sensor data from nuclear power plants. To determine the drivers behind the trade-offs presented by this array of models, this work also tests different combinations of CWP units as the training and testing data, degrees of data imbalance, and objective functions for hyperparameter tuning. It was found that black-box models tend to afford superior performance in cases where there are far more instances of one type of labeled data than of any other type. It is recommended that a guided procedure be followed for designing and delivering an ML system that is sufficiently explainable to all involved stakeholders.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Flowback Test Analyses at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

Abstract In 2017 and 2019, injection testing was carried out in three zones in a vertical well in granite at the Frontier Observatory for Research in Geothermal Energy site near Milford, Utah, USA. In several injection cycles, flowback was implemented rather than shut-in. The goal was to explore an alternative to prolonged shut-in periods for inferring closure stress, formation compressibility, and formation permeability (permeability thickness product). The flowback procedures involved a cyclic flowback/shut-in, while pressure decreased. The flowback data are presented, and analyses are shown. The inferred closure stress(es) from flowback analyses are lower than for equivalent injection cycles that were strictly shut-in. Relatively high formation compressibility obtained from the flowback analyses indicates an extensive, fractured system. This study also includes numerical simulation of the flowback events. The numerical model shows that the rebound pressure is not necessarily the lower bound of the minimum principal stress. The signature of stiffness change can be identified as the process when the depletion mainly transitions from hydraulic fracture to natural fractures from numerical analysis. Overall, flowback potentially has advantages over shut-in because of the reduced time to closure.

15 GEOTHERMAL ENERGY↗

Machine Learning technique for isotopic determination of radioisotopes using HPGe γ-ray spectra

γ-ray spectroscopy is a quantitative, non-destructive technique that may be utilized for the identification and quantitative isotopic estimation of radionuclides. Traditional methods of isotopic determination have various challenges that contribute to statistical and systematic uncertainties in the estimated isotopics. Furthermore, these methods typically require numerous pre-processing steps, and have only been rigorously tested in laboratory settings with limited shielding. Here, in this work, we examine the application of a number of machine learning based regression algorithms as alternatives to conventional approaches for analyzing γ-ray spectroscopy data in the Emergency Response arena. This approach not only eliminates many steps in the analysis procedure, and therefore offers potential to reduce this source of systematic uncertainty, but is also shown to offer comparable performance to conventional approaches in the Emergency Response Application.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Machine learning-powered data cleaning for LEGEND: a semi-supervised approach using affinity propagation and support vector machines

Neutrinoless double-beta decay ($0\nu\beta\beta$) is a rare nuclear process that, if observed, will provide insight into the nature of neutrinos and help explain the matter-antimatter asymmetry in the Universe. The large enriched germanium experiment for neutrinoless double-beta decay (LEGEND) will operate in two phases to search for $0\nu\beta\beta$. The first (second) stage will employ 200 (1000) kg of High-Purity Germanium (HPGe) enriched in 76 Ge to achieve a half-life sensitivity of 10 27 (10 28 ) years. In this study, we present a semi-supervised data-driven approach to remove non-physical events captured by HPGe detectors powered by a novel artificial intelligence model. We utilize affinity propagation to cluster waveform signals based on their shape and a support vector machine to classify them into different categories. We train, optimize, and test our model on data taken from a natural abundance HPGe detector installed in the Full Chain Test experimental stand at the University of North Carolina at Chapel Hill. We demonstrate that our model yields a maximum sacrifice of physics events of $0.024 ^{+0.004}_{-0.003} \%$ after data cleaning. Our model is being used to accelerate data cleaning development for LEGEND-200 and will serve to improve data cleaning procedures for LEGEND-1000.

artificial intelligence↗

Direct Measurements of Ionic Transport Behavior of Dual-Layer Porous Electrodes

To improve power and cycling performance of lithium-ion batteries, dual-layer or porosity-gradient electrodes have been proposed. By engineering a higher porosity close to the separator, the intention is to improve ion transport where it is most impactful. In this research, MacMullin numbers of two dual-layer anode samples are tested using an impedance measurement technique developed previously. To characterize the microstructure of each layer independently, we developed an improved transmission-line model that accounts for each layer's properties.Virtual experiments using COMSOL Multiphysics to simulate impedance measurements are used to examine and improve the accuracy of the numerical inversion procedure. The results for the two dual-layer anodes studied show that MacMullin numbers follow expected trends, though the anodes are quite different from each other.

Dual-Layer Electrodes↗

End-of-Life Evaluation of Compressed Natural Gas Vehicle Fuel Tanks

This study evaluated the structural integrity of Type III and Type IV CNG fuel tanks from the Los Angeles (LA) County Metropolitan Transportation Authority to characterize the fuel tank conditions after experiencing a full service life of 15 years in transit bus application. The data produced provide insight about the condition of the CNG fuel tanks at the conclusion of their defined EOL and potential risks of continued operation of the CNG vehicle without replacement of the expired fuel tanks. In addition to physical testing performed on the fuel tanks, a nondestructive evaluation of modal acoustic emission (MAE) was utilized to assess the structural integrity of the tanks. The CNG fuel tanks were evaluated in their received condition and after experiencing artificial damage. The MAE results were then compared to visual inspection results of the procedures defined in the Compressed Gas Association’s (CGA’s) C-6.2 and C-6.4 standards (Compressed Gas Association 2013; 2012) to better understand the effectiveness of the visual inspection and potential safety risks of continued use of the tanks.

03 NATURAL GAS↗

High Order Wall-Modeled Large-Eddy Simulation on Mixed Unstructured Meshes

In the present study, an algebraic equilibrium wall model previously developed for hexahedral elements is extended to handle mixed meshes including prismatic, tetrahedral, and pyramidal elements in the context of a discontinuous high-order method. This extension is needed for complex geometries, for which high-order mixed elements (e.g., tetrahedral and pyramidal elements) are often necessary near solid walls to avoid meshing challenges. Various design decisions are discussed to achieve the best performance on massively parallel CPU/GPU architectures for a production-level high-order large-eddy simulation solver based on the flux reconstruction/correction procedure via reconstruction method, hpMusic. The extension to other elements is first evaluated using a benchmark channel flow problem at various Reynolds numbers. After that, flow over the NASA high-lift Common Research Model (CRM-HL) from the 4th AIAA High-lift Prediction Workshop is computed to further test the new implementation. Computational results at the third- and fourth-order accuracies are compared with experimental data.

Engineering↗