Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data fitting”

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

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

At least 307 records · Page 17

Artificial intelligence “sees” split electrons

Chemical bonds between atoms are stabilized by the exchange-correlation (xc) energy, a quantum-mechanical effect in which “social distancing” by electrons lowers their electrostatic repulsion energy. Kohn-Sham density functional theory (DFT) states that the electron density determines this xc energy, but the density functional must be approximated. Furthermore, this is usually done by satisfying exact constraints of the exact functional (making the approximation predictive), by fitting to data (making it interpolative), or both. Two exact constraints—the ensemble-based piecewise linear variation of the total energy with respect to fractional electron number and fractional electron z-component of spin —require hard-to-control nonlocality. On page 1385 of this issue, Kirkpatrick et al. have taken a big step toward more accurate predictions for chemistry through the machine learning of molecular data plus the fractional charge and spin constraints, expressed as data that a machine can learn.

74 ATOMIC AND MOLECULAR PHYSICS↗

Physics-Based Model to Represent Membrane-Electrode Assemblies of Solid-Oxide Fuel Cells Based on Gadolinium-Doped Ceria

This paper reports a physics-based model that predicts membrane-electrode assembly (MEA) performance of solid-oxide fuel cells (SOFCs) with Ce 0.9 Gd 0.1 O 2− δ (GDC10) electrolyte membranes. The paper derives self-consistent thermodynamic and transport properties for GDC1o mobile charged defects (oxide vacancies and reduced-ceria small polarons) by fitting published measurements of oxygen non-stoichiometry and conductivity over ranges of temperature and O 2 partial pressures. The button-cell model is applied to evaluate how mixed ionic-electronic conductivity influences the performance of an SOFC MEA with a GDC10 electrolyte sandwiched between a porous, composite Ni-GDC10 anode and a porous, composite cathode of Sm 0.5 Sr 0.5 CoO 3− δ (i.e., SSC) and GDC10. SSC properties are also derived by fitting published conductivity and oxygen non-stoichiometry measurements. Mixed conductivity of GDC10 and competing charge transfer reactions at both electrodes reduce open circuit voltages due to leakage current and buildup of defect concentrations at electrode-electrolyte interfaces. To fit polarization data, the button-cell model includes heterogeneous reaction rates for defect incorporation on the GDC10 surface along with Butler–Volmer expressions derived for competing charge transfer reaction rates from rigorous analyses assuming rate-limiting, elementary charge transfer reactions for each electrode. The calibrated MEA model can support rigorous SOFC modeling with GDC10 electrolytes over the range of conditions within a fully operating cell.

Electrochemistry↗

Bloom Filter framework for Web Archives

The software provides a framework to build a fast look up layer that reflects the holdings of an archive or database and operates between search/discovery system and disk storage. The software utilizes Bloom filter (BF) data structure. The discovery service powered by the Bloom filter layer comes with a very high level of accuracy yet space-saving, since BF compresses data to fit into RAM.

Balakireva, Lyudmila↗

XCal: model-based approach to X-ray CT spectral calibration

Transmission X-ray computed tomography (CT) is widely used to quantitatively reconstruct 3D objects composed of multiple materials. However, accurate CT reconstruction requires the system to be calibrated to account for the effective X-ray spectrum. Unfortunately, measurement of the effective spectrum is ill-posed, and existing calibration methods require that the system be recalibrated when the system parameters are changed. In this paper, we propose XCal, a multi-energy model-based spectral calibration approach for X-ray CT. The XCal approach models the effective spectrum using a separable physics-based model of the CT system. The model parameters are then estimated by fitting calibration data with known objects at multiple energies. An important advantage of XCal is that it allows the user to change scanner settings, such as the source voltage or X-ray filters, without the need for recalibration. Evaluations on simulated and measured datasets demonstrate that XCal significantly improves the accuracy of the estimated spectrum as compared to existing calibration methods.

Li, Wenrui [Purdue Univ., West Lafayette, IN (Unit↗

Modeling suggests that virion production cycles within individual cells is key to understanding acute hepatitis B virus infection kinetics

Hepatitis B virus (HBV) infection kinetics in immunodeficient mice reconstituted with humanized livers from inoculation to steady state is highly dynamic despite the absence of an adaptive immune response. To recapitulate the multiphasic viral kinetic patterns, we developed an agent-based model that includes intracellular virion production cycles reflecting the cyclic nature of each individual virus lifecycle. The model fits the data well predicting an increase in production cycles initially starting with a long production cycle of 1 virion per 20 hours that gradually reaches 1 virion per hour after approximately 3–4 days before virion production increases dramatically to reach to a steady state rate of 4 virions per hour per cell. Together, modeling suggests that it is the cyclic nature of the virus lifecycle combined with an initial slow but increasing rate of HBV production from each cell that plays a role in generating the observed multiphasic HBV kinetic patterns in humanized mice.

59 BASIC BIOLOGICAL SCIENCES↗

Thermal equation of state of ice-VII revisited by single-crystal X-ray diffraction

Abstract Ice-VII is a high-pressure polymorph of H2O ice and an important mineral widely present in many planetary environments, such as in the interiors of large icy planetary bodies, within some cold subducted slabs, and in diamonds of deep origin as mineral inclusions. However, its stability at high pressures and high temperatures and thermoelastic properties are still under debate. In this study, we synthesized ice-VII single crystals in externally heated diamond-anvil cells and conducted single-crystal X-ray diffraction experiments up to 78 GPa and 1000 K to revisit the high-pressure and high-temperature phase stability and thermoelastic properties of ice-VII. No obvious unit-cell volume discontinuity or strain anomaly of the high-pressure ice was observed up to the highest achieved pressures and temperatures. The volume-pressure-temperature data were fitted to a high-temperature Birch-Murnaghan equation of state formalism, yielding bulk modulus KT0 = 21.0(4) GPa, its first pressure derivative KT0′ = 4.45(6), dK/dT = –0.009(4) GPa/K, and thermal expansion relation αT = 15(5) × 10–5 + 15(8) × 10–8 × (T – 300) K–1. The determined phase stability and thermoelastic properties of ice-VII can be used to model the inner structure of icy cosmic bodies. Combined with the thermoelastic properties of diamonds, we can reconstruct the isomeke P-T paths of ice-VII inclusions in diamond from depth, offering clues on the water-rich regions in Earth’s deep mantle and the formation environments of those diamonds.

Geochemistry & Geophysics↗

Constraints on Neutrino Oscillation Parameters from Neutrinos and Antineutrinos with Machine Learning

NOvA is a two detector, long baseline neutrino oscillation experiment measuring the oscillations of muon neutrinos from the \numi neutrino beam over a baseline of \SI{810}{km}. The experiment uses four oscillation channels, $\numu \rightarrow \numu$, $\numubar \rightarrow \numubar$, $\numu \rightarrow \nue$, and $\numubar \rightarrow \nuebar$, with a peak neutrino energy of \SI{1.8}{GeV}. This dissertation describes the analysis of these channels using a dataset of $13.6\times10^{20}$ protons on target neutrino beam mode and $12.5\times10^{20}$ protons on target antineutrino beam mode. The analysis makes use of improvements in the treatment of systematic uncertainties and machine learning techniques to reconstruct neutrino interactions. A technique for decorrelating systematic errors using principle component analysis was utilized to reduce and optimize neutrino cross section and beam related uncertainties. The improved machine learning algorithms make use of convolutional ne ural net works for neutrino event classification, particle classification, and instance segmentation. The selection of neutrino signal events utilizing the neutrino event classifier shows an efficiency of 63\% for the selection of electron neutrinos in neutrino beam mode and 75\% for electron antineutrinos in antineutrino beam mode. Using this algorithm, 82 appearing electron neutrino candidates and 33 appearing electron antineutrino candidates were observed with expected backgrounds of 26.8 and 14.0 respectively. In addition, 211 surviving muon neutrino candidates and 105 muon antineutrino candidates were identified with a purity of more than 96\% using the same neutrino event classifier. Fitting these data to the three flavor neutrino oscillation model, using constraints on \thetaonetwo, \thetaonethree, and \dmsqonetwo from solar and reactor neutrino experiments, the oscillation parameters are measured to be $\sintwothree = 0.57^{+0.04}_{-0.03}$, $\dmsqthreetwo = \SI[parse-numbers= false]{+ 2.41\pm0.07 \times 10^{-3}}{eV^2}$, and $\dcp=0.82^{+0.27}_{-0.87}\pi$ with a preference for the normal neutrino mass hierarchy. Leading systematic uncertainties for these measurements come from detector calibration and neutrino interaction models.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

BISON microstructure-based pulverization criterion in high burnup structure

To improve the economics of commercial nuclear power production, utilities are seeking to increase the allowable burnup limit of UO$_2$ fuel. One of the main factors that contributes to the current burnup limit of 62 GWd/MTU in commercial light water reactors (LWRs) is the risk of fine fragmentation or pulverization during a loss of coolant accident (LOCA). Pulverization primarily occurs at high burnups, especially when the high burnup structure (HBS) has formed. To allow the industry to pursue increased burnup and develop mitigation strategies, it is essential to have improved capability to predict the onset of pulverization. However, the mechanism of pulverization is not well understood, and the existing predictive capabilities implemented in the BISON fuel performance code are empirical in nature. In this report, mesoscale simulations are used to improve understanding of the formation mechanism of the HBS and how it responds during a LOCA transient, and inform development of a BISON pulverization criterion. A phase-field model was used to simulate the evolution of bubble pressure as a result of HBS formation. The simulations showed that gas atoms diffuse from grain interiors to the new grain boundaries created during HBS formation, and diffuse rapidly along these grain boundaries to reach existing bubbles. This causes an increase in bubble pressure in existing bubbles, leading to bubble growth during steady-state operation. To simulate the response of HBS bubbles to a LOCA transient, a newly developed phase-field model was used; in agreement with preliminary results from FY20, bubble size did not change significantly during the duration of the transient. A phase-field fracture model was used to study fragmentation patterns in the HBS, including using input from the phase-field model as initial conditions. Phase-field fracture simulations were used to determine a pulverization criterion for BISON. A function for the critical pressure for pulverization to occur was fit to data from the phase-field fracture simulations, and this function was implemented as a material property in BISON. For comparison, an analytical criterion for pulverization was developed and implemented within the same material property.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Perovskite Sorbent Oxygen Separation Modeling with MFiX

This document chronicles the development and implementation of computational kinetic rate models that capture absorption and desorption characteristics of the National Energy Technology Laboratory (NETL) developed perovskite, Sr 1-x Ca x FeO 3-δ . Two paths to create accurate kinetic rates were followed: (1) an isothermal rate approach where thermogravimetric (TGA) data are recast as oxygen capacities through a pseudo-second order Lagergren equation (He et al., 2009); and (2) a more traditional Arrhenius approach where experimental data are fit with a power law model to derive associate activation energies (Bulfin et al., 2020a). For reference, the mathematics and associate experimental strategies that support these derivations are included in this report. In addition, computational fluid dynamics (CFD) models were developed to utilize both kinetic rate formulations and applied to simulate oxygen uptake and release in small scale scenarios. The program Multiphase Flow with interphase eXchanges (MFiX) was used to create: (1) discrete element method (DEM) simulations of a single tube of granular perovskite experiencing isothermal O 2 -absorption; and desorption and (2) two-fluid-model (TFM) non-isothermal simulations of perovskite O 2 -absorption and desorption tubes that share a wall. Conjugate heat transfer between steel walled tubes and the perovskite bed were managed with user-defined functions. As the project moves to simulating larger scale devices that will require more robust conjugate heat transfer methods, developed kinetic rates and associate methodologies have been recast for use in the ANSYS Fluent CFD program.

36 MATERIALS SCIENCE↗

Finding my drumbeat: applying lessons learned from Remo Ruffini to understanding astrophysical transients [Slides]

Lessons Learned: Bandwagon science can miss key physics; Bandwagon scientists cling to their bandwagon, oftentimes denying fundamental physics; and, Better approach: Be aware of the physical limitations of a paradigm. What assumptions have been made? How can this be different in Nature?; Be cognizant of alternative models; Encourage the development of those models; and, Although validation is important, fundamental physics forms the basis for Occam’s razor, not whether a toy model fits the data well.

79 ASTRONOMY AND ASTROPHYSICS↗

Fuel Performance Analysis of Chromium-Coated Cladding under Burst Conditions

To reduce the oxidation of zirconium-based alloy cladding at high temperatures, accident tolerant fuel systems have been proposed. Of the concepts identified, chromium-coated cladding has been shown to slow oxidation without greatly impacting the fuel system geometry or neutronic performance. To determine how coated-cladding tubes will perform under high-temperature accident conditions, pressurized-tube burst tests have been performed using the Severe Accident Test Station at Oak Ridge National Laboratory. To begin modeling these tubes to better understand how the coating will impact cladding behavior, these burst tests were simulated with the BISON fuel performance code. Cladding tube surface temperatures for the burst test were developed by fitting thermocouple data into axial and azimuthal profiles, while pressure data were compared until cladding failure. The temperatures at failure and the pressure evolution show relatively good agreement between the simulation and experiment results. This is the first step of a larger effort to simulate the cladding deformation process under high-temperature transient conditions and assess the cladding margin to failure more accurately.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Next Generation Solvent Vapor Pressure Testing

Previous work by Savannah River National Laboratory (SRNL) indicated that the actual Next Generation Solvent vapor pressure would be higher than the Original Caustic Side Solvent Extraction (CSSX) solvent vapor pressure, but below a bounding vapor pressure using Raoult’s Law. Since solvent vapor pressure has a significant impact on Composite Lower Flammability Limits (CLFL) and attendant accident analyses, obtaining an additional margin from the bounding NGS vapor pressure would be valuable. In order to quantify how much margin might be gained from the NGS bounding solvent, SRNL researchers were requested to perform vapor pressure testing with the Next Generation Solvent (NGS) by Savannah River Mission Completion (SRMC). The vapor pressure curve for the NGS formulation set to be deployed at the Salt Waste Processing Facility (SWPF) has been determined by SRNL up to 55°C (131°F) using headspace Gas Chromatography (GC). It was expected that NGS would have a higher vapor pressure than the Original CSSX solvent; however, experimental results indicate a lower vapor pressure. At this time, it is uncertain if this difference is due to the 7x increase in concentration of the large calixarene in the solvent (0.007M BOBCalix in Original CSSX solvent vs. 0.05M MaxCalix in NGS) or to minor batch-to-batch variations in Isopar-L constituents. The NGS and the Original CSSX solvent vapor pressure data were fitted to the Antoine Equation. The Antoine equation gives a more accurate representation of the expected vapor pressure of the solvents outside of the temperature range tested. The Antoine equation fitting for NGS is given below: $P=10^{6.364⁻\frac{1788.4}{T+219.3}}$. Where, p is the vapor pressure (partial pressure) of NGS in mmHg and T is the temperature in °C. It is recommended that SRMC either continue using the more conservative Isopar-L vapor pressure calculations at SWPF with the equation developed for the Original CSSX solvent, or the equation presented above for the NGS solvent. Additionally, it is recommended to study the variability in Isopar-L vapor pressure between lots.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

On the Uranium and Plutonium Nuclear Data Evaluations [Slides]

This presentation provides overviews of uraniums, 233 U and 235 U, plutonium research including motivations, current status in ENDF/B-VIII.0, the inclusion of sub-thermal data, and the inclusion of LANL ratio capture-to-fission data. Additionally, the preliminary fit of Mosby’s data as reported, fluctuating neutron multiplicities, uncertainty in evaluated libraries, and experimental effects are also presented. The presentation concludes by providing a summary of plans for the U and Pu evaluation work.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Improving NOvA's Sterile Neutrino Search with the Booster Neutrino Beam

The NOvA experiment’s most recent search for eV-scale sterile neutrinos is systematically limited in the region of parameter space where $\Delta m^2_{41} \gtrsim 1~\mathrm{eV}^2$. This region of parameter space is preferred by sterile neutrino interpretations of current experimental anomalies; improving sensitivity here is high-priority. When added directly into the fit, additional data samples which are subject to orthogonal systematic uncertainties act as in-situ constraints, breaking the degeneracy between systematic uncertainties and sterile-induced oscillations. The NOvA experiment consists of two functionally identical detectors, 14.6 mrad off-axis of the NuMI beam, with the Near Detector (Far Detector) 1 km (810 km) from the beam source. The Near Detector’s position on-site at Fermilab means that it is also able to observe neutrinos from a second neutrino beam, the BNB, 160 mrad off-axis. NOvA has been taking BNB data since 2015, but has not yet analysed these data. The BNB and NuMI are subject to different beam-related uncertainties, allowing us to leverage this sample as an in-situ constraint. This poster will present the current status, preliminary simulations, and potential additional uses of this unique experimental setup

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Determination of Neutrino Oscillation Parameters through the Feldman-Cousins Method by the NOvA Experiment

The NOvA experiment presents new measurements of the neutrino oscillation parameters obtained through a fit to data from the one megawatt NuMI neutrino beam in the NOvA detectors. The analysis uses muon-neutrino disappearance and electron-neutrino appearance in both neutrino and antineutrino beam polarities. With the addition of $\sim$ 100%\) more neutrino-mode beam exposure over the previously reported results, this analysis employs the unified approach of Feldman and Cousins to determine the confidence level intervals for the oscillation parameters $\theta_{23}, \delta_{CP}$, and $\Delta m_{32}^2$ for both neutrino mass orderings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Modeling Approach for the Aluminum-clad Dry Storage Pilot using HFIR Fuel

To confirm that the dry storage of aluminum-clad research reactor spent nuclear fuel (ASNF) will remain within the safety envelope after applied drying schemes and that the resulting evolution of the gas space composition, temperature, and pressure conditions are understood, a dry storage pilot project is being established. The pilot will incorporate an instrumented lid for discrete interval or for on-demand gas composition and temperature monitoring of two DOE Standard Canisters (DSCs) loaded with three High Flux Isotope Reactor (HFIR) inner cores per DSC. Each DSC would be subjected to a separate alternative candidate drying scheme. Canisters will undergo 1 to 5 years of monitoring, including internal temperature and gas sampling to track pressure and composition changes. This report outlines the approach for modeling the ASNF-in-canister behavior in terms of evolving gas space conditions for the ASNF dry storage pilot using HFIR fuel. The ASNF has an adherent surface oxyhydroxide layer comprised of boehmite/bayerite that generates hydrogen when subjected to irradiation. Three-dimensional multi-physics computational fluid dynamics simulations will be executed to compute the thermal field within the DSC and provide inputs to a chemical model employed to compute pressure buildup as hydrogen is generated in the system. Implemented in Cantera, the chemical model solves gas phase and aluminum oxyhydroxide surface-mediated radiolysis reactions. Gas phase reactions are sourced from Wittman and Hanson (2015), whereas surface-mediated reactions are incorporated by fitting experimental data using an optimization algorithm (Abboud, 2023). Water radiolysis reactions from Wren and Ball (2001) are adopted with modifications as described in Abboud (2023c). Understanding the effect of the hydrogen buildup over time is important for long-term storage safety considerations. Modeling results will include the canister pressure, temperature, and composition evolution from the initial helium backfill with the addition of radiolytically-evolved chemical species (e.g., hydrogen and oxygen). The specific HFIR cores for the pilot program have not yet been selected, and the overall design is still in development. The CFD-chemical model used for this work will be based on prior models with necessary updates to allow for improved accuracy and efficiency. The experimental data obtained from the HFIR demonstration will be used to improve and validate the computational models to predict the ASNF-in-canister behavior.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Glass Property-Composition Models Update for use in Direct Feed High-Level Waste Flowsheet Development

A set of preliminary glass property models and constraints were developed and augmented by models from literature for use in design of direct-feed high-level waste (DFHLW) glasses for flowsheet evaluation, testing, and design of the Tank Waste Treatment and Immobilization Plant (WTP) high-level waste (HLW) Facility. These models and constraints are meant to be used as a place-holder while glass property-composition data gaps are filled and final plant operating models are developed. This report describes the motivation and intended use of the models, the compilation of data, model fitting and selection, methods to apply the models and constraints in glass design and offers example calculations demonstrating their intended use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Glass Property-Composition Models Update for use in Direct Feed High-Level Waste Flowsheet Development: EWG3.0

A set of preliminary glass property models and constraints were developed and augmented by models from literature for use in design of Direct Feed High-Level Waste glasses for flowsheet evaluation, testing, and design of the High-Level Waste Facility at the Hanford Waste Treatment and Immobilization Plant. These models and constraints are meant to be used as a placeholder while glass property-composition data gaps are filled and final plant operating models are developed. This report describes the motivation and intended use of the models, the compilation of data, model fitting and selection, and methods to apply the models and constraints in glass design, and offers example calculations demonstrating their intended use.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗