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

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Modeling DOE Standard Canister Configurations with Updated Surface Chemistry

Road-ready and final disposition packaging configurations for the advanced test reactor (ATR) fuel currently specifies storage within helium backfilled DOE sealed standard canisters. The aluminum cladding of the ATR fuel contains an oxyhydroxide layer of boehmite/bayerite that generates hydrogen when subjected to irradiation. Understanding the effect of this hydrogen buildup over time to important for long term storage considerations. Previous modeling efforts have built a coupled CFD-chemical model to simulate the temperature gas phase concentrations within the DOE sealed standard canisters. These models have coupled the temperature conditions to both the gas phase radiolysis chemistry and the surface chemistry associated with the oxyhydroxide layer. Continued experimental work has identified trends for aluminum surrogate samples with oxyhydroxide layers for tests done at higher dose rates. At low initial doses a fast generation rate of hydrogen occurs which starts to roll over to a lower generation rate as the total dose applied in increased. A previous study created a small-scale chemical model was built to replicate a mini-canister surrogate system at SRNL as well as for the smaller capsule tests performed at INL. The previous iteration of the model utilized step function for its G-values for the hydrogen generation over a 200-year period. This model makes an update to the surface chemistry to account for theorized surface chemistry reactions allowing for oxygen to remain bounded to the oxyhydroxide layer. As additional experiments continue, the kinetic fits may be adjusted to adapt to new data. Three canister configurations are modeled – the base 18-inch, 15-foot DOR standard canister with 30 ATR fuel elements, an 18-inch, 10-foot DOE standard canister with 32 ATR fuel elements and a 24-inch, 10-foot DOE standard canister with 40 ATR fuel elements. In previous reports, the primary sensitivity of the canister conditions was identified as the decay heat of the fuel and the dried condition of the fuel. Only these parameters are studied in the report. For the nominal case with dried fuel, the hydrogen generation is only about 2%, so it is even less than the flammability limit if it were exposed to oxygen. For the densely packed 18-inch case the total hydrogen concentration is only around 4% with the nominal decay heat. For the densely packed 24-inch case the total hydrogen concentration is only 2.5%, roughly 20% higher than the original packing design, and still under flammability conditions if exposed to oxygen.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Robust Vector BOTDA Signal Processing with Probabilistic Machine Learning

This paper presents a novel probabilistic machine learning (PML) framework to estimate the Brillouin frequency shift (BFS) from both Brillouin gain and phase spectra of a vector Brillouin optical time-domain analysis (VBOTDA). The PML framework is used to predict the Brillouin frequency shift (BFS) along the fiber and to assess its predictive uncertainty. We compare the predictions obtained from the proposed PML model with a conventional curve fitting method and evaluate the BFS uncertainty and data processing time for both methods. The proposed method is demonstrated using two BOTDA systems: (i) a BOTDA system with a 10 km sensing fiber and (ii) a vector BOTDA with a 25 km sensing fiber. The PML framework provides a pathway to enhance the VBOTDA system performance.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

WASP-117 b: An Eccentric Hot Saturn as a Future Complex Chemistry Laboratory

We present spectral analysis of the transiting Saturn-mass planet WASP-117 b, observed with the G141 grism of the Hubble Space Telescope's (HST) Wide Field Camera 3. We reduce and fit the extracted spectrum from the raw transmission data using the open-source software Iraclis before performing a fully Bayesian retrieval using the publicly available analysis suite TauREx 3.0. We detect water vapor alongside a layer of fully opaque cloud, retrieving a terminator temperature of T{sub term}=833{sub -156}{sup +260} K. In order to quantify the statistical significance of this detection, we employ the atmospheric detectability index (ADI), deriving a value of ADI = 2.30, which provides positive but not strong evidence against the flat-line model. Due to the eccentric orbit of WASP-117 b, it is likely that chemical and mixing timescales oscillate throughout orbit due to the changing temperature, possibly allowing warmer chemistry to remain visible as the planet begins transit, despite the proximity of its point of ingress to apastron. We present simulated spectra of the planet as would be observed by the future space missions such as the Atmospheric Remote-sensing Infrared Exoplanet Large-survey and the James Webb Space Telescope and show that, despite not being able to probe such chemistry with current HST data, these observatories should make it possible in the not too distant future.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

pyvisco [SWR-22-30]

pyvisco is a Python library that supports the identification of Prony series parameters for linear viscoelastic materials described by a Generalized Maxwell model. The necessary material model parameters are identified by fitting a Prony series to the experimental measurement data. pyvisco allows for the identification of Prony series parameters from experimental data measured in either the frequency-domain (via Dynamic Mechanical Thermal Analysis) or time-domain (via relaxation measurements). The experimental data can be provided as raw measurement sets at different temperatures or as pre-processed master curves. An optional minimization routine is included to reduce the number of Prony elements. This routine is helpful in Finite Element simulations where reducing the computational complexity of the linear viscoelastic material models can shorten the simulation time. See also, https://pypi.org/project/pyvisco/

Springer, Martin↗
DOE OSTI2025

CTN-004: Rubin Observatory Raw Data File Format

At the NSF-DOE Vera C. Rubin Observatory we write data from the LSSTCam and LATISS instruments using FITS format with one file written per detector. Here we discuss the layout of those FITS files and describe the FITS headers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The NuMI Flux Prediction at ICARUS

The Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation experiment seeking to probe fundamental symmetries within the structure of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) mixing matrix, and perform precision measurements its parameters including the neutrino mass ordering via the sign of $\Delta m^2_{31}$, and the charge-parity violating phase, $\delta_{CP}$. To make these measurements with high precision, DUNE will require external $\nu$-Ar scattering cross section data as a crucial input to the oscillation fit. Imaging Cosmic And Rare Underground Signals (ICARUS) is a 476 t liquid argon neutrino detector located at Fermi National Accelerator Laboratory (FNAL) where it is serving as the far detector for the Short-Baseline Neutrino (SBN) program along the Booster Neutrino Beam (BNB) axis. ICARUS additionally lies 795 m downstream and 100.1 mrad off-axis of the Neutrinos at the Main Injector (NuMI) neutrino beam. From this position, ICARUS is exposed to a large flux of NuMI (anti-)electron and (anti-)muon neutrinos, and poses a unique opportunity to provide high-statistics measurements of quasi-elastic and single pion-production cross sections for four neutrino flavors ($\nu_{\mu}$, $\nu_{e}$, $\bar{\nu}_{\mu}$, $\bar{\nu}_{e}$). This dissertation is centered around accurately characterizing the models and estimating their precision for use in making these measurements. This includes identifying major sources of uncertainty in the models such that they can be properly propagated to the cross section measurements. Specifically, this work focused on the model of the NuMI beamline and its impact on the neutrino fluxes, but also delved into the detector response model and its impact on reconstructed observables in the detector. Significant efforts were made to improve the characterization to enhance precision and thus reduce the level of propagated uncertainty. In particular, the NuMI flux was determined to be composed of 57% $\nu_{\mu}$, 38% $\bar{\nu}_{\mu}$, 3% $\nu_{e}$, and 2% $\bar{\nu}_{e}$ while the horns are operating in the positive-particle focusing configuration. The total uncertainty on the $\nu_{\mu} + \bar{\nu}_{\mu}$ ($\nu_{e} + \bar{\nu}_{e}$) flux while operating in the forward horn operating mode was determined to be 10.84% (9.04%). Compared to the on-axis flux, mesons that eventually decay to neutrinos more frequently reinteract within the NuMI structure, resulting in elevated uncertainty as these processes are not well-constrained by existing hadron interaction cross section measurements. Covariance matrices were calculated to propagate the flux uncertainty characterization to NuMI analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Evaluation of the Simplified Assessment Peak Equivalent Stress Design Limit Probability of Failure

The ASME Boiler and Pressure Vessel Code Section III Division 5 Subsection HH Subpart A (HHA) outlines requirements and qualification methods for graphite core components in high temperature reactor environments. One such structural qualification method is the Simplified Assessment outlined in HHA-3220, which represents a comparison of service level specific equivalent stresses to allowable stress values derived from target probability of failures (POFs). The target POF is based on the structural reliability class (SRC) for the components and service condition of interest, and is used to establish design limits for combined membrane and peak equivalent stresses. Combined membrane stress limits are derived from two parameter Weibull distribution fits of the graphite grade specific tensile strength data and the target POF. The combined membrane stress limits are then scaled based on the ratio of flexural strength to tensile strength (referred hereinafter as Rtf) to establish the corresponding peak equivalent stress limits. It is desired that the target POF is at least maintained for both combined membrane and peak equivalent design limits, especially with the use of Rtf. The assessment presented herein examines tensile and flexural data for medium and fine grade graphites relative to the calculated combined membrane and peak equivalent stress limits per HHA-3220 and illustrates the simplified assessment method results in anticipated, or at least conservative, peak equivalent design stress limits.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

First Estimation of Model Parameters for Neutrino-Induced Nucleon Knockout Using Simulation-Based Inference

To enable an accurate determination of oscillation parameters, accelerator-based neutrino experiments require detailed simulations of nuclear interaction physics in the GeV regime. While substantial effort from both theory and experiment is currently being invested to improve the fidelity of these simulations, their present deficiencies typically oblige experimental collaborations to resort to empirical tuning of simulation model parameters. As the precision requirements of the field continue to become more stringent, machine learning techniques may provide a powerful means of handling corresponding growth in the complexity of future neutrino interaction model tuning exercises. To study the suitability of simulation-based inference (SBI) for this physics application, in this paper we revisit a tuned configuration of the GENIE neutrino event generator that was originally developed by the MicroBooNE collaboration. Despite closely reproducing the adopted values of four physics parameters when confronted with the tuned cross-section predictions as input, we find that our trained SBI algorithm prefers modestly different values (within MicroBooNE's assigned uncertainties) and achieves slightly better goodness-of-fit when inference is run on the experimental data set originally used by MicroBooNE. We also find that our trained algorithm can create a fair approximation of an alternative neutrino scattering simulation, NuWro, that shares only a subset of its physics model parameters with GENIE.

Tame-Narvaez, Karla [Fermilab] (ORCID:000000022249↗
DOE OSTI2026

Simulation and Experimental Validation of an Integrated Heat Pump – Thermal Energy Storage Using a Room-Temperature Phase Change Material

As the dependence on electrical heat pumps (HPs) and intermittent renewables increases, grid strains are expected to grow. This necessitates an energy storage system to reduce the mismatch between energy supply and demand. Thus, a proposed dual-mode commercially available 14.1 kW HP was integrated with a single 22°C phase change material (PCM) thermal storage system (TES) to load-shift both cooling and heating loads. The HP-TES system was manufactured and experimentally tested using a novel test matrix based on AHRI 210/240 psychrometric conditions. Furthermore, transient dual-mode system-level HP-TES models were developed in Modelica and validated using the experimental test conditions. Base HP cooling and heating experimental tests at ambient temperatures of 35°C and −8.3°C show that the modified HP-TES maintained the rated system capacity and performance. The HP-TES discharge provided approximately 30% and 50% reductions in cooling and heating demand, respectively. The transient HP-TES models predicted system capacity and total power input for discharge and recharge operating modes within ±4% mean percentage error, and recharge power input within ±2%, with maximum errors occurring at the equipment startup. During system operation, the sources of model deviations are first-order polynomial fits of the PCM digital scanning calorimetry (DSC) data and unaccounted supercooling in the PCM during solidification. Nonetheless, the model predictions agree with the experimental tests, demonstrating the availability of robust, accurate, and validated transient models that can be used for further validation and the development of system controls.

25 ENERGY STORAGE↗
DOE OSTI2020

Identifying DQ-Domain Admittance Models of a 2.3-MVA Commercial Grid-Following Inverter Via Frequency-Domain and Time-Domain Data

Here, we present two methods to identify the admittance of a 2.3-MVA commercial grid-following inverter through frequency-domain data and time-domain data. In addition to the well-known harmonic injection method to obtain the admittance at frequency points followed by vector fitting, we adopt a step response-based method where the step response data of the converter are collected and their s-domain expressions are obtained. In turn, the s-domain admittance model of the converter is found. The two methods can be used for cross validation. Step responses and frequency-domain responses obtained from the two methods are compared. Results show that the time- domain data-based method leads to an admittance comparable with that from the frequency-domain measurement in the range less than 60 Hz. In addition, two insights are obtained from the frequency-domain admittance measurements. First, when the dq- frame is aligned to the point of common coupling (PCC) voltage, the per unit DQ-domain admittance directly reflects operating conditions. Second, existence of negative-sequence control can be detected via sequence-domain admittances.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Leaf gas exchange (BNL-PNNL collaboration), San Lorenzo, Panama, 2020

This data package contains Photosynthetic CO2 response (ACi curves) and Light Response (AQ) of mature sunlit canopy leaves of 11 species from PA-SLZ, February 2020. Branches were cut from the top of the canopy and re-cut under water. Fitted Vcmax and Jmax photosynthetic parameters were derived from measured data as well as the convexity, light use efficiency and apparent quantum yield. This data was collected as a collaboration between Brookhaven National Laboratory (BNL) and Pacific Northwest National Laboratory (PNNL), and is a subset of the 2020 BNL Panama campaign. The species included in this dataset are: Apeiba membranacea, Carapa guianensis, Cespedesia spathulate, Jacaranda copaia, Lonchocarpus heptaphyllus, Pera arboea, Pourouma bicolore, Symphonia globulifera, Tachigali versicolor, Tapirira guianensis, and Virola sebifera. The files included in this data package are in .csv and .pdf format, with two Excel files containing additional metadata.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Inference of the linear matter power spectrum at z = 0 using DESI DR1 Full-Shape data

Measurements of galaxy distributions at large cosmic distances capture clustering from the past. In this study, we use a cosmological model to translate these observations into the present-day galaxy distribution. Specifically, we reconstruct the 3D linear matter power spectrum at redshift z = 0 using Dark Energy Spectroscopic Instrument (DESI) Year 1 (DR1) galaxy clustering data and Cosmic Microwave Background (CMB) observations, assuming the ΛCDM model, and compare it to the result assuming the w 0 w a CDM model. Building on previous state-of-the-art methods, we apply Effective Field Theory (EFT) modelling of the galaxy power spectrum to account for small-scale effects in the 2-point statistics of galaxy data. Implementation of the EFT approach improves the modelling of the galaxy power spectrum, providing a more robust consistency test of the assumed cosmological model. By casting both CMB and galaxy clustering observations, spanning distinct redshift regimes, into k-space, we can identify discrepancies between the datasets of different redshifts, which would indicate potential inaccuracies in the assumed expansion history. While previous studies have shown consistency with ΛCDM, this work extends the analysis with higher-quality data to further test the expansion histories of both ΛCDM and w 0 w a CDM. Our findings show that both ΛCDM and w 0 w a CDM provide consistent fits to the linear matter power spectrum recovered from DESI DR1 data.

cosmological parameters from LSS↗
DOE OSTI2020

Search for new non-resonant phenomena in high-mass dilepton final states with the ATLAS detector

A search for new physics with non-resonant signals in dielectron and dimuon final states in the mass range above 2 TeV is presented. This is the first search for non-resonant signals in dilepton final states at the LHC to use a background estimate from the data. The data, corresponding to an integrated luminosity of 139 fb –1 , were recorded by the ATLAS experiment in proton-proton collisions at a center-of-mass energy of √s = 13 TeV during Run 2 of the Large Hadron Collider. The benchmark signal signature is a two-quark and two-lepton contact interaction, which would enhance the dilepton event rate at the TeV mass scale. To model the contribution from background processes a functional form is fit to the dilepton invariant-mass spectra in data in a mass region below the region of interest. It is then extrapolated to a high-mass signal region to obtain the expected background there. No significant deviation from the expected background is observed in the data. Upper limits at 95% CL on the number of events and the visible cross-section times branching fraction for processes involving new physics are provided. Observed (expected) 95% CL lower limits on the contact interaction energy scale reach 35.8 (37.6) TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Predicting RNA structure and dynamics with deep learning and solution scattering

Advanced deep learning and statistical methods can predict structural models for RNA molecules. However, RNAs are flexible, and it remains difficult to describe their macromolecular conformations in solutions where varying conditions can induce conformational changes. Small-angle x-ray scattering (SAXS) in solution is an efficient technique to validate structural predictions by comparing the experimental SAXS profile with those calculated from predicted structures. There are two main challenges in comparing SAXS profiles to RNA structures: the absence of cations essential for stability and charge neutralization in predicted structures and the inadequacy of a single structure to represent RNA’s conformational plasticity. We introduce a solution conformation predictor for RNA (SCOPER) to address these challenges. This pipeline integrates kinematics-based conformational sampling with the innovative deep learning model, IonNet, designed for predicting Mg 2+ ion binding sites. Validated through benchmarking against 14 experimental data sets, SCOPER significantly improved the quality of SAXS profile fits by including Mg 2+ ions and sampling of conformational plasticity. We observe that an increased content of monovalent and bivalent ions leads to decreased RNA plasticity. Therefore, carefully adjusting the plasticity and ion density is crucial to avoid overfitting experimental SAXS data. SCOPER is an efficient tool for accurately validating the solution state of RNAs given an initial, sufficiently accurate structure and provides the corrected atomistic model, including ions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Blood flow imaging by optimal matching of computational fluid dynamics to 4D-flow data

Three-dimensional, time-resolved blood flow measurement (4D-flow) is a powerful research and clinical tool, but improved resolution and scan times are needed. Therefore, this study aims to (1) present a postprocessing framework for optimization-driven simulation-based flow imaging, called 4D-flow High-resolution Imaging with a priori Knowledge Incorporating the Navier-Stokes equations and the discontinuous Galerkin method (4D-flow HIKING), (2) investigate the framework in synthetic tests, (3) perform phantom validation using laser particle imaging velocimetry, and (4) demonstrate the use of the framework in vivo. An optimizing computational fluid dynamics solver including adjoint-based optimization was developed to fit computational fluid dynamics solutions to 4D-flow data. Synthetic tests were performed in 2D, and phantom validation was performed with pulsatile flow. Reference velocity data were acquired using particle imaging velocimetry, and 4D-flow data were acquired at 1.5 T. In vivo testing was performed on intracranial arteries in a healthy volunteer at 7 T, with 2D flow as the reference. Results Synthetic tests showed low error (0.4%-0.7%). Phantom validation showed improved agreement with laser particle imaging velocimetry compared with input 4D-flow in the horizontal (mean -0.05 vs -1.11 cm/s, P < .001; SD 1.86 vs 4.26 cm/s, P < .001) and vertical directions (mean 0.05 vs -0.04 cm/s, P = .29; SD 1.36 vs 3.95 cm/s, P < .001). In vivo data show a reduction in flow rate error from 14% to 3.5%. Phantom and in vivo results from 4D-flow HIKING show promise for future applications with higher resolution, shorter scan times, and accurate quantification of physiological parameters.

4D-flow MRI↗
DOE OSTI2020

A generalized forward fit for neutron detectors with energy-dependent response functions

To date, most analysis of neutron time-of-flight data from inertial confinement fusion experiments has focused on the relatively small range of energies corresponding to the primary neutrons from DD and DT fusion, and have therefore employed instrument response functions (IRF’s) corresponding to monoenergetic 2.45-MeV or 14.03-MeV neutrons. For analysis of time-of-flight signals corresponding to broader ranges of neutron energies, accurate treatment of the data requires the use of an energy-dependent IRF. Here, this work describes interpolation of the IRF for neutrons of arbitrary energy, construction of an energy-dependent IRF, and application of this IRF in a forward fit via matrix multiplication. As an example of the application of this method, an analysis of synthetic data relevant to TT fusion experiments at the Omega Laser Facility is discussed. This example is used to illustrate the differences between a forward fit that uses an energy-dependent IRF and a forward fit that uses a monoenergetic IRF. Use of the energy-dependent IRF is shown to result in accurate inference of the fit parameters of interest.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Bridging the Gap between the X-ray Absorption Spectroscopy and the Computational Catalysis Communities in Heterogeneous Catalysis: A Perspective on the Current and Future Research Directions

X-ray absorption spectroscopy (XAS) [extended X-ray absorption fine structure (EXAFS) and X-ray absorption near-edge structure (XANES)] is a key technique within the heterogeneous catalysis community to probe the structure and properties of the active site(s) for a diverse range of catalytic materials. Furthermore, the interpretation of the raw experimental data to derive an atomistic picture of the catalyst requires modeling and analysis; the EXAFS data are compared to a model, and a goodness of fit parameter is used to judge the best fit. This EXAFS modeling can often be nontrivial and time-consuming; overcoming or improving these limitations remains a central challenge for the community. Considering these limitations, this Perspective highlights how recent developments in analysis software, increased availability of reliable computational models, and application of data science tools can be used to improve the speed, accuracy, and reliability of EXAFS interpretation. In particular, we emphasize the advantages of combining theory and EXAFS as a unified technique that should be treated as a standard (when applicable) to identify catalytic sites and not two separate complementary methods. Building on the recent trends in the computational catalysis community, we also present a community-driven approach to adopt FAIR Guiding Principles for the collection, analysis, dissemination, and storage of XAS data. Written with both the experimental and theory audience in mind, we provide a unified roadmap to foster collaborations between the two communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The miniJPAS survey: White dwarf science with 56 optical filters

We analyze the white dwarf population in miniJPAS, the first square degree observed with 56 medium-band, 145 Å in width optical filters by the Javalambre Physics of the accelerating Universe Astrophysical Survey (J-PAS), to provide a data-based forecast for the white dwarf science with low-resolution ($R$ ~ 50) photo-spectra. We define the sample of the bluest point-like sources in miniJPAS with $r$ < 21.5 mag, a point-like probability larger than 0.5, ($u$ - $r$)< 0.80 mag, and ($g$ - $i$)< 0.25 mag. This sample comprises 33 sources with spectroscopic information: 11 white dwarfs and 22 quasi-stellar objects (QSOs). We estimate the effective temperature ($T$ eff ), the surface gravity, and the composition of the white dwarf population by a Bayesian fitting to the observed photo-spectra. The miniJPAS data are sensitive to the Balmer series and the presence of polluting metals. Our results, combined with those from the Javalambre Photometric Local Universe Survey (J-PLUS) which has a lower spectral resolution but has already observed thousands of white dwarfs, suggest that J-PAS photometry would permit – down to $r$ ~ 21.5 mag and at least for sources with 7000 < $T$ eff < 22 000 K – both the classification of the observed white dwarfs into H-dominated and He-dominated with 99% confidence and the detection of calcium absorption for equivalent widths larger than 15 Å. The effective temperature is estimated with a 2% uncertainty, which is close to the 1% from spectroscopy. A precise estimation of the surface gravity depends on the available parallax information. In addition, the white dwarf population at $T$ eff > 7000 K can be segregated from the bluest extragalactic QSOs, providing a clean sample based on optical photometry alone. The J-PAS low-resolution photo-spectra would produce precise effective temperatures and atmospheric compositions for white dwarfs, complementing the data from Gaia. J-PAS will also detect and characterize new white dwarfs beyond the Gaia magnitude limit, providing faint candidates for spectroscopic follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗