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

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At least 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ranking Biological Features in Soil-Based Microbial Multi-Omics Data with Integration Modeling

Distinguishing the most important features (e.g. proteins, metabolites, etc.) per group (e.g. control and treatment) is a critical challenge in feature-rich multi-omics experiments, especially in soil data. Traditional feature identification and ranking approaches, such as differential expression, are based on single omics and thus not directly translatable to multi-omics experiments. Here, 5 multi-omics integration models (DIABLO, JACA, MOFA, MultiMLP, and SLIDE) that were not explicitly built for soil data applications were tested using a soil-based multi-omics experiment. The data were obtained from an experimental setup of an autoclaved soil system inoculated with 8 bacteria and using chitin as the carbon source and including samples collected at 0- (control), 4-, 8-, and 12-weeks post-inoculation. The omics data included metaproteomics, 16S rRNA sequencing, and LC-MS/MS metabolomics (in positive and negative mode). Each multi-omics integration model was implemented, and top features were compared to differential univariate statistics per omic type, demonstrating that integration approaches cut the potential number of top features from 2957 identified by differential statistics to 13-224 (a 99.6% to 92.4% reduction). Interestingly, most top features across integration models were not shared; though, scaling and averaging ranks across models shared similar patterns. This work highlights the usefulness of multi-omics integration models in soil-based microbial studies and the power of using multiple integration models together to interpret results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Plasma Facing Component Characterization and Correlation With Plasma Conditions in Lithium Tokamak Experiment-β

Lithium coatings in the Lithium Tokamak eXperiment (LTX) led to flat temperature profiles. The flat temperature profiles were observed along with a hot, low density edge, implying a broad, collisionless scrape-off layer (SOL). Additionally, in vacuo X-ray photoelectron spectroscopy (XPS) measurements established that lithium coatings evaporatively deposited onto high-Z plasma facing components (PFCs) became oxidized while retaining the ability to achieve good plasma performance long after lithium was applied to the PFCs. Longstanding theory predicted flat temperature profiles with low recycling walls, which was presumed to be due to hydrogen binding with elemental lithium to form lithium hydride. The presence of oxidized lithium, however, raised questions regarding the exact mechanism of hydrogen retention in LTX. To investigate these questions, the upgraded facility LTX- β includes a new sample exposure probe (SEP) for more detailed in vacuo analysis of PFC samples. The SEP is equipped with a vacuum suitcase capable of transporting samples representative of the LTX- β outer midplane PFCs to a stand-alone XPS system while maintaining pressures lower than the LTX- β base vacuum to limit the contamination between sample exposure and analysis. The low-energy resolution XPS system used in past experiments could only enable the determination of elemental percentages on the PFC sample surfaces. Because the new XPS system has higher energy resolution, it is more direct to assign chemical compounds to the measured binding energies. This capability has been confirmed by comparing XPS data from PFC test samples with measurements using a commercial high-resolution XPS system. Quartz crystal microbalances (QCMs) were used to quantify the thickness of the deposited lithium on the LTX- β PFCs. This article describes the application of the SEP to characterize the PFC surfaces using XPS and their relationship to plasma conditions.

Maan, Anurag↗
DOE OSTI2024

TEAMER: Triton Systems Oscillating Water Column Modeling Data and Report

This dataset provides the output of six Wave Energy Converter Simulator (WEC-Sim) simulations and accompanying documentation for the modeling of Triton Systems' oscillating water column (OWC) system at tank scale (validated using available data for tuning the model, Tests 1-2) and deployment scale (for which no validation data is available, Tests 4-6). Included are the output data in a MATLAB file structure, a comprehensive report on the modeling and design of the Triton OWC system, and a link to the WEC-Sim GitHub page. This work was supported by funding from TEAMER RFTS 5 (Request for Technical Support).

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Rapid, Approximate Multi-Axis Vibration Testing [Thesis]

The aerospace industry uses vibration shaker tables to perform component durability testing. In these tests a component, piece of equipment, or entire system is attached to a shaker table where it is subjected to dynamic excitation. The goal is to understand how the article under test will perform in its service environment without having to run it through its entire service life via field testing. In a vibration test, an aerospace system or component is qualified if it is shown to survive a test meant to replicate its lifetime service conditions. The test is designed based on recorded field data. To develop a test, a system is taken through all of its intended environments, e.g., transportation, launch, and reentry. Acceleration data measured from these environments is then brought back to the lab and imported into a shaker table controller. The controller then drives a vibration test intended to mimic the acceleration conditions experienced by the system or specific components of the system in the field. However, it is often difficult to match the measured field response in a lab test. This is largely due to the test’s boundary conditions and excitation methods. In a lab test, a shaker table is the excitation source. The two most common shaker table types, differentiated by their number of independent degrees of freedom, are single-axis and multi-axis shaker tables. Multi-axis shakers have the ability to reproduce service environments more realistically, as real accelerations inevitably produce multiple degrees of freedom of excitation simultaneously. Figure 1 depicts a generic multi-axis testing setup on a three-axis shaker table. Often multi-axis tests use six-degree-of-freedom (6DOF) shaker tables. Yet multi-axis shakers are not yet common in the aerospace industry due in part to their high cost and the difficulty for shaker controllers to handle the added complexity. Single-axis shaker tables are much more common. They are not as expensive to purchase and have a wide range of control software options.

42 ENGINEERING↗
DOE OSTI2022

An algorithmic approach to predicting mechanical draft cooling tower fan speeds from infrasound signals

Mechanical draft cooling towers (MDCTs) serve a critical heat management role in a variety of industries. For nuclear reactors in particular, the consistent, predictable operation of MDCTs is required to avoid damage to infrastructure and reduce the potential for catastrophic failure. Accurate, reliable measurement of MDCT fan speed is therefore an important maintenance and safety requirement. To that end, we have developed an algorithm for automatically predicting the rotational speeds of multiple, simultaneously operating fan rotors using contactless, infrasound measurements. The algorithm is based on identifying the blade passing frequencies (BPFs), their harmonics, as well as the motor frequencies (MFs) for each fan in operation. Using the algorithm, these frequencies can be automatically identified in the acoustic waveform’s short-time Fourier transform spectrogram. Attribution is aided by a set of filters that rely on the unique spectral and temporal characteristics of fan operation, as well as the intrinsic frequency ratios of the BPF harmonics and the BPF/MF signals. The algorithm was tested against infrasound data acquired from infrasound sensors deployed at two research reactors: the Advanced Test Reactor (ATR) located at Idaho National Laboratory (INL) and the High Flux Isotope Reactor (HFIR) located at Oak Ridge National Laboratory (ORNL). After manually identifying the MDCT gearbox ratio, the algorithm was able to quickly yield fan speeds at both reactors in good agreement with ground truth. Ultimately, this work demonstrates the ease by which MDCT fans may be monitored in order to optimize operational conditions and avoid infrastructure damage.

42 ENGINEERING↗
DOE OSTI2023

Evaluating the impact of wildfire smoke on solar photovoltaic production

There are growing needs to understand how extreme weather events impact the electrical grid. Renewable energy sources such as solar photovoltaics are expanding in use to help sustainably meet electricity demands. Wildfires and, notably, the widespread smoke resulting from them, are one such extreme event that can impair the performance of solar photovoltaics. However, isolating the impact that smoke has on photovoltaic energy production, separate from ambient conditions, can be difficult. In this work, we seek to understand and quantify the impacts of wildfire smoke on solar photovoltaic production within the Western United States. Our analysis focuses on the construction of a random forest regression model to predict overall solar photovoltaic production. The model is used to separate and quantify the impacts of wildfire smoke in particular. To do so, we fuse historical weather, solar photovoltaic energy production, and PM2.5 particulate matter (primary smoke pollutant) data to train and test our model. The additional weather data allows us to capture interactions between wildfire smoke and other ambient conditions, as well as to create a more powerful predictive model capable of better quantifying the impacts of wildfire smoke on its own. We find that solar PV energy production decreases 8.3% on average during high smoke days at PV sites as compared to similar conditions without smoke present. Finally, this work allows us to improve our understanding of the potential impact on photovoltaic-based energy production estimates due to wildfire events and can help inform grid and operational planning as solar photovoltaic penetration levels continue to grow.

14 SOLAR ENERGY↗
DOE OSTI2020

Accelerating quantum optics experiments with statistical learning

Quantum optics experiments, involving the measurement of low-probability photon events, are known to be extremely time-consuming. We present a methodology for accelerating such experiments using physically motivated ansatzes together with simple statistical learning techniques such as Bayesian maximum a posteriori estimation based on few-shot data. We show that it is possible to reconstruct time-dependent data using a small number of detected photons, allowing for fast estimates in under a minute and providing a one-to-two order of magnitude speed-up in data acquisition time. We test our approach using real experimental data to retrieve the second order intensity correlation function, G (2) ($τ$), as a function of time delay τ between detector counts, for thermal light as well as anti-bunched light emitted by a quantum dot driven by periodic laser pulses. The proposed methodology has a wide range of applicability and has the potential to impact the scientific discovery process across a multitude of domains.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A search for cosmogenic neutrinos with the ARIANNA test bed using 4.5 years of data

The primary mission of the ARIANNA ultra-high energy neutrino telescope is to uncover astrophysical sources of neutrinos with energies greater than 10 16 eV. A pilot array, consisting of seven ARIANNA stations located on the surface of the Ross Ice Shelf in Antarctica, was commissioned in November 2014. We report on the search for astrophysical neutrinos using data collected between November 2014 and February 2019. A straight-forward template matching analysis yielded no neutrino candidates, with a signal efficiency of 79%. We find a 90% confidence upper limit on the diffuse neutrino flux of E 2 Φ=1.7× 10 -6 GeV cm -2 s -1 sr -1 for a decade wide logarithmic bin centered at a neutrino energy of 1018,eV, which is an order of magnitude improvement compared to the previous limit reported by the ARIANNA collaboration. The ARIANNA stations, including purpose built cosmic-ray stations at the Moore's Bay site and demonstrator stations at the South Pole, have operated reliably. Sustained operation at two distinct sites confirms that the flexible and adaptable architecture can be deployed in any deep ice, radio quiet environment. We show that the scientific capabilities, technical innovations, and logistical requirements of ARIANNA are sufficiently well understood to serve as the basis for large area radio-based neutrino telescope with a wide field-of-view.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

drtsans

drtsans is highly modular, allowing users to customize collected data as well as test hypothetical or simulated neutron events data. Instrument scientists can use the advance features of drtsans to calibrate their instruments and reduced large quantities of datasets in a streamlined mode. Users can correct the collected data with dark current subtraction and normalization by neutron flux, detector sensitivity, solid angle subtended by the detectors, and scaling to absolute units. Conversion from time-of-flight and/or wavelength to 1D or 2D momentum transfer renders the final scattering quantities amenable to analysis.

Bilheux, JeanC↗
DOE OSTI2020

Water chemistry data and calculations for Fracture Sustainability Tests

Measured cation, anion, and silica are presented as well as calculations evaluating mass balance performed for 4 fracture sustainability tests under EGS conditions: Stripa granite, Metamudstone, Rhyolitic Ashflow Tuff, and Silicified Rhyolitic Tuff. Calculations of charge balance are included for water samples in the 4 tests.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Supercritical CO2 sterilization of N95 Masks

A preliminary investigation of the use of supercritical carbon dioxide for treating of 3M 1860 N95 masks was undertaken to evaluate a potential route to low-cost, scalable, sterilization of personal protective equipment for multiple reuse in hospital settings. Upon entering the supercritical regime, the normally distinct liquid and gaseous phases of CO 2 merge into a single homogeneous phase that has density, short-range order, and solvation capacity of a liquid, but the volume-filling and permeation properties that of a gas. This enables supercritical CO2 to function as a vehicle for delivery of biocidal agents such peracetic acid into microporous structures. The potentially adverse effect of a liquid-to-gas phase transition on mask filter media is avoided by conducting cleaning operations above 31 C, the critical temperature for carbon dioxide. A sample of fifteen 3M 1860 N95 masks was subjected to ten consecutive cycles of supercritical CO 2 cleaning to determine its effect on mask performance. These 15 masks, along with 5 control samples then underwent a battery of standardized tests at the CDC NIOSH NPPTL research facility in Pittsburgh, PA. The data from these tests strongly suggest (but do not prove) that supercritical carbon dioxide do not damage 3M 1860 N95 masks. Additional tests conducted during this project confirmed the compatibility of supercritical CO 2 with ventilator tubing that, like N95 masks, has been in short supply during portions of the COVID-19 pandemic and cannot be sterilized by conventional means. Finally, a control experiment was also conducted to examine the effect of supercritical CO 2 on a BSL-2 surrogate virus, vesicular stomatitis virus (VSV), Indiana serotype strain. In the absence of biocidal additives, supercritical CO 2 exhibited no measurable lethality against VSV. This surrogate virus experiment suggests that a biocidal additive such as peracetic acid will be necessary to achieve required sterilization metrics.

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

A User Guide to PARET/ANL

PARET was originally created in 1969 at what is now Idaho National Laboratory (INL), to analyze reactivity insertion events in research and test reactor cores cooled by light or heavy water, with fuel composed of either plates or pins. The use of PARET is also appropriate for fuel assemblies with curved fuel plates when their radii of curvatures are large with respect to the fuel plate thickness. The PARET/ANL version of the code has been developed at Argonne National Laboratory (ANL) under the sponsorship of the U.S. Department of Energy/NNSA since the inception of the Reactor Conversion Program. Since Reduced Enrichment for Research and Test Reactors (RERTR) began in 1978, PARET/ANL has been benchmarked to experimental data including SPERT testing, and used to determine the expected transient behavior of a large number of reactors regardless of enrichment both inside and outside the Reactor Conversion Program. This document provides the pertinent information for the use of PARET/ANL Version 7.6. PARET/ANL models the various fueled regions of a reactor core as channels. Each of these channels consists of a single flat fuel plate/pin (including cladding and, optionally, a gap) with water coolant on each side. In slab geometry the coolant channels for a given fuel plate are of identical dimensions (mirror symmetry), but they can be of different thickness in each channel. There can be many channels, but each channel is independent and coupled only through reactivity feedback effects to the whole core. The time-dependent differential equations that represent the system are replaced by an equivalent set of finite-difference equations in space and time, which are integrated numerically. PARET/ANL uses fundamentally the same numerical scheme as RELAP5 for the time-integration of the point-kinetics equations. The one-dimensional thermal-hydraulic model includes temperature-dependent thermal properties of the solid materials, such as heat capacity and thermal conductivity, as well as the transient heat production and heat transfer from the fuel meat to the coolant. Temperature- and pressure-dependent thermal properties of the coolant such as enthalpy, density, thermal conductivity, and viscosity are also used in determining parameters such as friction factors and heat transfer coefficients. The code first determines the steady-state solution for the initial state. Then the solution of the transient is obtained by integration in time and space. Multiple heat transfer, DNB and flow instability correlations are available. The code was originally developed to model reactors cooled by an open loop, which was adequate for rapid transients in pool-type cores. An external loop model appropriate for Miniature Neutron Source Reactors (MNSR’s) was also added to PARET/ANL to model natural circulation within the vessel, heat transfer from the vessel to pool and heat loss by evaporation from the pool. PARET/ANL also contains models for decay heat after shutdown, control rod reactivity versus time or position, time-dependent pump flow, and loss-of-flow event with flow reversal as well as logic for trips on period, power, and flow. Feedback reactivity effects from coolant density changes and temperature changes are represented by tables. Feedback reactivity from fuel heat-up (Doppler Effect) is represented by a four-term polynomial in powers of fuel temperature. Photo-neutrons produced in beryllium or in heavy water may be included in the point-kinetics equations by using additional delayed neutron groups.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

A User Guide to PARET/ANL

PARET was originally created in 1969 at what is now Idaho National Laboratory (INL), to analyze reactivity insertion events in research and test reactor cores cooled by light or heavy water, with fuel composed of either plates or pins. The use of PARET is also appropriate for fuel assemblies with curved fuel plates when their radii of curvatures are large with respect to the fuel plate thickness. The PARET/ANL version of the code has been developed at Argonne National Laboratory (ANL) under the sponsorship of the U.S. Department of Energy/NNSA since the inception of the Reactor Conversion Program. Since Reduced Enrichment for Research and Test Reactors (RERTR) began in 1978, PARET/ANL has been benchmarked to experimental data including SPERT testing, and used to determine the expected transient behavior of many reactors both inside and outside the Reactor Conversion Program. This document provides the pertinent information for the use of PARET/ANL Version 7.6.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Validating ENDF/B-VIII.1beta3 with LLNL Pulsed-Sphere Experiments and ICSBEP Benchmarks [Slides]

LPS experiments are not benchmarks but can provide valuable input. 22/1/24 LPS experiments are not benchmarks but can provide valuable input. LPS (run by Denise) help validate nuclear data up to 15 MeV. They test scattering and fission data. They have incomplete uncertainties from 2-8%. I take note when: (1) I see C/E differences above the peak and before late times => 20%. (2) Simulated results between libraries change by => 20% without a good explanation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Efficient Signal Processing in BOTDA: Utilizing PCA and PCA-Based Neural Networks for Temperature Monitoring

This work presents a comparative analysis of the various signal processing techniques used in the Brillouin gain spectrum (BGS) peak estimation. Traditional fitting methods such as Lorentzian curve fitting (LCF) are slow and less effective in noisy data. PCA-based methods were tested on the experimental data: A Euclidian distance-based approach, and a probabilistic deep neural network (PDNN) based approach, both using 5 principal components to represent a single BGS. Both methods significantly reduce computational time with respect to LCF, whereas PDNN offers uncertainty insights along with the parameter value. Measuring a range of temperatures, analyzing accuracy, and speed, it can be concluded that PCA trained PDNN outperforms other methods, and appears to be helpful in scenario where large datasets are generated.

Brillouin optical time domain analysis↗