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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Comparative Performance of Three Eye-Tracking Devices in Detection of Mild Traumatic Brain Injury in Acute Versus Chronic Subject Populations

ABSTRACT Introduction Presently, traumatic brain injury (TBI) triage in field settings relies on symptom-based screening tools such as the updated Military Acute Concussion Evaluation. Objective eye-tracking may provide an alternative means of neurotrauma screening due to sensitivity to neurotrauma brain-health changes. Previously, the US Army Medical Research and Development Command Non-Invasive NeuroAssessment Devices (NINAD) Integrated Product Team identified 3 commercially available eye-tracking devices (SyncThink EYE-SYNC, Oculogica EyeBOX, NeuroKinetics IPAS) as meeting criteria toward being operationally effective in the detection of TBI in service members. We compared these devices to assess their relative performance in the classification of mild traumatic brain injury (mTBI) subjects versus normal healthy controls. Materials and Methods Participants 18 to 45 years of age were assigned to Acute mTBI, Chronic mTBI, or Control group per study criteria. Each completed a TBI assessment protocol with all 3 devices counterbalanced across participants. Acute mTBI participants were tested within 72 hours following injury whereas time since last injury for the Chronic mTBI group ranged from months to years. Discriminant analysis was undertaken to determine device classification performance in separating TBI subjects from controls. Area Under the Curves (AUCs) were calculated and used to compare the accuracy of device performance. Device-related factors including data quality, the need to repeat tests, and technical issues experienced were aggregated for reporting. Results A total of 63 participants were recruited as Acute mTBI subjects, 34 as Chronic mTBI subjects, and 119 participants without history of TBI as controls. To maximize outcomes, poorer quality data were excluded from analysis using specific criteria where possible. Final analysis utilized 49 (43 male/6 female, mean [x̅] age = 24.3 years, SD [s] = 5.1) Acute mTBI subjects, and 34 (33 male/1 female, x̅ age = 38.8 years, s = 3.9) Chronic mTBI subjects were age- and gender-matched as closely as possible with Control subjects. AUCs obtained with 80% of total dataset ranged from 0.690 to 0.950 for the Acute Group and from 0.753 to 0.811 for the Chronic mTBI group. Validation with the remaining 20% of dataset produced AUCs ranging from 0.600 to 0.750 for Acute mTBI group and 0.490 to 0.571 for the Chronic mTBI group. Conclusions Potential eye-tracking detection of mTBI, per training model outcomes, ranged from acceptable to excellent for the Acute mTBI group; however, it was less consistent for the Chronic mTBI group. The self-imposed targeted performance (AUC of 0.850) appears achievable, but further device improvements and research are necessary. Discriminant analysis models differed for the Acute versus Chronic mTBI groups, suggesting performance differences in eye-tracking. Although eye-tracking demonstrated sensitivity in the Chronic group, a more rigorous and/or longitudinal study design is required to evaluate this observation. mTBI injuries were not controlled for this study, potentially reducing eye-tracking assessment sensitivity. Overall, these findings indicate that while eye-tracking remains a viable means of mTBI screening, device-specific variability in data quality, length of testing, and ease of use must be addressed to achieve NINAD objectives and DoD implementation.

General & Internal Medicine↗
DOE OSTI2022

Dataset for 'Ombadi, M. & Varadharajan, C. (2022). Urbanization and aridity mediate distinct salinity response to floods in rivers and streams across the Contiguous United States, Water Research'

This package contains data sets and code used to obtain the results in Ombadi, M., & Varadharajan, C. (2022). Urbanization and aridity mediate distinct salinity response to floods in rivers and streams across the Contiguous United States. Water Research, 118664. The folder "data" contains 259 .csv files, each of which has daily time series of concurrent streamflow (Q) and specific conductance (SC) for each of the sites used in this study originally downloaded from the USGS National Water Information System (NWIS; USGS, 2016). The number of data points in each of the files is at least 3650 (i.e. 10 years of daily measurements). The folder "RF_single_data" contains 259 .csv files, each of which include data used to train and test the Random Forest models at individual sites for predicting SC during days of floods. The folder "RF_regional_data" contains 3 .csv files, each of which include scaled data compiled from all sites within each climate zone (arid, temperate and wet). "metadata.csv" contains the physical properties of the 259 catchments corresponding to the sites used in this study; this data was extracted from GAGES-II dataset (Falcone et al., 2010). "RF_implementation.ipynb" is a Jupyter notebook with the code needed to implement the analysis using Random Forest models either for individual sites or for the regional models (for each climate zone). The code utilizes the data in the two folders: "RF_single_data" and "RF_regional_data" and the metadata.csv file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Using Low-Cost “Garage Band” Recording Technology for Acquiring High Resolution High-Speed Data

The Oak Ridge National Laboratory (ORNL) has developed and tested a novel system architecture for acquiring high fidelity high-speed data. The approach uses a consumer grade audio recording device that is normally associated with “garage band” recording of music. ORNL has coupled this low-cost data acquisition hardware with computing technology running open-source software. The main advantage of this approach is per-channel cost; an instrument grade data acquisition system typically costs between $800 to $2000 per channel compared to less than $50 per channel for these consumer grade components. Three systems, each featuring four channels, have been deployed for acquiring data from geophones and the electrical supply system that supports the High Flux Isotope Reactor (HFIR) and the Radiochemical Engineering Development Center (REDC) at ORNL. Each channel samples at 96 kHz at 24-bit resolution. The deployed systems operate continuously 24/7 and produce about 4 terabytes of data per month per system. This paper provides a technical overview of this approach, its implementation, and some preliminary results from qualification testing. This work was conducted in support of the Multi-Informatics for Nuclear Operations Scenarios (MINOS).Keywords: Data acquisition Measurement Informatics

Wetherington Jr, G↗
DOE OSTI2024

Glass-contact refractory of the nuclear waste vitrification melters in the United States: a review of corrosion data and melter life

The performance of the refractory lining in glass melters used for nuclear waste vitrification is critical to the melter reliability for long-term continuous operation. Monofrax® K-3, a high Cr 2 O 3 fused cast refractory material, has been widely used to build the liners of nuclear waste glass melters in the United States. Corrosion behaviour of Monofrax® K-3 refractory has been evaluated based on crucible-scale testing, inspection of the refractory components following scaled melter testing, and inspections of the Defense Waste Processing Facility (DWPF) melter refractory after service. The literature generally consists of empirical models based on short-term testing to describe refractory corrosion dependence on glass composition. Corrosion data from tests with longer testing times, at various temperatures, in the presence of molten salts, and with different redox reactions in the plenum atmosphere exist, may be insufficient to provide accurate refractory service life estimates. Additionally, the corrosion data collected under actual and scaled melter operating conditions are limited. Recommendations to achieve more direct correlation between the laboratory refractory corrosion data predictions and the observed melter service life are discussed to allow for more accurate predictions of the useful life of melter refractory linings.

Jin, Tongan↗
DOE OSTI2023

A Review of the Infrasonic Yield-Period Relation and Some Additional Comments on Observed Azimuth Deviations

In this report we will review the empirically derived infrasonic yield-period relation for atmospheric nuclear explosions. Data came from infrasonic arrays operated by the US Government during the period of atmospheric testing. Only US tests with announced yields will be discussed, and data presented here does not cover every US test because the observed periods came from a set of old Air Force Technical Applications Center (AFTAC) technical memos (TM). The TMs reported the average periods used to obtain a yield-period relation and we use those periods here; the period data from three of the Test Operations are in declassified reports, (see WT reports in References). In addition our analysis employs the announced unclassified yields.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2022

Common Information Model for Electromagnetic Transients (CIM for EMT): CRADA 533 [Abstract only}

The control and protection functions of inverter-based resources (IBR) have raised concerns with bulk system reliability. Most of the current interest lies with solar photovoltaic generation but increasing amounts of storage would pose the same risks. Newer North American Electric Reliability Corporation (NERC) guidelines call for electromagnetic transient (EMT) studies of IBR and recommend that transmission operators collect distributed energy resource (DER) data to support such modeling. IEEE Standard P2800.1 is defining tests for model parameterization, so good model data should become available from inverter vendors. (EMT studies also apply to large power transformer reliability, and transformer vendors can provide EMT models.) Utilities don’t currently have the rest of the bulk system represented for EMT studies at large scale. An International Electrotechnical Commission (IEC) standard Common Information Model (CIM) provides a way of supporting these detailed models from physical asset data, e.g., conductors, towers, transformer data sheets, control block diagrams, while avoiding software vendor lock-in. CIM-for-EMT, with proposed schema extensions and open-source converters, provides a way to exchange EMT data between organizations and tools. This project leverages Office of Electricity (OE) funding of CIM-for-EMT code base through the GridAPPS-DTM project, and of GridPACKTM (parallelized transmission solver), for interoperability testing in CIM-for-EMT. The project also leverages partner PGSTech investments in EMTP® interoperability with CIM.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Assessment of frequency and amplitude dependence on the cyclic degradation of polyurethane foams

Many energy absorption applications utilize flexible polymeric foams for their viscoelastic properties. It is desired that the material will perform consistently across repeated compression cycles. This study examines the effect of fatigue at low strain rates on the viscoelasticity of open-cell polyurethane foam. Six polyurethanes of the same base composition with two porosities (70% and 80%) and three chemical indexes (79i, 100i, and 121i) are tested. Large deformation cyclic compression of the foams is conducted on a universal testing system (UTS). These data are then post-processed leveraging dynamic mechanical analysis Fourier transform rheology to characterize changes in the viscoelasticity of the materials over fatigue cycles. Results show that foams can increase or decrease in stiffness up to 10% over 10 4 cycles. Specifically, higher chemical index, higher excitation frequency, and larger excitation amplitude correlate with a more pronounced decrease in stiffness. Damping can also change by 15% and correlates with chemical index and excitation frequency. Consequently, the findings suggest that internal foam structure and bulk material properties as well as applied loading parameters affect the viscoelastic fatigue response of flexible polymeric foams.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deterministic incident-wave elevation prediction in intermediate water depth

Potential performance gains from optimal (non-causal) impedance-matching control of wave energy devices in irregular ocean waves are dependent on deterministic wave elevation prediction techniques that work well in practical applications. Although a number of devices are designed for operation in intermediate water depths, little work has been reported on deterministic wave prediction in such depths. Here, we investigated a deterministic wave-prediction technique based on an approximate propagation model that leads to an analytical formulation, which may be convenient to implement in practice. To improve accuracy, an approach to combine predictions based on multiple up-wave measurement points is evaluated. The overall method is tested using experimental time-series measurements recorded in the U.S. Navy MASK basin in Carderock, MD, USA. For comparison, an alternative prediction approach based on Fourier coefficients is also tested with the same data. Comparison of prediction approaches with direct measurements suggest room for improvement. Possible sources of error including tank reflections are estimated, and potential mitigation approaches are discussed.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Predicting System Response at Unmeasured Locations

Traditional techniques to derive dynamic specification for components have a great deal of uncertainty. One of the major sources of uncertainty is that the number of response measurements in the operational system environment is insufficient to determine the component motion. This inadequacy is due to logistical limitations for data recording in field testing and space limitations for accelerometers, strain gages and associated wiring. Available measurements are often some distance from the component and therefore do not represent component motion. Typical straight-line envelopes of these unrepresentative measurements guarantee an increase in the uncertainty. In this paper multiple methods are attempted to expand a sparse set of field test measurements on a system to responses of interest that cannot be measured in the field due to the limitations. Proof of concept is demonstrated on the Modal Analysis Test Vehicle (MATV). The responses of interest, known as “truth responses”, are measured in a system vibration environment along with an optimized sparse set of 30 field responses. Methods to expand the field responses to the truth responses are demonstrated by comparing the acceleration spectral density of the expanded response to the measured response. Two methods utilize a validated finite element model of the MATV. One is developed from purely experiment based frequency response functions of a laboratory pre-test. Finally, these approaches are designed to drastically reduce the uncertainty of the component in-service motion as a basis for developing specifications that are guaranteed to be conservative with a known (instead of unknown) conservatism.

42 ENGINEERING↗
DOE OSTI2025

Machine learning for photovoltaic single axis tracker fault detection and classification

More than 81% of the annual capacity of utility-scale photovoltaic (PV) power plants in the U.S. use single-axis trackers (SATs) due to SATs delivering 4% in capacity factor on average over fixed-array systems. However, SATs are subject to faults, such as software misconfigurations and mechanical failures, resulting in suboptimal tracking. If left undetected, the overall power yield of the PV power plant is reduced significantly. Minimizing downtime and ensuring efficient operation of SATs requires robust detection and diagnosis mechanisms for SAT faults. We present a machine learning framework for implementing real-time SAT fault detection and classification. Our implementation of the proposed framework reliably identifies measurements taken from a test PV system undergoing emulated SAT faults relative to state-of-the-art algorithms and produces nearly zero false positives on our testing days. Code and data are available at https://pvpmc.sandia.gov/tools.

Fault classification↗
DOE OSTI2024

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Aerial drone fleet deployment optimization with endogenous battery replacements for direct delivery of time-sensitive products

Aerial drones offer a distinct potential to reduce the delivery time and energy consumption for the delivery of time-sensitive and small products. However, there is still a need in the relevant industry to understand the performance of drone-based delivery under different business needs and drone operating conditions. We studied a drone deployment optimization problem for direct delivery of time-sensitive products with release dates to customers maintaining a specified time window. This paper presents a new mixed-integer programming model, new valid inequalities, a new greedy heuristic algorithm, and a Genetic algorithm to help business owners optimally schedule and route their drone fleet minimizing the required fleet size, the required number of additional batteries, and total energy consumption. A realistic feature of the optimization method is that instead of replacing the drone battery after each return to the depot, it keeps track of the remaining energy in the drone battery and decides on battery replacements accounting for the drone routing and the user-specified minimum required battery energy. Numerical results based on real data from drone flight tests and prepared food delivery industry provide insights into the effect of different practical drone operating parameters on the required fleet size, the required number of battery replacements, and energy consumption. Here, results demonstrate that the proposed heuristic algorithm substantially outperforms the accelerated CPLEX in runtime while sacrificing the solution quality by a small amount. Additionally, results show that using a mixed fleet of hexacopter and quadcopter drones reduces the total energy consumption by 48.52% compared to using a homogeneous fleet of only hexacopters.

Drone energy consumption↗
DOE OSTI2021

An investigation into the effects of cyclic strain rate on the high cycle and very high cycle fatigue behaviors of wrought and additively manufactured Inconel 718

Additive Manufacturing (AM) has increasingly been used to fabricate parts in aerospace applications, which may require service lives beyond ten-million cycles due to the imposed high loading frequencies. Understanding the very high cycle fatigue (VHCF) behavior of these additive manufactured (AM) parts is an important step towards their design and qualification processes. This study focuses on the high cycle fatigue (HCF) and VHCF behaviors of both wrought and laser beam-powder bed fusion (LB-PBF) fabricated Inconel 718 in machined/polished surface condition, emphasizing on the influence of test frequency (i.e., cyclic strain rate). Uniaxial, fully-reversed force- and stress-controlled fatigue tests were conducted utilizing a servo-hydraulic and an ultrasonic test system operating at 5 Hz and 20 kHz, respectively, on wrought as well as LB-PBF vertically and diagonally built specimens. Fatigue cracks in the majority of the specimens were found to initiate from intra-granular slip bands near or at the surface, which gives rise to strong anisotropy in fatigue resistance in LB-PBF specimens due to the presence of columnar grains along the build directions. Longer fatigue lives were obtained at 20 kHz, which was ascribed to possibly lower-than-intended stresses applied in the ultrasonic tests. The corrected stress-life fatigue data at 20 kHz were found to converge to the one obtained from conventional testing at 5 Hz, implying no effect of cyclic strain rate on the fatigue behavior of Inconel 718 regardless of the fabrication process. The findings of this work confirm the use of ultrasonic fatigue testing to expedite generation of AM materials data to keep up with the current demand; however, the applied stress may need to be corrected.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Modeling reactivity insertion experiments of TRISO particles in NSRR using BISON

This research presents BISON simulations of stress, temperature, and failure probability of tristructural isotropic (TRISO) fuel particles subjected to transient power pulse conditions in the Nuclear Safety Research Reactor (NSRR). We report that by modifying the default elastic properties of the PyC and the UO 2 coefficient of thermal expansion correlation, BISON was found to produce suitable agreement with the observed and independently simulated results when appropriate shape and scale Weibull parameters for SiC failure were chosen. The Weibull parameter effects were also explored within the range of SiC failure and were applied using experimental data from hemispherical crush testing.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A Convolutional Neural Network Model for Battery Capacity Fade Curve Prediction using Early Life Data

Herein, early prediction of battery performance degradation trends can facilitate research of new materials and cell designs, rapid deployment of batteries in real-world applications, timely replacement of batteries in critical applications, and even the secondary use market. In this study, we design a convolutional neural network model to predict the entire battery capacity fade curve - a critical indicator of battery performance degradation - using first 100 cycles of data (~ three weeks of testing). We use the discharge voltage-capacity curves as input to the model and automate the feature extraction process through the convolutional layers of the network. Our approach can predict the per cycle capacity fade rate and rollover cycle (knee point) in the capacity fade curve, which indicate the onset of rapid capacity decay. On the publicly available graphite/LiFePO 4 battery dataset, optimized networks predict the capacity fade curves, rollover cycle, and end of life with 3.7% (worst-case), 19%, and 17% mean absolute percentage errors, respectively.

25 ENERGY STORAGE↗
DOE OSTI2021

Spatial heterogeneity analyses of pore structure and mineral composition of Barnett Shale using X-ray scattering techniques

The spatial heterogeneity of pore structure and mineral composition at mu m to mm scales in mm to cm-sized shale samples complicates the laboratory measurements of porosity & pore size distribution and consequently reservoir quality evaluation. Traditional fluid invasion characterization methods typically take hours to days to get data and can only test relatively small samples (usually 2.54 cm diameter core plugs and mm-sized rock chips). Furthermore, the Xray scattering techniques at the Advanced Photon Source of the Argonne National Laboratory have the capability to non-destructively determine the pore structure and mineral composition of mm x mm area in a short time of seconds and to hold several to hundreds of mm 2 sized sample to conduct large area heterogeneity analysis in the short duration of hours. With the use of ultra-small angle X-ray scattering (USAXS), small-angle X-ray scattering (SAXS), and wide-angle X-ray scattering (WAXS), the porosity, surface area and pore size distribution of two Barnett Shale samples have been mapped out and the mineral compositions are determined qualitatively. Overall, the porosity and pore surface area of the Barnett Shale Sample A over a 36 cm2 area ranges from 1.70 % to 8.13 % and 8.87 m 2 /g to 40.2 m 2 /g respectively. The porosity and surface area of Sample B over a 24 cm 2 area varies from 3.15 % to 11.7 % and 18.3 m 2 /g to 60.2 m 2 /g. In Sample A, the mineral composition shows a shift from carbonate-rich to siliciclastic-rich over a distance of several millimeters. For Sample B, the mineral compositions are mainly siliciclastic and do not show an obvious lithological change. The direct observations of high spatial heterogeneity of pore structure and mineral composition in shale illustrate the utility of integrated X-ray scattering techniques to provide valuable insights into shale studies and reservoir evaluation.

58 GEOSCIENCES↗
DOE OSTI2025

Performance studies of the Mu2e cosmic ray veto detector

The cosmic ray veto (CRV) detector of the Mu2e experiment consists of four layers of plastic scintillation counters that surround the detector solenoid. These counters are embedded with wavelength-shifting fibers and are read out by silicon photomultipliers (SiPMs). The performance of a subset of the CRV counters was studied in a cosmic-ray test stand. Here, using data taken over a two-year period, we report the single-layer muon detection efficiency and the rate at which the light yield degrades due to the aging of the plastic scintillation counters.

Aging↗
DOE OSTI2020

Transformational Challenge Reactor preconceptual core design studies

In the nuclear industry, a manufacturing-informed design approach has the potential to yield the most benefit from advanced manufacturing. By leveraging advanced materials, data science, and rapid testing and deployment, manufacturing-informed design can drive down costs and development times, ultimately improving future commercial viability. This approach is being demonstrated in the US Department of Energy Office of Nuclear Energy (DOE-NE) Transformational Challenge Reactor (TCR) program. Preconceptual design activities for TCR have been focused on analyzing and maturing four reactor core design concepts: two fast-spectrum and two thermal-spectrum systems. Furthermore, the designs were iteratively modified and analyzed, and subcomponents were manufactured in parallel over weeks instead of months or years. To meet key program initiatives (e.g., timeline and material use), several constraints—including fissile material availability, component availability, materials compatibility, and additive manufacturing capabilities—were factored into the design effort, yielding small cores less than one cubic meter in volume with near-term viability. Additionally, the TCR program has made significant progress on development of advanced moderator materials such as yttrium hydride, advancing the feasibility of gas-cooled thermal spectrum systems using less than 250 kg of high-assay low enriched uranium (HALEU) and occupying less than 1 m3. Each of the two resulting thermal designs uses a different fuel form: traditional UO2 ceramic fuel and tristructural isotropic (advanced TRISO) fuel particles embedded inside a SiC matrix. Core neutronics and thermal performance for these systems were assessed and summarized. Evaluation of the performance metrics for these two moderated designs has yielded the downselected TCR design: a TRISO-fueled and yttrium hydride moderated gas-cooled reactor.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗