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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Planetary Boundary Layer Height (PBLH) over SGP from 1998 to 2023

PBLH is a critical parameter influencing weather phenomena, air quality, and various meteorological processes. However, accurately retrieving PBLH has been a challenging task due to limitations such as coarse temporal resolution and measurement drift in traditional radiosonde observations. To address these limitations, we have devised a lidar-based methodology that capitalizes on a newly developed algorithm for PBLH retrieval. This algorithm demonstrates enhanced capabilities in capturing diurnal fluctuations in PBLH compared to existing lidar-based methods (Su et al. 2020). In addition, we have refined this algorithm specifically for PBLH retrieval under cloudy conditions through a novel scheme (Su et al. 2022). To ensure data reliability, a quality-control process has been implemented to filter out questionable data points. Accompanying the data set is a quality-control flag for ease of reference. It should be noted that we have assimilated all available radiosonde observations to provide a more robust estimate of PBLH, making the data set valuable for a variety of related studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SAIL-Net Raw and Post Corrected POPS Data Fall 2021 - Summer 2023

SAIL-Net is a DOE funded project in the East River Watershed near Crested Butte, Colorado with the goal of advancing our understanding of aerosol-cloud interactions in complex, mountainous regions. Through the deployment of a network of six low cost microphysics nodes in Fall 2021 in the same domain at the SAIL campaign, SAIL-Net provides data on aerosol size distributions, cloud condensation nuclei (CCN), and ice nucleation particles (INP). This network enables the investigation of small-scale variations in complex terrain. Two datasets are provided - one containing raw data and the other containing post-corrected data. The raw dataset provides the raw data recorded from the POPS which were deployed at each of the six sites. These data are organized by site and broken down into daily data files. The six site names used here are: “gothic”, “irwin”, “cbtop”, “cbmid”, “pumphouse”, and “snodgrass”. These data are not cleaned or post-corrected, but some flags have been added. The data are reported at 1 second time resolution. The post-corrected dataset provides the post-corrected and cleaned data recorded from the POPS which were deployed at each of the six sites. This data are also organized by site (same as those found in the raw data) and broken down into daily data files. Unlike the raw POPS data, these data have already been cleaned to remove what we believe are bad values. These data should be ready to use with no cleaning. For a full description of the cleaning and post-correction process, see the readme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ARM Aerial Facility (AAF) - Unmanned Aircraft Systems, Cloud Droplet Probe with QC and lat/lon/alt

The Cloud Droplet Probe (CDP) is designed to measure cloud droplet size distribution from 2 µm to 50 µm. The CDP and an appropriate data system can also calculate various other parameters including particle concentrations, effective diameter (ED), Median Volume Diameter (MVD), and Liquid Water Content (LWC). The b1 level adds standard quality control flags, and merges in flight navigation data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

NPFTURBULENCE: Fast Response Temperature by Airborne Measurements

The original data were collected during the field campaign of the “Turbulent layers promoting New Particle Formation” experiment (NPFTURBULENCE; https://www.arm.gov/research/campaigns/aaf2024npfturbulence; https://www.arm.gov/publications/programdocs/doe-sc-arm-25-004.pdf ) over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/sgp ) in north-central Oklahoma. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at Blackwell–Tonkawa Municipal Airport (IATA: BWL, ICAO: KBKN, FAA LID: BKN, 36.74475° N, 97.34918° W, 313.9 m MSL), for the field campaign from May 5 through May 29, 2024. The ArcticShark UAS performed 11 flights, including 10 research flights over the Central Facility of the ARM SGP to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration and size distribution. The current dataset presents fast response temperature in the atmospheric boundary layer and lower free troposphere measured on the airborne platform throughout the field campaign. The primary instruments used to create the current dataset were the fine wire thermocouple probe, Pitot-static system (part of the UAS control), and infrared gas analyzer sensor for H2O and CO2 (LI-840A). All parameters used in the temperature calculations (static and dynamic pressure, absolute humidity in form of dew point temperature) were included in the data set. For user convenience, one additional parameter was also included: the type of flight flag (level, up, down, turn, and combination of thereof).

Air temperature↗
DOE OSTI2025

Cleaned 5-Minute Resolution Air Quality and Meteorological Data from Nine TCEQ CAMS Sites in Houston, Texas (Nov 2021 – Oct 2022)

These data encompass 5-minute air monitoring and meteorological observations collected in the greater Houston, Texas metropolitan region, at nine (9) Continuous Ambient Monitoring Stations (CAMS) operated by the Texas Commission on Environmental Quality (TCEQ) between November 1, 2021 and October 31, 2022. The CAMS sites (CAMS 1, 8, 35, 45, 148, 403, 405, 410, and 1052) were chosen because their instrumentation includes measurements of PM2.5. These sites also provide continuous multi-parameter air-quality and meteorological measurements. Particulate matter (PM2.5, PM10) was sampled along with several trace gases, including ozone (O3), nitrogen oxides (NO, NO2, NOx), sulfur dioxide (SO2), and carbon monoxide (CO). The data set also contains standard surface meteorological parameters (temperature, humidity, pressure, wind speed, and wind direction). Several sites also include AutoGC-based measurements of volatile organic compounds (VOCs). Air monitoring instruments deployed at the selected sites comprise the following systems: BAM-1020 or TEOM (PM2.5), Thermo Scientific TEI 49i (O3), TEI 42i (NOx), and AutoGCs (VOCs). This data set is similar to the data included within the houairq5mX1.00 datastream, except for a few additional quality control steps. A systematic data cleaning and verification process was performed on the data set to ensure its quality and preparation for analysis. Removal of non-numeric status flags (e.g., [LIM], [QAS], [SPZ], [CAL], [PMA], [AQI], [SPN], [MAL]) was accomplished by employing rule-based string parsing to extract valid numerical values. Missing entries were set to -9999; however, invalid or anomalous values (e.g., 99999) were retained as originally reported by the TCEQ to preserve data provenance. The time sequence was verified for completeness, removal of duplicates, and uniformity at 5-minute intervals. Column labeling was standardized, and corresponding values were assessed for physical plausibility. All timestamps in the data set were reported in Coordinated Universal Time (UTC) as provided by the TCEQ. Further, the latitude and longitude coordinates were added for each CAMS site. A subset of the data (June 1–September 30, 2022) has been used in the following publication: Subba et al. 2025. “Implications of sea breeze circulations on boundary layer aerosols in the southern coastal Texas region.” EGUsphere 2025: 1–49, https://doi.org/10.5194/egusphere-2025-2659.

latitude↗
DOE OSTI2025

Fast Response Temperature by airborne measurements over BNF

The original data were collected during the AAF Engineering Flights (AEF2025) in the vicinity of the ARM Bankhead National Forest (BNF) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/bnf ) in northwestern Alabama in March 2025. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS, https://www.arm.gov/capabilities/observatories/aaf/uas) was based at the public-use airport of Posey Field, Alabama (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from March 9 through March 24, 2025. The ArcticShark UAS performed nine flights, including eight research flights over the AMF3 (BNF Main Site) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, and aerosol number concentration and size distribution. The current data set presents fast response temperature in the atmospheric boundary layer and lower free troposphere measured on the airborne platform throughout the field campaign. The primary instruments used to create the current data set were the fine wire thermocouple probe, the Aircraft Integrated Meteorological Measurement System (AIMMS-30), the Pitot-static system (part of UAS flight control), and the infrared gas analyzer sensor for H2O and CO2 (LI-840). All parameters used in temperature calculations (static pressure, True Air Speed, and absolute humidity in form of dew point temperature) were included in the data set. For user convenience, one additional parameter was also included: the type of flight flag (level, up, down, turn, and combination of thereof).

Air temperature, fast response↗
DOE OSTI2025

CHELAX-BNF: Fast Response Temperature by airborne measurements

The original data were collected on board the ARM Aerial Facility ArcticShark uncrewed aerial system (UAS; https://www.arm.gov/capabilities/observatories/aaf/uas ) during the “Characterizing HEterogeneous Land-Atmosphere eXchanges at BNF” field campaign (CHEAX-BNF; https://arm.gov/research/campaigns/aaf2025CHELAX-BNF ). The ARM Aerial Facility ArcticShark UAS was based at the public-use airport of Posey Field, AL (FAA LID: 1M4, 34.28027778° N, 87.60055556° W, 283m MSL) from May 28 to June 23, 2025. The ArcticShark UAS performed 5 flights, including 4 research flights over the BNF Main Site (ARM Mobile Facility 3, https://arm.gov/capabilities/observatories/amf ) and Supplemental Facilities to measure atmospheric state, turbulence, surface IR temperature and imagery, aerosol number concentration, and aerosol size distribution. The current data set presents fast response temperature in the atmospheric boundary layer and lower free troposphere measured on the airborne platform throughout the field campaign. The primary instruments used to create the current data set were the fine wire thermocouple probe, the Aircraft Integrated Meteorological Measurement System (AIMMS-30), the Pitot-static system (part of UAS flight control), and the infrared gas analyzer sensor for H2O and CO2 (LI-840). All parameters used in temperature calculations (static pressure, True Air Speed, and absolute humidity in the form of dew point temperature) were included in the data set. For user convenience, one additional parameter was also included: the type of flight flag (level, up, down, turn, and combination of thereof).

Air temperature, fast response↗
DOE OSTI2025

ARM SGP PBLH and MLH datasets from Raman lidar and Doppler lidar

The planetary boundary layer (PBL) plays a critical role in the atmosphere by transferring heat, moisture, and momentum. The warm PBL has a distinct diurnal cycle including the daytime convective mixing layer (ML) and nighttime residual layer developments. Thus, simultaneous determinations of PBL height (PBLH) and ML height (MLH) are necessary for studying PBL characterization and processes. Here, new approaches are developed to provide reliable PBLH and MLH estimates to characterize warm PBL evolution. The approaches use Raman lidar (RL) water vapor mixing ratio (WVMR) and Doppler lidar (DL) vertical velocity measurements at the Southern Great Plains (SGP) atmospheric observatory, which was established by the Atmospheric Radiation Measurement (ARM) User Facility. Compared to widely used lidar aerosol measurements for PBLH, WVMR is a better tracer for PBL vertical mixing. For PBLH, the approach classifies PBL water vapor structures into a few general patterns, then uses a slope method and dynamic threshold method to determine PBLH. For MLH, wavelet analysis is used to reconstruct 2D variance from DL vertical wind velocity measurements according to the turbulence eddy size to minimize the impacts of gravity wave and eddy size on variance calculations; then, a dynamic threshold method is used to determine MLH. Remotely-sensed PBLHs and MLHs are compared with radiosonde measurements based on the Richardson number method. Good agreements between them confirm that the proposed new algorithms are reliable for PBLH and MLH characterization. The algorithms are applied to warm-season RL and ML measurements at the SGP site for five years to study warm-season PBL structure and processes. The weekly composited diurnal evolutions of PBLHs and MLHs in a warm climate were provided to illustrate diurnal and seasonal PBL evolutions. This reliable data set of PBLH and MLH values will be valuable for studying PBL processes, model evolution, and PBL parameterization improvements. The MLH dataset includes the MLH in values of km above ground level. The PBLH dataset includes the PBLH in values of km above ground level, along with a flag ("situation_PBLH") to determine the state of the PBL (1 = Cloudy Condition, 2 = Stable Layer, 3 = Multi-layer WVMR structure, 4 = Well-Mixed PBL, 5 = A de-coupled layer, 6 = Other).

mixing layer height↗
DOE OSTI2025

CCN Measurements at Urban Site during CoURAGE

Cloud condensation nuclei (CCN) measurements were collected during CoURAGE from March - June 2025 at the BSEC urban atmospheric chemistry supersite (39.32057 N, 76.6246 W). CCN number concentrations (# cm-3) were obtained at a frequency of 1 second using a cloud condensation nuclei counter (CCN-100, Droplet Measurement Technologies). The CCN counter was operated in stepping mode, measuring CCN over a range of supersaturations from 0.2 to 1.0%. The settings of the instrument were set such that the supersaturation increased in increments of 0.2% up to the maximum supersaturation, and then decreased in increments of 0.2% down to the minimum supersaturation in a repeating cycle. The supersaturation of the instrument was calibrated weekly using ammonium sulfate. The weekly calibrated supersaturation values have been applied to the data. Data during transitions between supersaturation values were removed and replaced with a value of -999. Transitions are defined as the first 210 seconds after a new supersaturation value to ensure the instrument has stabilized following a change in supersaturation. Data were also flagged with a value of -999 if there were concerns with the function of the instrument, specifically the presence of alarm codes, fogging of the optical particle counter (1st stage monitor > 0.4 V), or a sheath to sample flow ratio outside the expected range (< 9 or > 11).

CCN number density↗
DOE OSTI2026

Local Tractor Activity at S2 (Mt. Airy) Site

This dataset documents local tractor activity at the S2 (Mt. Airy) site during CoURAGE. It identifies periods where local tractor activity impacted aerosol measurements using both PM10/PM2.5 ratios and ARM camera data for visual confirmation of tractor. Data flags are as follows: 1 = confirmed no local tractor influence on aerosol measurements 2 = one data indicator is present (extreme PM10/PM2.5 ratio OR visual confirmation of tractor sighting), but not both 3 = both data indicators confirm local tractor influence on aerosol 0 = missing data, no determination possible

Tractor Activity using ARM camera photos and PM10/↗
DOE OSTI2020

High Performance Computing Application I/O Traces

The dataset comprises trace files from high performance computing (HPC) simulations. The trace files contain records of every I/O operation executed by a simulation application run, including I/O operations from HDF5, MPI-IO, and POSIX and all of the parameters supplied to those operations, e.g. file name, offset, and flags. The traces are generated by executing a simulation application that is linked with the Recorder tracing tool (https://github.com/uiuc-hpc/Recorder). The Recorder trace tool intercepts the I/O calls made by the application, records the I/O trace record, and then calls the intended I/O call so that the operation executes.

Wang, C.↗
DOE OSTI2022

Corrosion of Containment Alloys in Molten Salt Reactors and the Prospect of Online Monitoring

The aim of this review is to communicate some essential knowledge of the underlying mechanism of the corrosion of structural containment alloys during molten salt reactor operation in the context of prospective online monitoring in future MSR installations. The formation of metal halide species and the progression of their concentration in the molten salt do reflect containment corrosion, tracing the depletion of alloying metals at the alloy salt interface will assure safe conditions during reactor operation. Even though the progress of alloying metal halides concentrations in the molten salt do strongly understate actual corrosion rates, their prospective 1 st order kinetics followed by near-linearly increase is attributed to homogeneous matrix corrosion. The service life of the structural containment alloy is derived from homogeneous matrix corrosion and near-surface void formation but less so from intergranular cracking (IGC) and pitting corrosion. Online monitoring of corrosion species is of particular interest for molten chloride systems since besides the expected formation of chromium chloride species CrCl 2 and CrCl 3 , other metal chloride species such as FeCl 2 , FeCl 3 , MoCl 2 , MnCl 2 and NiCl 2 will form, depending on the selected structural alloy. The metal chloride concentrations should follow, after an incubation period of about 10,000 hours, a linear projection with a positive slope and a steady increase of <1 ppm per day. During the incubation period metal concentration show 1 st order kinetics and increasing linearly with time. Ideally, a linear increase reflects homogeneous matrix corrosion, while a sharp increase in the metal chloride concentration could set a warning flag for potential material failure within the projected service life, e.g. as result of intergranular cracking or pitting corrosion. Continuous monitoring of metal chloride concentrations can therefore provide direct information about the mechanism of the ongoing corrosion scenario and offer valuable information for a timely warning of prospective material failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

NLR HPC Kestrel Jobs Data

Overview: Anonymized job-level records from the Kestrel HPC system at the National Laboratory of the Rockies (NLR). Each record represents a Slurm batch job with scheduling metadata, resource requests, utilization, energy estimates, and efficiency metrics. Sensitive fields (user, account, job name, submit line, working directory, submit script, and job type) are replaced with 7-character cryptographic hashes. System & Timeframe: Kestrel is located at the NLR campus. Standard compute nodes have 104 cores and 256 GB RAM; bigmem nodes have 2,000 GB. GPU nodes (gpu-h100 partition) use NVIDIA H100 GPUs. Data covers jobs submitted August 2023 through December 2025. Funding provided by the U.S. Department of Energy, EERE. Files: esif.hpc.kestrel.job-anon.zip — Anonymized job records (Hive-partitioned Parquet) datacard.md — Full dataset documentation ~11 million rows, 50 variables. Readable with PyArrow, pandas, DuckDB, Apache Spark, or any Parquet-compatible tool. Data Collection: Jobs collected via sacct with timezone-aware export (SLURM_TIME_FORMAT="%Y-%m-%dT%H:%M:%S%z"), loaded into PostgreSQL. Calculated columns updated via database triggers and batch functions. All timestamps use timestamptz and correctly handle DST transitions. Preprocessing: Anonymization of name, user, account, submit_line, work_dir, submit_script, and job_type via 7-char hex hashes Derived columns: queue_wait, cpu_eff, max/min/avg_mem_eff, energy estimates Simplified job state mapping (e.g., "CANCELLED by 132357" → "CANCELLED") Boolean flags: python_job, reframe_job Temporal decomposition: year, month, day, day_of_week, hour, minute from submit_time Shared node tracking: shared_job_count, nodes_shared, jobs_shared Key Variables: Scheduling: job_id, partition, state_simple, submit_time, start_time, end_time, queue_wait Resources: nodes_req/used, processors_req/used, memory_req, wallclock_req/used, gpus_requested Efficiency: cpu_eff, max/min/avg_mem_eff Energy: cpu_energy_tdp_estimated_max/used_watt_hours, consumed_energy_raw_joules, consumed_energy_raw_watt_hours Sharing: shared_job_count, nodes_shared, jobs_shared Partitions: short, standard, debug, gpu-h100 Job States: CANCELLED, COMPLETED, FAILED, PENDING, RUNNING QoS Levels: normal, high Important Notes: Timestamps include timezone offsets; DST transitions are handled correctly, though adding intervals across DST boundaries requires offset adjustment shared_job_count reflects physical node co-residency, not use of the shared partition Job step records and raw Slurm JSONB fields are excluded Do not attempt to re-identify individuals from hashed fields

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1973

Loss of atomic oxygen in mass spectrometer ion sources.

A gas beam consisting of a mixture of atomic and molecular oxygen has been directed at the ion source of a mass spectrometer like those used in sounding rockets for determining the neutral composition of the lower thermosphere. The loss of atomic oxygen on mass spectrometer surfaces was evaluated by flagging the beam in several ways and comparing the experimental results with predicted values. The results obtained suggest that in rocket flights using similar instruments the atomic oxygen densities computed assuming no-loss conditions may be low by a factor of 2.5. Studies made using a beam containing tracer O-18 indicate that carbon dioxide observed when atomic oxygen enters the source is formed in a reaction involving atomic oxygen from the beam and carbon monoxide from the surfaces bombarded.

Lake, L. R.↗
NASA NTRS1973

Video systems for real-time oil-spill detection

Three airborne television systems are being developed to evaluate techniques for oil-spill surveillance. These include a conventional TV camera, two cameras operating in a subtractive mode, and a field-sequential camera. False-color enhancement and wavelength and polarization filtering are also employed. The first of a series of flight tests indicates that an appropriately filtered conventional TV camera is a relatively inexpensive method of improving contrast between oil and water. False-color enhancement improves the contrast, but the problem caused by sun glint now limits the application to overcast days. Future effort will be aimed toward a one-camera system. Solving the sun-glint problem and developing the field-sequential camera into an operable system offers potential for color 'flagging' oil on water.

Millard, J. P.↗
NASA NTRS1975

Engineering studies of vectorcardiographs in blood pressure measuring systems, appendix 3

The following subjects were covered: (1) ASM80 manual, (2) signal preprocessing as an aid to on-line EKG analysis, and (3) high speed evaluation of magnetic tape recordings of electrocardiograms. A description of the ASM80 symbolic assembly program for the INTEL 8080 microprocessor and a user's manual were presented. The capability of three redundancy reduction algorithms to produce adequate representations of electrocardiographic data was examined. A hardware device was constructed which carried out zero order interpolation on a signal. Examination of the zero order interpolators reconstructed signal indicated that this representation was adequate for analysis of rhythm. A system to analyze magnetic tapes of electrocardiograms recorded over 24 hour intervals was designed. The recordings are sampled 200 times per second using a Nova computer and a special interface system. This system was tested on several recordings of clinical data, containing over 75 premature ventricular contractions, each one of which was flagged.

Mark, R. G.↗