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At least 937 records · Page 52

Acquisition and use of Orlando, Florida and Continental Airbus radar flight test data

Westinghouse is developing a lookdown pulse Doppler radar for production as the sensor and processor of a forward looking hazardous windshear detection and avoidance system. A data collection prototype of that product was ready for flight testing in Orlando to encounter low level windshear in corroboration with the FAA-Terminal Doppler Weather Radar (TDWR). Airborne real-time processing and display of the hazard factor were demonstrated with TDWR facilitated intercepts and penetrations of over 80 microbursts in a three day period, including microbursts with hazard factors in excess of .16 (with 500 ft. PIREP altitude loss) and the hazard factor display at 6 n.mi. of a visually transparent ('dry') microburst with TDWR corroborated outflow reflectivities of +5 dBz. Range gated Doppler spectrum data was recorded for subsequent development and refinement of hazard factor detection and urban clutter rejection algorithms. Following Orlando, the data collection radar was supplemental type certified for in revenue service on a Continental Airlines Airbus in an automatic and non-interferring basis with its ARINC 708 radar to allow Westinghouse to confirm its understanding of commercial aircraft installation, interface realities, and urban airport clutter. A number of software upgrades, all of which were verified at the Receiver-Transmitter-Processor (RTP) hardware bench with Orlando microburst data to produce desired advanced warning hazard factor detection, included some preliminary loads with automatic (sliding window average hazard factor) detection and annunciation recording. The current (14-APR-92) configured software is free from false and/or nuisance alerts (CAUTIONS, WARNINGS, etc.) for all take-off and landing approaches, under 2500 ft. altitude to weight-on-wheels, into all encountered airports, including Newark (NJ), LAX, Denver, Houston, Cleveland, etc. Using the Orlando data collected on hazardous microbursts, Westinghouse has developed a lookdown pulse Doppler radar product with signal and data processing algorithms which detect realistic microburst hazards and has demonstrated those algorithms produce no false alerts (or nuisance alerts) in urban airport ground moving vehicle (GMTI) and/or clutter environments.

Eide, Michael C.↗

CRGTBSO3 TBS Ozone Data

The Tethered Balloon System (TBS) operated for two weeks during a summer IOP of the CoURAGE campaign. This dataset includes data collected from an En-Sci electrochemical cell (ECC) ozonesonde on the TBS. The ozonesonde was connected to an iMet-4RSB radiosonde, and the overall data collected included ozone, relative humidity, temperature, and altitude. The data from the iMet is the same as that found in the TBSMERGED data product. The TBS also had another instrument (iMet XQ2) that collected meteorological data, which may have more accurate relative humidity (RH) data. This ozonesonde data set is intended to complement the TBSMERGED data product, the CRGTBSO3 surface ozone measurements, and the CoURAGE SWARM ozone lidar (TOLNet) measurements from other locations.

Atmospheric relative humidity↗

Utah FORGE Downhole Geophone Seismic Data (August 2022)

This is a link to downhole geophone data collected by Schlumberger. These data were collected in the Utah FORGE deep seismic monitoring wells 58-32 and 56-32. The format is a standard SEGY and the units are bits. To convert to acceleration (m/s2) multiply by 2.333 x 10-7. Use one of the scripts linked below to use wget commands to pull the data.

15 GEOTHERMAL ENERGY↗

A large interlaboratory electron diffraction study of monolayer graphene

Standardisation of data collection and analysis is essential to enable commercialisation of 2D materials in a wide range of technologies. Selected area electron diffraction (SAED) in the transmission electron microscope (TEM) is one of the key methods for distinguishing monolayer from bilayer and few-layer graphene by comparing the 1st and 2nd order diffraction spot intensities. Yet there are many factors that can affect the reliability of data collection and interpretation, causing the measurement of monolayer samples to deviate from the literature boundary condition of $I_{\{\bar{2}110\}}$$/$$I_{\{1\bar{1}00\}}$ < 1 for monolayer graphene (1LG). Here we present the results of a large interlaboratory SAED comparison study, where 15 international laboratories measured and analysed nominally identical samples of chemical vapour deposited graphene. Large variations were observed in the measured ratios of diffraction spot intensities, with the largest variance associated with poor quality SAED data resulting from inadequate specimen handling and storage. To inform the reliable determination of monolayer thickness from SAED patterns we provide a description of best practice for specimen handling, TEM operation, data collection and analysis. This work was undertaken within VAMAS Technical Working Area 41: Graphene and related 2D materials—Project 9, the results of which have been directly incorporated into ISO/TS 21356–2 for the characterisation of graphene sheets. We find that when this methodology is followed, 1LG can be distinguished from bilayer or thicker material with high confidence where analysis of a single SAED pattern gives $I_{\{\bar{2}110\}}$$/$$I_{\{1\bar{1}00\}}$ < 1.2, even in the absence of precise specimen tilting.

2D materials↗

Evolution of the Next Exploration Toilet through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four crew evaluations on prototypes for the different LOO hardware. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four crew evaluations on prototypes for the different LOO hardware. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Aerosol Optical Properties over the Oceans: Summary and Interpretation of Shadow-Band Radiometer Data from Six Cruises

The aerosol scattering component of the total radiance measured at the detectors of ocean color satellites is determined with atmospheric correction algorithms. These algorithms are based on aerosol optical thickness measurements made in two channels that lie in the near-infrared portion of the electromagnetic spectrum. The aerosol properties in the near-infrared region are used because there is no significant contribution to the satellite-measured radiance from the underlying ocean surface in that spectral region. In the visible wavelength bands, the spectrum of radiation scattered from the turbid atmosphere is convolved with the spectrum of radiation scattered from the surface layers of the ocean. The radiance contribution made by aerosols in the visible bands is determined from the near-infrared measurements through the use of aerosol models and radiation transfer codes. Selection of appropriate aerosol models from the near-infrared measurements is a fundamental challenge. There are several challenges with respect to the development, improvement, and evaluation of satellite ocean-color atmospheric correction algorithms. A common thread among these challenges is the lack of over-ocean aerosol data. Until recently, one of the most important limitations has been the lack of techniques and instruments to make aerosol measurements at sea. There has been steady progress in this area over the past five years, and there are several new and promising devices and techniques for data collection. The development of new instruments and the collection of more aerosol data from over the world's oceans have brought the realization that aerosol measurements that can be directly compared with aerosol measurements from ocean color satellite measurements are difficult to obtain. There are two problems that limit these types of comparisons: the cloudiness of the atmosphere over the world's oceans and the limitations of the techniques and instruments used to collect aerosol data from ships. To address the latter, we have developed a new type of shipboard sun photometer.

Miller, Mark A.↗

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four rounds of crew evaluations with multiple crewmembers on prototypes for the different LOO subsystems. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Evolution of the Next Exploration Toilet Through Human-in-the-Loop (HITL) Testing

Human waste collection in space is a unique and necessary function that all crewmembers must perform. The variability in how each crewmember uses the toilet to urinate and defecate introduces complexities and challenges with regards to overall hardware design. Because of this variability, it is important to consider crew inputs in all aspects of a toilet design especially with regards to crew interfaces that could impact overall waste collection. Access to crew feedback is essential to the design process and should be considered early and often through the various design phases. In 2020, NASA started a project for the Human Landing System (HLS) program to develop a Government Furnished Equipment (GFE) toilet option. The project is known as the Lavatory On-Orbit (LOO). During the early development of the LOO, the project team conducted several crew evaluations to collect and summarize valuable crew feedback on system design, function, and overall usability to influence the next design iteration. Because every person could use the system differently in space, it was extremely important to collect and analyze the data in a very methodical manner to appropriately influence the design based on the evaluation results. Establishing a standard process ensures consistent data collection from one evaluation to another, helps to maintain privacy for each test subject’s inputs and removes any potential bias from test subject to test subject. To date, the team has completed four rounds of crew evaluations with multiple crewmembers on prototypes for the different LOO subsystems. This paper will summarize the methodology used to conduct the evaluations as well as how data was collected and analyzed. The paper will also provide details on each of the evaluations and how the design was updated based on the results.

toilet↗

Short Term Plasticity for Artificial Neural Networks

Achieving efficient learning for AI systems was identified as a major challenge in the DOE's recently released, AI for Science , report. The human brain is capable of efficient and low-powered learning. It is likely that implementing brain-like principles will lead to more efficient AI systems. In this LDRD, I aim to contribute to this goal by creating a foundation for implementing and studying a brain phenomenon termed short term plasticity (STP) in spiking artificial neural networks within Sandia. First, data collected by the Allen Institute for Brain Science (AIBS) was analyzed to see if STP could be classified into types using the data collected. Although the data was inadequate at the time, AIBS has updated their database and created models that could be utilized in the future. Second, I began creating a software package to assess the ability of a Boltzmann machine utilizing STP to sample from national security data.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of wind speed and directional shear at the AWAKEN field campaign site

The American wake experiment (AWAKEN) is taking place in northern Oklahoma, USA, close to the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) atmospheric observatory. The planning for the deployment of the instruments in this observational field campaign required an assessment of the wind characteristics of the site. This paper analyzes long-term data collected by instruments at the ARM SGP observatory to characterize the winds near the AWAKEN site. The analysis shows that this site experiences high wind shear and veer events with a large number of nocturnal low-level jets. A total of 7086 low-level jet wind profiles over 6 years are examined and found to be dominant from the south and southeast. Significant nocturnal wind veer is observed, which causes southerly wind near the surface to become westerly wind aloft. By identifying a strong relationship between atmospheric stability and wind shear, the wind shear at the site is predicted using the Monin–Obukhov similarity theory (MOST) and validated with the observational data collected by a scanning Doppler lidar. The results show that wind speed at a height of 91 m, a proxy hub height for wind turbines in this area, can be predicted from data collected at a height of 10 m with a bias of −0.35 and 0.65 m s−1 in unstable and stable atmospheric boundary layers, respectively. The bias of the predicted wind speed is mostly in the region of low wind speed, and wind speed above 5 m s−1 at a height of 91 m can be predicted with a bias of less than 0.2 m s−1, and the limitations of the MOST in predicting winds during the stably stratified boundary layer is well-observed.

17 WIND ENERGY↗

Connecting Ground Validation and Algorithms

The Ground Validation (GV) component of the Global Precipitation Measurement (GPM) mission involved several field campaigns, involving aircraft, ground radars, and other instrument networks designed to measure various aspects of precipitation. In many cases, these instruments are still in operation at ongoing data collection sites at Wallops Flight Facility, VA and Marquette, MI. The data collected has been used for algorithm formulation and validation, but in many cases has been under-utilized. This presentation describes aspects of GPM algorithms that could benefit from GV data that has been collected and announces a workshop to be held for that purpose in March 2020.

Munchak, Stephen J.↗

Computer Interface For A Spectroreflectometer

FORTRAN program controls stepping motors and signal-processing electronics via S-100 computer bus. Group of spectroreflectometers modified to provide computer-controlled operation and data collection. Analog and digital signal-processing circuits enable use of computerized automatic data collection and analysis. Previously, spectroreflectometer data recorded on strip charts.

Hurd, William A.↗

Free-Flying Magnetometer Data System

The Free-Flying Magnetometer (FFM) is an autonomous "sensorcraft" developed at the Jet Propulsion Laboratory (JPL) for the Enstrophy sounding rocket mission. This mission was a collaborative project between the University of New Hampshire, Cornell University and JPL. The science goal of the mission was the study of current filamentation phenomena in the northern auroral region through multipoint measurements of magnetic field. The technical objective of the mission was the proof of concept of the JPL FFM design and the demonstration of an in-situ multipoint measurement technique employing many free-flying spacecraft. Four FFMs were successfully deployed from a sounding rocket launched from Poker Flats, Alaska on February 11, 1999. These hockey-puck-sized (80 mm diameter, 38 mm. height, 250 gram mass) free flyers each carry a miniature 3-axis flux-gate magnetometer that output +/- 2 V signals corresponding to a +/- 60,000 nT measurement range for each axis. The FFM uses a synchronized four-channel Sigma(Delta) Analog-to-Digital Converter (ADC) having a dynamic range of +/- 2.5V and converting at a rate of 279 samples/second/channel. Three channels are used to digitize the magnetometer signals to 17-bit (1.144 nT/bit) resolution. The fourth ADC channel is multiplexed for system monitoring of four temperature sensors and two battery voltages. The FFM also contains two sun sensors, a laser diode which emits a fan-shaped beam, a miniature S-band transmitter for direct communication to the ground station antennas, an ultra-stable Temperature Compensated Crystal Oscillator (TCXO) clock, an integrated data subsystem implemented in a Field-Programmable Gate Array (FPGA), a 4 Mbit Static Random Access Memory (SRAM) for data storage and Lithium Thionyl Chloride batteries for power. Communicating commands to the FFM prior to deployment is achieved with an infrared (IR) link. The FFM IR receiver responds to 9-bit pulse coded signals that are generated by an IR Light Emitting Diode (LED) in the payload for turning FFM power on or off and placing the FFM in a test mode or flight mode. The IR links are also used to synchronize (zero) the clocks onboard all the FFMs through a reset pulse originating from the payload GPS receiver that is issued when the FFMs are in flight mode. The FPGA based data subsystem manages continuous data collection from the four ADC channels and sun sensors, formatting and storing the data to SRAM, and controlling downlink transmission. The transmitter is powered only after a 2547 frame SRAM buffer has been filled (approx. 5 minutes of data). The data is Viterbi encoded and sent to the S-band transmitter via a First-In-First-Out (FIFO) buffer who's output is clocked at 100 bits/second. After the 26-second transmission, the transmitter is turned off to reduce noise coupling to the sensitive magnetometer. The data subsystem control consists of a master state machine that performs data flow management and is interfaced through a prioritized interrupt scheme to state machines that service the ADC, sun sensors and transmitter FIFO. Continuous data collection prevents the missing of data during transmission and provides implicit time tagging of the data acquired by the ADC because of synchronization with the TCXO clock.

Blaes, B.↗

High-Resolution Floating Solar PV Data

This dataset contains over two years of 1-minute resolution data collected from four floating solar sites, as well as data from a land-based PV system co-located with one of the floating sites. The dataset includes highly granular module temperature measurements - five modules per floating site, with three sensors per module, totaling 15 module temperature sensors per floating site. In addition to the module temperature data, meteorological data collected at the floating sites is also included, along with traditional PV system-level parameters. The data is intended for analysis of solar energy production, efficiency, and performance degradation over time. For information about the data file usage see the "README" resource below. See "Metadata File" for information about individual files and other metadata information.

Array↗

OSTA-1 - The Space Shuttle's first scientific payload

The capabilities of the first Space Shuttle scientific payload for remote sensing observations of the earth are evaluated, and the instruments used are from the Office of Space and Terrestrial Applications (OSTA-1). The payload gathered 10 million square kilometers of data over the earth's oceans, 6 million square kilometers of data over land masses, and global atmospheric data on carbon monoxide concentration. Shuttle imaging radar collected data over a 10,000 km sweep from Spain to Australia, a Shuttle multispectral infrared radiometer obtained 400,000 ten-channel spectra in clear weather conditions over four continents, and the Ocean Color Experiment detected water color for interpretation of major water constituents. The mission is considered to be a success based on the amount of data collected, and scientific and technical insight gained for the development of Shuttle flight instruments.

Moore, J. W.↗

The Field Guide to NASA’s Life Sciences Data Repositories

For over 30 years, NASA has invested in life sciences research both in space and on the ground. Data accessibility is an important tool for researchers, and NASA has committed to preserving this vital resource for ongoing use. The Life Sciences Data Archive’s multi-center collaboration between NASA’s Johnson Space Center, Ames Research Center, and Kennedy Space Center is geared toward preserving unique and high-value data from a wide variety of disciplines, data collection methods, and species within NASA’s Life Sciences Portal (NLSP). The data generated by the Human Research Program (HRP) require a systematic approach to data preservation that accounts for diverse data sources, formats, physical storage requirements, and security and privacy protections. This poster presentation will provide a guide to the repositories where the various types of human, non-human animal, plant, and microbial data NASA generates are archived and tips for navigating these data collections. Topics will include where different types of data, metadata, and biospecimens are archived or preserved, how the federated repositories work together as a data preservation ecosystem, and how researchers can access each repository’s collections.

Robert S Beaton↗

A Field Guide to NASA’s Life Sciences Data Repositories

For over 30 years, NASA has invested in life sciences research both in space and on the ground. Data accessibility is an important tool for researchers, and NASA has committed to preserving this vital resource for ongoing use. The Life Sciences Data Archive’s multi-center collaboration between NASA’s Johnson Space Center, Ames Research Center, and Kennedy Space Center is geared toward preserving unique and high-value data from a wide variety of disciplines, data collection methods, and species within NASA’s Life Sciences Portal (NLSP). The data generated by the Human Research Program (HRP) require a systematic approach to data preservation that accounts for diverse data sources, formats, physical storage requirements, and security and privacy protections. This poster presentation will provide a guide to the repositories where the various types of human, non-human animal, plant, and microbial data NASA generates are archived and tips for navigating these data collections. Topics will include where different types of data, metadata, and biospecimens are archived or preserved, how the federated repositories work together as a data preservation ecosystem, and how researchers can access each repository’s collections.

LSDA↗