SEARCH · Engineering Papers

Results for “data processing automation”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68

All sources NASA NTRS DOE OSTI

NASA NTRS2000

Life Sciences Research in the Centrifuge Accommodation Module of the International Space Station

The Centrifuge Accommodation Module (CAM) will be the home of the fundamental biology research facilities on the International Space Station (ISS). These facilities are being built by the Biological Research Project (BRP), whose goal is to oversee development of a wide variety of habitats and host systems to support life sciences research on the ISS. The habitats and host systems are designed to provide life support for a variety of specimens including cells, bacteria, yeast, plants, fish, rodents, eggs (e.g., quail), and insects. Each habitat contains specimen chambers that allow for easy manipulation of specimens and alteration of sample numbers. All habitats are capable of sustaining life support for 90 days and have automated as well as full telescience capabilities for sending habitat parameters data to investigator homesite laboratories. The habitats provide all basic life support capabilities including temperature control, humidity monitoring and control, waste management, food, media and water delivery as well as adjustable lighting. All habitats will have either an internal centrifuge or are fitted to the 2.5-meter diameter centrifuge allowing for variable centrifugation up to 2 g. Specimen chambers are removable so that the specimens can be handled in the life sciences glovebox. Laboratory support equipment is provided for handling the specimens. This includes a compound and dissecting microscope with advanced video imaging, mass measuring devices, refrigerated centrifuge for processing biological samples, pH meter, fixation and complete cryogenic storage capabilities. The research capabilities provided by the fundamental biology facilities will allow for flexibility and efficiency for long term research on the International Space Station.

Dalton, Bonnie P.↗

NASA NTRS2005

Automated Wildfire Detection Through Artificial Neural Networks

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Miller, Jerry↗

NASA NTRS2011

Software Architecture to Support the Evolution of the ISRU RESOLVE Engineering Breadboard Unit 2 (EBU2)

The In-Situ Resource Utilization (ISRU) Regolith & Environmental Science and Oxygen & Lunar Volatiles Extraction (RESOLVE) software provides operation of the physical plant from a remote location with a high-level interface that can access and control the data from external software applications of other subsystems. This software allows autonomous control over the entire system with manual computer control of individual system/process components. It gives non-programmer operators the capability to easily modify the high-level autonomous sequencing while the software is in operation, as well as the ability to modify the low-level, file-based sequences prior to the system operation. Local automated control in a distributed system is also enabled where component control is maintained during the loss of network connectivity with the remote workstation. This innovation also minimizes network traffic. The software architecture commands and controls the latest generation of RESOLVE processes used to obtain, process, and quantify lunar regolith. The system is grouped into six sub-processes: Drill, Crush, Reactor, Lunar Water Resource Demonstration (LWRD), Regolith Volatiles Characterization (RVC) (see example), and Regolith Oxygen Extraction (ROE). Some processes are independent, some are dependent on other processes, and some are independent but run concurrently with other processes. The first goal is to analyze the volatiles emanating from lunar regolith, such as water, carbon monoxide, carbon dioxide, ammonia, hydrogen, and others. This is done by heating the soil and analyzing and capturing the volatilized product. The second goal is to produce water by reducing the soil at high temperatures with hydrogen. This is done by raising the reactor temperature in the range of 800 to 900 C, causing the reaction to progress by adding hydrogen, and then capturing the water product in a desiccant bed. The software needs to run the entire unit and all sub-processes; however, throughout testing, many variables and parameters need to be changed as more is learned about the system operation. The Master Events Controller (MEC) is run on a standard laptop PC using Windows XP. This PC runs in parallel to another laptop that monitors the GC, and a third PC that monitors the drilling/ crushing operation. These three PCs interface to the process through a CompactRIO, OPC Servers, and modems.

Moss, Thomas↗

NASA NTRS2013

Reconstruction of Orion Engineering Development Unit (EDU) Parachute Inflation Loads

The process of reconstructing inflation loads of Capsule Parachute Assembly System (CPAS) has been updated as the program transitioned to testing Engineering Development Unit (EDU) hardware. The equations used to reduce the test data have been re-derived based on the same physical assumptions made by simulations. Due to instrumentation challenges, individual parachute loads are determined from complementary accelerometer and load cell measurements. Cluster inflations are now simulated by modeling each parachute individually to better represent different inflation times and non-synchronous disreefing. The reconstruction procedure is tailored to either infinite mass or finite mass events based on measurable characteristics from the test data. Inflation parameters are determined from an automated optimization routine to reduce subjectivity. Infinite mass inflation parameters have been re-defined to avoid unrealistic interactions in Monte Carlo simulations. Sample cases demonstrate how best-fit inflation parameters are used to generate simulated drag areas and loads which favorably agree with test data.

Ray, Eric S.↗

NASA NTRS2019

Geonex: Land Surface Monitoring from a New Generation of Geostationary Sensors

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Nemani, Ramakrishna R.↗

NASA NTRS2019

Earth Observations from Geostationary Satellites

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GeoNEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GeoNEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GeoNEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring.

Earth↗

NASA NTRS2019

GeoNEX: Land Monitoring from a New Generation of Geostationary Sensors

GeoNEX↗

NASA NTRS1998

Next Generation User Support Tools

One of the manually intensive efforts of Hubble Space Telescope (HST) observing is the specification and validation of the detailed proposals for scientists observing with the telescope. In order to meet the operational cost objectives for the Next Generation Space Telescope (NGST), this process needs to be dramatically less time consuming and less costly. We have prototyped a new proposal development system, the Scientist's Expert Assistant (SEA), using a combination of artificial intelligence and user interface techniques to reduce the time and effort involved for both scientists and the telescope operations staff. The Advanced Architectures and Automation Branch of NASA's Goddard Space Flight Center is working with the Space Telescope Science Institute (ST ScI) to explore SEA alternatives. We are testing the usefulness of rule-based expert systems to painlessly guide a scientist to his or her desired observation specification. We are also examining several potential user interface paradigms and exploring data visualization schemes to see which techniques are more intuitive. Our prototypes will be validated using HST's Advanced Camera for Surveys (ACS) instrument (scheduled for installation in 1999) as a live test instrument. Having an operational test-bed will ensure the most realistic feedback possible for the prototyping cycle. In addition, once the NGST instruments are better defined, the SEA will already be a proven platform that simply needs adapting to NGST-specific instruments.

Jones, Jeremy E.↗

NASA NTRS2006

What Happened, and Why: Toward an Understanding of Human Error Based on Automated Analyses of Incident Reports

The objective of the Aviation System Monitoring and Modeling project of NASA's Aviation Safety and Security Program was to develop technologies to enable proactive management of safety risk, which entails identifying the precursor events and conditions that foreshadow most accidents. Information about what happened can be extracted from quantitative data sources, but the experiential account of the incident reporter is the best available source of information about why an incident happened. In Volume I, the concept of the Scenario was introduced as a pragmatic guide for identifying similarities of what happened based on the objective parameters that define the Context and the Outcome of a Scenario. In this Volume II, that study continues into the analyses of the free narratives to gain understanding as to why the incident occurred from the reporter s perspective. While this is just the first experiment, the results of our approach are encouraging and indicate that it will be possible to design an automated analysis process guided by the structure of the Scenario that can achieve the level of consistency and reliability of human analysis of narrative reports.

Ferryman, Thomas A.↗

NASA NTRS2014

Characteristics of the 2012 Geminids

The parent of the Geminids, 3200 Phaethon, is a unique body in that it is classified as an asteroid, however is responsible for one of the most prolific meteor showers of the year and has shown comet-like behavior in its past (Jewitt and Li 2010). The Geminid meteor shower is also anomalous as its rates have been increasing since it was first detected. Understanding the composition and properties of meteoroids that belong to this meteor shower is an important area of study and of interest to both theoreticians and experimentalists. Using the light curve and decelerations of ten double-station Geminids as seen in the Meteoroid Environment Office's widefield meteor cameras, densities were able to be approximated using a model of meteoroid ablation by Campbell-Brown et al (2013) which employs thermal disruption to model the release of grains during ablation. Bulk densities of Geminids give unique insight into the composition of Phaethon that would only be derived by going to the asteroid itself. The bulk densities of these ten Geminids were found to be between 2.6 and 3.0 g/cm(3), supporting results from Babadzhanov (2009) and Borovicka et al (2010) which prove Phaethon has a much lower porosity than most other meteor shower parents. NASA's Meteoroid Environment Office established these two wide-field meteor cameras to observe meteors in the milligram-mass-range. Each camera consists of a 17 mm focal length Schneider lens (f/0.95) on a Watec 902U2 Ultimate CCD video camera, producing a 21.7x15.5 degree field-of-view. This configuration sees meteors down to a magnitude of +6. Data from these cameras are currently being used to calculate daily automated meteor fluxes. On the first night of operation, December 13-14, 2012, 18 double-station and 53 unique single-station Geminids were detected. The Geminid flux results from this system will be presented as well as ZHR's over the peak of the Geminids. The average flux density over the night was 0.058, 0.052, and 0.062 meteors/km(2)/hour down to a limiting magnitude of +6.5, for the double-station results and each single-station's results. This equates to ZHR's of 113, 102, and 122 respectively. Included in the flux algorithm is a process to find the collecting area per height and a method to find the limiting meteor magnitude per 10 minute time period.

Blaauw, R.↗

NASA NTRS2022

Optimized Umkehr Profile Algorithm for Ozone Trend Analyses

The long-term record of Umkehr measurements from four NOAA Dobson spectrophotometers was reprocessed after updates to the instrument calibration procedures. In addition, a new data quality-control tool was developed for the Dobson automation software (WinDobson). This paper presents a comparison of Dobson Umkehr ozone profiles from NOAA ozone network stations (Boulder, OHP, MLO, Lauder) against several satellite records, including Aura Microwave Limb Sounder (MLS; ver. 4.2), and combined SBUV and OMPS records (NASA AGG and NOAA COH). A subset of satellite data is selected to match Dobson Umkehr observations at each station spatially (distance less than 200 km) and temporally (within 24 hours). Umkehr Averaging Kernels (AKs) are applied to vertically smooth all overpass satellite profiles prior to comparisons. The station Umkehr record consists of several instrumental records, which have different optical characterizations, and thus instrument-specific stray light contributes to the data processing errors and creates step changes in the record. This work evaluates the overall quality of Umkehr long-term measurements at NOAA ground-based stations and assesses the impact of the instrumental changes on the stability of the Umkehr ozone profile record. This paper describes a method designed to correct biases and discontinuities in the retrieved Umkehr profile that originate from the Dobson calibration process, repair, or optical realignment of the instrument. The M2GMI and GMI CTM ozone profile model output matched to station location and date of observation is used to evaluate instrumental step changes in the Umkehr record. Homogenization of the Umkehr record and discussion of the apparent stray light error in retrieved ozone profiles are the focus of this paper. Homogenization of ground-based records is of great importance for studies of long-term ozone trends and climate change.

Umkehr↗

NASA NTRS2000

Climatological Processing of Radar Data for the TRMM Ground Validation Program

The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November, 1997. The main purpose of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented. The primary goal of TRMM GV is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies for the following primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, research analysts at NASA Goddard Space Flight Center (GSFC) generate standardized TRMM GV products using quality-controlled ground-based radar data from the four primary GV sites as input. This presentation will provide an overview of the TRMM GV climatological processing system. A description of the data flow between the primary GV sites, NASA GSFC, and the TRMM Science and Data Information System (TSDIS) will be presented. The radar quality control algorithm, which features eight adjustable height and reflectivity parameters, and its effect on monthly rainfall maps will be described. The methodology used to create monthly, gauge-adjusted rainfall products for each primary site will also be summarized. The standardized monthly rainfall products are developed in discrete, modular steps with distinct intermediate products. These developmental steps include: (1) extracting radar data over the locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) automated quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z-R relationships from the quality-controlled merged data over monthly time scales. A summary of recently reprocessed official GV rainfall products available for TRMM science users will be presented. Updated basic standardized product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for each primary GV site will be also displayed.

Kulie, Mark↗

NASA NTRS1990

Pressure Measurement Systems

System 8400 is an advanced system for measurement of gas and liquid pressure, along with a variety of other parameters, including voltage, frequency and digital inputs. System 8400 offers exceptionally high speed data acquisition through parallel processing, and its modular design allows expansion from a relatively inexpensive entry level system by the addition of modular Input Units that can be installed or removed in minutes. Douglas Juanarena was on the team of engineers that developed a new technology known as ESP (electronically scanned pressure). The Langley ESP measurement system was based on miniature integrated circuit pressure-sensing transducers that communicated pressure information to a minicomputer. In 1977, Juanarena formed PSI to exploit the NASA technology. In 1978 he left Langley, obtained a NASA license for the technology, introduced the first commercial product, the 780B pressure measurement system. PSI developed a pressure scanner for automation of industrial processes. Now in its second design generation, the DPT-6400 is capable of making 2,000 measurements a second and has 64 channels by addition of slave units. New system 8400 represents PSI's bid to further exploit the $600 million U.S. industrial pressure measurement market. It is geared to provide a turnkey solution to physical measurement.

Source record↗

NASA NTRSDate not supplied

Thermal Response of Thermoplastic Composite Tape During In-situ Consolidation Automated Fiber Placement Using a Laser Heat Source

Composite materials have tremendous potential in the design and manufacture of commercial aircraft due to their high strength-to-weight and stiffness-to-weight properties. However, the use of composite materials is currently limited by high cost and long manufacturing time. The National Aeronautics and Space Administration (NASA) initiated the Hi-rate Composite Aircraft Manufacturing (HiCAM) project to investigate promising composite processing technologies with a goal of vastly improving composite commercial aircraft manufacturing rate (4-6x faster than current production rates). Laser assisted automated fiber placement (AFP) of thermoplastics is a key technology that could increase speed of composite manufacturing, but the technology has not been fully developed. In-situ consolidation AFP of thermoplastics (ICAT) could reduce time and cost even further by eliminating the time and equipment required for post-consolidation. In this work, the thermal response of laser heated ICAT was investigated using forward looking infrared (FLIR) and embedded thermocouples (TCs) to better understand fusion between layers (autohesion). Detailed explanation of the algorithm to combine FLIR and TC data will be presented. In addition, the effect of robot speed on time above melting temperature was quantified.

Laser Heating↗

NASA NTRS2024

Search Technology for Optimal Rescue Missions (STORM)

Natural disasters, such as earthquakes, hurricanes, and wildfires are responsible for the deaths of 60,000 to 90,000 people per year. Today, search and rescue (SAR) operations heavily rely on humans to find and deliver life-saving supplies to those affected by these disasters. However, these operations have limits in visibility, navigation, communication systems, and data availability in the area affected, as well as endangering the SAR personnel. Search Technology for Optimal Rescue Missions (STORM) discusses a new system for SAR teams using autonomous drones able to find and deliver supplies to people, without risking more lives in the process. The concept includes the use of two drone types, STORM Search and STORM Rescue, which will survey and locate survivors and be able to drop equipment to the survivors identified, respectively. These two types of drones were optimized in drone design and durability (such as the use of dihedral wings and a toroidal propeller), detection and navigation systems (sturdy thermal and Light Detection and Ranging [LiDAR] cameras), automation and system design (Machine Learning and Computer Vision), server-drone communication (Meshnets), weight, and cost. Once implemented, the STORM concept is expected to improve, ease, and speed up SAR operations, and most important of all, rescue lives that would have never been currently possible to find.

Astha Ingole↗

NASA NTRS1980

Automated frequency standard stability data reduction

A design using a medium sized computer, a fiber optic communication link, and a desk top computer to reduce data collected at a remote site for analysis of frequency standard tests is described. Data generated at the Interim Frequency Standards Test Facility is collected on magnetic tape, which is then transported to a Sigma 5 computer. An Allan variance (two sample variance) is then calculated. The Allan variance (sigma vs tau) is then written to a data file in the Sigma 5. A fiber optic communication link between the Sigma 5 and a desk top computer was designed to transmit data in the Sigma 5 file to the desk top computer. A program was written for the desk top computer that will automatically access the data file in the Sigma 5, process the data and provide a data plot.

Knapp, L. J.↗

NASA NTRS1988

An automated ozone photometer

A photometer capable of automatically measuring ozone concentration data to very high resolution during scientific research flights in the Earth's atmosphere was developed at NASA Ames Research Center. This instrument was recently deployed to study the ozone hole over Antarctica. Ozone is detected by absorbing 253.7-nm radiation from an ultraviolet lamp which shines through the sample of air and impinges on a vacuum phototube. A lower output from the phototube indicates more ozone present in the air sample. The photometer employs a CMOS Z80 microprocessor with an STD bus system for experiment control, data collection, and storage. Data are collected and stored in nonvolatile memory for experiments lasting up to 8 hr. Data are downloaded to a portable ground-support computer and processed after the aircraft lands. An independent single-board computer in the STD bus also calculates ozone concentration in real time with less resolution than the CMOS Z80 system, and sends this value to a cockpit meter to aid the pilot in navigation.

Lavelle, Joseph R.↗

NASA NTRS1989

SHARP: A multi-mission artificial intelligence system for spacecraft telemetry monitoring and diagnosis

The Spacecraft Health Automated Reasoning Prototype (SHARP) is a system designed to demonstrate automated health and status analysis for multi-mission spacecraft and ground data systems operations. Telecommunications link analysis of the Voyager 2 spacecraft is the initial focus for the SHARP system demonstration which will occur during Voyager's encounter with the planet Neptune in August, 1989, in parallel with real time Voyager operations. The SHARP system combines conventional computer science methodologies with artificial intelligence techniques to produce an effective method for detecting and analyzing potential spacecraft and ground systems problems. The system performs real time analysis of spacecraft and other related telemetry, and is also capable of examining data in historical context. A brief introduction is given to the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory. The current method of operation for monitoring the Voyager Telecommunications subsystem is described, and the difficulties associated with the existing technology are highlighted. The approach taken in the SHARP system to overcome the current limitations is also described, as well as both the conventional and artificial intelligence solutions developed in SHARP.

Lawson, Denise L.↗