Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “production monitoring”

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.

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

At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Outbursts of H2O in Comet P/Halley

Comet Halley gas-production monitoring efforts in March 1986 with the NASA Kuiper Airborne Observatory's Fourier transform spectrometer have indicated rapid temporal variations in H2O emissions; a continuous record of an H2O outburst was thus obtained. The event, in which H2O brightness increased by a factor of 2.2 in less than 10 min, is ascribable to an energetic process in the nucleus whose character may have been that of amorphous H2O ice crystallization, chemical explosion, thermal stress, or a compressed gas pocket. The timing and energy of the event appear to require an internal energy source; amorphous ice crystallization is held to be most consistent with compositional and thermal models of cometary nuclei as well as the observations.

Larson, Harold P.↗
NASA NTRS1999

SIRTF Science Operations System Design

SIRTF Science Operations System Design William B. Green Manager, SIRTF Science Center California Institute of Technology M/S 310-6 1200 E. California Blvd., Pasadena CA 91125 (626) 395 8572 Fax (626) 568 0673 bgreen@ipac.caltech.edu. The Space Infrared Telescope Facility (SIRTF) will be launched in December 2001, and perform an extended series of science observations at wavelengths ranging from 20 to 160 microns for five years or more. The California Institute of Technology has been selected as the home for the SIRTF Science Center (SSC). The SSC will be responsible for evaluating and selecting observation proposals, providing technical support to the science community, performing mission planning and science observation scheduling activities, instrument calibration during operations and instrument health monitoring, production of archival quality data products, and management of science research grants. The science payload consists of three instruments delivered by instrument Principal Investigators located at University of Arizona, Cornell, and Harvard Smithsonian Astrophysical Observatory. The SSC is responsible for design, development, and operation of the Science Operations System (SOS) which will support the functions assigned to the SSC by NASA. The SIRTF spacecraft, mission profile, and science instrument design have undergone almost ten years of refinement. SIRTF development and operations activities are highly cost constrained. The cost constraints have impacted the design of the SOS in several ways. The Science Operations System has been designed to incorporate a set of efficient, easy to use tools which will make it possible for scientists to propose observation sequences in a rapid and automated manner. The use of highly automated tools for requesting observations will simplify the long range observatory scheduling process, and the short term scheduling of science observations. Pipeline data processing will be highly automated and data-driven, utilizing a variety of tools developed at JPL, the instrument development teams, and Space Telescope Science Institute to automate processing. An incremental ground data system development approach has been adopted, featuring periodic deliveries that are validated with the flight hardware throughout the various phases of system level development and testing. This approach minimizes development time and decreases operations risk. This paper will describe the top level architecture of the SOS and the basic design concepts. A summary of the incremental development approach will be presented. Examples of the unique science user tools now under final development prior to the first proposal call scheduled for mid-2000 will be shown.

Green, William↗
NASA NTRS1985

Laser Systems

Tunable diode lasers are employed as radiation sources in high resolution infrared spectroscopy to determine spectral characteristics of gaseous compounds. With other laser systems, they are produced by Spectra-Physics, and used to monitor chemical processes, monitor production of quantity halogen lamps, etc. The Laser Analytics Division of Spectra-Physics credits the system's reliability to a program funded by Langley in the 1970s. Company no longer U.S.-owned. 5/22/97

Source record↗
NASA NTRS2007

Measuring Image Navigation and Registration Performance at the 3-Sigma Level Using Platinum Quality Landmarks

Geostationary Operational Environmental Satellite (GOES) Image Navigation and Registration (INR) performance is specified at the 3- level, meaning that 99.7% of a collection of individual measurements must comply with specification thresholds. Landmarks are measured by the Replacement Product Monitor (RPM), part of the operational GOES ground system, to assess INR performance and to close the INR loop. The RPM automatically discriminates between valid and invalid measurements enabling it to run without human supervision. In general, this screening is reliable, but a small population of invalid measurements will be falsely identified as valid. Even a small population of invalid measurements can create problems when assessing performance at the 3-sigma level. This paper describes an additional layer of quality control whereby landmarks of the highest quality ("platinum") are identified by their self-consistency. The platinum screening criteria are not simple statistical outlier tests against sigma values in populations of INR errors. In-orbit INR performance metrics for GOES-12 and GOES-13 are presented using the platinum landmark methodology.

Carr, James L.↗
NASA NTRS2009

Compact, Miniature MMIC Receiver Modules for an MMIC Array Spectrograph

A single-pixel prototype of a W-band detector module with a digital back-end was developed to serve as a building block for large focal-plane arrays of monolithic millimeter-wave integrated circuit (MMIC) detectors. The module uses low-noise amplifiers, diode-based mixers, and a WR10 waveguide input with a coaxial local oscillator. State-of-the-art InP HEMT (high electron mobility transistor) MMIC amplifiers at the front end provide approximately 40 dB of gain. The measured noise temperature of the module, at an ambient temperature of 300 K, was found to be as low as 450 K at 95 GHz. The modules will be used to develop multiple instruments for astrophysics radio telescopes, both on the ground and in space. The prototype is being used by Stanford University to characterize noise performance at cryogenic temperatures. The goal is to achieve a 30-50 K noise temperature around 90 GHz when cooled to a 20 K ambient temperature. Further developments include characterization of the IF in-phase (I) and quadrature (Q) signals as a function of frequency to check amplitude and phase; replacing the InP low-noise amplifiers with state-of-the-art 35-nm-gate-length NGC low-noise amplifiers; interfacing the front-end module with a digital back-end spectrometer; and developing a scheme for local oscillator and IF distribution in a future array. While this MMIC is being developed for use in radio astronomy, it has the potential for use in other industries. Applications include automotive radar (both transmitters and receivers), communication links, radar systems for collision avoidance, production monitors, ground-penetrating sensors, and wireless personal networks.

Kangaslahti, Pekka P.↗
NASA NTRS2011

Detecting Abnormal Machine Characteristics in Cloud Infrastructures

In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

Bhaduri, Kanishka↗
NASA NTRS2012

An Effort to Map and Monitor Baldcypress Forest Areas in Coastal Louisiana, Using Landsat, MODIS, and ASTER Satellite Data

This presentation discusses a collaborative project to develop, test, and demonstrate baldcypress forest mapping and monitoring products for aiding forest conservation and restoration in coastal Louisiana. Low lying coastal forests in the region are being negatively impacted by multiple factors, including subsidence, salt water intrusion, sea level rise, persistent flooding, hydrologic modification, annual insect-induced forest defoliation, timber harvesting, and conversion to urban land uses. Coastal baldcypress forests provide invaluable ecological services in terms of wildlife habitat, forest products, storm buffers, and water quality benefits. Before this project, current maps of baldcypress forest concentrations and change did not exist or were out of date. In response, this project was initiated to produce: 1) current maps showing the extent and location of baldcypress dominated forests; and 2) wetland forest change maps showing temporary and persistent disturbance and loss since the early 1970s. Project products are being developed collaboratively with multiple state and federal agencies. Products are being validated using available reference data from aerial, satellite, and field survey data. Results include Landsat TM- based classifications of baldcypress in terms of cover type and percent canopy cover. Landsat MSS data was employed to compute a circa 1972 classification of swamp and bottomland hardwood forest types. Landsat data for 1972-2010 was used to compute wetland forest change products. MODIS-based change products were applied to view and assess insect-induced swamp forest defoliation. MODIS, Landsat, and ASTER satellite data products were used to help assess hurricane and flood impacts to coastal wetland forests in the region.

Spruce, Joseph P.↗
NASA NTRS2019

Deep Learning Emulation of Atmospheric Correction for Geostationary Sensors

New generation geostationary satellites make reflectance observations available at a continental scale with unprecedented spatiotemporal resolution and spectral range. Generating Earth monitoring products from these observations requires retrieval of the basic parameter, surface reflectance (SR), by atmospheric correction (AC). Algorithms for atmospheric correction, including Multi-Angle Implementation of Atmospheric Correction (MAIAC), are adapted for each sensor and are too computationally complex to be run in real time, relying instead on look-up tables with precomputed values. Machine learning methods, including convolutional neural networks, have demonstrated performance in learning complex, nonlinear mappings and extracting insight from high-dimensional remote sensing data. In this work, we present a deep learning emulator of MAIAC to retrieve both SR and cloud products. Using this adaptation of deep learning-based emulation to remote sensing, we demonstrate stable SR retrieval over a variety of land covers and viewing conditions and accurate cloud detection. Further, a comparison of computation time suggests emulation as a compelling alternative for expensive physical simulation, especially for applications benefited by near-real time data, such as agricultural management and disaster response.

Duffy, Kate↗
DOE OSTI2022

Initial Observations from AGR 5/6/7 Capsule 1

The fourth and final irradiation experiment in the Advanced Reactor Technologies (ART) Advanced Gas Reactor (AGR) fuel development and qualification program is designated as AGR-5/6/7. Data collected from the fabrication, irradiation, and post-irradiation examination (PIE) of this tristructural isotropic (TRISO) fuel are intended to serve as the primary data set for the qualification of this fuel for use in high-temperature gas-cooled reactors (INL 2021, Collin 2018b). However, data collected from the three preceding irradiations (i.e., AGR-1, AGR-2, and AGR-3/4) may also be used to supplement data collected from AGR-5/6/7. All components of the AGR-5/6/7 fuel (i.e., UCO kernels, TRISO coatings, and fuel compacts) were produced on an engineering scale at BWXT (Lynchburg, Virginia USA) according to the fuel specification (Marshall 2017). This fuel was irradiated in the northeast flux trap (NEFT) at the Advanced Test Reactor (ATR) at Idaho national Laboratory (INL) from February 16, 2018 to July 22, 2020 (Pham et al. 2021). Measurements in the fission product monitoring system (FPMS) indicated unexpected and significant numbers of failures of TRISO particles in Capsule 1 near the end of the sixth irradiation cycle (ATR Cycle 166A). In the fourth cycle (ATR Cycle 164B) and beyond, the sweep gas flow became very low (presumably from degradation of the capsule gas outlet line via an unidentified mechanism), and the program deliberately isolated Capsule 1 from gas flow periodically. In later cycles, attempts to reestablish any kind of flow in Capsule 1 were unsuccessful. With little or no flow through Capsule 1, FPMS measurements and enumerations of failed particles in Capsule 1 were difficult or impossible as was the ability to control the helium/neon gas mixture used for temperature control. Gas flows and fission gas activity in the effluent gas from the other AGR-5/6/7 capsules were also impacted by the Capsule 1 gas flow issues and the large increase in fission gas released from the Capsule 1.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2020

Version 2 Ozone Monitoring Instrument SO2 Product (OMSO2 V2): New Anthropogenic SO2 Vertical Column Density Dataset

The Ozone Monitoring Instrument (OMI) has been providing global observations of SO2 pollution since 2004. Here we introduce the new anthropogenic SO2 vertical column density (VCD) dataset in the version 2 OMI SO2 product (OMSO2 V2). As with the previous version (OMSO2 V1.3), the new dataset is generated with an algorithm based on principal component analysis of OMI radiances, but features several updates. The most important among those is the use of expanded lookup tables and model a priori profiles to estimate SO2 Jacobians for individual OMI pixels, in order to better characterize pixel-to-pixel variations in SO2 sensitivity, including over snow and ice. Additionally, new data screening and spectral fitting schemes have been implemented to improve the quality of the spectral fit. As compared with the planetary boundary layer SO2 dataset in OMSO2 V1.3, the new dataset has substantially better data quality, especially over areas that are relatively clean or affected by the south Atlantic anomaly. The updated retrievals over snow/ice yield more realistic seasonal changes in SO2 at high latitudes and offer enhanced sensitivity to sources during wintertime. An error analysis has been conducted to assess uncertainties in SO2 VCDs from both the spectral fit and Jacobian calculations. The uncertainties from spectral fitting are reflected in SO2 slant column densities (SCDs) and largely depend on the signal-to-noise ratio of the measured radiances, as implied by the generally smaller SCD uncertainties over clouds or for smaller solar zenith angles. The SCD uncertainties for individual pixels are estimated to be~0.15-0.3 DU (Dobson Units) between ~40°S and ~40°N and to be~0.2-0.5 DU at higher latitudes. The uncertainties from the Jacobians are approximately ~50-100% over polluted areas, and primarily attributed to errors in SO2 a priori profiles and cloud pressures, as well as the lack of explicit treatment for aerosols. Finally, the daily mean and median SCDs over the presumably SO2-free equatorial East Pacific have increased by only~0.0035 DU and ~0.003 DU respectively over the entire 15-year OMI record; while the standard deviation of SCDs has grown by only~0.02 DU or ~10%. Such remarkable long-term stability makes the new dataset particularly suitable for detecting regional changes in SO2 pollution.

OMI, SO2, Remote Sensing↗
NASA NTRS2016

Surface Water and Flood Extent Mapping, Monitoring, and Modeling Products and Services for the SERVIR Regions

SERVIR is a joint NASA - US Agency for International Development (USAID) project to improve environmental decision-making using Earth observations and geospatial technologies. A common need identified among SERVIR regions has been improved information for disaster risk reduction and in specific surface water and flood extent mapping, monitoring and forecasting. Of the 70 SERVIR products (active, complete, and in development), 4 are related to surface water and flood extent mapping, monitoring or forecasting. Visit http://www.servircatalog.net for more product details.

environment↗
NASA NTRSDate not supplied

RGB Imaging as a Tool to Monitor Indoor Crop Plant Production

Future crop production in space will require robust monitoring technologies that can optimize crop yield, reduce waste, and generate data for an automated plant growth design. Imaging has been suggested as a tool for measuring plant health, yet imaging systems for indoor crops have not been tested in spaceflight. Fortunately, RGB images of crop plants growing inside the Advanced Plant Habitat (APH) aboard the ISS have already been captured. In ground-based studies, the Kennedy Space Center (NASA, KSC) is collaborating with the United States Department of Agriculture (USDA ARS) to develop an imaging system for monitoring indoor crop plant health. In one study, we applied a drought stress to ‘Dragoon’ lettuce plants over a period of 14 days and captured RGB images in 24 h increments. Images were analyzed, and by applying a difference index, the images were able to be used to detect the drought stress in lettuce. This difference index was then applied to RGB images collected inside the APH ground unit for a pre-flight experiment growing ‘Outredgous’ lettuce under different substrate moisture conditions, and results showed that the RGB camera was capable of detecting drought stress inside the spaceflight plant growth hardware. These results suggest that RGB cameras already deployed to space may offer valuable information for monitoring plant production in extraterrestrial environments. This research was supported by NASA’s space biology program.

Rachel Tucker↗
NASA NTRS2005

Integrity monitoring of IGS products

The IGS has successfully produced precise GPS and GLONASS transmitter parameters, coordinates of IGS tracking stations, Earth rotation parameters, and atmospheric parameters. In this paper we discuss the concepts of integrity monitoring, system monitoring, and performance assessment, all in the context of IGS products. We report on a recent survey of IGS product users, and propose an integrity strategy for the IGS.

GPS↗
NASA NTRS2018

Harmonized Landsat/Sentinel-2 Products for Land Monitoring

The Harmonized Landsat-8 and Sentinel-2 (HLS) project is a NASA initiative aiming to produce a seamless, harmonized surface reflectance record from the Operational Land Imager (OLI) and Multi-Spectral Instrument (MSI) aboard Landsat-8 and Sentinel-2 remote sensing satellites, respectively. The HLS products are based on a set of algorithms to obtain seamless products from both sensors (OLI and MSI): atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function normalization and bandpass adjustment. As of version 1.3, the HLS v1.3 data set covers 9.12 million km2 and spans from first Landsat-8 data (2013) to present. HLS products provide near-daily surface reflectance information with a common geometric framework, and are suitable for a variety of agricultural and vegetation monitoring tasks, including analysis of crop type, condition, and phenology.

Masek, Jeffrey↗
NASA NTRS2017

Harmonized Landsat/Sentinel-2 Reflectance Products for Land Monitoring (Invited)

Many land applications require more frequent observations than can be obtained from a single 'Landsat class' sensor. Agricultural monitoring, inland water quality assessment, stand-scale phenology, and numerous other applications all require near-daily imagery at better than 1ha resolution. Thus the land science community has begun expressing a desire for a '30-meter MODIS' global monitoring capability. One cost-effective way to achieve this goal is via merging data from multiple, international observatories into a single virtual constellation. The Harmonized Landsat/Sentinel-2 (HLS) project has been working to generate a seamless surface reflectance product by combining observations from USGS/NASA Landsat-8 and ESA Sentinel-2. Harmonization in this context requires a series of radiometric and geometric transforms to create a single surface reflectance time series agnostic to sensor origin. Radiometric corrections include a common atmospheric correction using the Landsat-8 LaSRC/6S approach, a simple BRDF adjustment to constant solar and nadir view angle, and spectral bandpass adjustments to fit the Landsat-8 OLI reference. Data are then resampled to a consistent 30m UTM grid, using the Sentinel-2 global tile system. Cloud and shadow masking are also implemented. Quality assurance (QA) involves comparison of the output 30m HLS products with near-simultaneous MODIS nadir-adjusted observations. Prototoype HLS products have been processed for approximately 7% of the global land area using the NASA Earth Exchange (NEX) compute environment at NASA Ames, and can be downloaded from the HLS web site (https://hls.gsfc.nasa.gov). A wall-to-wall North America data set is being prepared for 2018. This talk will review the objectives and status of the HLS project, and illustrate applications of high-density optical time series data for agriculture and ecology. We also discuss lessons learned from HLS in the general context of implementing virtual constellations.

Reflectance↗
NASA NTRS1995

Lightweight Fiber Optic Gas Sensor for Monitoring Regenerative Food Production

In this final report, Physical Optics Corporation (POC) describes its development of sensors for oxygen, carbon dioxide, and relative humidity. POC has constructed a phase fluorometer that can detect oxygen over the full concentration range from 0 percent to 100 percent. Phase-based measurements offer distinct advantages, such as immunity to source fluctuation, photobleaching, and leaching. All optics, optoelectronics, power supply, and the printed circuit board are included in a single box; the only external connections to the fluorometer are the optical fiber sensor and a power cord. The indicator-based carbon dioxide sensor is also suitable for short-term and discrete measurements over the concentration range from 0 percent to 100 percent. The optical fiber-based humidity sensor contains a porous core for direct interaction of the light beam with water vapor within fiber pores; the detection range for the humidity sensor is 10 percent to 100 percent, and response time is under five minutes. POC is currently pursuing the commercialization of these oxygen and carbon dioxide sensors for environmental applications.

Schmidlin, Edward↗
NASA NTRS2009

In Situ Resource Utilization (ISRU) on the Moon: Moessbauer Spectroscopy as a Process Monitor for Oxygen Production

Essential consumables like oxygen must to be produced from materials on the lunar surface to enable a sustained, long-term presence of humans on the Moon. The Outpost Precursor for ISRU and Modular Architecture (OPTIMA) field test on Mauna Kea, Hawaii, facilitated by the Pacific International Space Center for Exploration Systems (PISCES) of the University of Hawaii at Hilo, was designed to test the implementation of three hardware concepts to extract oxygen from the lunar regolith: Precursor ISRU Lunar Oxygen Testbed (PILOT) developed by Lockheed Martin in Littleton, CO; Regolith & Environmental Science and Oxygen & Lunar Volatiles Extraction (RESOLVE) developed at the NASA Kennedy Space Center in Cape Canaveral, FL; and ROxygen developed at the NASA Johnson Space Center in Houston, TX. The three concepts differ in design, but all rely on the same general principle: hydrogen reduction of metal cations (primarily Fe2+) bonded to oxygen to metal (e.g., Fe0) with the production of water. The hydrogen source is residual hydrogen in the fuel tanks of lunar landers. Electrolysis of the water produces oxygen and hydrogen (which is recycled). We used the miniaturized M ssbauer spectrometer MIMOS II to quantify the yield of this process on the basis of the quantity of Fe0 produced. Iron M ssbauer spectroscopy identifies iron-bearing phases, determines iron oxidation states, and quantifies the distribution of iron between mineral phases and oxidation states. The oxygen yield can be calculated by quantitative measurements of the distribution of Fe among oxidation states in the regolith before and after hydrogen reduction. A M ssbauer spectrometer can also be used as a prospecting tool to select the optimum feedstock for the oxygen production plants (e.g., high total Fe content and easily reduced phases). As a demonstration, a MIMOS II backscatter spectrometer (SPESI, Germany) was mounted on the Cratos rover (NASA Glenn Research Center in Cleveland, OH), which is one of several rover concepts designed to excavate and transfer regolith to the stationary hydrogen reduction plants. Spaceflight versions of the MIMOS II are part of the instrument payloads of NASA s Mars Exploration Rovers and still operating five years after landing on the surface of the planet. MIMOS II was also selected for Phobos-Grunt, a Russian sample return mission to the martian moon Phobos scheduled to launch in 2009, and ESA s ExoMars rover, an exobiology mission scheduled to launch in 2013. An advanced version of the instrument is currently under development. A new detector system with a higher energy resolution will not only reduce the necessary measurement time considerably, but also allow the simultaneous acquisition of an X-ray fluorescence spectrum to determine the elemental composition of samples.

Morris, R.V.↗
NASA NTRS2010

Use of Multi-Year MODIS Phenological Data Products to Detect and Monitor Forest Disturbances at Regional and National Scales

This presentation discusses an effort to use select MODIS phenological products for forest disturbance monitoring at the regional and CONUS scales. Forests occur on ~1/3 of the U.S. land base and include regionally prevalent forest disturbances that can threaten forest sustainability. Regional and CONUS forest disturbance monitoring is needed for a national forest threat early warning system being developed by the USDA Forest Service with help from NASA, ORNL, and USGS. MODIS NDVI phenology products are being used to develop forest disturbance monitoring capabilities of this EWS.

Spruce, Joseph↗