Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Network 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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Software Health Management with Bayesian Networks

Most modern aircraft as well as other complex machinery is equipped with diagnostics systems for its major subsystems. During operation, sensors provide important information about the subsystem (e.g., the engine) and that information is used to detect and diagnose faults. Most of these systems focus on the monitoring of a mechanical, hydraulic, or electromechanical subsystem of the vehicle or machinery. Only recently, health management systems that monitor software have been developed. In this paper, we will discuss our approach of using Bayesian networks for Software Health Management (SWHM). We will discuss SWHM requirements, which make advanced reasoning capabilities for the detection and diagnosis important. Then we will present our approach to using Bayesian networks for the construction of health models that dynamically monitor a software system and is capable of detecting and diagnosing faults.

Mengshoel, Ole↗
NASA NTRS1977

Usefulness of LANDSAT data for monitoring plant development and range conditions in California's annual grassland

A network of sampling sites throughout the annual grassland region was established to correlate plant growth in stages and forage production to climatic and other environmental factors. Plant growth and range conditions were further related to geographic location and seasonal variations. A sequence of LANDSAT data was obtained covering critical periods in the growth cycle. Data were analyzed by both photointerpretation and computer aided techniques. Image characteristics and spectral reflectance data were then related to forage production, range condition, range site, and changing growth conditions.

Carneggie, D. M.↗
NASA NTRS2007

Solutions Network Formulation Report. The Potential Contribution of the International GPM Program to the NOAA Estuarine Reserves Division's System-wide Monitoring Program

Data collected via the International GPM Program could be used to provide a solution for the NOAA Estuarine Reserves Division s System-wide Monitoring Program by augmenting in situ rainfall measurements with data acquired via future satellite-acquired precipitation data. This Candidate Solution is in alignment with the Coastal Management National Application and will benefit society by assisting in estuary preservation.

Hilbert, Kent↗
NASA NTRS2008

Potential Use of a Bayesian Network for Discriminating Flash Type from Future GOES-R Geostationary Lightning Mapper (GLM) data

Continuous monitoring of the ratio of cloud flashes to ground flashes may provide a better understanding of thunderstorm dynamics, intensification, and evolution, and it may be useful in severe weather warning. The National Lighting Detection Network TM (NLDN) senses ground flashes with exceptional detection efficiency and accuracy over most of the continental United States. A proposed Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite (GOES-R) will look at the western hemisphere, and among the lightning data products to be made available will be the fundamental optical flash parameters for both cloud and ground flashes: radiance, area, duration, number of optical groups, and number of optical events. Previous studies have demonstrated that the optical flash parameter statistics of ground and cloud lightning, which are observable from space, are significantly different. This study investigates a Bayesian network methodology for discriminating lightning flash type (ground or cloud) using the lightning optical data and ancillary GOES-R data. A Directed Acyclic Graph (DAG) is set up with lightning as a "root" and data observed by GLM as the "leaves." This allows for a direct calculation of the joint probability distribution function for the lighting type and radiance, area, etc. Initially, the conditional probabilities that will be required can be estimated from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) together with NLDN data. Directly manipulating the joint distribution will yield the conditional probability that a lightning flash is a ground flash given the evidence, which consists of the observed lightning optical data [and possibly cloud data retrieved from the GOES-R Advanced Baseline Imager (ABI) in a more mature Bayesian network configuration]. Later, actual GLM and NLDN data can be used to refine the estimates of the conditional probabilities used in the model; i.e., the Bayesian network is a learning network. Methods for efficient calculation of the conditional probabilities (e.g., an algorithm using junction trees), finding data conflicts, goodness of fit, and dealing with missing data will also be addressed.

Solakiewiz, Richard↗
NASA NTRS2011

Automated Cryocooler Monitor and Control System

A system was designed to automate cryogenically cooled low-noise amplifier systems used in the NASA Deep Space Network. It automates the entire operation of the system including cool-down, warm-up, and performance monitoring. The system is based on a single-board computer with custom software and hardware to monitor and control the cryogenic operation of the system. The system provides local display and control, and can be operated remotely via a Web interface. The system controller is based on a commercial single-board computer with onboard data acquisition capability. The commercial hardware includes a microprocessor, an LCD (liquid crystal display), seven LED (light emitting diode) displays, a seven-key keypad, an Ethernet interface, 40 digital I/O (input/output) ports, 11 A/D (analog to digital) inputs, four D/A (digital to analog) outputs, and an external relay board to control the high-current devices. The temperature sensors used are commercial silicon diode devices that provide a non-linear voltage output proportional to temperature. The devices are excited with a 10-microamp bias current. The system is capable of monitoring and displaying three temperatures. The vacuum sensors are commercial thermistor devices. The output of the sensors is a non-linear voltage proportional to vacuum pressure in the 1-Torr to 1-millitorr range. Two sensors are used. One measures the vacuum pressure in the cryocooler and the other the pressure at the input to the vacuum pump. The helium pressure sensor is a commercial device that provides a linear voltage output from 1 to 5 volts, corresponding to a gas pressure from 0 to 3.5 MPa (approx. = 500 psig). Control of the vacuum process is accomplished with a commercial electrically operated solenoid valve. A commercial motor starter is used to control the input power of the compressor. The warm-up heaters are commercial power resistors sized to provide the appropriate power for the thermal mass of the particular system, and typically provide 50 watts of heat. There are four basic operating modes. "Cool " mode commands the system to cool to normal operating temperature. "Heat " mode is used to warm the device to a set temperature near room temperature. "Pump " mode is a maintenance function that allows the vacuum system to be operated alone to remove accumulated contaminants from the vacuum area. In "Off " mode, no power is applied to the system.

Britcliffe, Michael J.↗
NASA NTRS1981

Networks consolidation program: Maintenance and Operations (M&O) staffing estimates

The Mark IV-A consolidate deep space and high elliptical Earth orbiter (HEEO) missions tracking and implements centralized control and monitoring at the deep space communications complexes (DSCC). One of the objectives of the network design is to reduce maintenance and operations (M&O) costs. To determine if the system design meets this objective an M&O staffing model for Goldstone was developed which was used to estimate the staffing levels required to support the Mark IV-A configuration. The study was performed for the Goldstone complex and the program office translated these estimates for the overseas complexes to derive the network estimates.

Goodwin, J. P.↗
NASA NTRS1993

Micro-sensors for in-situ meteorological measurements

Improved in-situ meteorological measurements are needed for monitoring the weather and climate of the terrestrial and Martian atmospheres. We have initiated a program to assess the feasibility and utility of micro-sensors for precise in-situ meteorological measurements in these environments. Sensors are being developed for measuring pressure, temperature, wind velocity, humidity, and aerosol amounts. Silicon micro-machining and large scale integration technologies are being used to make sensors that are small, rugged, lightweight, and require very little power. Our long-term goal is to develop very accurate miniaturized sensors that can be incorporated into complete instrument packages or 'micro weather stations,' and deployed on a variety of platforms. If conventional commercially available silicon production techniques can be used to fabricate these sensor packages, it will eventually be possible to mass-produce them at low cost. For studies of the Earth's troposphere and stratosphere, they could be deployed on aircraft, dropsondes, radiosondes, or autonomous surface stations at remote sites. Improved sensor accuracy and reduced sensor cost are the primary challenges for these applications. For studies of the Martian atmosphere, these sensor packages could be incorporated into the small entry probes and surface landers that are being planned for the Mars Environmental SURvey (MESUR) Mission. That decade-long program will deploy a global network of small stations on the Martian surface for monitoring meteorological and geological processes. Low mass, low power, durability, large dynamic range and calibration stability are the principal challenges for this application. Our progress on each of these sensor types is presented.

Crisp, David↗
NASA NTRS2010

LDCM Ground System. Network Lesson Learned

This slide presentation reviews the Landsat Data Continuity Mission (LDCM) and the lessons learned in implementing the network that was assembled to allow for the acquisition, archiving and distribution of the data from the Landsat mission. The objective of the LDCM is to continue the acquisition, archiving, and distribution of moderate-resolution multispectral imagery affording global, synoptic, and repetitive coverage of the earth's land surface at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. It includes a review of the ground network, including a block diagram of the ground network elements (GNE) and a review of the RF design and testing. Also included is a listing of the lessons learned.

Gal-Edd, Jonathan↗
NASA NTRS2006

Comparison of Satellite Observations of Nitrogen Dioxide to Surface Monitor Nitrogen Dioxide Concentration

Nitrogen dioxide is one of the U. S. EPA s criteria pollutants, and one of the main ingredients needed for the production of ground-level ozone. Both ozone and nitrogen dioxide cause severe public health problems. Existing satellites have begun to produce observational data sets for nitrogen dioxide. Under NASAs Earth Science Applications Program, we examined the relationship between satellite observations and surface monitor observations of this air pollutant to examine if the satellite data can be used to facilitate a more capable and integrated observing network. This report provides a comparison of satellite tropospheric column nitrogen dioxide to surface monitor nitrogen dioxide concentration for the period from September 1996 through August 1997 at more than 300 individual locations in the continental US. We found that the spatial resolution and observation time of the satellite did not capture the variability of this pollutant as measured at ground level. The tools and processes developed to conduct this study will be applied to the analysis of advanced satellite observations. One advanced instrument has significantly better spatial resolution than the measurements studied here and operates with an afternoon overpass time, providing a more representative distribution for once-per-day sampling of this photochemically active atmospheric constituent.

Kleb, Mary M.↗
NASA NTRS2002

MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring

Development and evaluation of Intensive Care Unit (ICU) decision-support systems would be greatly facilitated by the availability of a large-scale ICU patient database. Following our previous efforts with the MIMIC (Multi-parameter Intelligent Monitoring for Intensive Care) Database, we have leveraged advances in networking and storage technologies to develop a far more massive temporal database, MIMIC II. MIMIC II is an ongoing effort: data is continuously and prospectively archived from all ICU patients in our hospital. MIMIC II now consists of over 800 ICU patient records including over 120 gigabytes of data and is growing. A customized archiving system was used to store continuously up to four waveforms and 30 different parameters from ICU patient monitors. An integrated user-friendly relational database was developed for browsing of patients' clinical information (lab results, fluid balance, medications, nurses' progress notes). Based upon its unprecedented size and scope, MIMIC II will prove to be an important resource for intelligent patient monitoring research, and will support efforts in medical data mining and knowledge-discovery.

NASA Discipline Cardiopulmonary↗
NASA NTRS1986

Unattended deep space station tracking station development: Monitor and control technology

The major developments leading to successful demonstration of fully unattended operation of a Deep Space Network (DSN) station (DSS 13) are reviewed. Unattended operation was demonstrated by reliably tracking, commanding, and delivering telemetry from the Pioneer 8 spacecraft. Transfer of automated monitor and control technology to DSN implementation is summarized, along with related accomplishments.

Foster, C.↗
NASA NTRS2014

Drought Prediction for Socio-Cultural Stability Project

The primary objective of this project is to answer the question: "Can existing, linked infrastructures be used to predict the onset of drought months in advance?" Based on our work, the answer to this question is "yes" with the qualifiers that skill depends on both lead-time and location, and especially with the associated teleconnections (e.g., ENSO, Indian Ocean Dipole) active in a given region season. As part of this work, we successfully developed a prototype drought early warning system based on existing/mature NASA Earth science components including the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) forecasting model, the Land Information System (LIS) land data assimilation software framework, the Catchment Land Surface Model (CLSM), remotely sensed terrestrial water storage from the Gravity Recovery and Climate Experiment (GRACE) and remotely sensed soil moisture products from the Aqua/Advanced Microwave Scanning Radiometer - EOS (AMSR-E). We focused on a single drought year - 2011 - during which major agricultural droughts occurred with devastating impacts in the Texas-Mexico region of North America (TEXMEX) and the Horn of Africa (HOA). Our results demonstrate that GEOS-5 precipitation forecasts show skill globally at 1-month lead, and can show up to 3 months skill regionally in the TEXMEX and HOA areas. Our results also demonstrate that the CLSM soil moisture percentiles are a goof indicator of drought, as compared to the North American Drought Monitor of TEXMEX and a combination of Famine Early Warning Systems Network (FEWS NET) data and Moderate Resolution Imaging Spectrometer (MODIS)'s Normalizing Difference Vegetation Index (NDVI) anomalies over HOA. The data assimilation experiments produced mixed results. GRACE terrestrial water storage (TWS) assimilation was found to significantly improve soil moisture and evapotransportation, as well as drought monitoring via soil moisture percentiles, while AMSR-E soil moisture assimilation produced marginal benefits. We carried out 1-3 month lead-time forecast experiments using GEOS-5 forecasts as input to LIS/CLSM. Based on these forecast experiments, we find that the expected skill in GEOS-5 forecasts from 1-3 months is present in the soil moisture percentiles used to indicate drought. In the case of the HOA drought, the failure of the long rains in April appears in the February 1, March 1 and April 1 initialized forecasts, suggesting that for this case, drought forecasting would have provided some advance warning about the drought conditions observed in 2011. Three key recommendations for follow-up work include: (1) carry out a comprehensive analysis of droughts observed over the entire period of record for GEOS-5 forecasts; (2) continue to analyze the GEOS-5 forecasts in HOA stratifying by anomalies in long and short rains; and (3) continue to include GRACE TWS, Soil Moisture/Ocean Salinity (SMOS) and the upcoming NASA Soil Moisture Active/Passive (SMAP) soil moisture products in a routine activity building on this prototype to further quantify the benefits for drought assessment and prediction.

Peters-Lidard, Christa↗
NASA NTRS2018

A Global Spatially Contiguous Solar-Induced Fluorescence (CSIF) Dataset Using Neural Networks

Satellite-retrieved solar-induced chlorophyll fluorescence (SIF) has shown great potential to monitor the photosynthetic activity of terrestrial ecosystems. However, several issues, including low spatial and temporal resolution of the gridded datasets and high uncertainty of the individual retrievals, limit the applications of SIF. In addition, inconsistency in measurement footprints also hinders the direct comparison between gross primary production (GPP) from eddy covariance (EC) flux towers and satellite-retrieved SIF. In this study, by training a neural network (NN) with surface reflectance from the MODerate-resolution Imaging Spectroradiometer (MODIS) and SIF from Orbiting Carbon Observatory-2 (OCO-2), we generated two global spatially contiguous SIF (CSIF) datasets at moderate spatiotemporal (0.05° 4-day) resolutions during the MODIS era, one for clear-sky conditions (2000–2017) and the other one in all-sky conditions (2000–2016). The clear-sky instantaneous CSIF (CSIF(sub clear-inst)) shows high accuracy against the clear-sky OCO-2 SIF and little bias across biome types. The all-sky daily average CSIF (CSIF(sub all-daily)) dataset exhibits strong spatial, seasonal and interannual dynamics that are consistent with daily SIF from OCO-2 and the Global Ozone Monitoring Experiment-2 (GOME-2). An increasing trend (0.39 %) of annual average CSIFall-daily is also found, confirming the greening of Earth in most regions. Since the difference between satellite-observed SIF and CSIF is mostly caused by the environmental down-regulation on SIF(sub yield), the ratio between OCO-2 SIF and CSIF(sub clear-inst) can be an effective indicator of drought stress that is more sensitive than the normalized difference vegetation index and enhanced vegetation index. By comparing CSIF(sub all-daily) with GPP estimates from 40 EC flux towers across the globe, we find a large cross-site variation (c.v. = 0.36) of the GPP–SIF relationship with the highest regression slopes for evergreen needleleaf forest. However, the cross-biome variation is relatively limited (c.v. = 0.15). These two contiguous SIF datasets and the derived GPP–SIF relationship enable a better understanding of the spatial and temporal variations of the GPP across biomes and climate.

Zhang, Yao↗
NASA NTRS1972

Large-scale solar magnetic fields and H-alpha patterns

Coronal and interplanetary magnetic fields computed from measurements of large-scale photospheric magnetic fields suffer from interruptions in day-to-day observations and the limitation of using only measurements made near the solar central meridian. Procedures were devised for inferring the lines of polarity reversal from H-alpha solar patrol photographs that map the same large-scale features found on Mt. Wilson magnetograms. These features may be monitored without interruption by combining observations from the global network of observatories associated with NOAA's Space Environment Services Center. The patterns of inferred magnetic fields may be followed accurately as far as 60 deg from central meridian. Such patterns will be used to improve predictions of coronal features during the next solar eclipse.

Mcintosh, P. S.↗
NASA NTRS1986

Reverse osmosis water purification system

A reverse osmosis water purification system, which uses a programmable controller (PC) as the control system, was designed and built to maintain the cleanliness and level of water for various systems of a 64-m antenna. The installation operates with other equipment of the antenna at the Goldstone Deep Space Communication Complex. The reverse osmosis system was designed to be fully automatic; with the PC, many complex sequential and timed logic networks were easily implemented and are modified. The PC monitors water levels, pressures, flows, control panel requests, and set points on analog meters; with this information various processes are initiated, monitored, modified, halted, or eliminated as required by the equipment being supplied pure water.

Ahlstrom, H. G.↗