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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Early warning and crop condition assessment research

The Early Warning Crop Condition Assessment Project of AgRISTARS was a multiagency and multidisciplinary effort. Its mission and objectives were centered around development and testing of remote-sensing techniques that enhance operational methodologies for global crop-condition assessments. The project developed crop stress indicators models that provide data filter and alert capabilities for monitoring global agricultural conditions. The project developed a technique for using NOAA-n satellite advanced very-high-resolution radiometer (AVHRR) data for operational crop-condition assessments. This technology was transferred to the Foreign Agricultural Service of the USDA. The project developed a U.S. Great Plains data base that contains various meteorological parameters and vegetative index numbers (VIN) derived from AVHRR satellite data. It developed cloud screening techniques and scan angle correction models for AVHRR data. It also developed technology for using remotely acquired thermal data for crop water stress indicator modeling. The project provided basic technology including spectral characteristics of soils, water, stressed and nonstressed crop and range vegetation, solar zenith angle, and atmospheric and canopy structure effects.

Boatwright, G. O.↗
NASA NTRS1985

Overview and highlights of Early Warning and Crop Condition Assessment project

Work of the Early Warning and Crop Condition Assessment (EW/CCA) project, one of eight projects in the Agriculture and Resources Inventory Surveys Through Aerospace Remote Sensing (AgRISTARS), is reviewed. Its mission, to develop and test remote sensing techniques that enhance operational methodologies for crop condition assessment, was in response to initiatives issued by the Secretary of Agriculture. Meteorologically driven crop stress indicator models have been developed or modified for wheat, maize, grain sorghum, and soybeans. These models provide early warning alerts of potential or actual crop stresses due to water deficits, adverse temperatures, and water excess that could delay planting or harvesting operations. Recommendations are given for future research involving vegetative index numbers and the NOAA and Landsat satellites.

Boatwright, G. O.↗
NASA NTRS2010

Material condition assessment with eddy current sensors

Eddy current sensors and sensor arrays are used for process quality and material condition assessment of conducting materials. In an embodiment, changes in spatially registered high resolution images taken before and after cold work processing reflect the quality of the process, such as intensity and coverage. These images also permit the suppression or removal of local outlier variations. Anisotropy in a material property, such as magnetic permeability or electrical conductivity, can be intentionally introduced and used to assess material condition resulting from an operation, such as a cold work or heat treatment. The anisotropy is determined by sensors that provide directional property measurements. The sensor directionality arises from constructs that use a linear conducting drive segment to impose the magnetic field in a test material. Maintaining the orientation of this drive segment, and associated sense elements, relative to a material edge provides enhanced sensitivity for crack detection at edges.

Goldfine, Neil J.↗
NASA NTRS2005

Condition Assessment and End-of-Life Prediction System for Electric Machines and Their Loads

An end-of-life prediction system developed for electric machines and their loads could be used in integrated vehicle health monitoring at NASA and in other government agencies. This system will provide on-line, real-time condition assessment and end-of-life prediction of electric machines (e.g., motors, generators) and/or their loads of mechanically coupled machinery (e.g., pumps, fans, compressors, turbines, conveyor belts, magnetic levitation trains, and others). In long-duration space flight, the ability to predict the lifetime of machinery could spell the difference between mission success or failure. Therefore, the system described here may be of inestimable value to the U.S. space program. The system will provide continuous monitoring for on-line condition assessment and end-of-life prediction as opposed to the current off-line diagnoses.

Parlos, Alexander G.↗
NASA NTRS1980

AgRISTARS: Soil moisture/early warning and crop condition assessment. Interface control document

The interactions and support functions required between the early warning/crop condition assessment (EW/CCA) project and soil moisture (SM) project are defined. The EW Project aims to develop, test and evaluate techniques and procedures for adapting remote sensing technology to provide early warning of events and the timely assessment of those factors which affect the quality and quantity of production of economically important crops. Those techniques to augment and reinforce the current assessment activities are to be developed to improve the definition of the relationship between the plant(s) and its environment. This assessment and evaluation will certainly include the need for soil moisture measurement and estimation. The SM Project aims to develop, test, and evaluate techniques and procedures to measure or predict soil moisture in the root zone using both contact and remote sensors.

Source record↗
NASA NTRS2010

Using Facility Condition Assessments to Identify Actions Related to Infrastructure

To support cost effective, quality research it is essential that laboratory and testing facilities are maintained in a continuous and reliable state of availability at all times. NASA Langley Research Center (LaRC) and its maintenance contractor, Jacobs Technology, Inc. Research Operations, Maintenance, and Engineering (ROME) group, are in the process of implementing a combined Facility Condition Assessment (FCA) and Reliability Centered Maintenance (RCM) program to improve asset management and overall reliability of testing equipment in facilities such as wind tunnels. Specific areas are being identified for improvement, the deferred maintenance cost is being estimated, and priority is being assigned against facilities where conditions have been allowed to deteriorate. This assessment serves to assist in determining where to commit available funds on the Center. RCM methodologies are being reviewed and enhanced to assure that appropriate preventive, predictive, and facilities/equipment acceptance techniques are incorporated to prolong lifecycle availability and assure reliability at minimum cost. The results from the program have been favorable, better enabling LaRC to manage assets prudently.

Rubert, Kennedy F.↗
NASA NTRSDate not supplied

GeoXO Atmospheric Composition Instrument (AC) Measurements Conditions Assessment

NOAA’s next generation Geostationary Extended Observations (GeoXO) satellite system will advance Earth observations from geostationary orbit. GeoXO will supply vital information supporting the U.S. weather, ocean, and climate operations. The recommended three-satellite constellation includes spacecraft at GOES-Central position, that will carry an Atmospheric Composition Instrument (ACX) among its payloads; the requirement on the ACX is to scan its region of interest in one hour. An assessment of ACX observational conditions is presented, based on view geometry and solar angle range over the year. The availability for observations of each pixel is estimated per day of the year, as function of the geometric air mass factor (AMF), which can be related to signal to noise ratio using a model of the ACX instrument performance, and ultimately to expected column error for specific atmospheric species. In addition, cloud climatology – based on statistics derived from GOES-16 ABI cloud product data – is considered to determine typical fractions of cloud-free ACX observations and typical cloud optical depths, for each pixel as function of time of day and season. The results of such assessments can be used to prepare for GeoXO ACX data and further the understanding and development of the future instrument operations.

Boryana Efremova↗
NASA NTRS1981

AgRISTARS: Early warning and crop condition assessment. Plant cover, soil temperature, freeze, water stress, and evapotranspiration conditions

Emissive (10.5 to 12.5 microns) and reflective (0.55 to 1.1 microns) data for ten day scenes and infrared data for six night scenes of southern Texas were analyzed for plant cover, soil temperature, freeze, water stress, and evapotranspiration. Heat capacity mapping mission radiometric temperatures were: within 2 C of dewpoint temperatures, significantly correlated with variables important in evapotranspiration, and related to freeze severity and planting depth soil temperatures.

Wiegand, C. L.↗
NASA NTRS2007

Condition Assessment of Kevlar Composite Materials Using Raman Spectroscopy

This viewgraph presentation includes the following main concepts. Goal: To evaluate Raman spectroscopy as a potential NDE tool for the detection of stress rupture in Kevlar. Objective: Test a series of strand samples that have been aged under various conditions and evaluate differences and trends in the Raman response. Hypothesis: Reduction in strength associated with stress rupture may manifest from changes in the polymer at a molecular level. If so, than these changes may effect the vibrational characteristics of the material, and consequently the Raman spectra produced from the material. Problem Statement: Kevlar composite over-wrapped pressure vessels (COPVs) on the space shuttles are greater than 25 years old. Stress rupture phenomena is not well understood for COPVs. Other COPVs are planned for hydrogen-fueled vehicles using Carbon composite material. Raman spectroscopy is being explored as an non-destructive evaluation (NDE) technique to predict the onset of stress rupture in Kevlar composite materials. Test aged Kevlar strands to discover trends in the Raman response. Strength reduction in Kevlar polymer will manifest itself on the Raman spectra. Conclusions: Raman spectroscopy has shown relative changes in the intensity and FWHM of the ~1613 cm(exp -1) peak. Reduction in relative intensity for creep, fleet leader, and SIM specimens compared to the virgin strands. Increase in FWHM has been observed for the creep and fleet leader specimens compared to the virgin strands. Changes in the Raman spectra may result from redistributing loads within the material due to the disruption of hydrogen bonding between crystallites or defects in the crystallites from aging the Kevlar strands. Peak shifting has not been observed to date. Analysis is ongoing. Stress measurements may provide a tool in the short term.

Washer, Glenn↗
NASA NTRSDate not supplied

Uncertainty Quantification of Inducer Natural Frequency using Conditional Assessment of Modeling and Modal Testing of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗
NASA NTRSDate not supplied

Uncertainty Quantification of Inducer Eigenvalues using Conditional Assessment of Models and Modal Test of Simpler Systems

The low pressure fuel pump inducer of the new Space Launch System RS25 core stage engine operates in a highly complex environment that substantially affects its modal characteristics. Some of the more important effects are fluid-added mass resulting from operation within a light liquid (Hydrogen), and the magnification of this effect due to tight tip clearance. Since higher order cavitation has been identified as a significant harmonic driver, knowledge of the natural frequency of potentially excitable modes is critical for safe operation, but this frequency cannot be measured during the severe operational environment. A comprehensive testing and analysis program has therefore been performed over the last four years to identify the nominal value and uncertainty of the frequency by modeling and testing four simpler structures which share some of the characteristics of the operational inducer. This testing was used to assess and adjust modeling techniques and excellent correlation was achieved. Identification of the uncertainty in the inducer frequency itself was still problematic, however. This difficulty led to an investigation of Bayesian uncertainty quantification techniques, and to the application of the relatively simple technique of Multi-Variate Normal conditional distributions to calculate the inducer natural frequency uncertainty. Assumptions on prior distributions of uncertainty of the fluid-added mass and tip clearance effect are initially applied to models of each of the simple structures and the inducer itself, and these uncertainties are propagated to generate natural frequencies using design of experiments. Simple response surfaces are then created from this data in order to calculate a Covariance Matrix relating all of these natural frequencies. Finally, the results from modal test of the simple structures are considered to be observations and used to calculate the conditional variance of the desired inducer frequencies. As this method is less rigorous than more complicated Bayesian methods reported in the literature, a conservative factor is applied to the result, but the resulting uncertainty is still significantly less than originally estimated and will greatly assist certification of the inducer for use in the engine.

Uncertainty Quantification↗
NASA NTRS1997

Adaptive responses of the cardiovascular system to prolonged spaceflight conditions: assessment with Holter monitoring

This article presents selected findings obtained with Holter monitoring from two crew members of the expedition, performed during a 175-day space mission on board orbital space station "MIR." Using mathematical processing of daily cardiointervals files, 5-minute sections of records were analyzed consecutively. Then, the average daily values of indices, the average-per-every-eight-hours values (morning, evening, night) and mean values per hour were computed. The results of analysis showed that prolonged exposure of man to microgravity conditions leads to important functional alteration in human neuroautonomic regulatory mechanisms. Both crew members had significant increase of heart rate, the rise of stress index, the decrease in power of the spectrum in the range of respiratory sinus arrhythmia. These marked signs of activation of the sympathetic section of the vegetative nervous system showed individual variations. The analysis of the daily collection of cardiointervals with Holter monitoring allows us to understand and forecast the functional feasibilities of the human organism under a variety of stress conditions associated with acute and chronic microgravity exposure.

manned↗
NASA NTRS1983

The effect of irradiation and reflectance variability on vegetation condition assessment

Surface reflectance and global irradiance variations across an imaged area determine the minimum signal difference from groups of pixels in different targets needed to discriminate them. The factors affecting such variations and their magnitudes are considered. The sensor output also depends upon the interaction of the spectral response of the sensor and the spectral upwelling radiance from the target. From a consideration of the spectral instrument responses of detectors in the Landsat multispectral scanners (MS), together with measured reflectance factors of a vegetative canopy stressed to different levels of severity, the feasibility of mapping and quantifying disease stress witlh Landsat vegetative indices (VINs) is demonstrated.

Duggin, M. J.↗
NASA NTRS1983

Radar remote sensing for crop classification and canopy condition assessment: Ground-data documentation

A vegetation and soil-moisture experiment was conducted in order to examine the microwave emission and backscattering from vegetation canopies and soils. The data-acquisition methodology used in conjunction with the mobile radar scatterometer (MRS) systems is described and associated ground-truth data are documented. Test fields were located in the Kansas River floodplain north of Lawrence, Kansas. Ten fields each of wheat, corn, and soybeans were monitored over the greater part of their growing seasons. The tabulated data summarize measurements made by the sensor systems and represent target characteristics. Target parameters describing the vegetation and soil characteristics include plant moisture, density, height, and growth stage, as well as soil moisture and soil-bulk density. Complete listings of pertinent crop-canopy and soil measurements are given.

Ulaby, F. T.↗