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Ten composite pressure vessels were instrumented with fiber Bragg grating sensors and pressure tested Through burst. This paper and presentation will discuss the testing methodology, the test results, compare the testing results to the analytical model, and also compare the fiber Bragg grating sensor data with data obtained against that obtained from foil strain gages.
The Ko displacement theory is formulated for a cantilever tubular wing spar under bending, torsion, and combined bending and torsion loading. The Ko displacement equations are expressed in terms of strains measured at multiple sensing stations equally spaced on the surface of the wing spar. The bending and distortion strain data can then be input to the displacement equations to calculate slopes, deflections, and cross-sectional twist angles of the wing spar at the strain-sensing stations for generating the deformed shapes of flexible aircraft wing spars. The displacement equations have been successfully validated for accuracy by finite-element analysis. The Ko displacement theory that has been formulated could also be applied to calculate the deformed shape of simple and tapered beams, plates, and tapered cantilever wing boxes. The Ko displacement theory and associated strain-sensing system (such as fiber optic sensors) form a powerful tool for in-flight deformation monitoring of flexible wings and tails, such as those often employed on unmanned aerial vehicles. Ultimately, the calculated displacement data can be visually displayed in real time to the ground-based pilot for monitoring the deformed shape of unmanned aerial vehicles during flight.
An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere ((Theta)) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from the Special Sensor Microwave/Imager (SSM/I). The statistical relation is established between the input parameters (the surface wind stress, the 850 mb wind, the precipitable water, time and location) and the target data ((Theta) calculated from rawinsondes and reanalysis of numerical weather prediction model). The results are validated with independent daily rawinsonde observations, monthly mean reanalysis data, and through regional water balance. This study clearly demonstrates the improvement of (Theta) derived from satellite data using SVR over previous data sets based on linear regression and neural network. The SVR methodology reduces both mean bias and standard deviation comparedwith rawinsonde observations. It agrees better with observations from synoptic to seasonal time scales, and compare more favorably with the reanalysis data on seasonal variations. Only the SVR result can achieve the water balance over South America. The rationale of the advantage by SVR method and the impact of adding the upper level wind will also be discussed.
The ability to generate chlorophyll a (Chl a) assessments from ocean color orbital sensors, such as VIIRS and MODIS, that satisfy the requirements to be climate-quality data record (CDR) quality is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. NASA has a mandate to collect, analyze, and distribute in situ data of the highest possible quality with documented uncertainties and in keeping with established performance metrics. Using a dataset of over 18,000 HPLC phytoplankton pigment samples representing water collected in all major ocean basins analyzed a central laboratory (Field Support Group (FSG) of the Ocean Ecology Laboratory (OEL) at NASA Goddard Space Flight Center (GSFC)), we performed an assessment of the global precision among sample replicates of Chl a as well as major accessory pigments. We investigated the impacts of filtration volume, water basin, collection technique, pigment concentration, and different filtration volumes for replicate filters on replicate filter precision, as well as investigating any pigment-specific differences. Our results quantify sample variability with the goal of understanding any systemic biases or biogeographic influences.
Australia’s unprecedented fire disasters at the end of 2019 to early 2020 emitted huge amounts of carbon monoxide (CO) and fire aerosol particles, and the long-range transport of the smoke plumes poses great impact to climate change, such as altering the Antarctic ozone (O3) hole. Spaceborne observations from satellites have been proven successful in monitoring CO from wildfires in the past decade and can be used to examine the associated CO transport. The primary remote sensing data used in this study is the Single Field of View (SFOV) Sounder Atmospheric Product (SiFSAP) derived from the Cross-track Infrared Sounder (CrIS) on SNPP, a new product that will be generated at NASA and released to the public in a few months. SiFSAP has a high spatial resolution of ~14 km and includes atmospheric profiles of temperature, water vapor, CO, O3, as well as cloud products, and as the SiFSAP algorithm performs both day- and night-time retrievals, it provides an additional observation for night-time in comparison to the day-time-only solar polar satellite instruments such as MOPPIT, OMPS, and TROPOMI. Most recent significant improvements in the quality of this product plus its good spatial resolution (better than most global weather and climate models) enable us to conduct process-oriented analysis of CO transport, and the variation of water vapor, O3 and clouds (optical depth, effective radius and cloud height) within and around the fire plumes. The wind fields from MERRA-2 reanalysis will be used to help characterize the transport. Other remote sensing data, such as CO from AIRS, MOPPIT and TROPOMI, O3 from OMPS and TROPOMI, as well as the UV aerosol index from OMI and OMPS, will be used and compared with SiFSAP sounder products. Cross-validation of CO and O3 from these different sensors with the corresponding MERRA-2 products will also be carried out. Along the plume transport path, some enhancement of O3 and correlation between fire aerosol, cloud optical depth and water vapor have been found but need further investigation. Using the transport of fire plumes over the Southern Pacific Ocean as a unique testbed, this study will demonstrate the trace species monitoring capability of current satellite observations, in particular, for CO and O3, and hopefully, it will provide some insight on the impacts on fire emissions on air quality and climate.
Despite challenges with data quality and scope, low-cost sensor networks have skyrocketed in popularity over the last 15 years, making air quality data available on refined spatial scales. More recently, studies have leveraged both high and low-quality instruments to create stronger “hybrid” models, with most studies focusing on particulate matter. Low-cost measurements typically represent ground-level emissions only, providing context for human health issues from climate change-driven events such as wildfires. Since low-cost sensors’ capabilities are localized, daily events and microclimates tend to dominate the data rather than larger regional or atmospheric trends. Likewise, their low cost explains their high uncertainty. In contrast, some regulatory-grade instruments produce column measurements as well, providing reliable information on a broader scope. To bridge this gap while expanding into gas-phase measurements, we deployed 12 air quality sensor packages in California, USA during the 2022 wildfire season. These INSTEP (Inexpensive Network Sensor Technology Exploring Pollution) monitors measure carbon monoxide (CO), carbon dioxide (CO2), ozone (O3), nitrogen dioxide (NO2), and several hydrocarbons including methane (CH4) and formaldehyde (HCHO). Half of the monitors were co-located with remote sensing spectrometers: NASA Pandora and Total Column Carbon Observing Network (TCCON). The overlap in pollutants includes NO2, O3, and HCHO between the INSTEP monitors and the Pandora column measurements. TCCON covers column CO, CO2, and CH4, rounding out our comparison. Most of the monitors were distributed throughout the San Francisco Bay area, and an additional three were located within 100 km of Los Angeles. The sites ranged in geographic and population characteristics, including desert, mountainous, coastal, and urban locations. Since varying environmental conditions such as temperature and pressure are known to challenge sensor performance, we will apply newer sensor “calibration” techniques meant to combat this. We will normalize our sensor signals by z-scoring them prior to applying a single calibration model in the form of multivariate linear regression or an artificial neural network. While this technique has been validated for the hydrocarbon and ozone sensor types (metal oxide), it has not yet been tested on electrochemical and non-dispersive infrared sensors, which are also used in the INSTEP monitors. This will serve as a test to see if this normalization technique – or another – is most effective in accounting for environmental differences among sensors. Related data analysis efforts have found success with a variety of geospatial analysis techniques, including weighted network models in which high-quality instruments are given higher weights than their low-cost counterparts. Our preliminary analysis will focus on kriging, which uses a Gaussian algorithm to assign weights, providing estimated pollution levels at locations between monitors. Smoke trajectory and evolution will also be considered using both measurement types. We also aim to baseline subtract our emission estimates from each region to determine which portion of emissions are regional and local, further characterizing burn differences in northern and southern California fires. Future directions include using INSTEP jointly with TEMPO satellite data, and mobile deployments on aircraft and uncrewed aerial vehicles (UAV).
NASA technical memorandum discusses research on use of data from network of ground-based magnetic direction-finding ground-strike lightning sensors to diagnose and predict occurrence and evolution of thunderstorms. Purposes of study to explore applicability and limitations of extrapolation techniques used to generate forecasts from data; to examine physically-based, nonlinear mathematical models for applicability to lightning-forecast problem; and to determine valid extrapolation ranges of such models for various weather scenarios.
A spacecraft Attitude Control and Determination Subsystem (ACDS) is heavily dependent upon simulation throughout its entire development, implementation and ground test cycle. Engineering simulation tools are typically developed to design and analyze control systems to validate the design and software simulation tools are required to qualify the flight software. However, the need for simulation does not end here. Operating the ACDS of a spacecraft on the ground requires the simulation of spacecraft dynamics, disturbance modeling and celestial body motion. Sensor data must also be simulated and substituted for actual sensor data on the ground so that the spacecraft will respond by sending commands to the actuators as they will on orbit. And finally, the simulators is the primary training tool and test-bed for the Flight Operations Team. In this paper various ACDS simulation, developed for or used by the Landsat 7 project will be described. The paper will include a description of each tool, its unique attributes, and its role in the overall development and testing of the ACDS. Finally, a section is included which discusses how the coordinated use of these simulation tools can maximize the probability of uncovering software, hardware and operations errors during the ground test process.
The data from the collimated sensors of the LEND instrument are shown to be of exceptionally high quality. Counting uncertainties are about 0.3% relative and are shown to be the only significant source of random error, thus conclusions based on small differences in count rates are valid. By comparison with the topography of Shoemaker crater, the spatial resolution of the instrument is shown to be consistent with the design value of 5 km for the radius of the circle over which half the counts from the lunar surface would be determined. The observed epithermal-neutron suppression factor due to the hydrogen deposit in Shoemaker crater of 0.25 plus or minus 0.04 cps is consistent with the collimated field-of-view rate of 1.7 cps estimated by Mitrofanov et al. (2010a). The statistical significance of the neutron suppressed regions (NSRs) relative to the larger surrounding polar region is demonstrated, and it is shown that they are not closely related to the permanently shadowed regions. There is a significant increase in H content in the polar regions independent of the H content of the NSRs. The non-NSR H content increases directly with latitude, and the rate of increase is virtually identical at both poles. There is little or no increase with latitude outside the polar region. Various mechanisms to explain this steep increase in the non-NSR polar H with latitude are investigated, and it is suggested that thermal volatilization is responsible for the increase because it is minimized at the low surface temperatures close to the poles.
This paper will introduce Mars Entry Descent and Landing Instrumentation (MEDLI2) on NASA's Mars2020 mission. Mars2020 is a flagship NASA mission with science and technology objectives to help answer questions about possibility of life on Mars as well as to demonstrate technologies for future human expedition. Mars2020 is scheduled for launch in 2020. MEDLI2 is a suite of instruments embedded in the heatshield and backshell thermal protection systems of Mars2020 entry vehicle. The objectives of MEDLI2 are to gather critical aerodynamics, aerothermodynamics and TPS performance data during EDL phase of the mission. MEDLI2 builds up the success of MEDLI flight instrumentation on Mars Science Laboratory mission in 2012. MEDLI instrumentation suite measured surface pressure and TPS temperature on the heatshield during MSL entry into Mars. MEDLI data has since been used for unprecedented reconstruction of aerodynamic drag, vehicle attitude, in-situ atmospheric density, aerothermal heating, transition to turbulence, in-depth TPS performance and TPS ablation. [1,2] In addition to validating predictive models, MEDLI data has highlighted extra margin available in the MSL forebody TPS, which can potentially be used to reduce vehicle parasitic mass. MEDLI2 expands the scope of instrumentation by focusing on quantities of interest not addressed in MEDLI suite. The type the sensors are expanded and their layout on the TPS modified to meet these new objectives. The paper will provide key motivation and governing requirements that drive the choice and the implementation of the new sensor suite. The implementation considerations of sensor selection, qualification, and demonstration of minimal risk to the host mission will be described. The additional challenges associated with mechanical accommodation, electrical impact, data storage and retrieval for MEDLI2 system, which extends sensors to backshell will also be described.
The Orion Crew Module is a component of NASA’s Multi-Purpose Crew Vehicle that will be used for future missions to low Earth orbit and beyond. Ten water impact tests of the Orion Ground Test Article (GTA) were conducted at the Hydro Impact Basin at NASA Langley Research Center in 2016 and were designed to provide data for the validation of the LS-DYNA model used to determine the Crew Module structural loads during ocean splashdown, and the determination of an acceptable Model Uncertainty Factor to apply to simulation results used to drive the design. Post-test data obtained from the onboard sensors were used to reconstruct the GTA trajectories both before and after water impact. Results from one vertical test and two swing tests are presented and compared to videos taken for each test.
The EOS Terra mission will be launched in July 1999. This mission has great relevance to the atmospheric radiation community and global change issues. Terra instruments include ASTER, CERES, MISR, MODIS and MOPITT. In addition to the fundamental radiance data sets, numerous global science data products will be generated, including various Earth radiation budget, cloud and aerosol parameters, as well as land surface, terrestrial ecology, ocean color, and atmospheric chemistry parameters. Significant investments have been made in on-board calibration to ensure the quality of the radiance observations. A key component of the Terra mission is the validation of the science data products. This is essential for a mission focused on global change issues and the underlying processes. The Terra algorithms have been subject to extensive pre-launch testing with field data whenever possible. Intensive efforts will be made to validate the Terra data products after launch. These include validation of instrument calibration (vicarious calibration) experiments, instrument and cross-platform comparisons, routine collection of high quality correlative data from ground-based networks, such as AERONET, and intensive sites, such as the SGP ARM site, as well as a variety field experiments, cruises, etc. Airborne simulator instruments have been developed for the field experiment and underflight activities including the MODIS Airborne Simulator (MAS), AirMISR, MASTER (MODIS-ASTER), and MOPITT-A. All are integrated on the NASA ER-2, though low altitude platforms are more typically used for MASTER. MATR is an additional sensor used for MOPITT algorithm development and validation. The intensive validation activities planned for the first year of the Terra mission will be described with emphasis on derived geophysical parameters of most relevance to the atmospheric radiation community. Detailed information about the EOS Terra validation Program can be found on the EOS Validation program homepage i/e.: http://ospso.gsfc.nasa.gov/validation/valpage.html).
The EOS Terra mission will be launched in July 1999. This mission has great relevance to the atmospheric radiation community and global change issues. Terra instruments include Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multi-Angle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Measurements of Pollution in the Troposphere (MOPITT). In addition to the fundamental radiance data sets, numerous global science data products will be generated, including various Earth radiation budget, cloud and aerosol parameters, as well as land surface, terrestrial ecology, ocean color, and atmospheric chemistry parameters. Significant investments have been made in on-board calibration to ensure the quality of the radiance observations. A key component of the Terra mission is the validation of the science data products. This is essential for a mission focused on global change issues and the underlying processes. The Terra algorithms have been subject to extensive pre-launch testing with field data whenever possible. Intensive efforts will be made to validate the Terra data products after launch. These include validation of instrument calibration (vicarious calibration) experiments, instrument and cross-platform comparisons, routine collection of high quality correlative data from ground-based networks, such as AERONET, and intensive sites, such as the SGP ARM site, as well as a variety field experiments, cruises, etc. Airborne simulator instruments have been developed for the field experiment and underflight activities including the MODIS Airborne Simulator (MAS) AirMISR, MASTER (MODIS-ASTER), and MOPITT-A. All are integrated on the NASA ER-2 though low altitude platforms are more typically used for MASTER. MATR is an additional sensor used for MOPITT algorithm development and validation. The intensive validation activities planned for the first year of the Terra mission will be described with emphasis on derived geophysical parameters of most relevance to the atmospheric radiation community.
Technology for manned space flight is mature and has an extensive history of the use of man-in-the-loop rendezvous and docking, but there is no history of automated rendezvous and docking. Sensors exist that can operate in the space environment. The Shuttle radar can be used for ranges down to 30 meters, Japan and France are developing laser rangers, and considerable work is going on in the U.S. However, there is a need to validate a flight qualified sensor for the range of 30 meters to contact. The number of targets and illumination patterns should be minimized to reduce operation constraints with one or more sensors integrated into a robust system for autonomous operation. To achieve system redundancy, it is worthwhile to follow a parallel development of qualifying and extending the range of the 0-12 meter MSFC sensor and to simultaneously qualify the 0-30(+) meter JPL laser ranging system as an additional sensor with overlapping capabilities. Such an approach offers a redundant sensor suite for autonomous rendezvous and docking. The development should include the optimization of integrated sensory systems, packaging, mission envelopes, and computer image processing to mimic brain perception and real-time response. The benefits of the Global Positioning System in providing real-time positioning data of high accuracy must be incorporated into the design. The use of GPS-derived attitude data should be investigated further and validated.
In this study, the observations from S-NPP VIIRS Day-Night band (DNB) and Moderate resolution bands (M bands) of Libya 4 and Dome C over the first four years of the mission are used to assess the DNB low gain calibration stability. The Sensor Data Records produced by NASA Land Product Evaluation and Algorithm Testing Element (PEATE) are acquired from nearly nadir overpasses for Libya 4 desert and Dome C snow surfaces. A kernel-driven bidirectional reflectance distribution function (BRDF) correction model is used for both Libya 4 and Dome C sites to correct the surface BRDF influence. At both sites, the simulated top-of-atmosphere (TOA) DNB reflectances based on SCIAMACHY spectral data are compared with Land PEATE TOA reflectances based on modulated Relative Spectral Response (RSR). In the Libya 4 site, the results indicate a decrease of 1.03% in Land PEATE TOA reflectance and a decrease of 1.01% in SCIAMACHY derived TOA reflectance over the period from April 2012 to January 2016. In the Dome C site, the decreases are 0.29% and 0.14%, respectively. The consistency between SCIAMACHY and Land PEATE data trends is good. The small difference between SCIAMACHY and Land PEATE derived TOA reflectances could be caused by changes in the surface targets, atmosphere status, and on-orbit calibration. The reflectances and radiances of Land PEATE DNB are also compared with matching M bands and the integral M bands based on M4, M5, and M7. The fitting trends of the DNB to integral M bands ratios indicate a 0.75% decrease at the Libya 4 site and a 1.89% decrease at the Dome C site. Part of the difference is due to an insufficient number of sampled bands available within the DNB wavelength range. The above results indicate that the Land PEATE VIIRS DNB product is accurate and stable. The methods used in this study can be used on other satellite instruments to provide quantitative assessments for calibration stability.
The Space Station Structural Characterization Experiment (SSSCE) 1,2 is an early space flight experiment that uses the space station as a generic structure to study the dynamic characteristics of Large Space Structures (LSS). On-orbit modal testing will be conducted to determine natural frequencies, mode shapes and damping of dominant structural modes of the space structure assembly. This experiment will utimately support the development of system identification and analytical modeling techniques for Large Space Structures. In order to ensure the success of SSSCE (in-space validation of modeling techniques for LSS), adequate measurement and instrumentation requirements have to be established during the experiment-definition study. Among the issues affecting these requirements, spatial and modal coverages of the modal test data are of particular interest. Topics such as total number of sensors, type of measurements (translation and rotation), optimal sensor locations (measurement degrees-of-freedom), selection of target modes, effects of modal superposition and truncation, separation of global and local modes, etc., are all a fundamental importance and must be investigated.
This paper is a summary of some research activities in calibrating DC-8 SAR data conducted in 1989/90 by the author and others. Firstly, by examining the process of 'symmetrization' in the production of DC-8 Stokes' matrix data, it is shown that an exact solution to the problem of calibrating this data exists, given certain assumptions. Secondly a new, more general, system model for radar polarimeters is proposed, together with a simple approach for verifying the model's validity. The importance of the orientation angle about the radar line of sight for some types of calibration devices is discussed and some results of an experiment to cross-calibrate the C-Band VV data from the DC-8 and DLR E-SAR sensors are presented.
The overall objective of this program was to design and fabricate the components required for optical closed-loop control of a F404-400 turbofan engine, by building on the experience of the NASA Fiber Optic Control System Integration (FOCSI) program. Evaluating the performance of fiber optic technology at the component and system levels will result in helping to validate its use on aircraft engines. This report includes descriptions of three test plans. The EOI Acceptance Test is designed to demonstrate satisfactory functionality of the EOI, primarily fail-safe throughput of the F404 sensor signals in the normal mode, and validation, switching, and output of the five analog sensor signals as generated from validated optical sensor inputs, in the optical mode. The EOI System Test is designed to demonstrate acceptable F404 ECU functionality as interfaced with the EOI, making use of a production ECU test stand. The Optical Control Engine Test Request describes planned hardware installation, optical signal calibrations, data system coordination, test procedures, and data signal comparisons for an engine test demonstration of the optical closed-loop control.