Improving Efficiency & Quality of Data Acquisition in the Environmental Test Lab
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environmental test laboratory↗
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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.
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Unsteady Pressure Measurement on a Simplified High-Lift Configuration of the Common Research Model using Active Flow Control
The High-Lift Common Research Model (CRM-HL) is a product of the NASA Advanced Air Transport Technology (AATT) Project intended to study various high-lift aerodynamic phenomena including enhanced lift, acoustic noise generation, and optimum placement of leading and trailing-edge devices. The current study was conducted in the NASA Langley 14-by 22-Foot Subsonic Tunnel (14x22) for the purpose of evaluating enhanced lift through the use of active flow control (AFC). The current paper documents the effect of sweeping-jet actuation combined with steady blowing on a simplified high-lift configuration using unsteady pressure measurements. The time-series parameters for the measurements are documented as well as the data acquisition system used to acquire the data. An uncertainty analysis will be presented in order to document the system performance and provide an estimate of the data quality. Repeatability of the data will be shown along with trends associated with model angle of attack, and those associated with changes in the nozzle pressure ratio (NPR) of the AFC system.
Common Research Model↗
Unsteady Pressure Measurements on a Simplified High-Lift Configuration of the Common Research Model using Active Flow Control
The High-Lift Common Research Model (CRM-HL) is a product of the NASA Advanced Air Transport Technology (AATT) Project intended to study various high-lift aerodynamic phenomena including enhanced lift, acoustic noise generation, and optimum placement of leading and trailing-edge devices. The current study was conducted in the NASA Langley 14-by 22-Foot Subsonic Tunnel (14x22) for the purpose of evaluating enhanced lift through the use of active flow control (AFC). The current paper documents the effect of sweeping-jet actuation combined with steady blowing on a simplified high-lift configuration using unsteady pressure measurements. The time-series parameters for the measurements are documented as well as the data acquisition system used to acquire the data. An uncertainty analysis will be presented in order to document the system performance and provide an estimate of the data quality. Repeatability of the data will be shown along with trends associated with model angle of attack, and also those associated with changes in the nozzle pressure ratio (NPR) of the AFC system.
Active Flow Control↗
Communication-Aware Orbit Design for Small Spacecraft Swarms around Small Bodies
Exploration of small Solar System bodies has traditionally been performed by single monolithic spacecraft carrying a number of science instruments. However, science instruments typically cannot be operated simultaneously due to the instrument requirements including optimal viewing angle, surface illumination, altitude and ground resolution, power, and data constraints. This observation has motivated interest in multi-spacecraft architectures where a swarm of small spacecraft, each carrying a single science instrument, studies a small body after being deployed by a carrier spacecraft, which then collects data from the vehicles and relays it to Earth. Such architectures hold promise to yield significant improvements in mission efficiency, increases in data quality, and shorter mission duration. A key difficulty in the design of such missions is the selection of orbits for the small spacecraft, which must satisfy not only instrument requirements, but also strict inter-spacecraft communication and on-board storage constraints. To address this, in this paper, we present a novel computationally-efficient optimization algorithm for \emph{communication-aware design} of the orbits of a small spacecraft swarm orbiting a small body. The proposed approach captures constraints including instrument requirements, inter-spacecraft communication bandwidths, and on-board memory usage, and it can accommodate highly irregular gravity field models and surface geometries. We propose an efficient algorithm for optimization of instrument observations and inter-spacecraft communications; we then leverage the differentiable nature of the proposed algorithm to accelerate a gradient-based global search algorithm. Numerical simulations of a six-spacecraft swarm studying 433 Eros show that the proposed approach successfully identifies high-quality orbits, and significantly outperform communication-agnostic optimization techniques, resulting in a 10% increase in scientific returns and a 30% increase in the quality of the collected data.
Rahmani, Amir↗
Deriving High-quality Climate Data Records from Two Decades of Satellite Hyperspectral Remote Sensors
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Xu Liu↗
On Quality Control Procedures Being Adopted for TRMM LBA and KWAJEX Soundings Data Sets
During NASA's Tropical Rainfall Measuring Mission (TRMM) field campaigns Large Scale Biosphere Atmosphere (LBA) held in Amazonia (Brazil) in the period January- February, 1999, and the Kwajalein Experiment (KWAJEX) held in the Republic of Marshall Islands in the period between August-September, 1999, extensive radiosonde observations (raob) were collected using VIZ and Vaisala sondes which have different response characteristics. In all, 320 raob for LBA and 972 fixed raob for KWAJEX have been obtained and are being processed. Most atmospheric sensible heat source (Q1) and apparent moisture sink (Q2) budget studies are based on sounding data, and the accuracy of the raob is important especially in regions of deep moist convection. A data quality control (QC) project has been initiated at GSFC by the principal investigator (JBH), and this paper addresses some of the quantitative findings for the level I and II QC procedures. Based on these quantitative assessment of sensor (or system) biases associated with each type of sonde, the initial data repair work will be started. Evidence of moisture biases between the two different sondes (VIZ and Vaisala) has been shown earlier by Halverson et al. (2000). Vaisala humidity sensors are found to have a low-level dry bias in the boundary layer, whereas above 600 mb the VIZ sensor tends to register a dryer atmosphere. All raob data were subjected to a limit check based on an algorithm already well tested for the raob data obtained during the Tropical Ocean Global Atmosphere (TOGA-COARE).
Roy, B.↗
Linking Asthma Exacerbation and Air Pollution Data: A Step Toward Public Health and Environmental Data Integration
Studies have shown that reducing exposure to triggers such as air pollutants can reduce symptoms and the need for medication in asthma patients. However, systems that track asthma are generally not integrated with those that track environmental hazards related to asthma. Tlvs lack of integration hinders public health awareness and responsiveness to these environmental triggers. The current study is a collaboration between health and environmental professionals to utilize NASA-derived environmental data to develop a decision support system (DSS) for asthma prediction, surveillance, and intervention. The investigators link asthma morbidity data from the University of Mississippi Medical Center (UMMC) and Mississippi Department of Health (MDH) with air quality data from the Mississippi Department of Environmental Quality (MDEQ) and remote sensing data from NASA. Daily ambient environmental hazard data for PM2.5 and ozone are obtained from the MDEQ air quality monitoring locations and are combined with remotely sensed data from NASA to develop a state-wide spatial and time series profile of environmental air quality. These data are then used to study the correlation of these measures of air quality variation with the asthma exacerbation incidence throughout the state over time. The goal is to utilize these readily available measures to allow real-time risk assessment for asthma exacerbations. GeoMedStat, a DSS previously developed for biosurveillance, will integrate these measures to monitor, analyze and report the real-time risk assessment for asthma exacerbation throughout the state.
Faruque, Fazlay↗
An Analysis of the Automated Meteorological Profiling System Low Resolution Flight Element
A study was conducted to determine the quality of thermodynamic and wind data measured by or derived from the Low Resolution Flight Element (LRFE) of the Automated Meteorological Profiling System (AMPS). The AMPS LRFE replaced the Meteorological Sounding System (MSS), which was used to provide vertical profiles of thermodynamic and low-resolution wind data in support of spacecraft launch operations at the Cape Canaveral Air Force Station (CCAFS) and NASA Kennedy Space Center (KSC), Florida. Air temperature, relative humidity, and height, which are directly measured by the LRFE, are used to derive air pressure and density. Test flights were conducted where an LRFE sonde and an MSS sonde were attached to the same balloon and the two profiles were compared. MSS data was used as the standard reference data. The objective of the thermodynamic testing was to determine a) if the LRFE met Space Shuttle Program (SSP) accuracy requirements outlined in the Space Shuttle Launch and Landing Program Requirements Document (PRD) and/or, b) if the LRFE met or exceeded MSS data quality. AMPS uses the Global Positioning System (GPS) to determine wind speed and direction. In order to provide a basis for comparison, either an AMPS High Resolution Flight Element (HRFE) or a radar tracked Jimsphere was released simultaneously with each AMPS LRFE at CCAFS. The goal of these tests was to determine if the LRFE wind data met the requirement for low-resolution wind data defined in the Shuttle PRD. Based on the available data, the LRFE is shown to produce more consistent thermodynamic measurements than the MSS. The LRFE is also shown to meet the Shuttle PRD requirements for low resolution wind data.
Leahy, Frank B.↗
Regional scale hydrology with a new land surface processes model
Through the CaPE Hydrometeorology Project, we have developed an understanding of some of the unique data quality issues involved in assimilating data of disparate types for regional-scale hydrologic modeling within a GIS framework. Among others, the issues addressed here include the development of adequate validation of the surface water budget, implementation of the STATSGO soil data set, and implementation of a remote sensing-derived landcover data set to account for surface heterogeneity. A model of land surface processes has been developed and used in studies of the sensitivity of surface fluxes and runoff to soil and landcover characterization. Results of these experiments have raised many questions about how to treat the scale-dependence of land surface-atmosphere interactions on spatial and temporal variability. In light of these questions, additional modifications are being considered for the Marshall Land Surface Processes Model. It is anticipated that these techniques can be tested and applied in conjunction with GCIP activities over regional scales.
Laymon, Charles↗
Comparison of Daily Total Precipitable Water From Satellite and Model Reanalysis Fields
Previous studies have shown that there is fairly good agreement between the monthly values of total precipitable water (TPW) from the NVAP data set, a multi satellite and radiosonde merged data product, and the NCEP reanalysis TPW data. However, there are regions and time periods where significant differences between the data sets are found in the monthly mean TPW time series and period of record trends. To better understand these differences seen in the monthly data values, the daily mean TPW data are examined. Possible contributions to the TPW differences such as data quality of the individual NVAP data set components associated with missing or irregular daily values are addressed. Also, effects associated with the weighting of the individual NVAP data set components to form a merged product are considered. The daily variations in TPW exhibited by each data set are also quantified and compared between the data sets.
Jedlovec, Gary J.↗
Analysis of RXTE data on Clusters of Galaxies
This grant provided support for the reduction, analysis and interpretation of of hard X-ray (HXR, for short) observations of the cluster of galaxies RXJO658--5557 scheduled for the week of August 23, 2002 under the RXTE Cycle 7 program (PI Vahe Petrosian, Obs. ID 70165). The goal of the observation was to search for and characterize the shape of the HXR component beyond the well established thermal soft X-ray (SXR) component. Such hard components have been detected in several nearby clusters. distant cluster would provide information on the characteristics of this radiation at a different epoch in the evolution of the imiverse and shed light on its origin. We (Petrosian, 2001) have argued that thermal bremsstrahlung, as proposed earlier, cannot be the mechanism for the production of the HXRs and that the most likely mechanism is Compton upscattering of the cosmic microwave radiation by relativistic electrons which are known to be present in the clusters and be responsible for the observed radio emission. Based on this picture we estimated that this cluster, in spite of its relatively large distance, will have HXR signal comparable to the other nearby ones. The planned observation of a relatively The proposed RXTE observations were carried out and the data have been analyzed. We detect a hard X-ray tail in the spectrum of this cluster with a flux very nearly equal to our predicted value. This has strengthen the case for the Compton scattering model. We intend the data obtained via this observation to be a part of a larger data set. We have identified other clusters of galaxies (in archival RXTE and other instrument data sets) with sufficiently high quality data where we can search for and measure (or at least put meaningful limits) on the strength of the hard component. With these studies we expect to clarify the mechanism for acceleration of particles in the intercluster medium and provide guidance for future observations of this intriguing phenomenon by instrument on GLAST. The details of the nonthermal particle population has important implications for the theories of cluster formation, mergers and evolution. The results of this work were first presented at the High Energy Division meeting of the American astronomical Society at Mt. Tremblene, Canada (Petrosian et al. 2003). and in an invited review talk at the General Assembly of the International Astronomical Union at Sydney, Australia (Petrosian, 2003). A paper describe the observations, the data analysis and its implication is being prepared for publication in the Astrophysical Journal.
Petrosian, Vahe↗
A Testbed Demonstration of an Intelligent Archive in a Knowledge Building System
The last decade's influx of raw data and derived geophysical parameters from several Earth observing satellites to NASA data centers has created a data-rich environment for Earth science research and applications. While advances in hardware and information management have made it possible to archive petabytes of data and distribute terabytes of data daily to a broad community of users, further progress is necessary in the transformation of data into information, and information into knowledge that can be used in particular applications in order to realize the full potential of these valuable datasets. In examining what is needed to enable this progress in the data provider environment that exists today and is expected to evolve in the next several years, we arrived at the concept of an Intelligent Archive in context of a Knowledge Building System (IA/KBS). Our prior work and associated papers investigated usage scenarios, required capabilities, system architecture, data volume issues, and supporting technologies. We identified six key capabilities of an IA/KBS: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting. Among these capabilities, large-scale data mining is perceived by many in the community to be an area of technical risk. One of the main reasons for this is that standard data mining research and algorithms operate on datasets that are several orders of magnitude smaller than the actual sizes of datasets maintained by realistic earth science data archives. Therefore, we defined a test-bed activity to implement a large-scale data mining algorithm in a pseudo-operational scale environment and to examine any issues involved. The application chosen for applying the data mining algorithm is wildfire prediction over the continental U.S. This paper reports a number of observations based on our experience with this test-bed. While proof-of-concept for data mining scalability and utility has been a major goal for the research reported here, it was not the only one. The other five capabilities of an WKBS named above have been considered as well, and an assessment of the implications of our experience for these other areas will also be presented. The lessons learned through the testbed effort and presented in this paper will benefit technologists, scientists, and system operators as they consider introducing IA/KBS capabilities into production systems.
Ramapriyan, Hampapuram↗
Visual Data Analysis for Satellites
The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.
Lau, Yee↗
An Intelligent Archive Testbed Incorporating Data Mining
Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).
Ramapriyan, H.↗
Characterization of Landsat-4 MSS and TM digital image data
The launch of Landsat-4 in July 1982 represents a continuation in the remote sensing of earth resources. The 80-m spatial resolution provided by the Multispectral Scanner (MSS) on board the satellite is fine enough to resolve many natural features and land-use details in both rural and urban settings. The second sensor of the spacecraft, the Thematic Mapper (TM), introduces a new era of sensing with refined spatial resolution (30 m) and expanded spectral coverage (7 bands). This paper describes results from engineering studies of the characteristics of digital image data from the two Landsat-4 sensors. These studies form a part of the Landsat-4 Image Data Quality Analysis program (LIDQA). The image data were generally found to be of high quality and the TM provided several improvements over the MSS, in its spatial and spectral characteristics.
Malila, W. A.↗
Characterization of LANDSAT-4 MSS and TM digital image data
The launch of LANDSAT-4 in July 1982 represents a continuation in the remote sensing of earth resources. The 80-m spatial resolution provided by the Multispectral Scanner (MSS) on board the satellite is fine enough to resolve many natural features and land-use details in both rural and urban settings. The second sensor of the spacecraft, the Thematic Mapper (TM), introduce a new era of sensing with refined spatial resolution (30 m) and expanded spectral coverage (7 bands). This paper describes results from engineering studies of the characteristics of digital image data from the two LANDSAT-4 sensors are described. These studies form a part of the LANDSAT-4 Image Data Quality Analysis program (LIDQA). The image data were generally found to be of high quality and the TM provided several improvements over the MSS, in its spatial and spectral characteristics.
Malila, W. A.↗
CERES Fast Longwave And SHortwave Radiative Flux (FLASHFlux): Research to Operation
The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed as to provide key data for applied science research involving the renewable energy and agricultural sectors within a week of observations. FLASHFlux achieves this by using simplified calibration, an operation meteorology product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1ox 1ogridded data that combines Aqua and Terra observations. We inter-compared of FLASHFlux Version4A calibration to the climate quality CERES Edition4A data product over time. In addition, we also inter-compared the impact of the fluxes by using the near real-time GMAO GEOS FP-IT instead of GMAO G5-CERES meteorology data. We also compare both SSF overpass and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement.
P. C. Sawaengphokhai↗
Data Democratization: Challenges and Opportunities
Democratizing Earth data is one of the challenges many organizations around the world face in order to maximize the use of their Earth data for research, applications, education, and societal benefits. For example, at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), over 1600 global and regional datasets in several NASA Earth science focus areas, including atmospheric composition, water and energy cycles, and climate variability, are archived and distributed to the public. Giovanni, the Geospatial Interactive Online Visualization and Analysis Infrastructure, was developed by GES DISC to facilitate data access and exploration, especially for novice users of Earth science. With Giovanni, users can analyze and visualize over 2000 Earth science variables (e.g., precipitation, aerosol, surface wind) without downloading data, software, the expert understanding of data formats and structures, and coding skills, lowering the barrier to data analysis/comparison by preprocessing and accessing to the data. Results of data analysis and visualization can be accessed in several popular formats (e.g., NetCDF, CSV). As a result of Giovanni's efforts, more than 3000 referral papers have been published in various fields. In spite of this, Giovanni is still difficult to use for some users. For instance, if one searches for "precipitation," it will return over 150 related variables. The question is, which one to use? Furthermore, variables from different data providers (e.g., satellites and models) are named differently with different units, further confusing users, especially those outside the communities. Data democratization is complex and multifaceted. Challenges include service and data discovery, user experiences, visualization, data quality, trustworthiness, and more. In this presentation, we will examine Giovanni as an example of challenges and opportunities in developing data democratization services.
data democratization↗