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At least 19 records

Characterization of Unimorph-Membrane Microactuators and Error-Analysis of the Characterization Process

Microactuators are versatile, low-cost, low-mass electrical-mechanical devices that can be used in many applications. Microactuators consist of two electrodes sandwiching a PZT (piezo-electric) film between them. The centers of the microactuators deflect when a voltage is applied across the electrodes. In order to correctly apply this technology for use, it is important to fully characterize the actuation behavior. Measuring the deflection profile as a function of the voltage of various microactuators is crucial. This measurement process has errors associated with it, so it is being studied to determine the accuracy of the data. In certain applications, microactuators may undergo many cycles of deflection; testing various microactuators through many cycles of deflection simulates these circumstances. However, due to an unknown issue, many of the microactuators exhibit defects that cause them to fail when voltage is applied to their electrodes. These defects do not allow for the acquisition of significant deflection profiles. Vibrations are the largest cause of error in deflection measurements, and the microactuators withstand continuous cycles of deflection, yet the cause of damage is still to be determined. Future projects will be needed to characterize the deflection profiles of various microactuators and to overcome the defects in the microactuators that are currently present.

Wright, Matthew W.

Characterization of Volume F Trash from the Three FY11 STS Missions: Trash Weights and Categorization and Microbial Characterization

The project reported here provides microbial characterization support to the Waste Management Systems (WMS) element of NASA's Life Support and Habitation Systems (LSHS) program. Conventional microbiological methods were used to detect and enumerate microorganisms in STS Volume F Compartment trash for three shuttle missions: STS 133, 134, and 135. This trash was usually made available within 2 days of landing at KSC. The Volume F bag was weighed, opened and the contents were cataloged and placed into categories: personal hygiene items - inclUding EVA maximum absorbent garments (MAGs) and Elbow packs (daily toilet wipes, etc), drink containers, food waste (and containers), office waste (paper), and packaging materials - plastic film and duct tape. The average wet trash generation rate for the three STS missions was 0.362 % 0.157 kgwet crew 1 d-1 . This was considerably lower and more variable than the average rate for 4 STS missions reported for FY10. Trash subtotals by category: personal hygiene wastes, 56%; drink items, 11 %; food wastes, 18%; office waste, 3%; and plastic film, 12%. These wastes have an abundance of easily biodegraded compounds that can support the growth of microorganisms. Microbial characterization of trash showed that large numbers of bacteria and fungi have taken advantage of this readily available nutrient source to proliferate. Exterior and interior surfaces of plastic film bags containing trash were sampled and counts of cultivatable microbes were generally low and mostly occurred on trash bundles within the exterior trash bags. Personal hygiene wastes, drink containers, and food wastes and packaging all contained high levels of, mostly, aerobic heterotrophic bacteria and lower levels of yeasts and molds. Isolates from plate count media were obtained and identified .and were mostly aerobic heterotrophs with some facultative anaerobes. These are usually considered common environmental isolates on Earth. However, several pathogens were also isolated: Staphylococcus aureus and Escherichia coli.

Strayer, Richard F.

Characterizing Young Giant Planets with the Gemini Planet Imager: An Iterative Approach to Planet Characterization

After discovery, the first task of exoplanet science is characterization. However experience has shown that the limited spectral range and resolution of most directly imaged exoplanet data requires an iterative approach to spectral modeling. Simple, brown dwarf-like models, must first be tested to ascertain if they are both adequate to reproduce the available data and consistent with additional constraints, including the age of the system and available limits on the planet's mass and luminosity, if any. When agreement is lacking, progressively more complex solutions must be considered, including non-solar composition, partial cloudiness, and disequilibrium chemistry. Such additional complexity must be balanced against an understanding of the limitations of the atmospheric models themselves. For example while great strides have been made in improving the opacities of important molecules, particularly NH3 and CH4, at high temperatures, much more work is needed to understand the opacity of atomic Na and K. The highly pressure broadened fundamental band of Na and K in the optical stretches into the near-infrared, strongly influencing the spectral shape of Y and J spectral bands. Discerning gravity and atmospheric composition is difficult, if not impossible, without both good atomic opacities as well as an excellent understanding of the relevant atmospheric chemistry. I will present examples of the iterative process of directly imaged exoplanet characterization as applied to both known and potentially newly discovered exoplanets with a focus on constraints provided by GPI spectra. If a new GPI planet is lacking, as a case study I will discuss HR 8799 c and d will explain why some solutions, such as spatially inhomogeneous cloudiness, introduce their own additional layers of complexity. If spectra of new planets from GPI are available I will explain the modeling process in the context of understanding these new worlds.

exoplanets

Raman Spectroscopic Characterization of the Feldspars: Implications for Surface Mineral Characterization in Planetary Exploration

The availability in the last decade of improved Raman instrumentation using small, stable, intense lasers, sensitive CCD array detectors, and advanced fast grating systems enabled us to develop the Mars Microbeam Raman Spectrometer (MMRS), a field-portable Raman spectrometer with precision and accuracy capable of identifying minerals and their different compositions. For example, we can determine Mg cation ratios in pyroxenes and olivines to +/-0.1 on the basis of Raman peak positions. Feldspar is another major mineral formed in igneous systems whose characterization is important for determining rock petrogenesis and alteration. From their Raman spectral pattern, feldspars can be readily distinguished from ortho- and chain-silicates and from other tecto-silicates such as quartz and zeolites. We show here how well Raman spectral analysis can distinguish among members within the feldspar group.

Freeman, J. J.

The Joint Agency Commercial Imagery Evaluation Team and Product Characterization Approach

The Joint Agency Commercial Imagery Evaluation (JACIE) team is a collaborative interagency group focused on the characterization of commercial remote sensing data products. The team members - the National Aeronautics and Space Administration (NASA), the National Imagery and Mapping Agency (NIMA), and the U.S. Geological Survey (USGS) - each have a vested interest in the purchase and use of commercial imagery to support government research and operational applications. For both research and applications, commercial products must be well characterized for precision, accuracy, and repeatability. Since commercial systems are built and operated with no government insight or oversight, the JACIE team provides an independent product characterization of delivered image and image-derived end products. End product characterization differs from the systems calibration approach that is typically used with government systems, where detailed system design information is available. The product characterization approach addresses three primary areas of product performance: geopositional accuracy, image quality, and radiometric accuracy. The JACIE team utilizes well-characterized test sites to support characterization activities. To characterize geopositional accuracy, the team utilizes sites containing several "photo-identifiable" targets and compares their precisely known locations with those defined by the commercial image product. In the area of image quality, spatial response is characterized using edge targets and pulse targets to measure edge response and to estimate image modulation transfer function. Additionally, imagery is also characterized using the National Imagery Interpretability Rating Scale, a means of quantifying the ability to identify certain targets (e.g., rail-cars, airplanes) within an image product. Radiometric accuracy is characterized using reflectance-based vicarious calibration methods at several uniform sites. Each JACIE agency performs an aspect of product characterization based on its area of expertise, thus minimizing duplication of effort. The JACIE team collaborated to perform comprehensive characterization of products from Space Imaging Inc.'s IKONOS satellite and from DigitalGlobe's QuickBird satellite and is currently characterizing products from OrbImage s OrbView-3. JACIE assessments have resulted in several improvements to commercial image product quality and have enhanced working relationships between government and industry. Assessment results are presented at an annual JACIE High Spatial Resolution Commercial Imagery Workshop.

Zanoni, Vicki

Software Suite to Support In-Flight Characterization of Remote Sensing Systems

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

Stanley, Thomas

Measurement Sets and Sites Commonly Used for Characterization

Scientists at NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center. This site enables the in-flight characterization of remote sensing systems and the data they acquire. The data are predominantly acquired by commercial, high spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the techniques used to characterize data from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active LIDAR systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible through long-wave infrared remote sensing systems and a description of the Stennis characterization. Other topics discussed include: 1) The use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations; 2) Additional sites used for radiometric, geometric, and spatial characterization in the continental United States; 3) The need for a standardized technique to be adopted by CEOS and other organizations.

Pagnutti, Mary

Measurement Sets and Sites Commonly used for Characterizations

Scientists with NASA's Earth Science Applications Directorate are creating a well-characterized Verification & Validation (V&V) site at the Stennis Space Center (SSC). This site enables the in-flight characterization of remote sensing systems and the data that they require. The data are predominantly acquired by commercial, high-spatial resolution satellite systems, such as IKONOS and QuickBird 2, and airborne systems. The smaller scale of these newer high-resolution remote sensing systems allows scientists to characterize the geometric, spatial, and radiometric data properties using a single V&V site. The targets and techniques used to characterize data from these newer systems can differ significantly from the earlier, coarser spatial resolution systems. Scientists are also using the SSC V&V site to characterize thermal infrared systems and active Light Detection and Ranging (LIDAR) systems. SSC employs geodetic targets, edge targets, radiometric tarps, and thermal calibration ponds to characterize remote sensing data products. This paper presents a proposed set of required measurements for visible-through-longwave infrared remote sensing systems, and a description of the Stennis characterization. Other topics discussed inslude: 1) use of ancillary atmospheric and solar measurements taken at SSC that support various characterizations, 2) other sites used for radiometric, geometric, and spatial characterization in the continental United States,a nd 3) the need for a standardized technique to be adopted by the Committee on Earth Observation Satellites (CEOS) and other organizations.

Pagnutti, Mary

Prelaunch Spectral Characterization of the Operational Land Imager-2

The Landsat-9 satellite, launched in September 2021, carries the Operational Land Imager-2 (OLI-2) as one of its payloads. This instrument is a clone of the Landsat-8 OLI and its mission is to continue the operational land imaging of the Landsat program. The OLI-2 instrument is not significantly different from OLI though the instrument-level pre-launch spectral characterization process was much improved. The focal plane modules used on OLI-2 were manufactured as spares for OLI and much of the spectral characterization of the components was performed for OLI. However, while the spectral response of the fully assembled OLI was characterized by a double monochromator system, the OLI-2 spectral characterization made use of the Goddard Laser for Absolute Measurement of Radiance (GLAMR). GLAMR is a system of tunable lasers that cover 350–2500 nm which are fiber-coupled to a 30 in integrating sphere permanently monitored by NIST-traceable radiometers. GLAMR allowed the spectral characterization of every detector of the OLI-2 focal plane in nominal imaging conditions. The spectral performance of the OLI-2 was, in general, much better than requirements. The final relative spectral responses (RSRs) represent the best characterization any Landsat instrument spectral response. This paper will cover the results of the spectral characterization from the component-level to the instrument-level of the Landsat-9 OLI-2.

Landsat-9

Use of CFD in the Design of the 10- by 10-Foot Supersonic Wind Tunnel Characterization Array

At the 10- by 10-Foot Supersonic Wind Tunnel at the NASA Glenn Research Center, a future full test section characterization generated an ideal opportunity to design and build new characterization hardware to improve the understanding of the flow field, including flow quality, uniformity, and uncertainty in primary variables of interest. An array of flow sensing probes, referred to as the Characterization Array, was designed and built to replace 1960’s-era test section characterization hardware. Many references exist to guide wind tunnel characterization practitioners in the design of new hardware to properly measure various aspects of the flow within their wind tunnel facilities. Although reliable sources of information, these references tend to be over 30 years old and are not exhaustive. In scenarios where design decisions needed to be validated, computational simulations of the flow field around the characterization hardware were used. Decisions regarding probe location, probe spacing, and performance of various probes were justified using computational fluid dynamic simulations and rules-of-thumb from the legacy resources available in literature. This paper is intended to serve as an example of the benefits from integrating CFD into the design of wind tunnel hardware, particularly hardware for wind tunnel characterization.

CFD

Use of CFD in the Design of the 10- by 10-Foot Supersonic Wind Tunnel Characterization Array

At the 10- by 10-Foot Supersonic Wind Tunnel at the NASA Glenn Research Center, a future full test section characterization generated an ideal opportunity to design and build new characterization hardware to improve the understanding of the flow field, including flow quality, uniformity, and uncertainty in primary variables of interest. An array of flow sensing probes, referred to as the Characterization Array, was designed and built to replace 1960’s-era test section characterization hardware. Many references exist to guide wind tunnel characterization practitioners in the design of new hardware to properly measure various aspects of the flow within their wind tunnel facilities. Although reliable sources of information, these references tend to be over 30 years old and are not exhaustive. In scenarios where design decisions needed to be validated, computational simulations of the flow field around the characterization hardware were used. Decisions regarding probe location, probe spacing, and performance of various probes were justified using computational fluid dynamic simulations and rules-of-thumb from the legacy resources available in literature. This paper is intended to serve as an example of the benefits from integrating CFD into the design of wind tunnel hardware, particularly hardware for wind tunnel characterization.

CFD

Summary of Terra and Aqua MODIS On-orbit Calibration and Characterization Results

The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard NASA's EOS Terra spacecraft has been in operation for more than seven years since its launch in December 1999 and the MODIS onboard Aqua spacecraft has been in operation for more than 4.5 years since its launch in May 2002. Compared to its heritage sensors, such as AVHRR, CZCS, SeaWiFS, HIRS, and Landsat TM, the MODIS instrument was developed with improved spectral and spatial resolutions, and temporal scale or global coverage frequency. The two MODIS instruments are nearly identical with each collecting data in 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.2jm and 16 thermal emissive bands (TEB) from 3.7 to 4.4 microns. MODIS makes the Earth view observations with a scan angle range of +/-55 degree relative to instrument nadir and at three nadir spatial resolutions: 0.25km for bands 1-2.05km for bands 3-7, and 1km for bands 8-36, thus enabling complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS observations have been routinely used to generate a broad range of science data products that are widely distributed and extensively applied for the studies of the Earth's land, oceans, and atmosphere and for the monitoring of climate and environmental changes. It is obvious that the MODIS science data product quality strongly relies on sensor on-orbit performance and its capability of continuously tracking sensor response changes over time. Because of this, each MODIS was built with a comprehensive set of on-board calibrators (OBC) that include a solar diffuser (SD) for the RSB calibration, a blackbody (BB) for the TEB calibration, and a spectro-radiometric calibration assembly (SRCA) for the spatial (RSB and TEB) and spectral (RSB only) characterization. Most importantly, extensive and dedicated sensor calibration and characterization efforts have been constantly made by the MODIS Characterization Support Team (MCST) at NASA/GSFC. In this presentation, we will provide an overview of MODIS sensor operations since 1aunh and the onorbit calibration and characterization methodologies with emphasis on the differences between Terra and Aqua MODIS characteristics. We will summarize both Terra and Aqua MODIS onorbit calibration and characterization results, including their RSB and TEB detector noise characterization, the sensor response changes, and the corrections to the optics degradation. In addition to radiometric calibration performance, we will illustrate both sensors' spectral and spatial characterization results in terms of their band-to-band registrations and spectral band center wavelength shifts.

Xiong, X.

Machine characterization and benchmark performance prediction

From runs of standard benchmarks or benchmark suites, it is not possible to characterize the machine nor to predict the run time of other benchmarks which have not been run. A new approach to benchmarking and machine characterization is reported. The creation and use of a machine analyzer is described, which measures the performance of a given machine on FORTRAN source language constructs. The machine analyzer yields a set of parameters which characterize the machine and spotlight its strong and weak points. Also described is a program analyzer, which analyzes FORTRAN programs and determines the frequency of execution of each of the same set of source language operations. It is then shown that by combining a machine characterization and a program characterization, we are able to predict with good accuracy the run time of a given benchmark on a given machine. Characterizations are provided for the Cray-X-MP/48, Cyber 205, IBM 3090/200, Amdahl 5840, Convex C-1, VAX 8600, VAX 11/785, VAX 11/780, SUN 3/50, and IBM RT-PC/125, and for the following benchmark programs or suites: Los Alamos (BMK8A1), Baskett, Linpack, Livermore Loops, Madelbrot Set, NAS Kernels, Shell Sort, Smith, Whetstone and Sieve of Erathostenes.

Saavedra-Barrera, Rafael H.

Automated clustering-based workload characterization

The demands placed on the mass storage systems at various federal agencies and national laboratories are continuously increasing in intensity. This forces system managers to constantly monitor the system, evaluate the demand placed on it, and tune it appropriately using either heuristics based on experience or analytic models. Performance models require an accurate workload characterization. This can be a laborious and time consuming process. It became evident from our experience that a tool is necessary to automate the workload characterization process. This paper presents the design and discusses the implementation of a tool for workload characterization of mass storage systems. The main features of the tool discussed here are: (1)Automatic support for peak-period determination. Histograms of system activity are generated and presented to the user for peak-period determination; (2) Automatic clustering analysis. The data collected from the mass storage system logs is clustered using clustering algorithms and tightness measures to limit the number of generated clusters; (3) Reporting of varied file statistics. The tool computes several statistics on file sizes such as average, standard deviation, minimum, maximum, frequency, as well as average transfer time. These statistics are given on a per cluster basis; (4) Portability. The tool can easily be used to characterize the workload in mass storage systems of different vendors. The user needs to specify through a simple log description language how the a specific log should be interpreted. The rest of this paper is organized as follows. Section two presents basic concepts in workload characterization as they apply to mass storage systems. Section three describes clustering algorithms and tightness measures. The following section presents the architecture of the tool. Section five presents some results of workload characterization using the tool.Finally, section six presents some concluding remarks.

Pentakalos, Odysseas I.

National Transonic Facility Characterization Status

This paper describes the current status of the characterization of the National Transonic Facility. The background and strategy for the tunnel characterization, as well as the current status of the four main areas of the characterization (tunnel calibration, flow quality characterization, data quality assurance, and support of the implementation of wall interference corrections) are presented. The target accuracy requirements for tunnel characterization measurements are given, followed by a comparison of the measured tunnel flow quality to these requirements based on current available information. The paper concludes with a summary of which requirements are being met, what areas need improvement, and what additional information is required in follow-on characterization studies.

Bobbitt, C., Jr.

Characterizing Digital Camera Systems: A Prelude to Data Standards

This viewgraph presentation profiles: 1) Digital imaging systems; 2) Specifying a digital imagery product; and 3) Characterization of data acquisition systems. Advanced large array digital imaging systems are routinely being used. Digital imagery guidelines are being developed by ASPRS and ISPRS. Guidelines and standards are of little use without standardized characterization methods. Characterization of digital camera systems is important for supporting digital imagery guidelines. Specifications are characterized in the lab and/or the field. Laboratory characterization is critical for optimizing and defining performance. In-flight characterization is necessary for an end-to-end system test.

Ryan, Robert

Results of MODIS Band-to-Band Registration Characterization Using On-Orbit Lunar Observations

Since launch, lunar observations have been made regularly by both Terra and Aqua MODIS and used for a number of sensor calibration and characterization related applications, including radiometric stability monitoring, spatial characterization, optical leak and electronic cross-talk characterization, and calibration inter-comparison. MODIS has 36 spectral bands with a total of 490 individual detectors. They are located on four focal plane assemblies (FPA). This paper focuses on the use of MODIS lunar observations to characterize its band-to-band registration (BBR). In addition to BBR, the approach developed by the MODIS Characterization Support Team (MCST) can be used to characterize MODIS detector-to-detector registration (DDR). Long-term BBR results developed from this approach are presented and compared with that derived from a unique on-board calibrator (OBC). Results show that on-orbit changes of BBR have been very small for both Terra and Aqua MODIS and this approach can be applied to other remote sensing instruments.

Xiong, Xiaoxiong

Preliminary Characterization Results from the DebriSat Project

The DebriSat project is a continuing effort sponsored by NASA and DoD to update existing break-up models using data obtained from two separate hypervelocity impact tests used to simulate on-orbit collisions. To protect the fragments resulting from the impact tests, "soft-catch" arenas made of polyurethane foam panels were utilized. After each impact test, the test chamber was cleaned and debris resulting from the catastrophic demise of the test article were collected and shipped to the University of Florida for post-impact processing. The post-impact processing activities include collecting, characterizing, and cataloging of the fragments. Since the impact tests, a team of students has been working to characterize the fragments in terms of their mass, size, shape, color and material content. The focus of the 20 months since the impact tests has been on the collection of 2 millimeters- and larger fragments resulting from impact test on the 56 kilogram-representative LEO (Low Earth Orbit) satellite referred to as DebriSat. To date we have recovered in excess of 115,000 fragments, 30,000 more than the prediction of 85,000 fragments from the existing model. We continue to collect fragments but have transitioned to the characterization phase of the post-impact activities. Since the start of the characterization phase, the focus has been to utilize automation to (i) expedite fragment characterization process and (ii) minimize human-in-the- loop. We have developed and implemented such automated processes; e.g., we have automated the data entry process to reduce operator errors during transcription of the measurement data. However, at all steps of the process, there is human oversight to ensure the integrity of the data. Additionally, we have developed and implemented repeatability and reproducibility tests to ensure that the instrumentation used in the characterization process is accurate and properly calibrated. In this paper, the implemented processes are described and preliminary results presented. Additionally, lessons learned from the implemented automations and their impacts on the integrity of the results are discussed.

Rivero, M.