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At least 19 records

Solar concentrator technology development for space based applications, volume 1

Thermoelectric conversion using a radio-isotope heat source has been used where outer planetary space craft are too far away for absorbing significant solar energy. Solar dynamic power (SDP) conversion is one technology that offers advantages for applications within the inner planet region. Since SDP conversion efficiency can be 2 to 3 times higher than photovoltaic, the collecting surfaces are much reduced in area and therefore lighter. This becomes an advantage in allocating more weight to launched payloads. A second advantage results for low earth orbit applications. The reduced area results in lower drag forces on the spacecraft and requires less reboost propellant to maintain orbit. A third advantage occurs because of the sun-to-shade cycling while in earth orbit. Photovoltaic systems require batteries to store energy for use when in the shade, and battery life for periods of 10 to 15 years is not presently achievable. For these reasons the Solar Dynamics and Thermal Systems Branch at NASA LeRC has funded work in developing SDP systems. The generic SDP system uses a large parabolic solar concentrator to focus solar energy onto a power conversion device. The concentrators are large areas and must therefore be efficient and have low specific weights. Yet these surfaces must be precise and capable of being stowed in a launch vehicle and then deployed and sometimes unfurled in space. There are significant technical challenges in engineering such structures, and considerable investigation has been made to date. This is the first of two volumes reporting on the research done by the Advanced Manufacturing Center at Cleveland State University to assist NASA LeRC in evaluating this technology. The objective of the grant was to restore the solar concentrator development technology of the 1960s while improving it with advances that have occurred since then. This report summarizes the work done from January 1989 through December 1991.

Pintz, A.↗

Solar concentrator technology development for space based applications, volume 2

Thermoelectric conversion using a radio-isotope heat source has been used where outer planetary space craft are too far away for absorbing significant solar energy. Solar dynamic power (SDP) conversion is one technology that offers advantages for applications within the inner planet region. Since SDP conversion efficiency can be 2 to 3 times higher than photovoltaic, the collecting surfaces are much reduced in area and therefore lighter. This becomes an advantage in allocating more weight to launched payloads. A second advantage results for low earth orbit applications. The reduced area results in lower drag forces on the spacecraft and requires less reboost propellant to maintain orbit. A third advantage occurs because of the sun-to-shade cycling while in earth orbit. Photovoltaic systems require batteries to store energy for use when in the shade, and battery life for periods of 10 to 15 years is not presently achievable. For these reasons the Solar Dynamics and Thermal Systems Branch at NASA LeRC has funded work in developing SDP systems. The generic SDP system uses a large parabolic solar concentrator to focus solar energy onto a power conversion device. The concentrators are large areas and must therefore be efficient and have low specific weights. Yet these surfaces must be precise and capable of being stowed in a launch vehicle and then deployed and sometimes unfurled in space. There are significant technical challenges in engineering such structures, and considerable investigation has been made to date. This is the second of two volumes reporting on the research done by the Advanced Manufacturing Center at Cleveland State University to assist NASA LeRC in evaluating this technology. This volume includes the appendices of selected data sets, drawings, and procedures. The objective of the grant was to restore the solar concentrator development technology of the 1960s while improving it with advances that have occurred since then. This report summarizes the work done from January 1989 through December 1991.

Pintz, A.↗

The Landsat Data Purchase and ESAD

The Earth Science Applications Directorate (ESAD) purchases satellite imagery for The Scientific Data Purchase (SDP) Project. SDP allows a variety of customers in turn to purchase Landsat, IKONOS, and other data. The SDP customer base includes includes private companies, universities, and government agencies. SDP customers are required to register and receive clearance.

Policelli, Fritz↗

Scientific Data Purchase Project Overview Presentation

The Scientific Data Purchase (SDP) project acquires science data from commercial sources. It is a demonstration project to test a new way of doing business, tap new sources of data, support Earth science research, and support the commercial remote sensing industry. Phase I of the project reviews simulated/prototypical data sets from 10 companies. Phase II of the project is a 3 year purchase/distribution of select data from 5 companies. The status of several SDP projects is reviewed in this viewgraph presentation, as is the SDP process of tasking, verification, validation, and data archiving. The presentation also lists SDP results for turnaround time, metrics, customers, data use, science research, applications research, and user feedback.

Holekamp, Kara↗

NASA Scientific Data Purchase Project: From Collection to User

NASA's Scientific Data Purchase (SDP) project is currently a $70 million operation managed by the Earth Science Applications Directorate at Stennis Space Center. The SDP project was developed in 1997 to purchase scientific data from commercial sources for distribution to NASA Earth science researchers. Our current data holdings include 8TB of remote sensing imagery consisting of 18 products from 4 companies. Our anticipated data volume is 60 TB by 2004, and we will be receiving new data products from several additional companies. Our current system capacity is 24 TB, expandable to 89 TB. Operations include tasking of new data collections, archive ordering, shipment verification, data validation, distribution, metrics, finances, customer feedback, and technical support. The program has been included in the Stennis Space Center Commercial Remote Sensing ISO 9001 registration since its inception. Our operational system includes automatic quality control checks on data received (with MatLab analysis); internally developed, custom Web-based interfaces that tie into commercial-off-the-shelf software; and an integrated relational database that links and tracks all data through operations. We've distributed nearly 1500 datasets, and almost 18,000 data files have been downloaded from our public web site; on a 10-point scale, our customer satisfaction index is 8.32 at a 23% response level. More information about the SDP is available on our Web site.

Nicholson, Lamar↗

The NASA Scientific Data Purchase: Summary and Evaluation

This report summarizes the results of the NASA Scientific Data Purchase (SDP) program implemented by the Stennis Space Center Earth Science Application Directorate in fiscal years 1998-2002. The SDP was conducted in support of NASA's Mission to Planet Earth (MTPE) program (currently known as NASA's Earth Science Enterprise). This Earth Science Enterprise (ESE) provides major observational capabilities for NASA's Earth system science research and the U.S. Global Change Research Program. Observations supported through the SDP were selected based upon their application to the five science themes of the MTPE/ESE: 1) Land cover and land use change research; 2) Seasonal to interannual climate variability and prediction; 3) Natural hazards research and applications; 4) Long-term climate: Natural variability and change research; 5) Atmospheric ozone research. The MTPE/ESE science themes, although they have evolved over time, are driven by a set of key science questions that help focus the research program on characterizing the Earth system.

Source record↗

NASA Scientific Data Purchase Laboratory Characterization of Positive Systems ADAR 5500 Sensor

This report summarizes the laboratory characterization of the Positive Systems ADAR 5500 SN4 multi-spectral imager measured dirijg the period of April 10-11, 2000 in the NASA CRSP Commercial Instrumentation Validation Laboratory (CIVL). This characterization is one component of the NASA Scientific Data Purchase (SDP) validation and verification process. A complete characterization will require analysis of airborne data. The spectral, radiometric, and spatial characteristics of this system were measured and compared with the product data specifications as defined in the SDP contract. These results are summarized in the specification compliance matrices in this summary. A complete description of the system, the SDP product specification and the sensor laboratory characterization is provided in the body of the main report.

Ryan, James↗

Anomaly Detection for the Roman Space Telescope Wide Field Instrument’s Science Data Processing Pipeline

The Roman Space Telescope (RST) Wide Field Instrument (WFI) will be utilizing a preliminary Science Data Processing (SDP) pipeline during its Integration and Test, and to some extent during Operations, to track basic statistics and identify known features such as cosmic rays, snowballs as well as possible anomalies in raw detector data. In our detectors, these anomalies appear as jumps in the ramp of a readout and are classified as cosmic rays if they appear as a streak or snowballs if they’re more circular. The WFI employs an array of 18 H4RG-10 detectors that collect image samples. Each set of raw frames within a non-destructive exposure is packaged by the SDP pipeline into image cubes for each detector. Each cube is a time series of 4096 × 4096 accumulating pixel frames. The preliminary analysis pipeline is used to locate anomalies in these time-series accumulation frames and identify the type of anomaly, either natural phenomena or detector characteristic. To compare different methods, we’ve implemented both heuristic-based and data-driven methods to identify anomalies. For the heuristic-based approach, we identify snowballs and cosmic rays by the size and shape of outlier pixel clusters between consecutive frames. For data driven methods, we evaluated a Convolutional Neural Network (CNN) model, and more traditional methods like Principal Component Analysis (PCA). CNN is a supervised learning/classification method. Thus, we used a labeled dataset of anomalies to perform segmentation of the image and identify anomalies. We used previously identified cosmic rays and snowballs to measure the accuracy and efficiency of the mentioned approaches. In evaluating these methods, we aim to pick the best fit for the SDP pipeline’s anomaly detection in terms of both performance and runtime.

Paul Horton↗

Earth observing system. Output data products and input requirements, version 2.0. Volume 3: Algorithm summary tables and non-EOS data products

Volume 3 assists Earth Observing System (EOS) investigators in locating required non-EOS data products by identifying their non-EOS input requirements and providing the information on data sets available at various Distributed Active Archive Centers (DAAC's), including those from Pathfinder Activities and Earth Probes. Volume 3 is intended to complement, not to duplicate, the the EOSDIS Science Data Plan (SDP) by providing detailed data set information which was not presented in the SDP. Section 9 of this volume discusses the algorithm summary tables containing information on retrieval algorithms, expected outputs and required input data. Section 10 describes the non-EOS input requirements of instrument teams and IDS investigators. Also described are the current and future data holdings of the original seven DAACS and data products planned from the future missions and projects including Earth Probes and Pathfinder Activities. Section 11 describes source of information used in compiling data set information presented in this volume. A list of data set attributes used to describe various data sets is presented in section 12 along with their descriptions. Finally, Section 13 presents the SPSO's future plan to improve this report .

Lu, Yun-Chi↗

Functional Flight Test Report for Positive Systems' ADAR System 5500 Sensor SN8 Linear

This report describes results of the functional flight test conducted with the Positive Systems' ADAR 5500 sensor system (serial number 8, linear configuration) near Winslow, Arizona on June 30 and July 1, 1999. The in-flight test is one component of the NASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. It allows to measure characteristics of the entire sensor system affected by both performance of the sensor during a flight and post-flight image processing. The following characteristics were analyzed: changes of dark digital numbers (DN's), radiometric linearity, signal-to-noise ratio (SNR), spatial resolution, and geolocation accuracy. The measured characteristics were compared with the image product specifications defined in the Positive Systems' SDP contract. Dependence of the dark DN's on several factors was analyzed, but no significant correlation was found. However, the observed changes in dark DN's were relatively small, which justifies usage of a constant value in the dark DN subtraction procedure during post-processing. Dependence of measured at-sensor, in-band radiance (in arbitrary units) on measured in-band ground reflectance is very well described by a linear function - The sensor fulfills the linearity requirement. Measured SNR values lower than the contract specifications, but accuracy of that test was possibly affected by non-uniformity of the employed gray-scale panels. The SNR values are generally sufficiently high for most applications. SNR can also be improved during standard flights by using longer exposure times. Full width at half maximum (FWHM) of an edge response derived line spread function was used as a measure of spatial resolution. FWHM was generally smaller than twice the ground sample distance (GSD), in agreement with the contract specifications. Accuracy of the geolocation information, which is provided for the particular images in a metadata file, was found to meet contract requirements as well.

Stanley, Tom↗