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NASA NTRS2013

The GLAS Science Algorithm Software (GSAS) User's Guide Version 7

The Geoscience Laser Altimeter System (GLAS) is the primary instrument for the ICESat (Ice, Cloud and Land Elevation Satellite) laser altimetry mission. ICESat was the benchmark Earth Observing System (EOS) mission for measuring ice sheet mass balance, cloud and aerosol heights, as well as land topography and vegetation characteristics. From 2003 to 2009, the ICESat mission provided multi-year elevation data needed to determine ice sheet mass balance as well as cloud property information, especially for stratospheric clouds common over polar areas. It also provided topography and vegetation data around the globe, in addition to the polar-specific coverage over the Greenland and Antarctic ice sheets.This document is the final version of the GLAS Science Algorithm Software Users Guide document. It contains the instructions to install the GLAS Science Algorithm Software (GSAS) in the production environment that was used to create the standard data products. It also describes the usage of each GSAS program in that environment with their required inputs and outputs. Included are a number of utility programs that are used to create ancillary data files that are used in the processing but generally are not distributed to the public as data products. Of importance is the values for the large number of constants used in the GSAS algorithm during processing are provided in an appendix.

Lee, Jeffrey E.↗

NASA NTRS1977

UH cosmic rays: Possible origin in massive stars

The origin of the Z greater than 28, ultraheavy, cosmic rays in supernova explosions of massive stars is considered. For Z greater than 70, the UH data is dominated by an r-process source distribution, but for the elements just beyond iron, 29 or = Z less than 36, the data cannot be explained by any single process of nucleosynthesis. This problem is solved naturally in a massive star model by secondary neutron capture reactions occuring during core helium burning and during explosive carbon burning. Interstellar propagation calculations were performed with these episodes of synthesis as source distributions, and the results offer an explanation for the current UH cosmic-ray data. The heavy element synthesis during explosive carbon burning is reexamined using more realistic initial conditions given by the post-helium-burning configuration of the star. Effects of preferential acceleration are considered, and experimental tests are discussed.

Wefel, J. P.↗

NASA NTRS2010

Reducing the Volume of NASA Earth-Science Data

A computer program reduces data generated by NASA Earth-science missions into representative clusters characterized by centroids and membership information, thereby reducing the large volume of data to a level more amenable to analysis. The program effects an autonomous data-reduction/clustering process to produce a representative distribution and joint relationships of the data, without assuming a specific type of distribution and relationship and without resorting to domain-specific knowledge about the data. The program implements a combination of a data-reduction algorithm known as the entropy-constrained vector quantization (ECVQ) and an optimization algorithm known as the differential evolution (DE). The combination of algorithms generates the Pareto front of clustering solutions that presents the compromise between the quality of the reduced data and the degree of reduction. Similar prior data-reduction computer programs utilize only a clustering algorithm, the parameters of which are tuned manually by users. In the present program, autonomous optimization of the parameters by means of the DE supplants the manual tuning of the parameters. Thus, the program determines the best set of clustering solutions without human intervention.

Lee, Seungwon↗

NASA NTRS2017

Lessons Learned While Exploring Cloud-Native Architectures for NASA EOSDIS Applications and Systems

NASA's Earth Observing System (EOS) is a coordinated series of satellites for long term global observations. NASA's Earth Observing System Data and Information System (EOSDIS) is a multi-petabyte-scale archive of environmental data that supports global climate change research by providing end-to-end services from EOS instrument data collection to science data processing to full access to EOS and other earth science data. On a daily basis, the EOSDIS ingests, processes, archives and distributes over 3 terabytes of data from NASA's Earth Science missions representing over 6000 data products ranging from various types of science disciplines. EOSDIS has continually evolved to improve the discoverability, accessibility, and usability of high-impact NASA data spanning the multi-petabyte-scale archive of Earth science data products. Reviewed and approved by Chris Lynnes.

Cumulus↗

NASA NTRS2012

IT Data Mining Tool Uses in Aerospace

Data mining has a broad spectrum of uses throughout the realms of aerospace and information technology. Each of these areas has useful methods for processing, distributing, and storing its corresponding data. This paper focuses on ways to leverage the data mining tools and resources used in NASA's information technology area to meet the similar data mining needs of aviation and aerospace domains. This paper details the searching, alerting, reporting, and application functionalities of the Splunk system, used by NASA's Security Operations Center (SOC), and their potential shared solutions to address aircraft and spacecraft flight and ground systems data mining requirements. This paper also touches on capacity and security requirements when addressing sizeable amounts of data across a large data infrastructure.

Monroe, Gilena A.↗

NASA NTRS1992

Science data processing in the Mission to Planet Earth era

The data-processing systems developed to support NASA's Mission to Planet Earth (MPE) are described in an overview of the system architectures. The MPE program is discussed in terms of flight segments and data types to examine the required elements of the information systems. The data-processing segments are described for the Atmospheric Laboratory for Applications and Science, the Tropical Rainfall Measuring Mission, the Earth Observing System, and the Geostationary Earth Observatory. The data and information systems for the separate segments provide some redundant processing services. Distributed active archive centers are employed for each segment composed of three subelements: (1) a product-generation system, (2) a data archive and distribution system, and (3) an information management system. The data processing design for the MPE is expected to facilitate the understanding of the entire earth system on a global scale.

Goodman, H. M.↗

NASA NTRS1993

EOS ground data systems: A description and interface overview

The Earth Observing System (EOS) is planned as a space-based measurement system, earth-science research program, and data and information system (EOSDIS). It will consist of several high data rate spacecraft with multiple earth sensing instruments which provide investigators with a thorough, longterm view of the earth's environment. Up to seven spacecraft may be supported at once, either in operational, checkout, or testing phases; and the average data rate from the EOS satellites in orbit at any one time is expected to be from 18 to 60 Mbps. Providing the data processing and flight operations support for EOS will be the EOSDIS Core System (ECS). The ECS will command and control the spacecraft; process and store the EOS data; provide access to the data for years; and support researchers. The data processing aspects of the ECS consist of a collection of Distributed Active Archive Centers (DAAC's) which perform the product generation, data archive and distribution, and information management services. Flight operations aspects will be provided by the EOS Operations Center, by instrument control centers, and by widely distributed instrument support terminals. The communications and system management aspects will be provided by the EOSDIS Science Network and the System Management Center. In addition to the EOS satellite data, other data sets from earlier earth science missions are also to be added to designated DAAC's. Other ground data systems which will provide support to EOS for acquiring, transporting, processing, and distributing the transformed spacecraft data are currently being defined or are being upgraded for the EOS era. These systems include the Space Network consisting of the Tracking and Data Relay Satellite System (TDRSS), the TDRSS Ground Terminals, and the Network Control Center as well as the night Dynamics Facility, the EOS Data and Operations System, and EOS Communications. This paper briefly describes data handling by the ECS, the support data systems, their interfaces, and their roles.

Smith, Gene↗

NASA NTRS1959

A Systematic Kernel Function Procedure for Determining Aerodynamic Forces on Oscillating or Steady Finite Wings at Subsonic Speeds

Details are given of a numerical solution of the integral equation which relates oscillatory or steady lift and downwash distributions in subsonic flow. The procedure has been programmed for the IBM 704 electronic data processing machine and yields the pressure distribution and some of its integrated properties for a given Mach number and frequency and for several modes of oscillation in from 3 to 4 minutes, results of several applications are presented.

Watkins, Charles E.↗

DOE OSTI2013

A Parallel Ghosting Algorithm for The Flexible Distributed Mesh Database

Critical to the scalability of parallel adaptive simulations are parallel control functions including load balancing, reduced inter-process communication and optimal data decomposition. In distributed meshes, many mesh-based applications frequently access neighborhood information for computational purposes which must be transmitted efficiently to avoid parallel performance degradation when the neighbors are on different processors. This article presents a parallel algorithm of creating and deleting data copies, referred to as ghost copies, which localize neighborhood data for computation purposes while minimizing inter-process communication. The key characteristics of the algorithm are: (1) It can create ghost copies of any permissible topological order in a 1D, 2D or 3D mesh based on selected adjacencies. (2) It exploits neighborhood communication patterns during the ghost creation process thus eliminating all-to-all communication. (3) For applications that need neighbors of neighbors, the algorithm can create n number of ghost layers up to a point where the whole partitioned mesh can be ghosted. Strong and weak scaling results are presented for the IBM BG/P and Cray XE6 architectures up to a core count of 32,768 processors. The algorithm also leads to scalable results when used in a parallel super-convergent patch recovery error estimator, an application that frequently accesses neighborhood data to carry out computation.

Mubarak, Misbah↗

NASA NTRS2003

Cardea: Providing Support for Dynamic Resource Access in a Distributed Computing Environment

The environment framing the modem authorization process span domains of administration, relies on many different authentication sources, and manages complex attributes as part of the authorization process. Cardea facilitates dynamic access control within this environment as a central function of an inter-operable authorization framework. The system departs from the traditional authorization model by separating the authentication and authorization processes, distributing the responsibility for authorization data and allowing collaborating domains to retain control over their implementation mechanisms. Critical features of the system architecture and its handling of the authorization process differentiate the system from existing authorization components by addressing common needs not adequately addressed by existing systems. Continuing system research seeks to enhance the implementation of the current authorization model employed in Cardea, increase the robustness of current features, further the framework for establishing trust and promote interoperability with existing security mechanisms.

Lepro, Rebekah↗

NASA NTRS1992

Recommendations for a service framework to access astronomical archives

There are a large number of astronomical archives and catalogs on-line for network access, with many different user interfaces and features. Some systems are moving towards distributed access, supplying users with client software for their home sites which connects to servers at the archive site. Many of the issues involved in defining a standard framework of services that archive/catalog suppliers can use to achieve a basic level of interoperability are described. Such a framework would simplify the development of client and server programs to access the wide variety of astronomical archive systems. The primary services that are supplied by current systems include: catalog browsing, dataset retrieval, name resolution, and data analysis. The following issues (and probably more) need to be considered in establishing a standard set of client/server interfaces and protocols: Archive Access - dataset retrieval, delivery, file formats, data browsing, analysis, etc.; Catalog Access - database management systems, query languages, data formats, synchronous/asynchronous mode of operation, etc.; Interoperability - transaction/message protocols, distributed processing mechanisms (DCE, ONC/SunRPC, etc), networking protocols, etc.; Security - user registration, authorization/authentication mechanisms, etc.; Service Directory - service registration, lookup, port/task mapping, parameters, etc.; Software - public vs proprietary, client/server software, standard interfaces to client/server functions, software distribution, operating system portability, data portability, etc. Several archive/catalog groups, notably the Astrophysics Data System (ADS), are already working in many of these areas. In the process of developing StarView, which is the user interface to the Space Telescope Data Archive and Distribution Service (ST-DADS), these issues and the work of others were analyzed. A framework of standard interfaces for accessing services on any archive system which would benefit archive user and supplier alike is proposed.

Travisano, J. J.↗

DOE OSTI2020

Distributed coherence directory subsystem with exclusive data regions

A processing system includes a first set of one or more processing units including a first processing unit, a second set of one or more processing units including a second processing unit, and a memory having an address space shared by the first and second sets. The processing system further includes a distributed coherence directory subsystem having a first coherence directory to support a first subset of one or more address regions of the address space and a second coherence directory to support a second subset of one or more address regions of the address space. In some implementations, the first coherence directory is implemented in the system so as to have a lower access latency for the first set, whereas the second coherence directory is implemented in the system so as to have a lower access latency for the second set.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Distributed coherence directory subsystem with exclusive data regions

Eckert, Yasuko↗

DOE OSTI2020

Kepler Data Analysis: Non-Gaussian Noise and Fourier Gaussian Process Analysis of Stellar Variability

We develop a statistical analysis model of Kepler stellar flux data in the presence of planet transits, non-Gaussian noise, and stellar variability. We first develop a model for the Kepler noise probability distribution in the presence of outliers, which make the noise probability distribution non-Gaussian. We develop a signal likelihood analysis based on this probability distribution, in which we model the signal as a sum of the star variability and planetary transits. We argue that these components need to be modeled together if optimal signal is to be extracted from the data. For the stellar variability model we develop an optimal Gaussian process analysis using a Fourier-based Wiener filter approach, where the power spectrum is non-parametric and learned from the data. We develop high dimensional optimization of the objective function, where we jointly optimize all the model parameters, including thousands of star variability modes, and planet transit parameters. We apply the method to Kepler-90 data and show that it gives a better match to the stellar variability than the existing methods, and robustly handles noise outliers. As a consequence, the planet radii have a higher value than what the existing methods give, including splines and celerite.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Scattering of a laser beam on a wet blood smear and measurement of red cell size distribution

We report an automated laser system that allows the red cell size distribution to be measured. Experiments are performed on laser light scattering by a suspension of oriented red blood cells (a wet blood smear). Based on an analysis of the angular distribution of light intensity in the diffraction pattern, we have restored the red cell size distribution. The average diameter of a red blood cell is determined with an error of less than 1%, and the spread of red blood cells in size – with an error of about 20%. We discuss the problems of photometry and processing of diffraction patterns, preparing blood samples and data processing algorithms, including methods for solving the inverse scattering problem. (laser biophotonics)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1981

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Clark, J.↗

NASA NTRS1975

ERTS-1 data collection system: Status and performance

The Data Collection System flown on the first Earth Resources Technology Satellite (ERTS-1) relays earth resources data from remotely located in-situ sensors to Goddard Space Flight Center. Data is received at Goddard at least twice each day from every sensor installation and is distributed to users (who operate the sensors and transmitters) by mail and teletype. The system consists of a data formatting and transmitting unit, called the Data Collection Platform (DCP), a receiver and a retransmitter aboard ERTS-1; and receiving, demodulating and decoding equipment located at the Goldstone, California and Goddard data acquisition stations. Data is transmitted from the data acquisition stations to the ERTS Control Center at Goddard, then to the NASA (ERTS) Data Processing Facility (NDPF) where it is processed and distributed to users. Experience to date indicates that the design of the ERTS-1 Data Collection System is adequate for operational use for 50% of the users and, with minor modifications, could meet the requirements of 75%. Some users will have to augment the system by other data collection techniques to meet their operational requirements.

Painter, J. E.↗

DOE OSTI2021

Application of Sequential Design of Experiments (SDoE) to Large Pilot-Scale Solvent-Based CO2 Capture Process at Technology Centre Mongstad (TCM)

The United States Department of Energy’s Carbon Capture Simulation for Industry Impact (CCSI2) program has developed a framework for sequential design of experiments (SDoE) that aims to maximize knowledge gained from budget- and schedule-limited pilot scale testing. SDoE was applied to the planning and execution of campaigns for testing CO2 capture systems at pilot-scale in order to optimally allocate resources available for the testing. In this methodology, a stochastic process model is developed by quantifying the parametric uncertainty in submodels of interest; for a solvent-based CO2 capture system, these may include physical properties and equipment performance submodels (e.g., mass transfer, interfacial area). This uncertainty is propagated through the full process model, over variable operating conditions, for estimating the resulting uncertainty in key model outputs (e.g., percentage of CO2 capture, solvent regeneration energy requirement). In developing a data collection plan, the predicted output uncertainty is incorporated into an algorithm that seeks simultaneously to select process operating conditions for which the predicted uncertainty is relatively high and to ensure that the entire space of operation is well represented. This test plan is then used to guide operation of the pilot plant at varying steady-state conditions, with resulting process data incorporated into the existing model using Bayesian inference to refine parameter distributions. The updated stochastic model, with reduced parametric uncertainty from data collected, is then used to guide additional data collection, thus the sequential nature of the experimental design. The SDoE process was implemented at the pilot test unit (12 MWe in scale) at Norway’s Technology Centre Mongstad (TCM) in a summer 2018 test campaign with aqueous monoethanolamine (MEA). During the test campaign, the varied operating conditions included the flowrates of circulated solvent, flue gas, and reboiler steam and the CO2 concentration in the flue gas. The process data were used to update probability distributions of mass transfer and interfacial area parameters of a stochastic process model developed by the CCSI2 team. Two iterations of the SDoE process were executed, resulting in the uncertainty in model predicted CO2 capture percentage decreasing by an average of 58.0 ± 4.7% over the full input space of interest. This work demonstrates the potential of the SDoE process for model refinement through reduction in process model parametric uncertainty, and ultimately risk in scale-up, in CO2 capture technology performance.

carbon capture↗