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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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NASA NTRS1992

High-performance equation solvers and their impact on finite element analysis

The role of equation solvers in modern structural analysis software is described. Direct and iterative equation solvers which exploit vectorization on modern high-performance computer systems are described and compared. The direct solvers are two Cholesky factorization methods. The first method utilizes a novel variable-band data storage format to achieve very high computation rates and the second method uses a sparse data storage format designed to reduce the number od operations. The iterative solvers are preconditioned conjugate gradient methods. Two different preconditioners are included; the first uses a diagonal matrix storage scheme to achieve high computation rates and the second requires a sparse data storage scheme and converges to the solution in fewer iterations that the first. The impact of using all of the equation solvers in a common structural analysis software system is demonstrated by solving several representative structural analysis problems.

Poole, Eugene L.↗

NASA NTRS2021

Assessing Relay Communications for Mars Sample Return Surface Mission Concepts

The Mars Sample Return (MSR) Campaign would be a 3-mission campaign concept supported by NASA and ESA to return samples from the Mars surface. MSR would, for the first time ever, present a need to communicate with multiple surface assets that are co-located on Mars in a coordinated effort to accomplish the unified objective of fetching, transporting, and returning samples from Mars. Currently, Mars surface assets relay data to and from Earth using a number of orbiters in what’s known as the Mars Relay Network (MRN). This network is characterized by a small number of surface assets distributed across the Martian globe and a larger number of orbiters to provide relay services. As of June 2020, there are two surface assets for which five orbiters are providing relay. During the MSR Campaign, there would be two rovers and a lander that all would require relay communication from a small number of Mars orbiters to meet the aggressive MSR timeline. The inversion of the current MRN paradigm, a system of many surface assets requiring relay and few orbiters to provide relay, necessitates the unique challenge of optimally allocating relay passes to maximize the operational capability of all assets. The allocation must consider a large number of trade variables including Mars asset operational requirements and Earth ground system constraints, including staffing schedules, operations planning across time zones, and more. To address these telecommunication challenges, the Mars Asset Relay Mission Link Allocation Design Environment (MARMLADE) tool was developed. It is a MATLAB-based tool to assign orbiter passes or Direct-From-Earth (DFE) links to each of the three surface assets and quantify the operational efficiency of each surface asset.MARMLADE uses a data set of simulated Mars relay orbiter geometry and telecommunication capabilities provided by JPL’s Telecom Orbit Analysis and Simulation Tool (TOAST) software to compute which asset should get each pass based on a series of heuristics and predictions of all assets’ states. Within MARMLADE, the user can provide inputs including the option for time-based pass splitting, fixed FWD data rate capabilities, DFE communication capabilities, and link parameters allowing for the assessment of complex operations and hardware trades using surface mission operational efficiency as a primary figure of merit. As the MSR mission concepts continue to mature, MARMLADE is being used to assess ability of all MSR elements to meet the surface mission timeline requirements and to provide relay link allocations to each of the MSR surface assets.This paper will describe the motivation and design of the MARMLADE tool and how it is being used to perform campaign and mission level trades, generate requirements, and support development of the MSR surface mission scenarios.

Lee, Charles↗

NASA NTRS2011

Geodetic Strain Analysis Tool

A geodetic software analysis tool enables the user to analyze 2D crustal strain from geodetic ground motion, and create models of crustal deformation using a graphical interface. Users can use any geodetic measurements of ground motion and derive the 2D crustal strain interactively. This software also provides a forward-modeling tool that calculates a geodetic velocity and strain field for a given fault model, and lets the user compare the modeled strain field with the strain field obtained from the user s data. Users may change parameters on-the-fly and obtain a real-time recalculation of the resulting strain field. Four data products are computed: maximum shear, dilatation, shear angle, and principal components. The current view and data dependencies are processed first. The remaining data products and views are then computed in a round-robin fashion to anticipate view changes. When an analysis or display parameter is changed, the affected data products and views are invalidated and progressively re-displayed as available. This software is designed to facilitate the derivation of the strain fields from the GPS and strain meter data that sample it to facilitate the understanding of the strengths and weaknesses of the strain field derivation from continuous GPS (CGPS) and other geodetic data from a variety of tectonic settings, to converge on the "best practices" strain derivation strategy for the Solid Earth Science ESDR System (SESES) project given the CGPS station distribution in the western U.S., and to provide SESES users with a scientific and educational tool to explore the strain field on their own with user-defined parameters.

Kedar, Sharon↗

DOE OSTI2023

Towards elastic in situ analysis for high-performance computing simulations

In situ analysis and visualization have grown increasingly popular for enabling direct access to data from high-performance computing (HPC) simulations. As a simulation progresses and interesting physical phenomena emerge, however, the data produced may become increasingly complex, and users may need to dynamically change the type and scale of in situ analysis tasks being carried out and consequently adapt the amount of resources allocated to such tasks. To date, none of the production in situ analysis frameworks offer such an elasticity feature, and for good reason: the assumption that the number of processes could vary during run time would force developers to rethink software and algorithms at every level of the in situ analysis stack. In this paper we present Colza, a data staging service with elastic in situ visualization capabilities. We demonstrate the use of Colza with the Deep Water Impact and the AMR-Wind simulations, coupling them with the ParaView Catalyst and Ascent in situ libraries, and show that Colza enables dynamic rescaling of these widely-used frameworks with no interruption to the simulation or staging service. Here, we highlight the challenges of enabling such elasticity, which requires overcoming these frameworks' reliance on MPI, using distinct engineering approaches, namely dependency injection and dependency overload. To the best of our knowledge, this work is the first to enable elastic in situ visualization capabilities for HPC applications on top of existing production analysis tools.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2011

Analysis of XMM-Newton Data from Extended Sources and the Diffuse X-Ray Background

Reduction of X-ray data from extended objects and the diffuse background is a complicated process that requires attention to the details of the instrumental response as well as an understanding of the multiple background components. We present methods and software that we have developed to reduce data from XMM-Newton EPIC imaging observations for both the MOS and PN instruments. The software has now been included in the Science Analysis System (SAS) package available through the XMM-Newton Science Operations Center (SOC).

Snowden, Steven↗

NASA NTRS2011

Improvements to the Ionizing Radiation Risk Assessment Program for NASA Astronauts

To perform dosimetry and risk assessment, NASA collects astronaut ionizing radiation exposure data from space flight, medical imaging and therapy, aviation training activities and prior occupational exposure histories. Career risk of exposure induced death (REID) from radiation is limited to 3 percent at a 95 percent confidence level. The Radiation Health Office at Johnson Space Center (JSC) is implementing a program to integrate the gathering, storage, analysis and reporting of astronaut ionizing radiation dose and risk data and records. This work has several motivations, including more efficient analyses and greater flexibility in testing and adopting new methods for evaluating risks. The foundation for these improvements is a set of software tools called the Astronaut Radiation Exposure Analysis System (AREAS). AREAS is a series of MATLAB(Registered TradeMark)-based dose and risk analysis modules that interface with an enterprise level SQL Server database by means of a secure web service. It communicates with other JSC medical and space weather databases to maintain data integrity and consistency across systems. AREAS is part of a larger NASA Space Medicine effort, the Mission Medical Integration Strategy, with the goal of collecting accurate, high-quality and detailed astronaut health data, and then securely, timely and reliably presenting it to medical support personnel. The modular approach to the AREAS design accommodates past, current, and future sources of data from active and passive detectors, space radiation transport algorithms, computational phantoms and cancer risk models. Revisions of the cancer risk model, new radiation detection equipment and improved anthropomorphic computational phantoms can be incorporated. Notable hardware updates include the Radiation Environment Monitor (which uses Medipix technology to report real-time, on-board dosimetry measurements), an updated Tissue-Equivalent Proportional Counter, and the Southwest Research Institute Radiation Assessment Detector. Also, the University of Florida hybrid phantoms, which are flexible in morphometry and positioning, are being explored as alternatives to the current NASA computational phantoms.

Semones, E. J.↗

NASA NTRS1987

Detection of faults and software reliability analysis

Specific topics briefly addressed include: the consistent comparison problem in N-version system; analytic models of comparison testing; fault tolerance through data diversity; and the relationship between failures caused by automatically seeded faults.

Knight, J. C.↗

NASA NTRS1972

Correlation signatures of wet soils and snows

Interpretation, analysis, and development of algorithms have provided the necessary computational programming tools for soil data processing, data handling and analysis. Algorithms that have been developed thus far, are adequate and have been proven successful for several preliminary and fundamental applications such as software interfacing capabilities, probability distributions, grey level print plotting, contour plotting, isometric data displays, joint probability distributions, boundary mapping, channel registration and ground scene classification. A description of an Earth Resources Flight Data Processor, (ERFDP), which handles and processes earth resources data under a users control is provided.

Phillips, M. R.↗

NASA NTRS2010

Computation of Earth Science Products on Spaceborne Platforms

Spaceborne sensors like NASA's Hyperion hyperspectral imager generate huge data volumes, and several near-term trends indicate that data volumes will only increase. Next-generation hyperspectral missions, such as NASA's Hyperspectral Infrared Imager (HyspIRI), will operate at higher duty cycles and higher data rates, and their users will expect products to be generated from the data in near real time [1]. Barring a sudden advance in satellite downlink capacity, these trends point to a need to process data and generate products onboard the spacecraft. Rather than downlink an entire hyperspectral image cube, onboard processing enables satellites to downlink partial or completed scientific data products, which are often one to two orders of magnitude smaller than the original image. In addition, a satellite with onboard data processing resources and direct broadcast transmission equipment could send data products directly to first responders, research scientists or other users on the ground. Next-generation space-capable data processors will have a combination of reconfigurable gate arrays, digital signal processors and general-purpose CPUs. Correctly programmed and configured, these resources are sufficient to run sophisticated data analysis programs, including hyperspectral image processing algorithms that commonly run on desktop computers [2]. This paper describes how we implemented one such program, the HSEG hierarchical image segmentation algorithm, software commonly used on desktop and parallel processors, on a hardware platform designed to mimic a next-generation space-capable data processor [3]. We also describe our approach to porting the algorithm to and optimizing it for the new platform, and determine the expected performance gains enabled by our design. This extended abstract will describe the HSEG algorithm and hardware platform in greater detail, provide an analysis of the key function within the algorithm that required hardware acceleration, and describe our implementation of that function in hardware.

Fisher, Kevin↗

NASA NTRS1989

DATAMAP upgrade version 4.0

The changes made on the data analysis and management program DATAMAP (Data from Aeromechanics Test and Analytics - Management and Analysis Package) are detailed. These changes are made to Version 3.07 (released February, 1981) and are called Version 4.0. Version 4.0 improvements were performed by Sterling Software under contract to NASA Ames Research Center. The increased capabilities instituted in this version include the breakout of the source code into modules for ease of modification, addition of a more accurate curve fit routine, ability to handle higher frequency data, additional data analysis features, and improvements in the functionality of existing features. These modification will allow DATAMAP to be used on more data sets and will make future modifications and additions easier to implement.

Watts, Michael E.↗

NASA NTRS2018

Recent Developments to the Porous Microstructure Analysis (PuMA) Software

The Porous Microstructure Analysis (PuMA) software is a suite of tools for the analysis of porous materials and generation of material microstructures. From microstructural data, often obtained through X-ray microtomography, PuMA can determine a number of effective material properties and perform material response simulations. Version 2.2 includes capabilities for computing volume fractions, porosity, specific surface area, effective thermal and electrical conductivities, and continuum and rarefied diffusive tortuosity. PuMA can also simulate competitive diffusion/reaction processes at the micro-scale, such as surface oxidation. In this poster, recent advancements to the PuMA software are detailed, including the full refactoring of PuMA into v3.0, a new module to compute heat conduction in anisotropic materials, a particle method for simulating molecular beam experiments, a new finite-volume Laplace solver, complex fibrous material generation, woven material generation, and a coupling of PuMA with the DAKOTA software for advanced statistics.

PuMA↗

DOE OSTI2024

Python wrapper library and analysis functions for Geotab Altitude API [SWR-24-77]

This software library serves as a Python wrapper for Geotab's Altitude API. It streamlines querying of the API, converts loosely structured API outputs into a standardized tabular data format, and enables analysis of the resulting data tables. It also includes example notebooks showing how to use the library.

Bruchon, Matthew↗

NASA NTRS2009

NASA Orbital Debris Engineering Model ORDEM2008 (Beta Version)

This is an interim document intended to accompany the beta-release of the ORDEM2008 model. As such it provides the user with a guide for its use, a list of its capabilities, a brief summary of model development, and appendices included to educate the user as to typical runtimes for different orbit configurations. More detailed documentation will be delivered with the final product. ORDEM2008 supersedes NASA's previous model - ORDEM2000. The availability of new sensor and in situ data, the re-analysis of older data, and the development of new analytical techniques, has enabled the construction of this more comprehensive and sophisticated model. Integrated with the software is an upgraded graphical user interface (GUI), which uses project-oriented organization and provides the user with graphical representations of numerous output data products. These range from the conventional average debris size vs. flux magnitude for chosen analysis orbits, to the more complex color-contoured two-dimensional (2-D) directional flux diagrams in terms of local spacecraft pitch and yaw.

Stansbery, Eugene G.↗

NASA NTRSDate not supplied

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↗

NASA NTRS2013

An Overview of Modifications Applied to a Turbulence Response Analysis Method for Flexible Aircraft Configurations

A software program and associated methodology to study gust loading on aircraft exists for a classification of geometrically simplified flexible configurations. This program consists of a simple aircraft response model with two rigid and three flexible symmetric degrees of freedom and allows for the calculation of various airplane responses due to a discrete one-minus-cosine gust as well as continuous turbulence. Simplifications, assumptions, and opportunities for potential improvements pertaining to the existing software program are first identified, then a revised version of the original software tool is developed with improved methodology to include more complex geometries, additional excitation cases, and output data so as to provide a more useful and accurate tool for gust load analysis. Revisions are made in the categories of aircraft geometry, computation of aerodynamic forces and moments, and implementation of horizontal tail mode shapes. In order to improve the original software program to enhance usefulness, a wing control surface and horizontal tail control surface is added, an extended application of the discrete one-minus-cosine gust input is employed, a supplemental continuous turbulence spectrum is implemented, and a capability to animate the total vehicle deformation response to gust inputs in included. These revisions and enhancements are implemented and an analysis of the results is used to validate the modifications.

Funk, Christie J.↗

NASA NTRS2004

Prioritizing Scientific Data for Transmission

A software system has been developed for prioritizing newly acquired geological data onboard a planetary rover. The system has been designed to enable efficient use of limited communication resources by transmitting the data likely to have the most scientific value. This software operates onboard a rover by analyzing collected data, identifying potential scientific targets, and then using that information to prioritize data for transmission to Earth. Currently, the system is focused on the analysis of acquired images, although the general techniques are applicable to a wide range of data modalities. Image prioritization is performed using two main steps. In the first step, the software detects features of interest from each image. In its current application, the system is focused on visual properties of rocks. Thus, rocks are located in each image and rock properties, such as shape, texture, and albedo, are extracted from the identified rocks. In the second step, the features extracted from a group of images are used to prioritize the images using three different methods: (1) identification of key target signature (finding specific rock features the scientist has identified as important), (2) novelty detection (finding rocks we haven t seen before), and (3) representative rock sampling (finding the most average sample of each rock type). These methods use techniques such as K-means unsupervised clustering and a discrimination-based kernel classifier to rank images based on their interest level.

Castano, Rebecca↗

NASA NTRS1990

Thermal Analysis Software

A new version of Space Payload Thermal Analyzer (SSPTA) that can be used on a 386 personal computer was developed by Nicholas Teti. SSPTA/386 software package includes the programs that Goddard has traditionally used in thermal design and analysis. The original programs were modified to run on the 386 system and automatic data transfer between programs was improved. SSPTA/386 includes all the features available in Goddard's VAX version of SSPTA. The software package is highly flexible in that it allows the user to run the programs interactively or in batch mode. It provides a menu system that allows the user to select a program or a combination of programs.

Source record↗

NASA NTRS1991

The Land Analysis System (LAS)

The Land Analysis System (LAS) is an interactive software system, available in the public domain, for the analysis, display, and management of multispectral and other digital image data. The system was developed to support earth sciences research and development activities. LAS provides over 240 applications functions and utilities, a flexible user interface, complete on-line and hardcopy documentation, extensive image data file management, reformatting, and conversion utilities, and high level device independent access to image display hardware. The capabilities are summarized of the latest release of the system (version 5). Emphasis is given to the system portability and the isolation of hardware and software dependencies in this release.

Lu, Yun-Chi↗