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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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At least 433 records · Page 24

The Linux operating system: An introduction

Linux is a Unix-like operating system for Intel 386/486/Pentium based IBM-PCs and compatibles. The kernel of this operating system was written from scratch by Linus Torvalds and, although copyrighted by the author, may be freely distributed. A world-wide group has collaborated in developing Linux on the Internet. Linux can run the powerful set of compilers and programming tools of the Free Software Foundation, and XFree86, a port of the X Window System from MIT. Most capabilities associated with high performance workstations, such as networking, shared file systems, electronic mail, TeX, LaTeX, etc. are freely available for Linux. It can thus transform cheap IBM-PC compatible machines into Unix workstations with considerable capabilities. The author explains how Linux may be obtained, installed and networked. He also describes some interesting applications for Linux that are freely available. The enormous consumer market for IBM-PC compatible machines continually drives down prices of CPU chips, memory, hard disks, CDROMs, etc. Linux can convert such machines into powerful workstations that can be used for teaching, research and software development. For professionals who use Unix based workstations at work, Linux permits virtually identical working environments on their personal home machines. For cost conscious educational institutions Linux can create world-class computing environments from cheap, easily maintained, PC clones. Finally, for university students, it provides an essentially cost-free path away from DOS into the world of Unix and X Windows.

Bokhari, Shahid H.↗

A Method of Integrating Aeroheating into Conceptual Reusable Launch Vehicle Design: Evaluation of Advanced Thermal Protection Techniques for Future Reusable Launch Vehicles

A method for integrating Aeroheating analysis into conceptual reusable launch vehicle (RLV) design is presented in this thesis. This process allows for faster turn-around time to converge a RLV design through the advent of designing an optimized thermal protection system (TPS). It consists of the coupling and automation of four computer software packages: MINIVER, TPSX, TCAT, and ADS. MINIVER is an Aeroheating code that produces centerline radiation equilibrium temperatures, convective heating rates, and heat loads over simplified vehicle geometries. These include flat plates and swept cylinders that model wings and leading edges, respectively. TPSX is a NASA Ames material properties database that is available on the World Wide Web. The newly developed Thermal Calculation Analysis Tool (TCAT) uses finite difference methods to carry out a transient in-depth 1-D conduction analysis over the center mold line of the vehicle. This is used along with the Automated Design Synthesis (ADS) code to correctly size the vehicle's thermal protection system (TPS). The numerical optimizer ADS uses algorithms that solve constrained and unconstrained design problems. The resulting outputs for this process are TPS material types, unit thicknesses, and acreage percentages. TCAT was developed for several purposes. First, it provides a means to calculate the transient in-depth conduction seen by the surface of the TPS material that protects a vehicle during ascent and reentry. Along with the in-depth conduction, radiation from the surface of the material is calculated along with the temperatures at the backface and interior parts of the TPS material. Secondly, TCAT contributes added speed and automation to the overall design process. Another motivation in the development of TCAT is optimization. In some vehicles, the TPS accounts for a high percentage of the overall vehicle dry weight. Optimizing the weight of the TPS will thereby lower the percentage of the dry weight accounted for by the TPS. Also, this will lower the cost of the TPS and the overall cost of the vehicle.

Olds, John R.↗

Evaluation of Advanced Thermal Protection Techniques for Future Reusable Launch Vehicles

A method for integrating Aeroheating analysis into conceptual reusable launch vehicle RLV design is presented in this thesis. This process allows for faster turn-around time to converge a RLV design through the advent of designing an optimized thermal protection system (TPS). It consists of the coupling and automation of four computer software packages: MINIVER, TPSX, TCAT and ADS. MINIVER is an Aeroheating code that produces centerline radiation equilibrium temperatures, convective heating rates, and heat loads over simplified vehicle geometries. These include flat plates and swept cylinders that model wings and leading edges, respectively. TPSX is a NASA Ames material properties database that is available on the World Wide Web. The newly developed Thermal Calculation Analysis Tool (TCAT) uses finite difference methods to carry out a transient in-depth I-D conduction analysis over the center mold line of the vehicle. This is used along with the Automated Design Synthesis (ADS) code to correctly size the vehicle's thermal protection system JPS). The numerical optimizer ADS uses algorithms that solve constrained and unconstrained design problems. The resulting outputs for this process are TPS material types, unit thicknesses, and acreage percentages. TCAT was developed for several purposes. First, it provides a means to calculate the transient in-depth conduction seen by the surface of the TPS material that protects a vehicle during ascent and reentry. Along with the in-depth conduction, radiation from the surface of the material is calculated along with the temperatures at the backface and interior parts of the TPS material. Secondly, TCAT contributes added speed and automation to the overall design process. Another motivation in the development of TCAT is optimization.

Olds, John R.↗

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of HTML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, Piyush↗

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of XML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management ,facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, P.↗

Susceptibility to Welding Cracking, Welding Sensitivity, Susceptibility to Welding Seam Cracking, and Test Methods for These Failures

In the years after the First World war a very rapid development, which even today has by no means come to an end, took place in the field of welding; here also, as in most technical innovations, failures made their appearance. Thereupon comprehensive Investigations were undertaken by steel manufacturers and consumers with cooperation of the authorities. b most cases the reasons for failure could be determined and eliminated and further occurrences avoided by the use of new test methods.

Zeyen, K. L.↗

High speed optical object recognition processor with massive holographic memory

Real-time object recognition using a compact grayscale optical correlator will be introduced. A holographic memory module for storing a large bank of optimum correlation filters, to accommodate the large data throughput rate needed for many real-world applications, has also been developed. System architecture of the optical processor and the holographic memory will be presented. Application examples of this object recognition technology will also be demonstrated.

512 X 512 grayscale optical correlator holographic↗

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Knox, W. Bradley↗

A Low Risk Strategy for the Exploration of Near-Earth Objects

The impetus for asteroid exploration is scientific, political, and pragmatic. The notion of sending human explorers to asteroids is not new. Piloted missions to these primitive bodies were first discussed in the 1960s, pairing Saturn V rockets with enhanced Apollo spacecraft to explore what were then called "Earth-approaching asteroids." Two decades ago, NASA's Space Exploration Initiative (SEI) also briefly examined the possibility of visiting these small celestial bodies. Most recently, the U.S. Human Space Flight Review Committee (the second Augustine Commission) suggested that near-Earth objects (NEOs) represent a target-rich environment for exploration via the "Flexible Path" option. However, prior to seriously considering human missions to NEOs, it has become clear that we currently lack a robust catalog of human accessible targets. The majority of the NEOs identified by a study team across several NASA centers as "human-accessible" are probably too small and have orbits that are too uncertain to consider mounting piloted expeditions to these small worlds. The first step in developing such a catalog is, therefore, to complete a space-based NEO survey. The resulting catalog of candidate NEOs would then be transformed into a matrix of opportunities for robotic and human missions for the next several decades. This initial step of a space-based NEO survey first is the linchpin to laying the foundation of a low-risk architecture to venture out and explore these primitive bodies. We suggest such a minimalist framework architecture from 1) extensive ground-based and precursor spacecraft investigations (while applying operational knowledge from science-driven robotic missions), 2) astronaut servicing of spacecraft operating at geosynchronous Earth orbit to retain essential skills and experience, and 3) applying the sum of these skills, knowledge and experience to piloted missions to NEOs.

Landis, Rob R.↗

The Algorithm Theoretical Basis Document for the GLAS Atmospheric Data Products

The purpose of this document is to present a detailed description of the algorithm theoretical basis for each of the GLAS data products. This will be the final version of this document. The algorithms were initially designed and written based on the authors prior experience with high altitude lidar data on systems such as the Cloud and Aerosol Lidar System (CALS) and the Cloud Physics Lidar (CPL), both of which fly on the NASA ER-2 high altitude aircraft. These lidar systems have been employed in many field experiments around the world and algorithms have been developed to analyze these data for a number of atmospheric parameters. CALS data have been analyzed for cloud top height, thin cloud optical depth, cirrus cloud emittance (Spinhirne and Hart, 1990) and boundary layer depth (Palm and Spinhirne, 1987, 1998). The successor to CALS, the CPL, has also been extensively deployed in field missions since 2000 including the validation of GLAS and CALIPSO. The CALS and early CPL data sets also served as the basis for the construction of simulated GLAS data sets which were then used to develop and test the GLAS analysis algorithms.

Palm, Stephen P.↗

Probabilistic Prognosis of Non-Planar Fatigue Crack Growth

Quantifying the uncertainty in model parameters for the purpose of damage prognosis can be accomplished utilizing Bayesian inference and damage diagnosis data from sources such as non-destructive evaluation or structural health monitoring. The number of samples required to solve the Bayesian inverse problem through common sampling techniques (e.g., Markov chain Monte Carlo) renders high-fidelity finite element-based damage growth models unusable due to prohibitive computation times. However, these types of models are often the only option when attempting to model complex damage growth in real-world structures. Here, a recently developed high-fidelity crack growth model is used which, when compared to finite element-based modeling, has demonstrated reductions in computation times of three orders of magnitude through the use of surrogate models and machine learning. The model is flexible in that only the expensive computation of the crack driving forces is replaced by the surrogate models, leaving the remaining parameters accessible for uncertainty quantification. A probabilistic prognosis framework incorporating this model is developed and demonstrated for non-planar crack growth in a modified, edge-notched, aluminum tensile specimen. Predictions of remaining useful life are made over time for five updates of the damage diagnosis data, and prognostic metrics are utilized to evaluate the performance of the prognostic framework. Challenges specific to the probabilistic prognosis of non-planar fatigue crack growth are highlighted and discussed in the context of the experimental results.

Leser, Patrick E.↗

Lower Omo Food Security & Agriculture: Mapping Land Cover Change in Unprotected and Protected Areas in the Lower Omo River Valley, Ethiopia

Ethiopia is home to unique wildlife, biodiversity, and ecosystem services and, like much of the world, is undergoing population growth, development, and land use change. As a result, some biodiverse regions may be at risk of being urbanized, cultivated as agricultural plots, or losing access to water bodies that are essential for maintaining both terrestrial and aquatic life. The DEVELOP team partnered with the Ethiopian Wildlife Conservation Authority to quantify the land cover change between the years 1994, 2010, and 2018. The team utilized Ethiopia’s dry season (January to May) for training point development which was crucial in differentiating the level of greenness between the four land cover classes: water, natural vegetation, cultivated land, and bare ground. The study area covered 62,000 km2 of the Lower Omo River Valley and includes eight protected areas. Data from Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Shuttle Radar Topography Mission were used to employ a Random Forest classifier and identify the four classes within Google Earth Engine. For each of the supervised classifications, overall model accuracy was between 83% (2018) and 89% (1994). Between 1994 and 2018, the Lower Omo Valley experienced an overall increase of 258% (919 km2) in water and 291% (7,188 km2) in cultivated areas, while experiencing a 9% (2,761 km2) decrease in natural vegetation and 19% (5,346 km2) bare ground. There was an increase in water and cultivated land and a decrease in natural vegetation and bare ground in unprotected areas and all protected areas. However, protected areas maintained natural vegetation better than unprotected areas and only experienced a 1% (59 km2) loss compared to a 10% (2,701 km2) loss in unprotected areas.

Food Security & Agriculture↗

Lower Omo Food Security & Agriculture: Mapping Land Cover Change in Unprotected and Protected Areas in the Lower Omo River Valley, Ethiopia

Ethiopia is home to unique wildlife, biodiversity, and ecosystem services and, like much of the world, is undergoing population growth, development, and land use change. As a result, some biodiverse regions may be at risk of being urbanized, cultivated as agricultural plots, or losing access to water bodies that are essential for maintaining both terrestrial and aquatic life. The DEVELOP team partnered with the Ethiopian Wildlife Conservation Authority to quantify the land cover change between the years 1994, 2010, and 2018. The team utilized Ethiopia’s dry season (January to May) for training point development which was crucial in differentiating the level of greenness between the four land cover classes: water, natural vegetation, cultivated land, and bare ground. The study area covered 62,000 sq.km of the Lower Omo River Valley and includes eight protected areas. We used Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, and Shuttle Radar Topography Mission imagery within Google Earth Engine to employ a Random Forest Classifier and identify these four distinct classes. For each of our supervised classifications, overall model accuracy was between 83% (2018) and 89% (1994). Between 1994 and 2018, the Lower Omo Valley experienced an overall increase of 258.57% in water bodies and 291.23% in cultivated areas, while experiencing an 8.91% decrease in natural vegetation and 18.76% bare ground. There was an increase in water bodies and cultivated land and a decrease in natural vegetation and bare ground in unprotected areas and all protected areas. However, protected areas disproportionately experienced an increase in land cover change, including Tama Community Conservation Area which saw a 17,272.33% increase between 1994 and 2018.

Food Security & Agriculture↗

Customized Science Carrier Modules and Accessories Developed for Microgravity Simulation Devices

Because the access to the true weightless environment of the ISS and other Low Earth Orbit (LEO) vehicles is limited and cost prohibitive, the need for ground-based microgravity simulation analogs to bridge the gravity continuum gap between 1g gravity and costly space flight studies with true weightlessness was realized. As such, the Microgravity Simulation Support Facility (MSSF) was established at NASA John F. Kennedy Space Center (KSC) to fulfill the need of the scientific community. Our facility provides the US science community with a focal point in the field of gravitational research by granting access to an array of two-dimensional(2D) and three-dimensional (3D)clinostats, and Random Positioning Machine (RPM) platforms developed by teams throughout the world. The availability of these capabilities will allow further understanding the role of altered gravity vectors from “functional weightlessness”, partial gravity conditions (1 x 10-3to 0.9g, and Moon and Mars ‘g vectors), to hypergravity (up to3g) on biological processes. We have designed and 3D printed a variety of specialized attachments(and associated “static control” hardware)to allow researchers to mount their samples onto these microgravity simulation devices to meet their unique science requirements. A summary of each attachment module will be presented below. Note: All software or code information should be requested to the author Ye Zhang, Kennedy Space Center ye.zhang-1@nasa.gov

Ye Zhang↗

Alignment of Optical Backscatter Measurements from the EXPORTS Northeast Pacific Field Deployment

Backscattering of light is commonly measured by ocean observing systems, including ships and autonomous platforms, and is used as a proxy for the concentration of water column constituents such as phytoplankton and particulate carbon. Multiple on-going projects involve large numbers of independent measurements of backscatter, as well as other biologically relevant parameters, to understand how biology is changing in time and space throughout the global ocean. Rarely are there sufficient measurements to test how well these instruments are inter-calibrated in real-world deployment conditions. This paper develops a procedure to align multiple independently calibrated backscatter instruments to each other using nearby profiling casts and applies this method to nine instruments deployed during a recent field campaign in the North Pacific during August–September of 2018. This process revealed several incorrect calibrations; post-alignment, all nine instruments aligned extremely well with each other. We also tested an alignment to a deep-water reference and found that this method is generally sufficient but has significant limitations; this procedure lacks the ability to correct instruments measuring only shallow profiles and can only account for additive offsets, not multiplicative changes. These findings highlight the utility of process studies involving several independent measurements of similar parameters in the same area.

North Pacific↗

Global Energy and Water Exchanges Program Surface Radiation Budget Release 4 Integrated Product: Algorithm Theoretical Basis Document

This document represents the Algorithm Theoretical Basis Document (ATBD) describing the NASA Langley Research Center's Surface Radiation budget (SRB) developed in collaboration with the World Research Climate Programme's Global Energy and Water Exchanges Program. The top of atmosphere and surface fluxes span from July 1, 1983 through June 30, 2017. The shortwave or solar wavelengths span the entire record. The thermal infrared or longwave fluxes span globally from January 1, 1988 to December 30, 2009. Before 1988, only the land-only fluxes are available. After 2009 only the ocean fluxes are available. This document describes all the inputs and radiative transfer algorithms used to generate the TOA and surface radiative fluxes. The fluxes include upward and downward, all-sky, clear-sky and pristine sky conditions. Surface net fluxes and cloud radiative effect are computed and presented as part of the analysis. Comparisons to other data products are made to assess the top-of-atmosphere and surface fluxes. Additionally, surface measurements are utilized to validation the surface fluxes. The surface validation analysis shows the the radiative fluxes are improved compared to the previous version. Data set cautions are also presented.

surface radiation budget↗

The Road to Endurance: Outcomes From the Endurance Science Workshop

Endurance is a mission concept for a long-range, highly autonomous lunar rover (Fig. 1) designed to explore the farside of the Moon and the largest and oldest (undisputed) impact crater in the Solar System: South Pole–Aitken basin (SPA) (Fig. 2). Endurance would traverse nearly 2,000 kilometers, acquiring a large volume of in situ data, and a large mass of samples (up to 100 kg of material from 12 sites), before rendezvousing with Artemis astronauts at the south pole of the Moon. The Endurance concept was developed during the recent Origins, Worlds, and Life Planetary Science and Astrobiology Decadal Survey [1–2], which recommended Endurance as the highest priority new strategic mission for NASA’s Lunar Discovery and Exploration Program. Since the release of the Decadal Survey in 2022, NASA has been further studying this concept, and investigating the range of implementation options [3–5].

J. T. Keane↗

Crowd-Sourced Technology Challenge for Improving Visual Color Detection of Hydrazine and Monomethylhydrazine Vapors in Spacecraft Environments

NASA currently uses a visual colorimetric detection method for potential hydrazine, monomethylhydrazine (MMH), or unsymmetrical dimethylhydrazine (UDMH) contamination in the International Space Station. Astronauts exposed to propellants or their residues during extravehicular activities may transfer contaminants into the airlock. The colorimetric detection method employs the Contamination Detection Kit (CDK), which uses a potassium tetrachloroaurate redox reaction with the propellant hydrazine vapors and a color comparison card to determine airborne concentrations. Seeking ideas for improvement, the NASA Tournament Lab (NTL) crowdsourced a way to tackle the challenge of detecting hydrazine and MMH vapors using colorimetric detection methods. This Rid the Rocket competition drew over 200 participants and 20 submissions from around the world proposing innovative ways to develop a new chemical colorimetric detection method for hydrazine and MMH vapors on spacecraft. Using a phased approach to evaluate contestants, NASA eventually narrowed the field to five finalists from the United States, Romania, Taiwan, and India. Concept papers and hardware submissions were judged on feasibility, creativity, and ability to detect hydrazine and MMH vapors before being sent to the NASA White Sands Test Facility for laboratory evaluation. Finalists employed variations of sampling methods and color-detection chemistry using a variety of sampling pumps and indicator pads or solutions—including those employing potassium or hydrogen tetrachloroaurate, para -dimethylaminobenzaldehyde (PDAB), and modifiers including sodium metasilicate and cetyltrimethylammonium bromide—to enhance gold nanoparticle formation and surface plasmon resonance (SPR) resulting in visual blue to purple color development. This paper presents a summary of the crowdsourced submissions and results of laboratory testing.

Crowd-Sourced↗