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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

The Influence of Microbiology on Spacecraft Design and Controls: A Historical Perspective of the Shuttle and International Space Station Programs

For over 40 years, NASA has been putting humans safely into space in part by minimizing microbial risks to crew members. Success of the program to minimize such risks has resulted from a combination of engineering and design controls as well as active monitoring of the crew, food, water, hardware, and spacecraft interior. The evolution of engineering and design controls is exemplified by the implementation of HEPA filters for air treatment, antimicrobial surface materials, and the disinfection regimen currently used on board the International Space Station. Data from spaceflight missions confirm the effectiveness of current measures; however, fluctuations in microbial concentrations and trends in contamination events suggest the need for continued diligence in monitoring and evaluation as well as further improvements in engineering systems. The knowledge of microbial controls and monitoring from assessments of past missions will be critical in driving the design of future spacecraft.

Castro, Victoria A.↗
NASA NTRS1995

Automated Consultation for the Diagnosis of Interplanetary Telecommunications

SHARP (Spacecraft Health Automated Reasoning Program) is a knowledge-based system for the diagnosis of problems in NASA's Deep Space Network (DSN) telecommunications system. This system provides the means of communication between a spacecraft and operations personnel at Jet Propulsion Laboratory. SHARP analyzes problems that occur in both the on-board spacecraft telecom subsystem, and the DSN.

SHARP spacecraft health automated reasoning progra↗
NASA NTRS1979

Infrared Heaters

The heating units shown in the accompanying photos are Panelbloc infrared heaters, energy savers which burn little fuel in relation to their effective heat output. Produced by Bettcher Manufacturing Corporation, Cleveland, Ohio, Panelblocs are applicable to industrial or other facilities which have ceilings more than 12 feet high, such as those pictured: at left the Bare Hills Tennis Club, Baltimore, Maryland and at right, CVA Lincoln- Mercury, Gaithersburg, Maryland. The heaters are mounted high above the floor and they radiate infrared energy downward. Panelblocs do not waste energy by warming the surrounding air. Instead, they beam invisible heat rays directly to objects which absorb the radiation- people, floors, machinery and other plant equipment. All these objects in turn re-radiate the energy to the air. A key element in the Panelbloc design is a coating applied to the aluminized steel outer surface of the heater. This coating must be corrosion resistant at high temperatures and it must have high "emissivity"-the ability of a surface to emit radiant energy. The Bettcher company formerly used a porcelain coating, but it caused a production problem. Bettcher did not have the capability to apply the material in its own plant, so the heaters had to be shipped out of state for porcelainizing, which entailed extra cost. Bettcher sought a coating which could meet the specifications yet be applied in its own facilities. The company asked The Knowledge Availability Systems Center, Pittsburgh, Pennsylvania, a NASA Industrial Applications Center (IAC), for a search of NASA's files

Source record↗
NASA NTRS2005

Learning for Autonomous Navigation

Robotic ground vehicles for outdoor applications have achieved some remarkable successes, notably in autonomous highway following (Dickmanns, 1987), planetary exploration (1), and off-road navigation on Earth (1). Nevertheless, major challenges remain to enable reliable, high-speed, autonomous navigation in a wide variety of complex, off-road terrain. 3-D perception of terrain geometry with imaging range sensors is the mainstay of off-road driving systems. However, the stopping distance at high speed exceeds the effective lookahead distance of existing range sensors. Prospects for extending the range of 3-D sensors is strongly limited by sensor physics, eye safety of lasers, and related issues. Range sensor limitations also allow vehicles to enter large cul-de-sacs even at low speed, leading to long detours. Moreover, sensing only terrain geometry fails to reveal mechanical properties of terrain that are critical to assessing its traversability, such as potential for slippage, sinkage, and the degree of compliance of potential obstacles. Rovers in the Mars Exploration Rover (MER) mission have got stuck in sand dunes and experienced significant downhill slippage in the vicinity of large rock hazards. Earth-based off-road robots today have very limited ability to discriminate traversable vegetation from non-traversable vegetation or rough ground. It is impossible today to preprogram a system with knowledge of these properties for all types of terrain and weather conditions that might be encountered.

mixture of Gaussians↗
NASA NTRS2014

System Engineering of Autonomous Space Vehicles

Human exploration of the solar system requires fully autonomous systems when travelling more than 5 light minutes from Earth. This autonomy is necessary to manage a large, complex spacecraft with limited crew members and skills available. The communication latency requires the vehicle to deal with events with only limited crew interaction in most cases. The engineering of these systems requires an extensive knowledge of the spacecraft systems, information theory, and autonomous algorithm characteristics. The characteristics of the spacecraft systems must be matched with the autonomous algorithm characteristics to reliably monitor and control the system. This presents a large system engineering problem. Recent work on product-focused, elegant system engineering will be applied to this application, looking at the full autonomy stack, the matching of autonomous systems to spacecraft systems, and the integration of different types of algorithms. Each of these areas will be outlined and a general approach defined for system engineering to provide the optimal solution to the given application context.

Watson, Michael D.↗
NASA NTRS2016

A Process for Capturing the Art of Systems Engineering

There is both an art and a science to systems engineering. The science of systems engineering is effectively captured in processes and procedures, but the art is much more elusive. We propose that there is six step process that can be applied to any systems engineering organization to create an environment from which the "art" of that organization can be captured, be allowed to evolve collaboratively and be shared with all members of the organization. This paper details this process as it was applied to NASA Launch Services Program (LSP) Integration Engineering Branch during a pilot program of Confluence, a Commercial Off The Shelf (COTS) wiki tool.

Commercial Off The Shelf↗
NASA NTRS2017

Embracing Open Source for NASA's Earth Science Data Systems

The overarching purpose of NASAs Earth Science program is to develop a scientific understanding of Earth as a system. Scientific knowledge is most robust and actionable when resulting from transparent, traceable, and reproducible methods. Reproducibility includes open access to the data as well as the software used to arrive at results. Additionally, software that is custom-developed for NASA should be open to the greatest degree possible, to enable re-use across Federal agencies, reduce overall costs to the government, remove barriers to innovation, and promote consistency through the use of uniform standards. Finally, Open Source Software (OSS) practices facilitate collaboration between agencies and the private sector. To best meet these ends, NASAs Earth Science Division promotes the full and open sharing of not only all data, metadata, products, information, documentation, models, images, and research results but also the source code used to generate, manipulate and analyze them. This talk focuses on the challenges to open sourcing NASA developed software within ESD and the growing pains associated with establishing policies running the gamut of tracking issues, properly documenting build processes, engaging the open source community, maintaining internal compliance, and accepting contributions from external sources. This talk also covers the adoption of existing open source technologies and standards to enhance our custom solutions and our contributions back to the community. Finally, we will be introducing the most recent OSS contributions from NASA Earth Science program and promoting these projects for wider community review and adoption.

Earth Science↗
NASA NTRS2017

NASA's GeneLab Phase II: Federated Search and Data Discovery

GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

exobiology↗
NASA NTRS2017

NASAs GeneLab Phase II: Federated Search and Data Discovery

GeneLab is currently being developed by NASA to accelerate open science biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics (omics) data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

genome↗
NASA NTRS2018

GeneLab Analysis Working Group Kick-Off Meeting

Goals to achieve for GeneLab AWG - GL vision - Review of GeneLab AWG charter Timeline and milestones for 2018 Logistics - Monthly Meeting - Workshop - Internship - ASGSR Introduction of team leads and goals of each group Introduction of all members Q/A Three-tier Client Strategy to Democratize Data Physiological changes, pathway enrichment, differential expression, normalization, processing metadata, reproducibility, Data federation/integration with heterogeneous bioinformatics external databases The GLDS currently serves over 100 omics investigations to the biomedical community via open access. In order to expand the scope of metadata record searches via the GLDS, we designed a metadata warehouse that collects and updates metadata records from external systems housing similar data. To demonstrate the capabilities of federated search and retrieval of these data, we imported metadata records from three open-access data systems into the GLDS metadata warehouse: NCBI's Gene Expression Omnibus (GEO), EBI's PRoteomics IDEntifications (PRIDE) repository, and the Metagenomics Analysis server (MG-RAST). Each of these systems defines metadata for omics data sets differently. One solution to bridge such differences is to employ a common object model (COM) to which each systems' representation of metadata can be mapped. Warehoused metadata records are then transformed at ETL to this single, common representation. Queries generated via the GLDS are then executed against the warehouse, and matching records are shown in the COM representation (Fig. 1). While this approach is relatively straightforward to implement, the volume of the data in the omics domain presents challenges in dealing with latency and currency of records. Furthermore, the lack of a coordinated has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

GeneLab↗
NASA NTRS2018

FAIRness and Usability for Open-Access Omics Data Systems

Omics data sharing is especially crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. 14 metrics. The range of Pass ratings was 29-79% of the 14 metrics, Partial Pass 0-21%, and Fail 7-50%. The range of overall FAIRness scores was 5-12 (out of 14). The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. We propose two new principles that Big Data systems, in particular, should consider for increasing data accessibility. We relate our experiences implementing semantic integration of omics data from several systems for the federated querying and retrieval functions of the GLDS, given the shortcomings in data interoperability of these systems.

Berrios, Daniel C.↗
NASA NTRS2018

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the "FAIRness" of NASA's GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗
NASA NTRS2019

Short Course on Lithium-Ion Batteries: Fundamental Concepts, Battery Safety, and Modeling Techniques

When developing this course several years back I asked myself, "What do I think the TFAWS community needs to know about lithium-ion batteries and why should they care?" I think the answers to these questions can be boiled down to the following statements: 1. Lithium-ion (Li-ion) battery electrical performance and efficiency are heavily driven by thermal conditions. 2. Li-ion battery assemblies can experience single cell thermal runaway events which can lead to cell-to-cell propagation; these are thermally driven failure events that can be controlled with effective thermal management systems. 3. Knowledge of BOTH Li-ion battery fundamentals AND traditional thermal design principles are required to develop safe battery assemblies that are both gravimetrically and volumetrically optimized.This year the Short Course on Lithium-ion Batteries will be presented in a 2-part series. The first portion, "Fundamentals, Battery Safety, and Thermal Runaway," will focus on educating participants on the fundamental aspects of Li-ion batteries and on battery safety related topics (i.e. thermal runaway, cell-to-cell propagation, safe handling practices, et...). The second portion, "Practical Thermal Simulation Techniques," will provide participants with a real time demonstration of how to use Thermal Desktop to model of Li-ion battery assemblies. This part of the lesson will cover geometry simplification, mesh development, boundary conditions, and heat loads for both nominal operations (charge and discharge) and for thermal runaway events.

Walker, William↗
NASA NTRS2018

FAIRness and Usability for Open-access Omics Data Systems

Omics data sharing is crucial to the biological research community, and the last decade or two has seen a huge rise in collaborative analysis systems, databases, and knowledge bases for omics and other systems biology data. We assessed the “FAIRness” of NASA’s GeneLab Data Systems (GLDS) along with four similar kinds of systems in the research omics data domain, using 14 FAIRness metrics. The range of overall FAIRness scores was 6-12 (out of 14), average 10.1, and standard deviation 2.4. The range of Pass ratings for the metrics was 29-79%, Partial Pass 0-21%, and Fail 7-50%. The systems we evaluated performed the best in the areas of data findability and accessibility, and worst in the area of data interoperability. Reusability of metadata, in particular, was frequently not well supported. We relate our experiences implementing semantic integration of omics data from some of the assessed systems for federated querying and retrieval functions, given their shortcomings in data interoperability. Finally, we propose two new principles that Big Data system developers, in particular, should consider for maximizing data accessibility.

Berrios, Daniel C.↗
NASA NTRS2020

Systems Development, Data Mining, and Knowledge Discovery

I worked as a NASA OSTEM virtually during the Fall 2020 term. Working in the IT division under my mentor Dr. Ali Shaykhian, our overall goal for the duration of this internship is to get a better understanding of the Visual Basic Language and how it can be used to make forms and collaboration with other workers to be more dynamics. I also worked with 3 other interns throughout this internship, using Microsoft Office to help each other to get a better understanding of how we approached our projects individually. Every week, my mentor Dr. Ali assigned me a task and a goal to finish by the end of each week. My overall project was figuring out a way to make email submissions and emails in general more dynamic for the NASA database. For example, instead of only using the same generic email for hundreds of different workers, a code can be used to send an individual email with more personalization such as each recipient’s name and personal info. I have also been assigned to create an email graphical user interface by the end of this internship. For these tasks to be made possible, I had to learn more about the capabilities of Microsoft Office, such as Macros in Microsoft Excel and Visual Basic in both Microsoft Excel and Word. Although it was challenging at first, I developed new programming skilled in a new language and actually made it possible to create this code along the way. Alongside doing the individual assignments, Dr. Ali also assigned up to replicate other intern’s work to get a better understanding of their approach and learn how to do it ourselves.

Janelisse Morales Gonzalez↗
NASA NTRS2021

Validation of Small Satellite Dynamics Simulation Modules using ASTERIA Flight Data

ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) was a CubeSat space telescope that operated in low-Earth orbit, having been deployed from the International Space Station in 2017. The spacecraft has achieved sub-arcsecond pointing stability and millikelvin thermal stability over 20-minute observations. A key enabling feature of the ASTERIA mission is the low level of pointing error that has been demonstrated under ASTERIA’s fine pointing control mode. Prior to launch, the ASTERIA mission performed analysis and simulations to estimate the in-flight pointing performance. This analysis used reaction wheel models provided by JPL’s Small Satellite Dynamics Testbed (SSDT), which had performed Kistler table testing to characterize the jitter caused by the reaction wheels of the Blue Canyon Technologies XACT attitude control unit within ASTERIA. These models were subsequently incorporated into the SSDT simulation. The main source of jitter, the high-frequency attitude disturbance over the camera exposure time, on ASTERIA is the set of rotating reaction wheels that are used for maintaining fine pointing during observations. The reaction wheels impart disturbance forces and torques continuously that cause unwanted motion during imaging. Increased jitter consequently leads to blurring of the image. Therefore, to benefit all SmallSat missions devoted to photometric or spectroscopic astrophysics applications, an on-orbit flight data acquisition and jitter testing campaign was performed in an attempt to help validate the SSDT’s simulation models. This paper describes the process used to validate several simulation models and attempt to characterize the ASTERIA jitter by analyzing the size of the resulting spot size for the target stars as a function of wheel speed, having commanded four wheel speeds for each of three stars of known brightness. After summarizing the on-orbit observation and jitter level measurement process, this paper compares the results obtained from the flight operational environment to the corresponding set of simulation jitter levels. Though the flight data obtained during this experiment was not sufficient to validate the simulation’s jitter model, other models have been validated with flight data, including the magnetic field, orbit propagation, sun position, and long-duration orbit decay models, which may be used by all other projects that use the SSDT’s simulation to increase system capability knowledge.

Mohan, Swati↗
NASA NTRSDate not supplied

Dual Fiber Spectrometer for Highly Non-Degenerate Entanglement Source

NASA is developing quantum metrology capabilities for potential space-based quantum components in future navigation and communications systems. Innate knowledge of component operation is key for the space qualification of these components. This paper focuses on the measurement and analysis of an important characteristic of an entanglement source, the joint spectrum. We describe a spectrometer based on dispersive optical fibers and present experimental measurements of the joint spectrum of a highly non-degenerate SPDC-based entanglement source that emits entangled photons in the near-infrared and telecommunications bands. How the analysis of such a joint spectrum could be applied to the modeling and simulation of entanglement swapping operations as possible extensions of quantum networks is examined. Lastly, we discuss how the separability of the two-photon state is quantified via Schmidt decomposition and how the degree of separability impacts the spectral purity of heralded single-photon emissions.

SPDC↗