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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 NTRS2002

A Grid Infrastructure for Supporting Space-based Science Operations

Emerging technologies for computational grid infrastructures have the potential for revolutionizing the way computers are used in all aspects of our lives. Computational grids are currently being implemented to provide a large-scale, dynamic, and secure research and engineering environments based on standards and next-generation reusable software, enabling greater science and engineering productivity through shared resources and distributed computing for less cost than traditional architectures. Combined with the emerging technologies of high-performance networks, grids provide researchers, scientists and engineers the first real opportunity for an effective distributed collaborative environment with access to resources such as computational and storage systems, instruments, and software tools and services for the most computationally challenging applications.

Bradford, Robert N.↗

NASA NTRS1991

Project UM-HAUL: A self-unloading reusable lunar lander

The establishment of a lunar base is technologically and financially challenging. Given the necessary resources and political support, it can be done. In addition to the geopolitical obstacles, however, there are logistical problems involved in establishing such bases that can only be overcome with the acquisition of a significant transportation and communications network in the Earth-Moon spatial region. Considering the significant number of payloads that will be required in this process, the mass-specific cost of launching these payloads, and the added risk and cost of human presence in space, it is clearly desirable to automate major parts of such an operation. One very costly and time-consuming factor in this picture is the delivery of payloads to the Moon. Foreseeable payloads would include atmospheric modules, inflatable habitat kits, energy and oxygen plant elements, ground vehicles, laboratory modules, crew supplies, etc. The duration of high-risk human presence on the Moon could be greatly reduced if all such payloads were delivered to the prospective base site in advance of crew arrival. In this view, the idea of a 'Self-Unloading Reusable Lunar Lander' (SURLL) arises naturally. The general scenario depicts the lander being brought to low lunar orbit (LLO) from Earth atop a generic Orbital Transfer Vehicle (OTV). From LLO, the lander shuttles payloads down to the lunar surface, where, by means of some resident, detachable unloading device, it deploys the payloads and returns to orbit. The general goal is for the system to perform with maximum payload capability, automation, and reliability, while also minimizing environmental hazards, servicing needs, and mission costs. Our response to this demand is UM-HAUL, or the UnManned Heavy pAyload Unloader and Lander. The complete study includes a system description, along with a preliminary cost analysis and a design status assessment.

Source record↗

NASA NTRS2002

Orbital Aggregation and Space Infrastructure Systems (OASIS)

This paper summarizes the results of a NASA lead study performed to identify synergistic opportunities and concepts between human exploration initiatives and commercialization of space. The goal of this initiative, called Orbital Aggregation & Space Infrastructure Systems (OASIS), is to develop an in-space architecture and associated concepts that provide common infrastructure for enabling a large class of space missions. The concepts include communications, navigation and power systems, propellant modules, tank farms, habitats, and in-space transportation systems using several propulsion technologies. OASIS features in-space aggregation of systems and resources in support of mission objectives. The concepts feature a high level of reusability and are supported by inexpensive launch of propellant and logistics payloads from the Earth/moon system. Industry, NASA and other users could share infrastructure costs. The anticipated benefits of synergistic utilization of space infrastructure are reduced mission costs and increased mission flexibility for future space exploration and commercialization initiatives.

Troutman, Patrick A.↗

NASA NTRS2003

Technology for a NASA Space-Based Science Operations Grid

This viewgraph representation presents an overview of a proposal to develop a space-based operations grid in support of space-based science experiments. The development of such a grid would provide a dynamic, secure and scalable architecture based on standards and next-generation reusable software and would enable greater science collaboration and productivity through the use of shared resources and distributed computing. The authors propose developing this concept for use on payload experiments carried aboard the International Space Station. Topics covered include: grid definitions, portals, grid development and coordination, grid technology and potential uses of such a grid.

Bradford, Robert N.↗

NASA NTRS2008

Transformation of OODT CAS to Perform Larger Tasks

A computer program denoted OODT CAS has been transformed to enable performance of larger tasks that involve greatly increased data volumes and increasingly intensive processing of data on heterogeneous, geographically dispersed computers. Prior to the transformation, OODT CAS (also alternatively denoted, simply, 'CAS') [wherein 'OODT' signifies 'Object-Oriented Data Technology' and 'CAS' signifies 'Catalog and Archive Service'] was a proven software component used to manage scientific data from spaceflight missions. In the transformation, CAS was split into two separate components representing its canonical capabilities: file management and workflow management. In addition, CAS was augmented by addition of a resource-management component. This third component enables CAS to manage heterogeneous computing by use of diverse resources, including high-performance clusters of computers, commodity computing hardware, and grid computing infrastructures. CAS is now more easily maintainable, evolvable, and reusable. These components can be used separately or, taking advantage of synergies, can be used together. Other elements of the transformation included addition of a separate Web presentation layer that supports distribution of data products via Really Simple Syndication (RSS) feeds, and provision for full Resource Description Framework (RDF) exports of metadata.

Mattmann, Chris↗

NASA NTRS2017

Mars Molniya Orbit Atmospheric Resource Mining

This NASA Innovative Advanced Concepts (NIAC) Phase I study examined the revolutionary concept of performing resource collection and utilization during Mars orbital operations in order to enable the landing of large payloads. An exploration architecture was developed, out of which several mission alternatives were developed. Concepts of operations were then developed for each mission alternative, followed by concepts for spacecraft systems, which were traded to assess their feasibility. A novel architecture using Mars Molniya Orbit Atmospheric Resource Mining is feasible to enable an Earth-independent and pioneering, permanent human presence on Mars by providing a reusable, single-stage-to-orbit transportation system. This will allow cargo and crew to be routinely delivered to and from Mars without transporting propellants from Earth.In Phase I, our study explored how electrical energy could be harnessed from the kinetic energy of the incoming spacecraft and then be used to produce the oxygen necessary for landing. This concept of operations is revolutionary in that its focus is on using in situ resources in complementary and varied forms: the upper atmosphere of Mars is used for aerocapture, which is followed by aerobraking, the kinetic energy of the spacecraft is transformed into usable electrical energy during aerobraking, and the atmospheric composition is the source of oxidizer for a landing under supersonic retropropulsion. This NASA Innovative Advanced Concepts (NIAC) Phase I study explores a novel mission architecture to establish routine, Earth-independent transfer of large mass payloads between Earth and the Mars surface and back to Mars orbit. The first stage of routine mission operations involves an atmospheric resource mining aerobraking campaign following aerocapture into a highly elliptical Mars orbit. During each pass through the atmosphere, the vehicle ingests the atmospheric oxidizer and stores it onboard, using solid oxide electrolysis to convert the primarily CO2 atmosphere into usable O2 for propellant. Power is made available through the use of magnetohydrodynamic energy generation, which converts the motion of the plasma in the shock later into usable electrical energy. Upon termination of the aerobraking sequence, the descent vehicle detaches from the orbit stack, deorbits, and executes the entry, descent, and landing sequence. Hypersonic deceleration is achieved via a deployable heat shield to lower the vehicle ballistic coefficient, and supersonic and subsonic deceleration are achieved via retropropulsion. Mars surface operations involve resource mining of the Martian regolith to produce CH4 and O2 propellant to be used for the subsequent MDAV ascent back to high Mars orbit (HMO) providing an apoapsis raise maneuver to initialize the aerobraking sequence, in addition to providing fuel from the Mars surface for EDL propulsive descent. The Resource Collector Vehicle (RCV), which is used for the orbital mining operations, is raised back to HMO via onboard deployable augmented solar electric propulsion. Concepts of operations were developed for each mission alternative, to evaluate between them and assess feasibility.

Mining↗

NASA NTRS1971

Spaceborne computer executive routine functional design specification. Volume 1: Functional design of a flight computer executive program for the reusable shuttle

A flight computer functional executive design for the reusable shuttle is presented. The design is given in the form of functional flowcharts and prose description. Techniques utilized in the regulation of process flow to accomplish activation, resource allocation, suspension, termination, and error masking based on process primitives are considered. Preliminary estimates of main storage utilization by the Executive are furnished. Conclusions and recommendations for timely, effective software-hardware integration in the reusable shuttle avionics system are proposed.

Curran, R. T.↗

NASA NTRS2022

Data Needs to be…

Findable, Accessible, Interoperable, and Reusable (FAIR) data are essential to heliophysics, indeed all scientific research. We make recommendations intended to prioritize resources needed to satisfy FAIR data principles, treating them as a fundamental research infrastructure, rather than a simple research product.

A Halford↗

NASA NTRSDate not supplied

RadLab and the Environmental Data Application Dashboard: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Ionizing radiation in particular has been established in ground-based experiments as being correlated with increased risk of carcinogenesis and cardiovascular and neurological effects. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (osdr.nasa.gov) has developed two Web applications: the Environmental Data Application (EDA) and a radiation-specific RadLab. Each consists of an API (application programming interface) and an associated GUI (graphical user interface) that provide single points of access to the data. To date, OSDR has focused on the sensors from payloads and radiation detectors located on the ISS. The Web applications process telemetry information and associated data, such as spacecraft location and orientation, from multiple international databases. The applications’ request syntax enables users to interrogate these data by craft, sensor type, time range, radiation type (galactic cosmic rays, solar particle events, the contribution of the South Atlantic Anomaly), facilitating arbitrary comparisons of original source data at varying time resolutions. The applications provide programmatic access for use in computational pipelines and GUIs for data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

radiation↗

NASA NTRSDate not supplied

RadLab: Graphical and Programming Interfaces for Interrogation of Space Telemetry Data

Sensors on multiple spacecraft in and beyond low Earth orbit continuously monitor and collect space radiation data and transmit it back to Earth. These data are of vast importance to space biology research, as ionizing radiation affects living organisms—astronauts and non-human experiment subjects alike—placing them at higher risk of carcinogenesis, degenerative diseases, and radiation sickness. Therefore, knowledge of the biological effects of space radiation is essential for planning future crewed missions beyond low Earth orbit. The RadLab project, initiated by GeneLab and ALSDA (the Open Science Data Repository; OSDR) and sponsored by the NASA Human Research Program, is a new effort aimed at connecting dosimetry data from radiation detectors located on the International Space Station (ISS), as well as other spacecraft. To date, access to these data has been fragmented across space agencies and databases; to address this issue, we have developed an application programming interface (API) and an associated graphical user interface (GUI) designed to provide a single point of access to the data. As of now, OSDR has focused on the detectors located on the ISS, with the long-term goal to establish a self-sustained portal receiving continuous updates through APIs connecting to multiple radiation databases of varying scope, as well as individual investigator contributions. The RadLab API implements a request syntax enabling users to query data by craft, sensor type, timespan, etc, allowing for arbitrary combinations of original source data, thus providing programmatic access for use in computational pipelines, while the GUI facilitates data visualization and exploration, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

radiation↗

NASA NTRSDate not supplied

The Environmental Data Application for Analysis of Space Telemetry Data

Sensors on the International Space Station (ISS) and multiple spacecraft elsewhere in Earth orbit and in deep space continuously monitor and collect environmental data, transmitting this information back to Earth. These data include ionizing radiation and, on the ISS and spacecrafts, CO2, relative humidity levels, and temperature, and are of great importance to space biology research. Looking ahead to future long duration crewed missions beyond low Earth orbit, the ability to study how factors including CO2 levels, light cycle, temperature modulate the response to ionizing radiation and microgravity is essential. To date, access to these data has been fragmented across space agencies, spacecraft, and databases. To address this issue, NASA’s Open Science Data Repository (OSDR) has developed a user interface for interrogation of telemetry data: the Environmental Data Application (EDA). The EDA provides the capability to visualize telemetry and radiation data collected on the International Space Station and corresponding ground platforms during the Rodent Research missions. Telemetry data includes temperature, relative humidity, and CO2 levels. Radiation data includes galactic cosmic rays, the contribution of the South Atlantic Anomaly, total radiation dose rate, and accumulated radiation dose. The application allows users to view single missions, compare multiple missions, and view and download summary or full data tables. In summary, the EDA provides GUIs for data visualization and exploration, as well as means for data export, making these data FAIR (Findable, Accessible, Interoperable, and Reusable), complementing the biological data contained in OSDR, and providing the space science community with a valuable resource for scientific analyses.

telemetry↗

NASA NTRS2017

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗

NASA NTRS2006

Room to Live: the sizing of Lunar and Martian Habitats

In order for man to return to space or extra terrestrial bodies for long duration missions it is important that adequate habitat volume be defined early to avoid costly delays and redesign. To properly define a habitat volume two major factors need to be considered. The first factor is the free or open space. This is the space that allows the crew room to move about the habitat. This space will vary based on crew size and length of the mission. The second major factor is the stowage space required for equipment and supplies. This includes both fixed volumes and consumables. Fixed volumes include items such as tools, communication equipment, Advanced Life Support (ALS) equipment, and support equipment. Consumables include items like filters, food, water and oxygen. This space is also dependent on crew size and mission length. A review of past missions into alien environments, such as deep sea habitats as well as space based habitats will be used to validate the assumption made in this paper. Once these key factors are defined trades must be run to optimize the overall volume of a habitat. This includes trades of disposable vs. reusable for items such as clothing, dishes, and water. Another factor to consider is the availability of in situ resources to aid in the construction of the habitat structure as well as re-supply of consumable items. A review of past missions into alien environments, such as deep sea habitats as well as space based habitats will be used to validate the assumption made in this paper. The result is a habitat sizing tool to provide a first order estimate of habitat volumes for extended mission to the surface of the moon and Mars.

McGregor, Walter L.↗

NASA NTRSDate not supplied

MEDPRAT Treatment Clusters: Improving Representation of Mission Medical Risk

INTRODUCTION The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) implements a computational model that aims to quantify spaceflight medical risk by utilizing probabilistic techniques to simulate critical event incidence and outcomes over thousands of simulated mission trials. The goal of MEDPRAT is to characterize mission medical risk and provide insight into medical resource utilization. In order to analyze the medical resource space, treatment must be mapped from each simulated condition, and resources consumed as a result of this treatment must be tracked throughout the course of the mission. A new MEDPRAT feature, ‘treatment clusters’, provide a more sophisticated method of defining the structure and interaction between resources, more closely mimicking the way treatment is carried out clinically. METHODS Treatment clusters expand on the two existing treatment groupings (combination and alternate) adding a new grouping: bundled treatment. Treatment clusters may be combined to any depth, giving users the ability to specify complex treatment trees whose behavior is governed by several user-specified parameters. This approach emphasizes reusability, as treatment clusters, once defined, can be used to create more complex treatment trees or applied to many conditions. By configuring parameters for contribution, efficacy, necessity, primacy, and equivalence, resource relationships and dependencies can be more accurately represented, thereby allowing users to build capabilities with desired treatment properties, for example an intravenous capability for conditions such as anaphylaxis, acute radiation syndrome, etc. MEDPRAT v1.0 remains backward compatible with existing treatment structures, giving users the ability to define new treatment clusters as evidence becomes available, without having to recode their existing treatment databases. In addition to facilitating the representation of more complex treatment options, by pairing treatment clusters with the internal optimization routine, the MEDPRAT set selector, medical resources can be identified as organized in bundles, where appropriate, so that optimized resource sets include groups of highly-dependent resources only when all resources of the group are together. For example, it would be wasteful to include ultrasound gel but not an ultrasound machine, since the gel provides no benefit as a treatment without the ultrasound machine. With treatment clusters, the user may require that both resources are available to provide any benefit as treatment, so that if one resource is optimized out of the set, the other resource will be optimized out as well. RESULTS AND CONCLUSIONS We will report on MEDPRAT treatment clusters used in a bundling study under the IMPACT project of the ExMC element. We will discuss an example of a complex treatment tree. Through the implementation of this feature MEDPRAT enables treatment to be defined and applied in a way that is more representative of the real world, providing more accurate insight into mission medical risk and the medical resource space.

Lawrence Leinweber↗

NASA NTRS2017

Implementation of a Space Communications Cognitive Engine

Although communications-based cognitive engines have been proposed, very few have been implemented in a full system, especially in a space communications system. In this paper, we detail the implementation of a multi-objective reinforcement-learning algorithm and deep artificial neural networks for the use as a radio-resource-allocation controller. The modular software architecture presented encourages re-use and easy modification for trying different algorithms. Various trade studies involved with the system implementation and integration are discussed. These include the choice of software libraries that provide platform flexibility and promote reusability, choices regarding the deployment of this cognitive engine within a system architecture using the DVB-S2 standard and commercial hardware, and constraints placed on the cognitive engine caused by real-world radio constraints. The implemented radio-resource allocation-management controller was then integrated with the larger spaceground system developed by NASA Glenn Research Center (GRC).

reinforcement learning↗

NASA NTRS2017

Implementation of a Space Communications Cognitive Engine

reinforcement learning↗

NASA NTRS2003

CLARAty Functional-Layer Software

Functional-layer software for the Coupled Layer Architecture for Robotics Autonomy (CLARAty) is being developed. [CLARAty was described in Coupled-Layer Architecture for Advanced Software for Robots (NPO-21218), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48. To recapitulate: CLARAty was proposed to improve the modularity of robotic software while tightening the coupling between planning/execution and control subsystems. Whereas prior robotic software architectures have typically contained three levels, the CLARAty architecture contains two layers: a decision layer and a functional layer.] Just as an operating system provides abstraction from computational hardware, the CLARAty functional-layer software provides for abstraction for the different robotic systems. The functional-layer software establishes interrelated, object-oriented hierarchies that contain active and passive objects that represent the different levels of system abstrations and components. The functional-layer software is decomposed into a set of reusable core components and a set of extended components that adapt the reusable set to specific hardware implementations. The reusable components (a) provide behavior and interface definitions and implementations of basic functionality, (b) provide local executive capabilities, (c) manage local resources, and (d) support state and resource queries by the decision layer. Software for robotic systems can be built by use of these components.

Nesnas, Issa↗

NASA NTRS2001

Progress and Status of the 2nd Generation Reusable Launch Vehicle Program

Safe, low-cost space transportation is the key enabler of the commercial development and civil exploration of space. Human space flight remains a hazardous endeavor in spite of advances in aerospace technology. NASA intends to reduce the resources devoted to routine space operations, thus enabling additional science research, technology development, and exploration activities. NASA developed the Integrated Space Transportation Plan (ISTP) to address the needs for space access. ISTP is a balanced and comprehensive plan that embodies strategies for achieving goals for earth-to-orbit and in-space transportation operations. ISTP calls for near-term safety related upgrades to the Space Shuttle, development of a Crew Return Vehicle, a new Space Launch Initiative (SLI), and development of an Aero-Space Base to provide foundation technology for future space systems. NASA formed the SLI to coordinate the development of the 2nd Generation Reusable Launch Vehicle (RLV) architecture, The SLI is implemented by the 2nd Generation RLV Program Office.

Dumbacher, Daniel L.↗