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NASA NTRS2019

NASA GeneLab Platform Utilized for Space Radiation Dosimetry Biological Response Compared to Radiation Ground Studies

Ionizing radiation from Galactic Cosmic Rays (GCR) is one of the major risk factors factor that will impact health of astronauts on extended missions outside the protective effects of the Earth's magnetic field. Currently there are gaps in our knowledge of the health risks associated with chronic low dose, low dose rate ionizing radiation, specifically ions associated with high (H) atomic number (Z) and energy (E). The NASA GeneLab project (genelab.nasa.gov) aims to provide a detailed library of Omics datasets associated with biological samples exposed to HZE. The GeneLab Data System (GLDS) includes datasets from both spaceflight and ground-based studies, a majority of which involved exposure to ionizing radiation. Recently GeneLab has also assessed radiation dosimetry data with omics datasets associated with samples flown to the International Space Station (ISS). The combination of the detailed information on radiation exposure for ground-based studies and curated dosimetry information for spaceflight experiments allows GeneLab to be the first comprehensive Omics database for space related research from which an investigator can generate hypotheses to direct future experiments utilizing both ground and space biological radiation data. We demonstrate the usefulness of these datasets by analyzing multiple GeneLab datasets associated with both radiation ground-based studies and spaceflight studies. The radiation ground based studies we analyzed includes both in vivo and in vitro work with a range ions from protons to iron particles with doses from 0.1Gy to 2Gy. These datasets were compared to both in vivo and in vitro datasets from samples flown to the ISS and on shorter shuttle missions with total doses of 0.1 mGy to 30 mGys. From this analysis we were able to associate distinct biological signatures associating specific ions to specific biological response to radiation exposure in space. For example, we discovered radiation biological response related to cardiovascular effects from proton ground studies are the dominating response for samples related to cardiovascular effects on the ISS. With this work we will provide a summary of how different ions will impact different biological response in space and how this can be used in future studies to assess optimal ground experiments to simulate space radiation.

Beheshti, Afshin↗

NASA NTRSDate not supplied

Maturation of Additive Manufactured Aerospace Alloys and Development of Mechanical and Thermophysical Properties for Space Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000’s. Several efforts have focused on the understanding of AM processes through design optimization, component fabrication, material characterization, testing, standards development, and infusion into propulsion development for flight applications. NASA and partners have matured commonly used aerospace alloys from various alloy families (Nickel, Steel, Iron, Aluminum, and Titanium) and AM processes. An extensive effort has been ongoing between NASA, industry partners, and academia to complete detailed AM process and heat treatment characterization, in addition to generating temperature-dependent mechanical and thermophysical properties. This presentation highlights the characterization and property results using laser powder bed fusion (L-PBF) and laser powder directed energy deposition (LP-DED) processes among various alloys. In addition to commonly used alloys, there is a need for ongoing AM optimized alloys using integrated computational materials engineering (ICME) and process development for high performance applications. The applications targeted are launch vehicles, liquid rocket engines, advanced propulsion systems, advanced power systems, and in-space propulsion with high heat fluxes, high pressure, and that utilize propellants such as hydrogen, which can degrade alloys. This presentation will also discuss some of the ongoing novel alloy development and maturation using AM for use in these harsh environments, such as GRCop-42, GRCop-84, NASA HR-1, and C-103. The results from these processes have demonstrated that AM can enable rapid development and new AM optimized alloys can yield higher performance. These alloys have undergone modeling, fundamental metallurgical evaluations, heat treatment studies, and microstructure characterization and mechanical testing campaigns. This, combined with direct application-specific component fabrication and hot-fire testing, can enable the increase of the Technology Readiness Level (TRL) through high duty-cycle testing. This presentation provides a background and overview of these various common and AM-enabled alloys and processing developments including the initial effort related to metallurgical, mechanical, and thermophysical property studies. It also covers the latest advancement in the parallel component development, hot-fire testing, and future developments for these alloys.

Additive Manufacturing↗

NASA NTRS1997

Organometallic Polymeric Conductors

For aerospace applications, the use of polymers can result in tremendous weight savings over metals. Suitable polymeric materials for some applications like EMI shielding, spacecraft grounding, and charge dissipation must combine high electrical conductivity with long-term environmental stability, good processability, and good mechanical properties. Recently, other investigators have reported hybrid films made from an electrically conductive polymer combined with insulating polymers. In all of these instances, the films were prepared by infiltrating an insulating polymer with a precursor for a conductive polymer (either polypyrrole or polythiophene), and oxidatively polymerizing the precursor in situ. The resulting composite films have good electrical conductivity, while overcoming the brittleness inherent in most conductive polymers. Many aerospace applications require a combination of properties. Thus, hybrid films made from polyimides or other engineering resins are of primary interest, but only if conductivities on the same order as those obtained with a polystyrene base could be obtained. Hence, a series of experiments was performed to optimize the conductivity of polyimide-based composite films. The polyimide base chosen for this study was Kapton. 3-MethylThiophene (3MT) was used for the conductive phase. Three processing variables were identified for producing these composite films, namely time, temperature, and oxidant concentration for the in situ oxidation. Statistically designed experiments were used to examine the effects of these variables and synergistic/interactive effects among variables on the electrical conductivity and mechanical strength of the films. Multiple linear regression analysis of the tensile data revealed that temperature and time have the greatest effect on maximum stress. The response surface of maximum stress vs. temperature and time (for oxidant concentration at 1.2 M) is shown. Conductivity of the composite films was measured for over 150 days in air at ambient temperature. The conductivity of the films dropped only half an order of magnitude in that time. Films aged under vacuum at ambient temperature diminished slightly in conductivity in the first day, but did not change thereafter. An experimental design approach will be applied to maximize the efficiency of the laboratory effort. The material properties (initial and long term) will also be monitored and assessed. The experimental results will add to the existing database for electrically conductive polymer materials. Attachments: 1) Synthesis Crystal Structure, and Polymerization of 1,2:5,6:9,10-Tribenzo-3,7,11,13-tetradehydro(14) annulene. 2) Reinvestigation of the Photocyclization of 1,4-Phenylene Bis(phenylmaleic anhydride): Preparation and Structure of (5)Helicene 5,6:9,10-Dianhydride. 3) Preparation and Structure Charecterization of a Platinum Catecholate Complex Containing Two 3-Ethynyltheophone Groups. and 4) Rigid-Rod Polymers Based on Noncoplanar 4,4'-Biphenyldiamines: A Review of Polymer Properties vs Configuration of Diamines.

Youngs, Wiley J.↗

NASA NTRS2002

Lobed Mixer Design for Noise Suppression Acoustic and Aerodynamic Test Data Analysis

A comprehensive database for the acoustic and aerodynamic characteristics of several model-scale lobe mixers of bypass ratio 5 to 6 has been created for mixed jet speeds up to 1080 ft/s at typical take-off (TO) conditions of small-to-medium turbofan engines. The flight effect was simulated for Mach numbers up to 0.3. The static thrust performance and plume data were also obtained at typical TO and cruise conditions. The tests were done at NASA Lewis anechoic dome and ASK's FluiDyne Laboratories. The effect of several lobe mixer and nozzle parameters, such as, lobe scalloping, lobe count, lobe penetration and nozzle length was examined in terms of flyover noise at constant altitude. Sound in the nozzle reference frame was analyzed to understand the source characteristics. Several new concepts, mechanisms and methods are reported for such lobed mixers, such as, "boomerang" scallops, "tongue" mixer, detection of "excess" internal noise sources, and extrapolation of flyover noise data from one flight speed to different flight speeds. Noise reduction of as much as 3 EPNdB was found with a deeply scalloped mixer compared to annular nozzle at net thrust levels of 9500 lb for a 29 in. diameter nozzle after optimizing the nozzle length.

Mengle, Vinod G.↗

NASA NTRS2015

Impact of AMS-02 Measurements on Reducing GCR Model Uncertainties

For vehicle design, shield optimization, mission planning, and astronaut risk assessment, the exposure from galactic cosmic rays (GCR) poses a significant and complex problem both in low Earth orbit and in deep space. To address this problem, various computational tools have been developed to quantify the exposure and risk in a wide range of scenarios. Generally, the tool used to describe the ambient GCR environment provides the input into subsequent computational tools and is therefore a critical component of end-to-end procedures. Over the past few years, several researchers have independently and very carefully compared some of the widely used GCR models to more rigorously characterize model differences and quantify uncertainties. All of the GCR models studied rely heavily on calibrating to available near-Earth measurements of GCR particle energy spectra, typically over restricted energy regions and short time periods. In this work, we first review recent sensitivity studies quantifying the ions and energies in the ambient GCR environment of greatest importance to exposure quantities behind shielding. Currently available measurements used to calibrate and validate GCR models are also summarized within this context. It is shown that the AMS-II measurements will fill a critically important gap in the measurement database. The emergence of AMS-II measurements also provides a unique opportunity to validate existing models against measurements that were not used to calibrate free parameters in the empirical descriptions. Discussion is given regarding rigorous approaches to implement the independent validation efforts, followed by recalibration of empirical parameters.

Slaba, T. C.↗

NASA NTRS2001

Improved Spacecraft Materials for Radiation Protection

Methods by which radiation shielding is optimized need to be developed and materials of improved shielding characteristics identified and validated. The galactic cosmic rays (GCR) are very penetrating and the energy absorbed by the astronaut behind the shield is nearly independent of shield composition and even the shield thickness. However, the mix of particles in the transmitted beam changes rapidly with shield material composition and thickness. This results in part from the breakup of the high-energy heavy ions of the GCR which make contributions to biological effects out of proportion to their deposited energy. So the mixture of particles in the radiation field changes with shielding and the control of risk contributions from dominant particle types is critical to reducing the hazard to the astronaut. The risk of biological injury for a given particle type depends on the type of biological effect and is specific to cell or tissue type. Thus, one is faced with choosing materials which may protect a given tissue against a given effect but leave unchanged or even increase the risk of other effects in the same tissue or increase the risks to other adjacent tissues of a different type in the same individual. The optimization of shield composition will then be tied to a specific tissue and risk to that tissue. Such peculiarities arise from the complicated mixture of particles, the nature of their biological response, and the details of their interaction with material constituents. Aside from the understanding of the biological response to specific components, one also needs an accurate understanding of the radiation emerging from the shield material. This latter subject has been a principal element of this project. In the past ten years our understanding of space radiation interactions with materials has changed radically, with a large impact on shield design. For example, the NCRP estimated that only 2 g/sq cm. of aluminum would be required to meet the annual 500 mSv limit for the exposure of the blood forming organs (this limit is strictly for LEO but can be used as a guideline for the Mars mission analysis). The current estimates require aluminum shield thicknesses above 50 g/sq cm., which is impractical. In such a heavily shielded vehicle, the neutrons produced throughout the vehicle also contribute significantly to the exposure and this demands greater care in describing the angular dependence of secondary particle production processes. As such the continued testing of databases and transport procedures in laboratory and spaceflight experiments has continued. This has been the focus of much of the last year's activity and has resulted in improved neutron prediction capability. These new methods have also improved our understanding of the surface environment of Mars. The Mars 2003 NRA HEDS related surface science requirements were driven by the need to validate predictions on the upward flux of neutrons produced in the Martian regolith and bedrock made by the codes developed under this project. The codes used in the surface environment definition are also being used to look at in situ resources for the development of construction material for Martian surface facilities. For example, synthesis of polyimides and polyethylene as binders of regolith for developing basic structural elements has been studied and targets built for accelerator beam testing of radiation shielding properties. Preliminary mechanical tests have also been promising. Improved spacecraft materials have been identified (using the criteria reported by this project at the last conference) as potentially important for future shielding materials. These are liquid hydrogen, hydrogenated nanofibers, liquid methane, LiH, Polyethylene, Polysulfone, and Polyetherimide (in order of decreasing shield performance). Some of the materials are multifunctional and are required for other onboard systems. We are currently preparing software for trade studies with these materials relative to the Mars Reference Mission as required in the project's final year.

Wilson, John W.↗

NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Medical Operations↗

NASA NTRS2013

Downscaling Satellite Precipitation with Emphasis on Extremes: A Variational 1-Norm Regularization in the Derivative Domain

The increasing availability of precipitation observations from space, e.g., from the Tropical Rainfall Measuring Mission (TRMM) and the forthcoming Global Precipitation Measuring (GPM) Mission, has fueled renewed interest in developing frameworks for downscaling and multi-sensor data fusion that can handle large data sets in computationally efficient ways while optimally reproducing desired properties of the underlying rainfall fields. Of special interest is the reproduction of extreme precipitation intensities and gradients, as these are directly relevant to hazard prediction. In this paper, we present a new formalism for downscaling satellite precipitation observations, which explicitly allows for the preservation of some key geometrical and statistical properties of spatial precipitation. These include sharp intensity gradients (due to high-intensity regions embedded within lower-intensity areas), coherent spatial structures (due to regions of slowly varying rainfall),and thicker-than-Gaussian tails of precipitation gradients and intensities. Specifically, we pose the downscaling problem as a discrete inverse problem and solve it via a regularized variational approach (variational downscaling) where the regularization term is selected to impose the desired smoothness in the solution while allowing for some steep gradients(called 1-norm or total variation regularization). We demonstrate the duality between this geometrically inspired solution and its Bayesian statistical interpretation, which is equivalent to assuming a Laplace prior distribution for the precipitation intensities in the derivative (wavelet) space. When the observation operator is not known, we discuss the effect of its misspecification and explore a previously proposed dictionary-based sparse inverse downscaling methodology to indirectly learn the observation operator from a database of coincidental high- and low-resolution observations. The proposed method and ideas are illustrated in case studies featuring the downscaling of a hurricane precipitation field.

Hurricanes↗

NASA NTRSDate not supplied

Biomass Harmonization and SAR Analysis with the Multi-mission Algorithm and Analysis Platform (MAAP)

The Multi‐mission Algorithm and Analysis Platform (MAAP) is a collaborative effort between NASA and the European Space Agency (ESA) to support above ground biomass (AGB) research in an open science framework. MAAP brings together relevant data, algorithms, and computing capabilities in a common cloud environment to address the challenges of sharing and processing data from field, airborne and satellite measurements. MAAP was publicly released in October 2021, providing computing capabilities co-located with the data, a collaborative coding and analysis environment, and a set of interoperable tools and algorithms developed to support the estimation and visualization of data. MAAP has allowed scientists from both North America and Europe to collaborate on the generation and analysis/visualization of data derived from multiple, discipline-adjacent missions in an open, collaborative environment that has reached beyond traditional scientific investigation. MAAP has been used to support multiple scientific activities. To date, existing LiDAR data from multiple platforms has been calibrated with field measurements and combined for more comprehensive and accurate estimates of above ground biomass AGB; these LiDAR platforms include airborne (e.g. LVIS), the International Space Station (NASA’s Global Ecosystem Dynamics Investigation (GEDI), and satellites (e.g. ICESat-2). The current challenge is to effectively and seamlessly combine the aforementioned LiDAR-based data with new data sources such as P-band RADAR from ESA’s upcoming BIOMASS mission, existing ESA Sentinel-1 C-band SAR, and the 30 PB/yr of high cadence global coverage L-band SAR data from the upcoming NASA-ISRO SAR (NISAR) mission. Recent analysis using MAAP merged ICESat-2 and optical data (Harmonized Landsat Sentinel) produced the most comprehensively precise estimate of boreal-wide AGB to date. Another effort using MAAP is the production and open distribution of global comparisons of AGB map estimates, including from ICESat-2 and GEDI, to bolster stakeholder uptake for policy applications. These map estimates will feed into the Intergovernmental Panel on Climate Change (IPCC) database, likely aiding the next Global Carbon Stocktake of the UNFCCC. Furthermore, the biomass retrieval intercomparison exercise BRIX-2 could benefit from the MAAP providing standardized test cases (based on airborne campaign and spaceborne data) allowing the community to develop and apply retrieval algorithms based on these test cases, while forthcoming SAR data training curricula could also use the MAAP as a teaching and learning platform. The MAAP is meeting the challenges inherent in international, open science collaboration and large scale computing with a platform that is entirely open source and cloud native, using open standards for data access, manipulation, protocols, and formats. The MAAP data system consists of a dedicated data store whose data is indexed in an online catalog conforming to established metadata, application programmatic interfaces (APIs), and service interface standards, using an implementation of the open sourced NASA Common Metadata Repository. Federation of user identities allows users from either NASA or ESA to access and consume services from the other using a unified metadata catalog for the data utilized across the ESA and NASA MAAP platforms. Similarly, we are exploring how to increase interoperability to achieve a common approach to packaging, orchestrating and executing algorithms, with interoperable access to data for subsetting, fast browse, and cloud-optimized access, all using interoperable standards such as those from the Open Geospatial Consortium (OGC). Designed for interoperability, ESA and NASA utilize a common architecture for the software platform. It provides a cloud-based algorithm development environment (ADE) that enables scientists to develop algorithms collaboratively with access to the MAAP data catalog as well as other data archives. MAAP provides an Eclipse Che-based ADE supporting both Python and R languages, popular in this biomass community. Algorithms developed and containerized within the ADE can be deployed to run to thousands of computational nodes in the MAAP’s data processing system (DPS), dramatically speeding up processing and giving scientists a rapid, iterative turnaround of results. NASA’s implementation of the DPS is based on the Hybrid Science Data System (HySDS) framework, used by NASA flight projects to produce Earth science standard products.

cloud computing↗

NASA NTRS2019

Nonmodal Growth of TravelingWaves on Blunt Cones at Hypersonic Speeds

The existing database of transition measurements in hypersonic ground facilities has established that, as the nosetip bluntness is increased, the onset of boundary layer transition over a circular cone at zero angle of attack shifts downstream. However, this trend is reversed at sufficiently large values of the nose Reynolds number, so that the transition onset location eventually moves upstream with a further increase in nose-tip bluntness. Because modal amplification is too weak to initiate transition at moderate-to-large bluntness values, nonmodal growth has been investigated as the potential basis for a physics-based model for the frustum transition. The present analysis investigates the nonmodal growth of traveling disturbances initiated within the nose-tip vicinity that peak within the entropy layer. Results show that, with increasing nose bluntness, both planar and oblique traveling disturbances experience appreciable energy amplification up to successively higher frequencies. For moderately blunt cones, the initial nonmmodal growth is followed by a partial decay that is more than overcome by an eventual, modal growth as Mack-mode waves. For larger bluntness values, the Mack-mode waves are not amplified anywhere upstream of the experimentally measured transition location, but the traveling modes still undergo a significant amount of nonmodal growth. This finding does not provide a definitive link between optimal growth and the onset of transition, but it is qualitatively consistent with the experimental observations that frustum transition in the absence of sufficient Mack-mode amplification implies a double peak in disturbance amplification and the appearance of transitional events above the boundary-layer edge.

Hypersonic speed↗

NASA NTRS2003

Operation of MRO's High Resolution Imaging Science Experiment (HiRISE): Maximizing Science Participation

Science return from the Mars Reconnaissance Orbiter (MRO) High Resolution Imaging Science Experiment (HiRISE) will be optimized by maximizing science participation in the experiment. MRO is expected to arrive at Mars in March 2006, and the primary science phase begins near the end of 2006 after aerobraking (6 months) and a transition phase. The primary science phase lasts for almost 2 Earth years, followed by a 2-year relay phase in which science observations by MRO are expected to continue. We expect to acquire approx. 10,000 images with HiRISE over the course of MRO's two earth-year mission. HiRISE can acquire images with a ground sampling dimension of as little as 30 cm (from a typical altitude of 300 km), in up to 3 colors, and many targets will be re-imaged for stereo. With such high spatial resolution, the percent coverage of Mars will be very limited in spite of the relatively high data rate of MRO (approx. 10x greater than MGS or Odyssey). We expect to cover approx. 1% of Mars at approx. 1m/pixel or better, approx. 0.1% at full resolution, and approx. 0.05% in color or in stereo. Therefore, the placement of each HiRISE image must be carefully considered in order to maximize the scientific return from MRO. We believe that every observation should be the result of a mini research project based on pre-existing datasets. During operations, we will need a large database of carefully researched 'suggested' observations to select from. The HiRISE team is dedicated to involving the broad Mars community in creating this database, to the fullest degree that is both practical and legal. The philosophy of the team and the design of the ground data system are geared to enabling community involvement. A key aspect of this is that image data will be made available to the planetary community for science analysis as quickly as possible to encourage feedback and new ideas for targets.

E Eliason↗

NASA NTRS2005

Modular Software Interfaces for Revolutionary Flexibility in Space Operations

To make revolutionary improvements in exploration, space systems need to be flexible, realtime reconfigurable, and able to trade data transparently among themselves and mission operations. Onboard operations systems, space assembly coordination and EVA systems in exploration and construction all require real-time modular reconfigurability and data sharing. But NASA's current exploration systems are still largely legacies from hastily-developed, one-off Apollo-era practices. Today's rovers, vehicles, spacesuits, space stations, and instruments are not able to plug-and-play, Lego-like: into different combinations. Point-to-point dominates - individual suit to individual vehicle, individual instrument to rover. All are locally optimized, all unique, each of the data interfaces has been recoded for each possible combination. This will be an operations and maintenance nightmare in the much larger Project Constellation system of systems. This legacy approach does not scale to the hundreds of networked space components needed for space construction and for new, space-based approaches to Earth-Moon operations. By comparison, battlefield information management systems, which are considered critical to military force projection, have long since abandoned a point-to-point approach to systems integration. From a system-of-systems viewpoint, a clean-sheet redesign of the interfaces of all exploration systems is a necessary prerequisite before designing the interfaces of the individual exploration systems. Existing communications and Global Information Grid and middleware technologies are probably sufficient for command and control and information interfaces, with some hardware and time-delay modifications for space environments. NASA's future advanced space operations must also be information and data compatible with aerospace operations and surveillance systems being developed by other US Government agencies such as the Department of Homeland Security, Federal Aviation Administration and Department of Defense. This paper discusses fundamental system-of-systems infrastructure: approaches and architectures for modular plug-and-play software interfaces for revolutionary improvements in flexibility, modularity, robustness, ease of maintenance, reconfigurability, safety and productivity. Starting with middleware, databases, and mobile communications technologies, our technical challenges will be to apply these ideas to the requirements of constellations of space systems and to implement them initially on prototype space hardware. This is necessary to demonstrate an integrated information sharing architecture and services. It is a bottom-up approach, one that solves the problem of space operations data integration. Exploration demands uniform software mechanisms for application information interchange, and the corresponding uniformly available software services to enhance these mechanisms. We will examine the issues in plug-and-play, real-time-configurable systems, including common definition and management and tracking of data and information among many different space systems. Different field test approaches are discussed, including the use of the International Space Station and terrestrial analog mission operations at field sites.

Glass, Brian↗

NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

NASA NTRS2010

NASA Tech Briefs, March 2010

Topics covered include: Software Tool Integrating Data Flow Diagrams and Petri Nets; Adaptive Nulling for Interferometric Detection of Planets; Reducing the Volume of NASA Earth-Science Data; Reception of Multiple Telemetry Signals via One Dish Antenna; Space-Qualified Traveling-Wave Tube; Smart Power Supply for Battery-Powered Systems; Parallel Processing of Broad-Band PPM Signals; Inexpensive Implementation of Many Strain Gauges; Constant-Differential-Pressure Two-Fluid Accumulator; Inflatable Tubular Structures Rigidized with Foams; Power Generator with Thermo-Differential Modules; Mechanical Extraction of Power From Ocean Currents and Tides; Nitrous Oxide/Paraffin Hybrid Rocket Engines; Optimized Li-Ion Electrolytes Containing Fluorinated Ester Co-Solvents; Probabilistic Multi-Factor Interaction Model for Complex Material Behavior; Foldable Instrumented Bits for Ultrasonic/Sonic Penetrators; Compact Rare Earth Emitter Hollow Cathode; High-Precision Shape Control of In-Space Deployable Large Membrane/Thin-Shell Reflectors; Rapid Active Sampling Package; Miniature Lightweight Ion Pump; Cryogenic Transport of High-Pressure-System Recharge Gas; Water-Vapor Raman Lidar System Reaches Higher Altitude; Compact Ku-Band T/R Module for High-Resolution Radar Imaging of Cold Land Processes; Wide-Field-of-View, High-Resolution, Stereoscopic Imager; Electrical Capacitance Volume Tomography with High-Contrast Dielectrics; Wavefront Control and Image Restoration with Less Computing; Polarization Imaging Apparatus; Stereoscopic Machine-Vision System Using Projected Circles; Metal Vapor Arcing Risk Assessment Tool; Performance Bounds on Two Concatenated, Interleaved Codes; Parameterizing Coefficients of a POD-Based Dynamical System; Confidence-Based Feature Acquisition; Algorithm for Lossless Compression of Calibrated Hyperspectral Imagery; Universal Decoder for PPM of any Order; Algorithm for Stabilizing a POD-Based Dynamical System; Mission Reliability Estimation for Repairable Robot Teams; Processing AIRS Scientific Data Through Level 3; Web-Based Requesting and Scheduling Use of Facilities; AutoGen Version 5.0; Time-Tag Generation Script; PPM Receiver Implemented in Software; Tropospheric Emission Spectrometer Product File Readers; Reporting Differences Between Spacecraft Sequence Files; Coordinating "Execute" Data for ISS and Space Shuttle; Database for Safety-Oriented Tracking of Chemicals; Apparatus for Cold, Pressurized Biogeochemical Experiments; Growing B Lymphocytes in a Three-Dimensional Culture System; Tissue-like 3D Assemblies of Human Broncho-Epithelial Cells; Isolation of Resistance-Bearing Microorganisms; Oscillating Cell Culture Bioreactor; and Liquid Cooling/Warming Garment.

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NASA NTRS2012

Automating Mid- and Long-Range Scheduling for the NASA Deep Space Network

NASA has recently deployed a new mid-range scheduling system for the antennas of the Deep Space Network (DSN), called Service Scheduling Software, or S(sup 3). This system was designed and deployed as a modern web application containing a central scheduling database integrated with a collaborative environment, exploiting the same technologies as social web applications but applied to a space operations context. This is highly relevant to the DSN domain since the network schedule of operations is developed in a peer-to-peer negotiation process among all users of the DSN. These users represent not only NASA's deep space missions, but also international partners and ground-based science and calibration users. The initial implementation of S(sup 3) is complete and the system has been operational since July 2011. This paper describes some key aspects of the S(sup 3) system and on the challenges of modeling complex scheduling requirements and the ongoing extension of S(sup 3) to encompass long-range planning, downtime analysis, and forecasting, as the next step in developing a single integrated DSN scheduling tool suite to cover all time ranges.

Deep Space Network↗

NASA NTRS2007

Shuttle Entry Imaging Using Infrared Thermography

During the Columbia Accident Investigation, imaging teams supporting debris shedding analysis were hampered by poor entry image quality and the general lack of information on optical signatures associated with a nominal Shuttle entry. After the accident, recommendations were made to NASA management to develop and maintain a state-of-the-art imagery database for Shuttle engineering performance assessments and to improve entry imaging capability to support anomaly and contingency analysis during a mission. As a result, the Space Shuttle Program sponsored an observation campaign to qualitatively characterize a nominal Shuttle entry over the widest possible Mach number range. The initial objectives focused on an assessment of capability to identify/resolve debris liberated from the Shuttle during entry, characterization of potential anomalous events associated with RCS jet firings and unusual phenomenon associated with the plasma trail. The aeroheating technical community viewed the Space Shuttle Program sponsored activity as an opportunity to influence the observation objectives and incrementally demonstrate key elements of a quantitative spatially resolved temperature measurement capability over a series of flights. One long-term desire of the Shuttle engineering community is to calibrate boundary layer transition prediction methodologies that are presently part of the Shuttle damage assessment process using flight data provided by a controlled Shuttle flight experiment. Quantitative global imaging may offer a complementary method of data collection to more traditional methods such as surface thermocouples. This paper reviews the process used by the engineering community to influence data collection methods and analysis of global infrared images of the Shuttle obtained during hypersonic entry. Emphasis is placed upon airborne imaging assets sponsored by the Shuttle program during Return to Flight. Visual and IR entry imagery were obtained with available airborne imaging platforms used within DoD along with agency assets developed and optimized for use during Shuttle ascent to demonstrate capability (i.e., tracking, acquisition of multispectral data, spatial resolution) and identify system limitations (i.e., radiance modeling, saturation) using state-of-the-art imaging instrumentation and communication systems. Global infrared intensity data have been transformed to temperature by comparison to Shuttle flight thermocouple data. Reasonable agreement is found between the flight thermography images and numerical prediction. A discussion of lessons learned and potential application to a potential Shuttle boundary layer transition flight test is presented.

Horvath, Thomas↗

NASA NTRS1999

Remote Sensing of Rain

The first problem addressed concerns passive-microwave rain retrievals. Most current approaches start by building off-line a cloud-model-derived database. Given data, the retrieval algorithms search the database for the microwave temperatures "closest" to the observed data, then after some fine-tuning (performed in different ways by different implementations) the rain is estimated to be that which corresponds to the selected (and fine-tuned) set of database temperatures. These approaches have three drawbacks: they cannot properly take into account the ambiguities which arise from the fact that several rain scenarios can produce the same observed temperatures; they are quite inefficient since they require manipulating a large database along with often complex "fine-tuning" procedures; and they cannot refine their estimates if additional data is available. This past year we have derived closed formulae relating observed microwave brightness temperatures, T(sub b), and the underlying rain rates, R: average T(sub b) =f (rain) and average rain = g (T(sub b)), along with the corresponding covariance matrices. These results are sufficient to describe the conditional probabilities p(R/T(sub b)) and p(T(sub b)/R) to second order. Progress has also been made towards deriving a robust description of the rain drop size distribution (DSD). The widespread approach consisting in parameterizing the DSD as a gamma-distribution in terms of the drop diameter D suffers from the facts that, in reality, the DSD is not a smooth function of D and that the largely arbitrary Gamma model imposes unintended behavior, which has implications on any quantities derived from the DSD model. We have therefore developed a non-parametric yet practical description of the DSD, which is particularly well-suited for use in remote-sensing applications. The diagram on the left shows a comparison between an actual DSD sample and the truncated non-parametric representation. One figure shows the relation between radar reflectivity and rain rate derived using this representation. Validation of the Tropical Rainfall Measuring Mission (TRMM) radar-radiometer combined R and DSD algorithm is underway. This algorithm was designed to make optimal use of the instantaneous reflectivity profiles measured by the TRMM radar and the microwave brightness temperatures measured by the TRMM passive radiometer. So far, it appears to be the most reliable TRMM rain algorithm.

Haddad, Ziad S.↗