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The purpose of the SPRAT conference is to bring members of the space solar cell community together in a relatively informal conference setting to discuss the recent developments in solar cell technology and to discuss the future directions of the field. The conference is sponsored by the Photovoltaic and Space Environmental Effects Branch at the NASA Glenn Research Center.
The NASA Real Time Mission Monitor (RTMM) is a situational awareness tool that integrates satellite, airborne and surface data sets; weather information; model and forecast outputs; and vehicle state data (e.g., aircraft navigation, satellite tracks and instrument field-of-views) for field experiment management RTMM optimizes science and logistic decision-making during field experiments by presenting timely data and graphics to the users to improve real time situational awareness of the experiment's assets. The RTMM is proven in the field as it supported program managers, scientists, and aircraft personnel during the NASA African Monsoon Multidisciplinary Analyses experiment during summer 2006 in Cape Verde, Africa. The integration and delivery of this information is made possible through data acquisition systems, network communication links and network server resources built and managed by collaborators at NASA Dryden Flight Research Center (DFRC) and Marshall Space Flight Center (MSFC). RTMM is evolving towards a more flexible and dynamic combination of sensor ingest, network computing, and decision-making activities through the use of a service oriented architecture based on community standards and protocols.
The science of field geology is the investigative process of determining the distribution of rock units and structures on a planet fs surface, and it is the first-order data set that informs all subsequent studies of a planet, such as geochemistry, geochronology, geophysics, or remote sensing. For future missions to the Moon and Mars, the surface systems deployed must support the conduct of field geology if these endeavors are to be scientifically useful. This lecture discussed what field geology is all about.why it is important, how it is done, how conducting field geology informs many other sciences, and how it affects the design of surface systems and the implementation of operations in the future.
St. Bernard Parish, in southeast Louisiana, is rapidly losing coastal forests and wetlands due to a combination of natural and anthropogenic disturbances (e.g. subsidence, saltwater intrusion, low sedimentation, nutrient deficiency, herbivory, canal dredging, levee construction, spread of invasive species, etc.). After Hurricane Katrina severely impacted the area in 2005, multiple Non-Governmental Organizations (NGOs) have worked not only on rebuilding destroyed dwellings, but on rebuilding the ecosystems that once protected the citizens of St. Bernard Parish. Volunteer groups, NGOs, and government entities often work separately and independently of each other and use different sets of information to choose the best planting sites for coastal forests. Using NASA EOS, NRCS soil surveys, and ancillary road and canal data in conjunction with ground truthing, the team created maps of optimal planting sites for several species of wetland trees to aid in unifying these organizations, who share a common goal, under one plan. The methodology for this project created a comprehensive Geographic Information System (GIS) to help identify suitable planting sites in St. Bernard Parish. This included supplementing existing elevation data using LIDAR data and classifying existing land cover in the study area from ASTER multispectral satellite data. Low altitude AVIRIS hyperspectral imagery was used to assess the health of vegetation over an area near the intersection of the Mississippi River Gulf Outlet Canal (MRGO) and Bayou la Loutre. Historic extent of coastal forests was mapped using aerial photos from USGS collected between 1952 and 1956. The final products demonstrated the utility of combining NASA EOS with other geospatial data in assessing, monitoring, and restoring of coastal ecosystems in Louisiana. This methodology also provides a useful template for other ecological forecasting and coastal restoration applications.
Approaches used in Earth science research such as case study analysis and climatology studies involve discovering and gathering diverse data sets and information to support the research goals. To gather relevant data and information for case studies and climatology analysis is both tedious and time consuming. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. In cases where researchers are interested in studying a significant event, they have to manually assemble a variety of datasets relevant to it by searching the different distributed data systems. This paper presents a specialized search, aggregation and curation tool for Earth science to address these challenges. The search rool automatically creates curated 'Data Albums', aggregated collections of information related to a specific event, containing links to relevant data files [granules] from different instruments, tools and services for visualization and analysis, and information about the event contained in news reports, images or videos to supplement research analysis. Curation in the tool is driven via an ontology based relevancy ranking algorithm to filter out non relevant information and data.
As part of NASAs UAS in the NAS project, human factor guidelines are being developed for the ground control station of unmanned aircraft systems. A critical task for the pilot of a UAS is the management and control of the terrestrial radio links used to provide control of the vehicle and relay communications with air traffic control. An analysis of the task of the UAS pilot has been conducted to identify areas where guidelines are required. This analysis has identified a set of information requirements that must be supported by the radio equipment used to provide Control and Non-payload Communication (CNPC). Key requirements include the need for an alert when the link is lost, information on the current quality and latency of the link, and information to enable the future quality of the link to be anticipated as the aircraft changes location. These identified requirements can assist in the development of minimum operational performance standards for CNPC equipment.
Highly promising locales for biosignature prospecting on Mars are ancient hydrothermal deposits, formed by the interaction of surface water with heat from volcanism or impacts. On Earth, they occur throughout the geological record (to at least approx. 3.5 Ga), preserving robust mineralogical, textural and compositional evidence of thermophilic microbial activity. Hydrothermal systems were likely present early in Mars' history, including at two of the three finalist candidate landing sites for M2020, Columbia Hills and NE Syrtis Major. Hydrothermal environments on Earth's surface are varied, constituting subaerial hot spring aprons, mounds and fumaroles; shallow to deep-sea hydrothermal vents (black and white smokers); and vent mounds and hot-spring discharges in lacustrine and fluvial settings. Biological information can be preserved by rapid, spring-sourced mineral precipitation, but also could be altered or destroyed by postdepositional events. Thus, field observations need to be followed by detailed laboratory analysis to verify potential biosignatures. See Attachment
Decision making structures, such as control boards, process information on many topics as they select options for the system and project. The decisions are based on the information known to the board members and presenters (subject matter experts) and shared at the board during discussion. This information flow through this process can be modelled using information theory. Information theory provides a mathematical basis to understand the flow of information through the decision making process and the information needed for a particular decision. Information theory also provides the mathematical relationships on which to base the optimal decision making structure for a specific system development and organizational structure. Since decision making bodies provide control for the system or project, control theory can be used to construct a decision making model. This provides a starting point for adding cognitive science models. Information processing by each individual board participant can be represented through cognitive processes which are integrated across the board participants through information theory relationship. The set theory view of information theory provides a structure in which to look at the relationships between the participants in a decision making structure.
Decision making structures, such as control boards, process information on many topics as they select options for the system and project. The decisions are based on the information known to the board members and presenters (subject matter experts) and shared at the board during discussion. This information flow through this process can be modelled using information theory. Information theory provides a mathematical basis to understand the flow of information through the decision making process and the information needed for a particular decision. Information theory also provides the mathematical relationships on which to base the optimal decision making structure for a specific system development and organizational structure. Since decision making bodies provide control for the system or project, control theory can be used to construct a decision making model. This provides a starting point for adding cognitive science models. Information processing by each individual board participant can be represented through cognitive processes which are integrated across the board participants through information theory relationship. The set theory view of information theory provides a structure in which to look at the relationships between the participants in a decision making structure.
The Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) is a high spatial resolution imaging instrument, due to be launched on NASA's Earth Observing System AM-1 satellite platform in 1998. ASTER acquires data in 14 bands, spanning the wavelength region from the visible, near infrared, short wavelength infrared, and thermal infrared, with spatial resolution varying from 15 m to 90 m, depending on wavelength region. In order to evaluate our ability to use ASTER data for geological mapping, we used aircraft data over Cuprite, Nevada to create a simulated 14-band ASTER data set. The study site has sparse vegetation, and exposes a wide range of unaltered and hydrothermally altered volcanic rocks. The wide range of wavelengths covered by ASTER allowed us to recognize or separate iron oxide minerals, clay-bearing minerals, sulfate minerals, ammonia minerals, siliceous rocks, and carbonates. Combined with laboratory spectral measurements, we were able to identify these constituents. Based on both sets of information, we produced an alteration map showing the distribution of argillized rocks, opalized rocks with alunite, silicified rocks, and areas dominated by kaolinite and buddingtonite. The map was as accurate as published maps made by traditional field methods. ASTER promises to be a major improvement over existing satellite systems for geologic mapping.
Variable Pressure (or Environmental) Scanning Electron Microscopy (VP-SEM) combined with Energy Dispersive X-ray Spectroscopy (EDS) is one of the most powerful methods for characterizing the sub-micron topography and chemical composition of uncoated samples. Terrestrially, VP-SEM is extensively used to non-destructively study geologic and manufactured materials with high spatial resolution (tens of nanometers) and large depth-of-field. An SEM offers a geologist a first survey of microscopic mineral phases via secondary electron imaging (SEI), which provides a topographic look at a sample, as well as backscattered electron (BEI) imaging, which contrasts the phases present based on their geochemistry (atomic number). A VP-SEM utilizes a gas in the sample chamber as a charge dissipation and signal amplification method, allowing analysis of a sample without preparation in the form of a conductive coating. A miniaturized VP-SEM operating in-situ on a lander or rover would be able to use the CO2-rich Martian atmosphere (e.g., Nier et al., 1976; Williams 2016) as an imaging medium for this purpose. Adaptation of a VP-SEM for in-situ Mars surface studies will provide a new imaging capability (via SEI) that is at least an order of magnitude higher resolution than the Mars Hand Lens Imager (MAHLI) on the Mars Science Laboratory (Williams et al., 2015), and equal to or better than the achieved resolution of the Atomic Force Microscope on the Phoenix Mars lander (Pike et al., 2011). In addition, the MVP-SEM is capable of BSI and simultaneous chemical analysis of the imaged region. In this sense, the MVP-SEM can be regarded as an instrument suite that will provide a new set of information not achievable by any other instrument. The Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) was designed, built, and benchtop tested by a team at NASA’s Marshall Space Flight Center and Jet Propulsion Laboratory (JPL), Jacobs Space Exploration Group, Applied Physics Technologies, Inc. (AP-Tech), and Creare LLC, working with a team of technical and science collaborators. Benchtop testing was successful, proving concept feasibility. To date, the MVP-SEM has achieved an imaging resolution of <100 nm in the lab, and with continued optimization, even better performance (~50 nm resolution) is possible. Use in-situ on the lunar or other planetary surfaces would require some redesign to optimize instrument performance, but such an instrument would be equally useful.
Variable Pressure (or Environmental) Scanning Electron Microscopy (VP-SEM) combined with Energy Dispersive X-ray Spectroscopy (EDS) is one of the most powerful methods for characterizing the sub-micron topography and chemical composition of uncoated samples. Terrestrially, VP-SEM is extensively used to non-destructively study geologic and manufactured materials with high spatial resolution (tens of nanometers) and large depth-of-field. An SEM offers a geologist a first survey of microscopic mineral phases via secondary electron imaging (SEI), which provides a topographic look at a sample, as well as backscattered electron (BEI) imaging, which contrasts the phases present based on their geochemistry (atomic number). A VP-SEM utilizes a gas in the sample chamber as a charge dissipation and signal amplification method, allowing analysis of a sample without preparation in the form of a conductive coating. A miniaturized VP-SEM operating in-situ on a lander or rover would be able to use the CO2-rich Martian atmosphere (e.g., Nier et al., 1976; Williams 2016) as an imaging medium for this purpose. Adaptation of a VP-SEM for in-situ Mars surface studies will provide a new imaging capability (via SEI) that is at least an order of magnitude higher resolution than the Mars Hand Lens Imager (MAHLI) on the Mars Science Laboratory (Williams et al., 2015), and equal to or better than the achieved resolution of the Atomic Force Microscope on the Phoenix Mars lander (Pike et al., 2011). In addition, the MVP-SEM is capable of BSI and simultaneous chemical analysis of the imaged region. In this sense, the MVP-SEM can be regarded as an instrument suite that will provide a new set of information not achievable by any other instrument. The Miniaturized Variable Pressure Scanning Electron Microscope (MVP-SEM) was designed, built, and benchtop tested by a team at NASA’s Marshall Space Flight Center and Jet Propulsion Laboratory (JPL), Jacobs Space Exploration Group, Applied Physics Technologies, Inc. (AP-Tech), and Creare LLC, working with a team of technical and science collaborators. Benchtop testing was successful, proving concept feasibility. To date, the MVP-SEM has achieved an imaging resolution of <100 nm in the lab, and with continued optimization, even better performance (~50 nm resolution) is possible. Use in-situ on the lunar or other planetary surfaces would require some redesign to optimize instrument performance, but such an instrument would be equally useful.
One approach to quantifying spaceflight risk at NASA makes use event driven probabilistic techniques. The Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is such a tool that estimates medical risk metrics via simulation and enables optimization of medical resources subject to mission constraints [1]. Previous analyses have informed medical set composition, exercise countermeasures, and water intake, where each analysis quantifies the risk associated with proposed variations in system design. As future mission profiles extend beyond Low-Earth Orbit (LEO) and lengthen in duration, understanding these risks and contributing factors is critical. MEDPRAT employs Monte Carlo sampling techniques to simulate missions and track the occurrence of medical events. These events follow fault-tree-like progressions through levels of severity and mitigation via medical treatment to many possible outcomes and these are reported throughout the mission. Making this possible, are the medical databases that contain evidence gathered by the Human Research Program (HRP). Quantifying the impact of uncertainty or variability in the input data is an important step in evaluating the credibility of modeling and simulation results. In this work, we investigate the sensitivity of medical risk metrics with respect to the condition incidence parameters within the Evidence Library (EL) [2] as the medical database input for MEDPRAT. The medical conditions, contained in the EL, are equipped with incidence rates that describe the likelihood that the condition will occur. These incidence rates reflect historical spaceflight data or when appropriate, terrestrial data. In this presentation, we will explore how uncertainty in these rates propagate to the medical risk described by MEDPRAT. These results identify the conditions and parameters with the largest contribution to medical risks.
The NASA Orbital Debris Program Office (ODPO) relies on ground-based radar measurements from both the Haystack Ultrawideband Satellite Imaging Radar (HUSIR) and the Goldstone Solar System Radar (Goldstone) to characterize mm to cm debris population in low Earth orbit (LEO). Radar measurements help characterize the size of orbital debris objects, particularly fragmentation debris. However, debris size is not directly measured by radar but inferred from the measured radar cross section (RCS) which depends on several parameters in addition to physical size including electrical conductivity and polarization. To interpret the observed RCS of orbital debris objects detected by radar measurements as physical sizes, NASA uses an empirical size estimation model (SEM) based on laboratory RCS measurements of breakup fragments generated during hypervelocity impact tests as well as some pieces of non-impact-generated “artificial” debris-like objects expected to be representative of the debris population. Since the development of the ODPO SEM, many new materials have been introduced to spacecraft construction. Consequently, ODPO plans to update the radar SEM based on planned laboratory RCS measurements of debris fragments from DebriSat, a ground-based hypervelocity impact experiment conducted in 2014 that consisted of a high-fidelity spacecraft model characteristic of a modern LEO spacecraft. Prior to measuring DebriSat fragments, a set of calibration targets with well-defined geometries and material compositions were measured at The Ohio State University’s ElectroScience Laboratory (OSU-ESL) compact radar range. These calibration measurements help to validate, and understand any limitations of, laboratory measurements of RCS. Calibration targets include idealizations of typical shape categories seen in DebriSat fragments such as nuggets, flat plates, and cylinders. As with DebriSat, calibration target materials were chosen to represent typical modern-day spacecraft components and include stainless steel, aluminum, printed circuit board (PCB) substrate, and carbon fiber-reinforced polymer (CFRP). These materials also represent a wide range of electrical conductivities, which strongly influences measured RCS and inferred target size. The RCS calibration measurements were collected over a frequency sweep from 2 to 18 GHz and stepping through different azimuth angles from 0 to 360 degrees at an elevation of 0 degrees. A second set of calibration measurements is in work consisting of more complex shapes such as bent rods and plates as well as different mounting options including epoxy and a 3D printed holder. These further measurements along with our initial calibration set will inform selection of representative DebriSat fragments for laboratory RCS measurements that will contribute to the planned update to the ODPO radar SEM. An appropriate subset of both the radar calibration and DebriSat samples will also be measured in the ODPO Optical Measurements Center to cross-calibrate size estimates over these different wavelength regimes.
To provide information on the potential for long life service of oxidation resistant carbon-carbon (ORCC) materials in the National Aero-Space Plane (NASP) airframe environment, NASP ascent, entry, and cruise trajectories were analytically flown. Temperature and pressure profiles were generated for 20 vehicle locations. Orbital (ascent and entry) and cruise profile sets from four locations are presented along with the humidity exposure and testing sequences that are being used to evaluate ORCC materials. The four profiles show peak temperatures during the ascent leg of an orbital mission of 2800, 2500, 2000, and 1700 F. These profiles bracket conditions where carbon-carbon might be used on the NASP vehicle.
Presented here is an identification technique that uses the sensor information to choose a new model out of a finite set of discrete model space, in order to follow the observed changes to the given time varying flexible structure. Boundary condition sets or other information on model variations are used to organize the set of possible models laterally into a search tree with levels of abstraction used to order the models vertically within branches. An object-oriented programming approach is used to represent the model set in the search tree. A modified A (asterisk) best first search algorithm finds the model where the model response best matches the current observations. Several extensions to this methodology are discussed. Methods of possible integration of rules with the current search algorithm are considered to give weight to interpreted trends that may be found in a series of observations. This capability might lead, for instance, to identifying a model that incorporates a progressive damage rather than with incorrect paramenters such as added mass. Another new direction is to consider the use of noisy time domain sensor feedback rather than frequency domain information in the search algorithm to improve the real-time capability of the developed procedure.
While the 'Catalog Interoperability' (CI) project began as a NASA effort to facilitate identification, location, and access to data of interest to space and earth sciences researchers, it now has a membership encompassing numerous U.S. and international agencies as well as academic institutions. CI is creating a global network of interconnected directory, catalog, and inventory systems. Its directories contain brief summary information about data sets, and can either furnish automated links to other information systems yielding greater detail on matters of interest or indicate to whom requests for additional information can go.
In the multiresolution approximation, a signal is examined on a hierarchy of resolution scales by projection onto sets of smoothing functions. Wavelets are used to carry the detail information connecting adjacent sets in the resolution hierarchy. An algorithm has been implemented to perform a multiresolution decomposition in n greater than or equal to 2 dimensions based on wavelets generated from products of 1-D wavelets and smoothing functions. The functions are chosen so that an n-D wavelet may be associated with a single resolution scale and orientation. The algorithm enables complete reconstruction of a high resolution signal from decomposition coefficients. The signal may be oversampled to accommodate non-orthogonal wavelet systems, or to provide approximate translational invariance in the decomposition arrays.