REAL Knowledge at NASA: A Knowledge Services Model for the Modern Project Environment
REAL Knowledge at NASA: A Knowledge Services Model for the Modern Project Environment
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REAL Knowledge at NASA: A Knowledge Services Model for the Modern Project Environment
In today's applications, the need for the division of code and data has focused on the growth of object oriented programming. This philosophy gives software engineers greater control over the environment of an application. Yet the use of object oriented design does not exclude the need for greater understanding by the application of what the controller is doing. Such understanding is only possible by using expert systems. Providing a controller that is capable of controlling an object by using rule-based expertise would expedite the use of both object oriented design and expert knowledge of the dynamic of an environment in modern controllers. This project presents a model of a controller that uses the CLIPS expert system and objects in C++ to create a generic controller. The polymorphic abilities of C++ allow for the design of a generic component stored in individual data files. Accompanying the component is a set of rules written in CLIPS which provide the following: the control of individual components, the input of sensory data from components and the ability to find the status of a given component. Along with the data describing the application, a set of inference rules written in CLIPS allows the application to make use of sensory facts and status and control abilities. As a demonstration of this ability, the control of the environment of a house is provided. This demonstration includes the data files describing the rooms and their contents as far as devices, windows and doors. The rules used for the home consist of the flow of people in the house and the control of devices by the home owner.
Over the past decade, high performance computing has evolved rapidly; systems based on commodity microprocessors have been introduced in quick succession from at least seven vendors/families. Porting codes to every new architecture is a difficult problem; in particular, here at NASA, there are many large CFD applications that are very costly to port to new machines by hand. The LCM ("Legacy Code Modernization") Project is the development of an integrated parallelization environment (IPE) which performs the automated mapping of legacy CFD (Fortran) applications to state-of-the-art high performance computers. While most projects to port codes focus on the parallelization of the code, we consider porting to be an iterative process consisting of several steps: 1) code cleanup, 2) serial optimization,3) parallelization, 4) performance monitoring and visualization, 5) intelligent tools for automated tuning using performance prediction and 6) machine specific optimization. The approach for building this parallelization environment is to build the components for each of the steps simultaneously and then integrate them together. The demonstration will exhibit our latest research in building this environment: 1. Parallelizing tools and compiler evaluation. 2. Code cleanup and serial optimization using automated scripts 3. Development of a code generator for performance prediction 4. Automated partitioning 5. Automated insertion of directives. These demonstrations will exhibit the effectiveness of an automated approach for all the steps involved with porting and tuning a legacy code application for a new architecture.
A parachute simulation environment (PSE) has been developed that aims to take advantage of legacy parachute simulation codes and modern object-oriented programming techniques. This hybrid simulation environment provides the parachute analyst with a natural and intuitive way to construct simulation tasks while preserving the pedigree and authority of established parachute simulations. NASA currently employs four simulation tools for developing and analyzing air-drop tests performed by the CEV Parachute Assembly System (CPAS) Project. These tools were developed at different times, in different languages, and with different capabilities in mind. As a result, each tool has a distinct interface and set of inputs and outputs. However, regardless of the simulation code that is most appropriate for the type of test, engineers typically perform similar tasks for each drop test such as prediction of loads, assessment of altitude, and sequencing of disreefs or cut-aways. An object-oriented approach to simulation configuration allows the analyst to choose models of real physical test articles (parachutes, vehicles, etc.) and sequence them to achieve the desired test conditions. Once configured, these objects are translated into traditional input lists and processed by the legacy simulation codes. This approach minimizes the number of sim inputs that the engineer must track while configuring an input file. An object oriented approach to simulation output allows a common set of post-processing functions to perform routine tasks such as plotting and timeline generation with minimal sensitivity to the simulation that generated the data. Flight test data may also be translated into the common output class to simplify test reconstruction and analysis.
Background noise measurements were made of the acoustic environment in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel (40x80) at NASA Ames Research Center. The measurements were acquired subsequent to the 40x80 Aeroacoustic Modernization Project, which was undertaken to improve the anechoic characteristics of the 40x80's closed test section as well as reduce the levels of background noise in the facility. The resulting 40x80 anechoic environment was described by Soderman et. al., and the current paper describes the resulting 40x80 background noise, discusses the sources of the noise, and draws comparisons to previous 40x80 background noise levels measurements. At low wind speeds or low frequencies, the 40x80 background noise is dominated by the fan drive system. To obtain the lowest fan drive noise for a given tunnel condition, it is possible in the 40x80 to reduce the fans' rotational speed and adjust the fans' blade pitch, as described by Schmidtz et. al. This idea is not new, but has now been operationally implemented with modifications for increased power at low rotational speeds. At low to mid-frequencies and at higher wind speeds, the dominant noise mechanism was thought to be caused by the surface interface of the previous test section floor acoustic lining. In order to reduce this noise mechanism, the new test section floor lining was designed to resist the pumping of flow in and out of the space between the grating slats required to support heavy equipment. In addition, the lining/flow interface over the entire test section was designed to be smoother and quieter than the previous design. At high wind speeds or high frequencies, the dominant source of background noise in the 40x80 is believed to be caused by the response of the in-flow microphone probes (required by the nature of the closed test section) to the fluctuations in the freestream flow. The resulting background noise levels are also different for probes of various diameters and types. The inflow microphone support strut is also a source of background noise but this source's impact may be minimized by careful design of the strut. In the present paper, the mechanisms mentioned above are discussed in detail. Their frequency and velocity ranges of dominance are defined and the differences between past and current facility background noise levels are presented. This paper gives valuable information for those wishing to make acoustic measurements in the 40x80. With this report and an estimate of the noise levels produced by the noise source of interest, it should be possible to determine the signal-to-noise ratios and measurement locations to successfully perform aeroacoustic testing in the NASA Ames Research Center's 40- by 80-Foot Wind Tunnel.
Among the conceivable modern habitats to be explored for searching life on Mars are those potentially developed underground. Subsurface habitats are currently environments that, under certain physicochemical circumstances, have high thermal and hydrochemical stability [1, 2]. In planets like Mars lacking an atmospheric shield, such systems are obviously protected against radiation, which strongly alters the structure of biological macromolecules. Low porosity but fractured aquifers currently emplaced inside ancient volcano/sedimentary and hydrothermal systems act as excellent habitats [3] due to its thermal and geochemical properties. In these aquifers the temperature is controlled by a thermal balance between conduction and advection processes, which are driven by the rock composition, geological structure, water turnover of aquifers and heat generation from geothermal processes or chemical reactions [4]. Moreover, microbial communities based on chemolithotrophy can obtain energy by the oxidation of metallic ores that are currently associated to these environments. Such a community core may sustain a trophic web composed of non-autotrophic forms like heterotrophic bacteria, fungi and protozoa.
Understanding orbital mechanics is essential in space flight and navigation applications, and leveraging modern force models for flight path projection remains an important aspect in space mission design and operation. However, force models do not capture all the dynamics or perturbations in the space environment and thus are subject to errors in predicting the state vectors. The further out the predicted miss distance between spacecraft is from the time of closest approach (TCA), the larger the propagated errors in the predicted miss distance at TCA is. The dependency on these force models for spacecraft flight state prediction calls for a more reliable method that can quantify, or even reduce, these propagated errors. With recent advances in the field artificial intelligence, specifically in machine and deep learning algorithms, a model that implements these approaches can improve on the modern force model approach. The goal for this work is to provide an early-information decision-making threshold, in order to prioritize risk assessment implementation, given the ongoing increase of space objects. In analyzing the relationship of several parameters from conjunction data messages(CDMs) and solar information, early information becomes viable in miss distance prediction with unsupervised learning techniques, which learn the parameters that are linked together with miss distance and probability of collision (Pc) variables. Another approach implemented for identifying relationships within CDMs is supervised learning, in which a shallow neural network binary classifier learns to distinguish events with Pc values¡108. These parameters detected in the unsupervised process are then applied to a regression neural network, which predicts the miss distance at TCA for a specific event within a given uncertainty bound. For the regression neural network, a Long Short Term Memory (LSTM) neural network is implemented, which yields memory about each time step in an event. Using an LSTM network, the model learns to predict miss distance within 0.2km of the value measured at TCA. Although there is a limited amount of "close miss" data to train a network, the network learns to associate parameters, like large energy dissipation rates with the secondary object, with an elevated Pc
The Planetary Data System (PDS) was established in 1989 as a distributed system to assure scientific oversight. Initially the PDS followed guidelines recommended by the National Academies Committee on Data Management and Computation (CODMAC, 1982) and placed emphasis on archiving validated datasets. But overtime user demands, supported by increased computing capabilities and communication methods, have placed increasing demands on the PDS. The PDS must add additional services to better enable scientific analysis within distributed environments and to ensure that those services integrate with existing systems and data. To face these challenges the Planetary Data System (PDS) must modernize its architecture and technical implementation. The PDS 2010 project addresses these challenges. As part of this project, the PDS has three fundamental project goals that include: (1) Providing more efficient client delivery of data by data providers to the PDS (2) Enabling a stable, long-term usable planetary science data archive (3) Enabling services for the data consumer to find, access and use the data they require in contemporary data formats. In order to achieve these goals, the PDS 2010 project is upgrading both the technical infrastructure and the data standards to support increased efficiency in data delivery as well as usability of the PDS. Efforts are underway to interface with missions as early as possible and to streamline the preparation and delivery of data to the PDS. Likewise, the PDS is working to define and plan for data services that will help researchers to perform analysis in cost-constrained environments. This presentation will cover the PDS 2010 project including the goals, data standards and technical implementation plans that are underway within the Planetary Data System. It will discuss the plans for moving from the current system, version PDS 3, to version PDS 4.
The session "Astrobiology: Analogs and Applications to the Search for Life" included the folowing reports:The Search for Life on Mars Using Macroscopically Visible Microbial Mats (Stromatolites) in 3.5/3.3 Ga Cherts from the Pilbara in Australia and Barberton in South Africa as Analogues; Life in a Mars Analog: Microbial Activity Associated with Carbonate Cemented Lava Breccias from NW Spitsbergen; Groundwater-fed Iron-rich Microbial Mats in a Freshwater Creek: Growth Cycles and Fossilization Potential of Microbial Features; Episodic Fossilization of Microorganisms on an Annual Timescale in an Anthropogenically Modified Natural Environment: Geochemical Controls and Implications for Astrobiology; Proterozoic Microfossils and Their Implications for Recognizing Life on Mars; Microbial Alteration of Volcanic Glass in Modern and Ancient Oceanic Crust as a Proxy for Studies of Extraterrestrial Material ; Olivine Alteration on Earth and Mars; Searching for an Acidic Aquifer in the R!o Tinto Basin. First Geobiology Results of MARTE Project; In-Field Testing of Life Detection Instruments and Protocols in a Mars Analogue Arctic Environment; Habitability of the Shallow Subsurface on Mars: Clues from the Meteorites; Mars Analog Rio Tinto Experiment (MARTE): 2003 Drilling Campaign to Search for a Subsurface Biosphere at Rio Tinto Spain; Characterization of the Organic Matter in an Archean Chert (Warrawoona, Australia); and The Solfatara Crater, Italy: Characterization of Hydrothermal Deposits, Biosignatures and Their Astrobiological Implication.
Prokaryotic lifeforms can be observed to demonstrate many keen adaptive advantages, perhaps facilitated by a nature simplistic relative to divergent domains of life. In particular, decompartmentalized gene expression facilitates adaptation by allowing free exchange of genetic material, albeit at the cost of increased susceptibility to genetic damage. Thus, these lifeforms must compensate by embracing diverse investment strategies in an attempt to “brute force” the evolvability equation through precipitous genesis, lean metabolic efficiency, and sheer population. This prokaryotic archetype also enables symbiotic relationships with secondary mobile genetic elements known as plasmids, which have been shown to drive evolution on rapid temporal scales through processes such as conjugation and transformation. This study attempts to decipher whether these mechanisms of horizontal gene transfer (HGT) are major factors in determining prokaryote fitness within a unique isolated environment, the International Space Station (ISS). The ISS Microbial Tracking (MT) project has generated a wealth of data concerning the successive reigns of microbial genera that appear to thrive amidst harsh conditions for life. Despite relatively higher doses of ionizing radiation as compared to Earth, complications associated with microgravity, and the anti-microbial mélange deployed, microbial life still persists in this environment. The NASA GeneLab serves as a data repository and analysis platform to enable researchers to access space flight factor related data. With the use of GeneLab’s modern computational suites (computomics), phylogenetic and functional genomic investigations of HGT events were conducted on the data generated from the MT-1 project. The putative data concerning the plasmid population (plasmidome) of the ISS was algorithmically derived and compared to those of habitats with similar environmental dynamics- such as living quarters and hospitals- to investigate whether these HGT elements may play crucial role(s) in shaping the microbiome of this closed habitat that serves as the only inhabited structure in space.
The vision of this project was to improve our understanding of the processes by which microbiological information is captured and preserved in rapidly mineralizing sedimentary environments. Specifically, the research focused on the ways in which microbial mats and biofilms influence the sedimentology, geochemistry and paleontology of modem hydrothermal spring deposits in Yellowstone national Park and their ancient analogs. Toward that goal, we sought to understand how the preservation of fossil biosignatures is affected by 1) taphonomy- the natural degradation processes that affect an organism from the time of its death, until its discovery as a fossil and 2) diagenesis- longer-term, post-depositional processes, including cementation and matrix recrystallization, which collectively affect the mineral matrix that contains fossil biosignature information. Early objectives of this project included the development of observational frameworks (facies models) and methods (highly-integrated, interdisciplinary approaches) that could be used to explore for hydrothermal deposits in ancient terranes on Earth, and eventually on Mars.
Modern NASA planetary exploration missions employ complex systems of hardware and software managed by large teams of. engineers and scientists in order to study remote environments. The most complex and successful of these recent projects is the Mars Exploration Rover mission. The Computational Sciences Division at NASA Ames Research Center delivered a 30 visualization program, Viz, to the MER mission that provides an immersive, interactive environment for science analysis of the remote planetary surface. In addition, Ames provided the Athena Science Team with high-quality terrain reconstructions generated with the Ames Stereo-pipeline. The on-site support team for these software systems responded to unanticipated opportunities to generate 30 terrain models during the primary MER mission. This paper describes Viz, the Stereo-pipeline, and the experiences of the on-site team supporting the scientists at JPL during the primary MER mission.
Panoramic images with a wide field of view intend to provide a better understanding of an environment by placing objects of the environment on one seamless image. However, understanding the sizes and relative positions of the objects in a panorama is not intuitive and prone to errors because the field of view is unnatural to human perception. Scientists are often faced with the difficult task of interpreting the sizes and relative positions of objects in an environment when viewing an image of the environment on computer monitors or prints. A panorama can display an object that appears to be to the right of the viewer when it is, in fact, behind the viewer. This misinterpretation can be very costly, especially when the environment is remote and/or only accessible by unmanned vehicles. A 270 cylindrical display has been developed that surrounds the viewer with carefully calibrated panoramic imagery that correctly engages their natural kinesthetic senses and provides a more accurate awareness of the environment. The cylindrical immersive display offers a more natural window to the environment than a standard cubic CAVE (Cave Automatic Virtual Environment), and the geometry allows multiple collocated users to simultaneously view data and share important decision-making tasks. A CAVE is an immersive virtual reality environment that allows one or more users to absorb themselves in a virtual environment. A common CAVE setup is a room-sized cube where the cube sides act as projection planes. By nature, all cubic CAVEs face a problem with edge matching at edges and corners of the display. Modern immersive displays have found ways to minimize seams by creating very tight edges, and rely on the user to ignore the seam. One significant deficiency of flat-walled CAVEs is that the sense of orientation and perspective within the scene is broken across adjacent walls. On any single wall, parallel lines properly converge at their vanishing point as they should, and the sense of perspective within the scene contained on only one wall has integrity. Unfortunately, parallel lines that lie on adjacent walls do not necessarily remain parallel. This results in inaccuracies in the scene that can distract the viewer and subtract from the immersive experience of the CAVE.
A consortium consisting of the NASA Orbital Debris Program Office, U.S. Air Force's Space and Missile Systems Center, the Aerospace Corporation, and University of Florida is planning a series of hypervelocity impact experiments on mockup targets at the U.S. Air Force's Arnold Engineering Development Complex (AEDC) in early 2014. The target for the first experiment resembles a rocket upper stage whereas the target for the second experiment represents a typical 60‐cm/50‐kg class payload that incorporates modern spacecraft materials and components as well as exterior wrap of multi‐layer insulation and three solar panels. The projectile is designed with the maximum mass that AEDC's Range G two‐stage light gas gun can accelerate to an impact speed of 7 km/sec. The impact energy is expected to be close to 15 MJ to ensure catastrophic destruction of the target after the impact. Low density foam panels are installed inside the target chamber to slow down and soft‐catch the fragments for post‐impact processing. Diagnostic instruments, such as x‐ray and high speed optical cameras, will also be used to record the breakup process. The main goal of this "DebriSat" project is to characterize the physical properties, including size, mass, shape, and density distributions, of orbital debris that would be generated by a hypervelocity collision involving an upper stage or a modern satellite in the low Earth orbit environment. In addition, representative fragments will be selected for laboratory optical and radar measurements to allow for better interpretation of data obtained by telescope and radar observations. This paper will provide a preliminary report of the impact results and the plans to process, measure, and analyze the fragments.
Institutions need ways to retain valuable information even as experienced individuals leave an organization. Modern electronic systems have enough capacity to retain large quantities of information that can mitigate the loss of experience. Performance information for long-term space applications is relatively scarce and specific information (typically held by a few individuals within a single project) is often rather narrowly distributed. Spacecraft operate under severe conditions and the consequences of hardware and/or system failures, in terms of cost, loss of information, and time required to replace the loss, are extreme. These risk factors place a premium on appropriate choice of materials and components for space applications. An expert system is a very cost-effective method for sharing valuable and scarce information about spacecraft performance. Boeing has an artificial intelligence software package, called the Boeing Expert System Tool (BEST), to construct and operate knowledge bases to selectively recall and distribute information about specific subjects. A specific knowledge base to evaluate the on-orbit performance of selected materials on spacecraft has been developed under contract to the NASA SEE program. The performance capabilities of the Spacecraft Materials Selector (SMS) knowledge base are described. The knowledge base is a backward-chaining, rule-based system. The user answers a sequence of questions, and the expert system provides estimates of optical and mechanical performance of selected materials under specific environmental conditions. The initial operating capability of the system will include data for Kapton, silverized Teflon, selected paints, silicone-based materials, and certain metals. For situations where a mission profile (launch date, orbital parameters, mission duration, spacecraft orientation) is not precisely defined, the knowledge base still attempts to provide qualitative observations about materials performance and likely exposures. Prior to the NASA contract, a knowledge base, the Spacecraft Environments Assistant (SEA,) was initially developed by Boeing to estimate the environmental factors important for a specific spacecraft mission profile. The NASA SEE program has funded specific enhancements to the capability of this knowledge base. The SEA qualitatively identifies over 25 environmental factors that may influence the performance of a spacecraft during its operational lifetime. For cases where sufficiently detailed answers are provided to questions asked by the knowledge base, atomic oxygen fluence levels, proton and/or electron fluence and dose levels, and solar exposure hours are calculated. The SMS knowledge base incorporates the previously developed SEA knowledge base. A case history for previous flight experiment will be shown as an example, and capabilities and limitations of the system will be discussed.
The NASA Cooperative Agreement NAG4-210 was granted under the FY2000 Faculty Awards for Research (FAR) Program. The project was proposed to examine the effects of charged particles and neutrons on selected random access memory (RAM) technologies. The concept of the project was to add to the current knowledge of Single Event Effects (SEE) concerning RAM and explore the impact of selected forms of radiation on Error Detection and Correction Systems. The project was established as an extension of a previous FAR awarded to Prairie View A&M University (PVAMU), under the direction of Dr. Richard Wilkins as principal investigator. The NASA sponsored Center for Applied Radiation Research (CARR) at PVAMU developed an electronic test-bed to explore and quantify SEE on RAM from charged particles and neutrons. The test-bed was developed using 486DX microprocessor technology (PC-104) and a custom test board to mount RAM integrated circuits or other electronic devices. The test-bed had two configurations - a bench test version for laboratory experiments and a 400 Hz powered rack version for flight experiments. The objectives of this project were to: 1) Upgrade the Electronic Test-bed (ETB) to a Pentium configuration; 2) Accommodate more than only 8 Mbytes of RAM; 3) Explore Error Detection and Correction Systems for radiation effects; 4) Test modern RAM technologies in radiation environments.
This Software Guide (SG) describes the software developed to test the Assessment Environment for Complex Systems (AECS) by the West Virginia High Technology Consortium (WVHTC) Foundation's Mission Systems Group (MSG) for the National Aeronautics and Space Administration (NASA) Aeronautics Research Mission Directorate (ARMD). This software is referred to as the AECS Test Project throughout the remainder of this document. AECS provides a framework for developing, simulating, testing, and analyzing modern avionics systems within an Integrated Modular Avionics (IMA) architecture. The purpose of the AECS Test Project is twofold. First, it provides a means to test the AECS hardware and system developed by MSG. Second, it provides an example project upon which future AECS research may be based. This Software Guide fully describes building, installing, and executing the AECS Test Project as well as its architecture and design. The design of the AECS hardware is described in the AECS Hardware Guide. Instructions on how to configure, build and use the AECS are described in the User's Guide. Sample AECS software, developed by the WVHTC Foundation, is presented in the AECS Software Guide. The AECS Hardware Guide, AECS User's Guide, and AECS Software Guide are authored by MSG. The requirements set forth for AECS are presented in the Statement of Work for the Assessment Environment for Complex Systems authored by NASA Dryden Flight Research Center (DFRC). The intended audience for this document includes software engineers, hardware engineers, project managers, and quality assurance personnel from WVHTC Foundation (the suppliers of the software), NASA (the customer), and future researchers (users of the software). Readers are assumed to have general knowledge in the field of real-time, embedded computer software development.
The High-Rate Delay Tolerant Networking (HDTN) project has taken a distributed service-based approach to the development of a highly efficient delay tolerant networking (DTN) implementation. Through the analysis of many DTN implementations, system and mission requirements as well as the DTN protocol specifications, HDTN has worked to infuse modern computing technologies into the NASA approach to interplanetary networking. The initial use case of the HDTN software runs on a hypervisor representative of the International Space Station (ISS) DTN Gateway. In this scenario, multiple emulated payloads will send science data through HDTN to a mission operations center. HDTN will provide store and forward capability as well as network flow management. This paper discusses the infusion path of cognitive networking technologies in the NASA SCaN networks using the DTN architecture and protocols as the basis for cognitive routing and network management capabilities. HDTN has been developing the Bundle Protocol encoding and decoding mechanisms and messaging framework that can be used as the basis for integrating DTN with various learning and decision-making processes. The concepts of distributed computing, network virtualization, software defined networking and delay tolerant networking are basic building blocks which will further the development of cognitive networking. In addition to discussion of the HDTN software development and testing, this paper examines the role that each of these technologies play in the evolution of the current state of space networking into an intelligent network of networks.