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The Deep Space One (DS1) mission, scheduled to fly in 1998, will be the first NASA spacecraft to feature an on-board planner. The planner is part of an artificial intelligence based control architecture that comprises the planner/scheduler, a plan execution engine, and a model-based fault diagnosis and reconfiguration engine...This paper describes the on-board planning and scheduling component of the DS1 autonomy architecture.
Computer applications for design have evolved rapidly over the past several decades, and significant payoffs are being achieved by organizations through reductions in design cycle times. These applications are overwhelmed by the requirements imposed during complex, open engineering systems design. Organizations are faced with a number of different methodologies, numerous legacy disciplinary tools, and a very large amount of data. Yet they are also faced with few interdisciplinary tools for design collaboration or methods for achieving the revolutionary product designs required to maintain a competitive advantage in the future. These organizations are looking for a software infrastructure that integrates current corporate design practices with newer simulation and solution techniques. Such an infrastructure must be robust to changes in both corporate needs and enabling technologies. In addition, this infrastructure must be user-friendly, modular and scalable. This need is the motivation for the research described in this dissertation. The research is focused on the development of an open computing infrastructure that facilitates product and process design. In addition, this research explicitly deals with human interactions during design through a model that focuses on the role of a designer as that of decision-maker. The research perspective here is taken from that of design as a discipline with a focus on Decision-Based Design, Theory of Languages, Information Science, and Integration Technology. Given this background, a Model of IPPD is developed and implemented along the lines of a traditional experimental procedure: with the steps of establishing context, formalizing a theory, building an apparatus, conducting an experiment, reviewing results, and providing recommendations. Based on this Model, Design Processes and Specification can be explored in a structured and implementable architecture. An architecture for exploring design called DREAMS (Developing Robust Engineering Analysis Models and Specifications) has been developed which supports the activities of both meta-design and actual design execution. This is accomplished through a systematic process which is comprised of the stages of Formulation, Translation, and Evaluation. During this process, elements from a Design Specification are integrated into Design Processes. In addition, a software infrastructure was developed and is called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment). This represents a virtual apparatus in the Design Experiment conducted in this research. IMAGE is an innovative architecture because it explicitly supports design-related activities. This is accomplished through a GUI driven and Agent-based implementation of DREAMS. A HSCT design has been adopted from the Framework for Interdisciplinary Design Optimization (FIDO) and is implemented in IMAGE. This problem shows how Design Processes and Specification interact in a design system. In addition, the problem utilizes two different solution models concurrently: optimal and satisfying. The satisfying model allows for more design flexibility and allows a designer to maintain design freedom. As a result of following this experimental procedure, this infrastructure is an open system that it is robust to changes in both corporate needs and computer technologies. The development of this infrastructure leads to a number of significant intellectual contributions: 1) A new approach to implementing IPPD with the aid of a computer; 2) A formal Design Experiment; 3) A combined Process and Specification architecture that is language-based; 4) An infrastructure for exploring design; 5) An integration strategy for implementing computer resources; and 6) A seamless modeling language. The need for these contributions is emphasized by the demand by industry and government agencies for the development of these technologies.
Personnel in the NASA Glenn Research Center Network and Architectures branch have performed a variety of research related to space-based sensor webs, network centric operations, security and delay tolerant networking (DTN). Quality documentation and communications, real-time monitoring and information dissemination are critical in order to perform quality research while maintaining low cost and utilizing multiple remote systems. This has been accomplished using a variety of Internet technologies often operating simultaneously. This paper describes important features of various technologies and provides a number of real-world examples of how combining Internet technologies can enable a virtual team to act efficiently as one unit to perform advanced research in operational systems. Finally, real and potential abuses of power and manipulation of information and information access is addressed.
Here, we develop a microscopic diagrammatic theory for cavity-mediated photon scattering in a topological one-dimensional insulator described by the Su–Schrieffer–Heeger model. Within the velocity-gauge formulation, we derive the photon self-energy and vertex corrections arising from virtual electron–hole excitations coupled to a quantized cavity mode, and we evaluate the resulting polariton dispersion and two-photon correlation spectra. Our analysis shows that vacuum fluctuations of the cavity field induce a momentum-resolved self-energy that mixes conduction and valence bands through virtual photon exchange, producing interband hybridization and avoided crossings in the electronic dispersion. This “cavity dressing” is symmetry-dependent, vanishing at the Brillouin-zone edge where the dipole matrix element is zero, and its strength is controlled by the spatial coherence range ζ ≈ (l c /a) 2 of virtual excitations. We further examine how the cavity modifies nonlinear optical observables, including the Kerr nonlinearity and biphoton spectral entanglement, and identify the regimes where these effects become sensitive to the underlying topological phase. The theoretical framework established here provides a unified description of light–matter coupling in topological and polaritonic systems, bridging solid-state cavity QED with the emerging field of cavity-modified quantum materials. Our results suggest that engineered photonic environments can coherently reshape the electronic landscape of topological insulators, offering new routes to control collective electronic and optical phenomena through vacuum-field fluctuations.
Managing traffic between the Earth-Moon and Earth-Mars is a complex process requiring significant investment in resources and expertise at NASA. INSPiRE improves the performance of space networks by enabling a dynamic re-configuration process that works for any mixed topology over a heterogeneous and multi-vendor network. To achieve the desired functionality, INSPiRE incorporates a set of algorithms, machine learning processes, and policy inference to handle unpredictable, disruptive events. INSPiRE draws parallels from the current notion of the 3GPP (5G and beyond) Network Slicing approach, where the same physical network divides into several virtual networks, and for each of these virtual networks, there is a guaranteed Quality of Service for the missions that they serve.
The 3D Scanning Lab uses a number of technologies to capture 3D surface data. Those technologies are structured light scanning, discrete point measurement photogrammetry and Light Detecting and Ranging(LIDAR). Structured light is a non-contact optical technique used to capture as built surface geometries quickly and accurately. LIDAR is a laser scanning technique used to capture 3D surfaces. And photogrammetry uses a certified DSLR camera to measure discrete registered and non-registered points in 3D space. MSFC’s 3D Scanning Team uses 3D scanning to provide hardware inspections, reverse engineered CAD models, manufacturing/process development and digital assemblies. The inspection process compares the captured data to CAD, providing a color plot detailing the deviations of the scan data to the CAD model. Dimensional measurements and GD&T can also be interrogated. Inspection can provide scan-to-scan data comparisons which is ideal for assessing tested hardware, e.g. comparing data captured before and after hardware testing. Reverse engineering is used to develop CAD models from scan data. This is useful for heritage hardware studies, developing building or structural models and inputs for simulation studies and design efforts. The lab uses the 3D surface scan data to drive manufacturing/machining processes, termed match machining. This technique has been used to modify nozzles, injectors, additive manufactured parts, composite barrel sections, etc. Parts of an assembly can be scanned and assembled in a virtual environment providing an accurate 3D representation of the assembled hardware in its as-scanned state. This can provide detailed information of internal components that would otherwise not be accessible.
We believe that the next evolutionary step in supporting wide-area application and services delivery to customers is a network framework that provides for collocation of applications and services at distinct sites in the network, an interconnection between these sites that is performance optimized for these applications, and value-added services for applications. We use the term IsoWAN to describe an advanced, isolated network interconnect services framework that will enable applications to be more secure, and able to access and be in use in both local and remote environments. The main functions of an IsoWAN are virtual localization of application services, an application service interface, coordinated delivery of applications and associated data to the customer, and supporting collaborative application development for customers. An initial pilot network between three NASA Centers: Ames Research Center, the Jet Propulsion Laboratory, and Marshall Space Flight Center, has been built and its properties will be discussed.
Fire protection of critical space assets, including launch and fueling facilities and manned flight hardware, demands automatic sensors for continuous monitoring, and in certain high-threat areas, fast-reacting automatic suppression systems. Perhaps the most essential characteristic for these fire detection and suppression systems is high reliability; in other words, fire detectors should alarm only on actual fires and not be falsely activated by extraneous sources. Existing types of fire detectors have been greatly improved in the past decade; however, fundamental limitations of their method of operation leaves open a significant possibility of false alarms and restricts their usefulness. At the Civil Engineering Laboratory at Tyndall Air Force Base in Florida, a new type of fire detector is under development which 'sees' a fire visually, like a human being, and makes a reliable decision based on known visual characteristics of flames. Hardware prototypes of the Machine Vision (MV) Fire Detection System have undergone live fire tests and demonstrated extremely high accuracy in discriminating actual fires from false alarm sources. In fact, this technology promises to virtually eliminate false activations. This detector could be used to monitor fueling facilities, launch towers, clean rooms, and other high-value and high-risk areas. Applications can extend to space station and in-flight shuttle operations as well; fiber optics and remote camera heads enable the system to see around obstructed areas and crew compartments. The capability of the technology to distinguish fires means that fire detection can be provided even during maintenance operations, such as welding.
Measurement and Controls Data Acquisition System (MCDAS) is an application program that integrates the functions of two stand-alone programs: one for acquisition of data, the other for controls. MCDAS facilitates and improves testing of complex engineering systems by helping to perform calibration and setup of test systems and acquisition, dissemination, and processing of data. Features of MCDAS include an intuitive, user-friendly graphical user interface, a capability for acquiring data at rates greater than previously possible, cooperation between the data-acquisition software subsystem and alarm-checking and analytical components of the control software subsystem, and a capability for dissemination of data through fiber optics and virtual and wide-area networks, including networks that contain hand-held display units. The integration of the data acquisition and control software offers a safety advantage by making alarm information available to the control software in a more timely manner. By enabling the use of hand-held devices, MCDAS reduces the time spent by technicians asking for screen updates to determine effects of setup actions. Previously recorded data can be processed without interruption to current acquisition of data. Analysts can continue to view test parameters while test-data files are being generated.
NASA is preparing to land the first woman and first person of color on the Moon within the next decade and establish a permanent sustainable human presence before sending humans onto Mars. To ensure the success of these missions, NASA has performed operational testing in terrestrial, aquatic, and laboratory analog environments that simulate Lunar and Martian environmental characteristics to evaluate exploration concepts of operations (ConOps), engineering design requirements, science support needs, mission operations techniques, and crew training. Terrestrial analogs include Desert Research and Technology Studies (D-RATS), Biologic Analog Science Associated with Lava Terrains (BASALT), and Next Space Technologies for Exploration Partnerships (NextSTEP)Habitat Ground Testing. Aquatic analogs include NASA Extreme Environment Mission Operations (NEEMO) and Pavilion Lake Research Project (PLRP).Laboratory analogs include the Neutral Buoyancy Laboratory (NBL), Active Response Gravity Offload System(ARGOS), rock yards, and virtual and hybrid reality simulation environments. While no single Earth-based analog environment is perfect for simulating all characteristics of other planetary surfaces, testing across multiple locations leverages the strengths of each to provide an integrated understanding of how to best conduct real spaceflight surface exploration missions.
Technical knowledge is essential to the work done by NASA practitioners. So it may be surprising to learn that the most ingenious and elegant solutions to project challenges often arise not from a specific technical discipline perspective, but from a systems-focused mindset. While technical discipline expertise is a critical component of project success, sometimes the simplest resolution to a problem involves a systems-wide solution. Because of this, encouraging a systems mentality among project team members can be a powerful tool in mitigating risk and eliminating threats. Join us for an exploration of the critical ways in which a systems engineering and integration perspective can enhance project management efforts. Presenter Bo Bejmuk is the former Space Shuttle Orbiter Program Director and manager of Sea Launch Program operations and development for Boeing. He recently served as Chairman of the Standing Review Board for the NASA Constellation Program. Moderator Ramien Pierre is from NASA's Academy for Program/Project and Engineering Leadership (APPEL).
There are a number of architecture models for implementing Integrated Systems Health Management (ISHM) capabilities. For example, approaches based on the OSA-CBM and OSA-EAI models, or specific architectures developed in response to local needs. NASA s John C. Stennis Space Center (SSC) has developed one such version of an extensible architecture in support of rocket engine testing that integrates a palette of functions in order to achieve an ISHM capability. Among the functional capabilities that are supported by the framework are: prognostic models, anomaly detection, a data base of supporting health information, root cause analysis, intelligent elements, and integrated awareness. This paper focuses on the role that intelligent elements can play in ISHM architectures. We define an intelligent element as a smart element with sufficient computing capacity to support anomaly detection or other algorithms in support of ISHM functions. A smart element has the capabilities of supporting networked implementations of IEEE 1451.x smart sensor and actuator protocols. The ISHM group at SSC has been actively developing intelligent elements in conjunction with several partners at other Centers, universities, and companies as part of our ISHM approach for better supporting rocket engine testing. We have developed several implementations. Among the key features for these intelligent sensors is support for IEEE 1451.1 and incorporation of a suite of algorithms for determination of sensor health. Regardless of the potential advantages that can be achieved using intelligent sensors, existing large-scale systems are still based on conventional sensors and data acquisition systems. In order to bring the benefits of intelligent sensors to these environments, we have also developed virtual implementations of intelligent sensors.
The authors have identified a software tool suite that will support NASA's Virtual Mission (VM) effort. This is accomplished by transforming a spreadsheet database of mission events, task inputs and outputs, timelines, and organizations into process visualization tools and a Vdot process management model that includes embedded analysis software as well as requirements and information related to data manipulation and transfer. This paper describes the progress to date, and the application of the Virtual Mission to not only Constellation but to other architectures, and the pertinence to other aerospace applications. Vdot s intuitive visual interface brings VMs to life by turning static, paper-based processes into active, electronic processes that can be deployed, executed, managed, verified, and continuously improved. A VM can be executed using a computer-based, human-in-the-loop, real-time format, under the direction and control of the NASA VM Manager. Engineers in the various disciplines will not have to be Vdot-proficient but rather can fill out on-line, Excel-type databases with the mission information discussed above. The author s tool suite converts this database into several process visualization tools for review and into Microsoft Project, which can be imported directly into Vdot. Many tools can be embedded directly into Vdot, and when the necessary data/information is received from a preceding task, the analysis can be initiated automatically. Other NASA analysis tools are too complex for this process but Vdot automatically notifies the tool user that the data has been received and analysis can begin. The VM can be simulated from end-to-end using the author s tool suite. The planned approach for the Vdot-based process simulation is to generate the process model from a database; other advantages of this semi-automated approach are the participants can be geographically remote and after refining the process models via the human-in-the-loop simulation, the system can evolve into a process management server for the actual process.
The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) is a software system to simulate human performance in support of human reliability analysis (HRA) in nuclear power plants. This paper summarizes recent work to integrate HUNTER with a plant simulator, namely the Rancor Microworld Simulator. Rancor is an offshoot of earlier work at Idaho National Laboratory (INL) to support plant modernization. The graphical software tools used to mimic digital human-system interface upgrades at INL’s Human Systems Simulation Laboratory were linked to the Rancor Microworld Simulator, an INL-developed simplified plant model. HUNTER becomes a “virtual operator” coupled to the Rancor simulator, thereby allowing a tight coupling between a digital human twin and a digital twin of the plant. Rancor-HUNTER may be run through Monte Carlo iterations across a dynamic range of performance shaping factors, thereby producing distributions of human performance in terms of procedure paths, errors instantiations, and task durations. This paper overviews the various unique features of Rancor-HUNTER and presents an example run of Rancor-HUNTER for a startup scenario.
The issues related to developing an environment in which engineering systems can be implemented on MIMD machines are discussed. The problem is presented in terms of implementing the finite element method under such an environment. However, neither the concepts nor the prototype implementation environment are limited to this application. The topics discussed include: the ability to schedule and synchronize tasks efficiently; granularity of tasks; load balancing; and the use of a high level language to specify parallel constructs, manage data, and achieve portability. The objective of developing a virtual machine concept which incorporates solutions to the above issues leads to a design that can be mapped onto loosely coupled, tightly coupled, and hybrid systems.
According to a Nielsen survey at the time of this reporting, 41% of all households have a game console. This is one market in which NASA has been absent from education and outreach efforts. Kinect Engineering with Learning (KEWL) is made to enter into that market and bring NASA education and outreach to a very familiar venue. KEWL creates an education and outreach experience that is more participatory, both in a school and museum environment. KEWL is a set of applications that runs on an Xbox 360 using the Kinect controller used for education and outreach. These applications currently include: Train R2, a visual simulation of Robonaut 2 that allows students to control a virtual R2 in a game environment; Drive R2, an interface using the Xbox 360 and Kinect controller that allows students to control the real R2 using the methods they learned playing Train R2; ISS experience, a visual tour of the interior of the International Space Station where students use their body to fly through the virtual ISS; Gravity Ball, a simulation of throwing balls in the gravity of different planets; Solar Array repair, a simulation of the simplified STS-121 solar array repair mission; and PlaySpace, a Mars/Moon application that allows students to experience different aspects of Mars/Moon. Users can "fly through" the ISS using their body, allowing an experience similar to what an astronaut would have on orbit. In PlaySpace, users can fly over the surface of Mars and view surface data obtained by Mars rovers. Users of Train R2 and Drive R2 can experience what it is like to control a robot over a distance with a time delay, simulating the time delay that would occur between ground control and an on-orbit robot. The initial ISS experiences were built using parts of code from the NASA Enigma software. The models used in these experiences were also from the Integrated Graphics Operations and Analysis Lab model database. The PlaySpace experience incorporates surface data obtained from NASA rovers and satellites and was built by NASA JPL.
The Lunar Prospector was co-developed by NASA Ames Research Center and Lockheed Martin, and was launched on January 6th, 1998. Its mission is to search for water ice and various elements in the Moon's surface, map its magnetic and gravity fields, and detect volcanic activity. For the first time, the World Wide Web is being used to graphically display near-real-time data from a planetary exploration mission to the global public. Science data from the craft's instruments, as well as engineering data for the spacecraft subsystems, are continuously displayed in time-varying XY plots. The craft's current location is displayed relative to the whole Moon, and as an off-craft observer would see in the reference frame of the craft, with the lunar terrain scrolling underneath. These features are implemented as Java applets. Analyzed data (element and mass distribution) is presented as 3D lunar maps using VRML and Javascript. During the development phase, implementations of the Java Virtual Machine were just beginning to mature enough to adequately accommodate our target featureset; incomplete and varying implementations were the biggest bottleneck to our ideal of ubiquitous browser access. Bottlenecks notwithstanding, the reaction from the Internet community was overwhelmingly enthusiastic.
In a spacecraft cabin environment, the size range of indoor aerosols is much larger and they persist longer than on Earth because they are not removed by gravitational settling. A previous aerosol experiment in 1991 documented that over 90 of the mass concentration of particles in the NASA Space Shuttle air were between 10 m and 100 m based on measurements with a multi-stage virtual impactor and a nephelometer (Liu et al. 1991). While the now-retired Space Shuttle had short duration missions (less than two weeks), the International Space Station (ISS) has been continually inhabited by astronauts for over a decade. High concentrations of inhalable particles on ISS are potentially responsible for crew complaints of respiratory and eye irritation and comments about 'dusty' air. Air filtration is the current control strategy for airborne particles on the ISS, and filtration modeling, performed for engineering and design validation of the air revitalization system in ISS, predicted that PM requirements would be met. However, aerosol monitoring has never been performed on the ISS to verify PM levels. A flight experiment is in preparation which will provide data on particulate matter in ISS ambient air. Particles will be collected with a thermophoretic sampler as well as with passive samplers which will extend the particle size range of sampling. Samples will be returned to Earth for chemical and microscopic analyses, providing the first aerosol data for ISS ambient air.