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The political and legal repercussions of space programs both domestic and foreign are explored. Emphasis are placed on earth resources exploration (exploration based on information rights), jurisdictional problems, problems of sharing space benefits with other countries, criminal launch and use of satellites, intrusion into territorial sovereignty, and problems of establishing data ownership.
Space Exposed Experiment Developed for Students (SEEDS), resulted in the distribution of over 132,000 SEED kits in 1990. The kits contained Rutger's tomato seeds that had flown on the Long Duration Exposure Facility (LDEF) as well as seeds that had been stored in a climate controlled warehouse for the same period of time. Students compared germination and growth rate characteristics of the two seeds groups and returned data to NASA for analysis. The scientific information gained was valuable as students shared the excitement of taking part in a national project. Of greater importance was the subsequent interest generated in science education.
Activities and accomplishments of the first six months of the Consortium for International Earth Science Information Network (CIESIN's) 1992 technical program have focused on four main missions: (1) the development and implementation of plans for initiation of the Socioeconomic Data and Applications Center (SEDAC) as part of the EOSDIS Program; (2) the pursuit and development of a broad-based global change information cooperative by providing systems analysis and integration between natural science and social science data bases held by numerous federal agencies and other sources; (3) the fostering of scientific research into the human dimensions of global change and providing integration between natural science and social science data and information; and (4) the serving of CIESIN as a gateway for global change data and information distribution through development of the Global Change Research Information Office and other comprehensive knowledge sharing systems.
This paper discusses the implementation and use of reflexive reasoning in real-time, distributed knowledge-based applications. Recently there has been a great deal of interest in agent-oriented systems. Implementing such systems implies a mechanism for sharing knowledge, goals and other state information among the agents. Our techniques facilitate an agent examining both state information about other agents and the parameters of the knowledge-based system shell implementing its reasoning algorithms. The shell implementing the reasoning is the Distributed Artificial Intelligence Toolkit, which is a derivative of CLIPS.
The Advanced Life Support (ALS) Program has recently accelerated an effort to develop an On-line Project Information System (OPIS) for research project and technology development data centralization and sharing. There has been significant advancement in the On-line Project Information System (OPIS) over the past year (Hogan et al, 2004). This paper presents the resultant OPIS development approach. OPIS is being built as an application framework consisting of an uderlying Linux/Apache/MySQL/PHP (LAMP) stack, and supporting class libraries that provides database abstraction and automatic code generation, simplifying the ongoing development and maintenance process. Such a development approach allows for quick adaptation to serve multiple Programs, although initial deployment is for an ALS module. OPIS core functionality will involve a Web-based annual solicitation of project and technology data directly from ALS Principal Investigators (PIs) through customized data collection forms. Data provided by PIs will be reviewed by a Technical Task Monitor (TTM) before posting the information to OPIS for ALS Community viewing via the Web. Such Annual Reports will be permanent, citable references within OPIS. OPlS core functionality will also include Project Home Sites, which will allow PIS to provide updated technology information to the Community in between Annual Report updates. All data will be stored in an object-oriented relational database, created in MySQL(Reistered Trademark) and located on a secure server at NASA Ames Research Center (ARC). Upon launch, OPlS can be utilized by Managers to identify research and technology development (R&TD) gaps and to assess task performance. Analysts can employ OPlS to obtain the current, comprehensive, accurate information about advanced technologies that is required to perform trade studies of various life support system options. ALS researchers and technology developers can use OPlS to achieve an improved understanding of the NASA and ALS Program needs and to understand how other researchers and technology developers are addressing those needs. OPlS core functionality will launch for 'Ihe ALS Program in October, 2005. However, the system has been developed with the ability to evolve with Program needs. Because of open-source construction, software costs are minimized. Any functionality that is technologically feasible can be built into OPIS, and OPlS can expand through module cloning and adaptation, to any level deemed useful to the Agency.
A computer program for scheduling the activities of multiple agents that share limited resources has been incorporated into the Automated Scheduling and Planning Environment (ASPEN) software system, aspects of which have been reported in several previous NASA Tech Briefs articles. In the original intended application, the agents would be multiple spacecraft and/or robotic vehicles engaged in scientific exploration of distant planets. The program could also be used on Earth in such diverse settings as production lines and military maneuvers. This program includes a planning/scheduling subprogram of the iterative repair type that reasons about the activities of multiple agents at abstract levels in order to greatly improve the scheduling of their use of shared resources. The program summarizes the information about the constraints on, and resource requirements of, abstract activities on the basis of the constraints and requirements that pertain to their potential refinements (decomposition into less-abstract and ultimately to primitive activities). The advantage of reasoning about summary information is that time needed to find consistent schedules is exponentially smaller than the time that would be needed for reasoning about the same tasks at the primitive level.
This software is provided by the Mars Relay Operations Service (MaROS) task to a variety of Mars projects for the purpose of coordinating communications sessions between landed spacecraft assets and orbiting spacecraft assets at Mars. The Information Management Service centralizes a set of functions previously distributed across multiple spacecraft operations teams, and as such, greatly improves visibility into the end-to-end strategic coordination process. Most of the process revolves around the scheduling of communications sessions between the spacecraft during periods of time when a landed asset on Mars is geometrically visible by an orbiting spacecraft. These relay sessions are used to transfer data both to and from the landed asset via the orbiting asset on behalf of Earth-based spacecraft operators. This software component is an application process running as a Java virtual machine. The component provides all service interfaces via a Representational State Transfer (REST) protocol over https to external clients. There are two general interaction modes with the service: upload and download of data. For data upload, the service must execute logic specific to the upload data type and trigger any applicable calculations including pass delivery latencies and overflight conflicts. For data download, the software must retrieve and correlate requested information and deliver to the requesting client. The provision of this service enables several key advancements over legacy processes and systems. For one, this service represents the first time that end-to-end relay information is correlated into a single shared repository. The software also provides the first multimission latency calculator; previous latency calculations had been performed on a mission-by-mission basis.
The crew on-board the International Space Station (ISS) have to be prepared for any possible emergency. The emergencies of most concern are a fire, depressurization or a toxic atmosphere. The crew members train on the ground before launch but also need to practice their emergency response skills while they are on orbit for 6 months. On-Board Training (OBT) events for emergency response proficiency used to require the crew and ground teams to use paper "scripts" that showed the path through the emergency procedures. This was not very realistic since the participants could read ahead and never deviate from this scripted path. The new OBT emergency simulator allows the crew to view dynamic information on an iPad only when it would become available during an event. The simulator interface allows the crew member to indicate hatch closures, don and doff masks, read pressures, and sample smoke or atmosphere levels. As the crew executes their actions using the on-board simulator, the ground teams are able to monitor those actions via ground display data flowing through the ISS Ku Band communication system which syncs the on-board simulator software with a ground simulator which is accessible in all the control centers. The OBT Working Group (OBT WG), led by the Chief Training Office (CTO) at Johnson Space center is a Multilateral working group with partners in Russia, Japan, Germany and U.S.A. The OBTWG worked together to create a simulator based on these principles: (a) Create a dynamic simulation that gives real-time data feedback; (b) Maintain real-time interface between Mission Control Centers and crew during OBTs; (c) Provide flexibility for decision making during drill execution; (d) Materially reduce Instructor and Flight Control Team man-hour costs involved with developing, updating, and maintaining emergency OBT cases/scenarios; and (e) Introduce an element of surprise to emergency scenarios so the team can't tell the outcome of the case by reading ahead in a paper script. This paper details some of the background as the project evolved with the International Partners. It also provides more details on how the simulator information for the crew is also shared with the ground teams. Finally, the paper will discuss how this remote simulator concept can be useful for future, longer term space missions.
Brief updates of Digital Information Platform (DIP) plans for platform-enabled sustainable aviation services. DIP will provide the capability to integrate key flight information from multiple sources and make it easier to access data critical to developing services using advanced techniques such as machine learning. NASA will share ML-based microservices on the platform for industry to use as reference implementations. The platform will support an ecosystem to share reusable services and promote innovation for digital information.
NASA will visit Boeing in Fairfax, VA to share an overview of the Digital Information Platform (DIP) and the digital aviation services that can be enabled from the data discovered on the platform. The goal is to walk though the goals, objectives and concept as well as the problem statements under consideration for a flight deck service to improve airspace operational efficiency for long-haul oceanic flights. Potential digital service capabilities will be discussed with goal to solicit input from Boeing attendees.
As the governing body of flight operations in the highly anticipated emergent area of Upper Class E airspace (60,000 ft and above), the Federal Aviation Administration (FAA) has recognized the potential for a possible extensible traffic management system for new entrants into this domain. Following the successes with Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and Advanced / Urban Air Mobility (AAM / UAM) Traffic Management programs, FAA put forth an initial concept of operations for supporting the start of the Upper Class E Traffic Management (ETM) concept. Like UTM and AAM / UAM, ETM is envisioned to also be a community-based, industry driven cooperative management concept. However, tailoring it to be adaptable to the atmospheric communication, navigation, and surveillance deficits, as well as the diverse vehicle and mission profiles operating in the ETM environment will be the challenge. As such, the National Aeronautics and Space Administration (NASA) Ames Research Center has been investigating several technologies that will help enable industry in the development of this new type of cooperative operating environment. These technologies are being prototyped and will be tested in a collaborative evaluation of an initial ETM system in late 2023. The evaluation will concentrate on building out ETM system technologies that will inform the participants regarding operational intent sharing, strategic conflict detection, and the resultant deconfliction process. In addition to the technical aspects, key roles and responsibilities will need to be defined. This will be done through exploring community-agreed upon Cooperative Operating Practices (COPs) that include procedures and capabilities to aid in timely, strategic conflict identification and resolution to be developed during the evaluation. As an initial step to the evaluation, the ETM research team at NASA Ames solicited industry feedback on various aspects of ETM operations from subject matter experts. A virtual tabletop walkthrough session was held over a two-day period to follow a roadmap through the functional steps needed to build COPs, focusing on strategic conflict detection and resolution. Overall, the ETM tabletop provided insights into how the community wanted to instantiate the generation and sharing of operational intent, detect strategic conflicts and resolve those conflicts using a preliminary set of procedural community-agreed upon COPs.
As the governing body of flight operations in the highly anticipated emergent area of Upper Class E airspace (60,000 ft and above), the Federal Aviation Administration (FAA) has recognized the potential for a possible extensible traffic management system for new entrants into this domain. Following the successes with Unmanned Aircraft Systems (UAS) Traffic Management (UTM) and Advanced / Urban Air Mobility (AAM / UAM) Traffic Management programs, FAA put forth an initial concept of operations for supporting the start of the Upper Class E Traffic Management (ETM) concept. Like UTM and AAM / UAM, ETM is envisioned to also be a community-based, industry driven cooperative management concept. However, tailoring it to be adaptable to the atmospheric communication, navigation, and surveillance deficits, as well as the diverse vehicle and mission profiles operating in the ETM environment will be the challenge. As such, the National Aeronautics and Space Administration (NASA) Ames Research Center has been investigating several technologies that will help enable industry in the development of this new type of cooperative operating environment. These technologies are being prototyped and will be tested in a collaborative evaluation of an initial ETM system in late 2023. The evaluation will concentrate on building out ETM system technologies that will inform the participants regarding operational intent sharing, strategic conflict detection, and the resultant deconfliction process. In addition to the technical aspects, key roles and responsibilities will need to be defined. This will be done through exploring community-agreed upon Cooperative Operating Practices (COPs) that include procedures and capabilities to aid in timely, strategic conflict identification and resolution to be developed during the evaluation. As an initial step to the evaluation, the ETM research team at NASA Ames solicited industry feedback on various aspects of ETM operations from subject matter experts. A virtual tabletop walkthrough session was held over a two-day period to follow a roadmap through the functional steps needed to build COPs, focusing on strategic conflict detection and resolution.
Optimizing the power output, and economic value, of geothermal power plants over decades of operation is a major challenge in renewable energy. Optimizing the output requires the ability to predict the mass flow rates and the output temperatures of production wells based on the inputs of injection wells, as well as the time history of the system. Machine Learning (ML) that incorporates the known physics of geothermal systems is one possible solution to this challenge. In this work, we explore the ability of ML algorithms to predict future temperature outputs based on historical data. Considering the challenges with obtaining an empirical dataset from field data that is large enough to enable reliable ML, we propose an alternate approach: developing a high-fidelity reservoir model and using computational resources to build a dataset that enables ML. As a first step towards achieving this goal, we present preliminary results from applying ML to predict the temperature timeseries of simple modeled geothermal systems. We describe the application of relevant state-of-the-art ML approaches, such as the Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to extract temporal structures in the model data. We assess the accuracy of the forecasts we obtain, compare the selected approaches, and share the lessons learned that would inform the process of training and utilizing ML algorithms for larger and more complex geothermal systems.
This panel focused on where multiple countries have collaborated to solve difficult remediation and cleanup challenges through either formal or informal means. The focus was to share real examples of where collaboration has accelerated cleanup saving time and money. This could be through policy or process improvements, technology transfer or sharing R and D, or other means of collaborative efforts. Panelists with presentations: Canada-AECL Collaboration Across Borders (Richard Sexton, Alastair MacDonald); Collaboration Across Borders to Deliver Cleanup and Decommissioning Challenges (Anthony Banford); IAEA Perspective on International Collaboration in D and ER (Horst Monken Fernandes); How, Why and Benefits of Collaboration (Kurt Gerdes)
An ongoing effort is underway at NASA Amcs Research Center (ARC) tu develop an On-line Project Information System (OPIS) for the Advanced Life Support (ALS) Program. The objective of this three-year project is to develop, test, revise and deploy OPIS to enhance the quality of decision-making metrics and attainment of Program goals through improved knowledge sharing. OPIS will centrally locate detailed project information solicited from investigators on an annual basis and make it readily accessible by the ALS Community via a web-accessible interface. The data will be stored in an object-oriented relational database (created in MySQL(Trademark) located on a secure server at NASA ARC. OPE will simultaneously serve several functions, including being an R&TD status information hub that can potentially serve as the primary annual reporting mechanism. Using OPIS, ALS managers and element leads will be able to carry out informed research and technology development investment decisions, and allow analysts to perform accurate systems evaluations. Additionally, the range and specificity of information solicited will serve to educate technology developers of programmatic needs. OPIS will collect comprehensive information from all ALS projects as well as highly detailed information specific to technology development in each ALS area (Waste, Water, Air, Biomass, Food, Thermal, and Control). Because the scope of needed information can vary dramatically between areas, element-specific technology information is being compiled with the aid of multiple specialized working groups. This paper presents the current development status in terms of the architecture and functionality of OPIS. Possible implementation approaches for OPIS are also discussed.
An ongoing effort is underway at NASA Ames Research Center (ARC) to develop an On-line Project Information System (OPIS) for the Advanced Life Support (ALS) Program. The objective of this three-year project is to develop, test, revise and deploy OPIS to enhance the quality of decision-making metrics and attainment of Program goals through improved knowledge sharing. OPIS will centrally locate detailed project information solicited from investigators on an annual basis and make it readily accessible by the ALS Community via a Web-accessible interface. The data will be stored in an object-oriented relational database (created in MySQL) located on a secure server at NASA ARC. OPE will simultaneously serve several functions, including being an research and technology development (R&TD) status information hub that can potentially serve as the primary annual reporting mechanism for ALS-funded projects. Using OPIS, ALS managers and element leads will be able to carry out informed R&TD investment decisions, and allow analysts to perform accurate systems evaluations. Additionally, the range and specificity of information solicited will serve to educate technology developers of programmatic needs. OPIS will collect comprehensive information from all ALS projects as well as highly detailed information specific to technology development in each ALS area (Waste, Water, Air, Biomass, Food, Thermal, Controls and Systems Analysis). Because the scope of needed information can vary dramatically between areas, element-specific technology information is being compiled with the aid of multiple specialized working groups. This paper presents the current development status in terms of the architecture and functionality of OPIS. Possible implementation approaches for OPIS are also discussed.
The ISSLive! project is a JSC innovation award- winning, combined MOD/Education project to publish export control and PAO-approved ISS telemetry, and simplified and scrubbed crew timelines. The publication of this data will be real-time or near real time and will include links to the crew's social media feeds and existing streaming public video/audio feeds, via public-friendly website, mobile devices and tablet applications. Additionally, the project will offer interactive virtual 3D views of an ISS model based on real-time telemetry and a 3D virtual mission control center based on existing Front Room console positions in made for public displays. The ISSLive! project is MOD-managed and includes collaborations with subject-matter expertise from the ISS flight controllers regarding daily operations and planning, education program specialists from the JSC Office of Education, instructional designers, human computer interface experts, and software/hardware experts from MOD facility organization, and senior web designers. In support of the Agency s Strategic Goal #6 with respect to using the ISS National Laboratory for education activities, ISSLive! uses the Station itself as STEM education subject matter and provides data for STEM-based lessons plans using national standards. Specifically, ISSLive! supports and enables the National Laboratory Education (NLE) project to address the Agency s Strategic Goal #6. This goal mandates, sharing NASA with the public, educators, and students to provide opportunities to participate in our Mission, foster innovation .. ISSLive! satisfies the Agency s outcomes of Strategic Goal; that is, engages the public in NASA's missions by providing new pathways for participation (Outcome 6.3) and it informs, engages, and inspires the public by sharing NASA s missions, challenges, and results (Outcome 6.4). Additionally, ISSLive! enables MOD s support of JSC Outreach and NASA's Open Data and Open Government Initiatives. The audience for the ISSLive! website and its application(s) are: teachers, students, citizen scientists, and the general public who will be given new and interactive insights on how the ISS Operates.
Consider the statement,'A system has two coupled subsystems, one of which dominates the design process. Each subsystem consists of discrete and continuous variables, and is solved using sequential analysis and solution.' To address this type of statement in the design of complex systems, three steps are required, namely, the embodiment of the statement in terms of entities on a computer, the mathematical formulation of subsystem models, and the resulting solution and system synthesis. In complex system decomposition, the subsystems are not isolated, self-supporting entities. Information such as constraints, goals, and design variables may be shared between entities. But many times in engineering problems, full communication and cooperation does not exist, information is incomplete, or one subsystem may dominate the design. Additionally, these engineering problems give rise to mathematical models involving nonlinear functions of both discrete and continuous design variables. In this dissertation an algorithm is developed to handle these types of scenarios for the domain-independent integration of subsystem embodiment, coordination, and system synthesis using constructs from Decision-Based Design, Game Theory, and Multidisciplinary Design Optimization. Implementation of the concept in this dissertation involves testing of the hypotheses using example problems and a motivating case study involving the design of a subsonic passenger aircraft.