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This paper sets forth a method to develop an architectural approach to the design, development, creation, and implementation of knowledge management at a specific organization.
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As notional life support system (LSS) architectures are developed and evaluated, myriad options must be considered pertaining to process technologies, components, and equipment assemblies. Each option must be evaluated relative to its impact on key functional interfaces within the LSS architecture. A leading notional architecture has been developed to guide the path toward realizing future crewed space exploration goals. This architecture includes atmosphere revitalization, water recovery and management, and environmental monitoring subsystems. Guiding requirements for developing this architecture are summarized and important interfaces within the architecture are discussed. The role of environmental monitoring within the architecture is described.
A hybrid requirements analysis methodology was developed, based on the practices actually used in developing a Space Generic Open Avionics Architecture. During the development of this avionics architecture, a method of analysis able to effectively define the requirements for this space avionics architecture was developed. In this methodology, external interfaces and relationships are defined, a static analysis resulting in a static avionics model was developed, operating concepts for simulating the requirements were put together, and a dynamic analysis of the execution needs for the dynamic model operation was planned. The systems engineering approach was used to perform a top down modified structured analysis of a generic space avionics system and to convert actual program results into generic requirements. CASE tools were used to model the analyzed system and automatically generate specifications describing the model's requirements. Lessons learned in the use of CASE tools, the architecture, and the design of the Space Generic Avionics model were established, and a methodology notebook was prepared for NASA. The weaknesses of standard real-time methodologies for practicing systems engineering, such as Structured Analysis and Object Oriented Analysis, were identified.
Information and discussion of the development of an Avionics Architecture Tool that is model-based using commercial off the shelf (COTS) products will be provided.
Traditional NASA missions, both near Earth and deep space, have been stovepipe in nature and point-to-point in architecture. Recently, NASA and others have conceptualized missions that required space-based networking. The notion of networks in space is a drastic shift in thinking and requires entirely new architectures, radio systems (antennas, modems, and media access), and possibly even new protocols. A full system engineering approach for some key mission architectures will occur that considers issues such as the science being performed, stationkeeping, antenna size, contact time, data rates, radio-link power requirements, media access techniques, and appropriate networking and transport protocols. This report highlights preliminary architecture concepts and key technologies that will be investigated.
Digital computer components which perform two dimensional array logic operations (Tse logic) on binary data arrays are described. The properties of Golay transforms which make them useful in image processing are reviewed, and several architectures for Golay transform processors are presented with emphasis on the skeletonizing algorithm. Conventional logic control units developed for the Golay transform processors are described. One is a unique microprogrammable control unit that uses a microprocessor to control the Tse computer. The remaining control units are based on programmable logic arrays. Performance criteria are established and utilized to compare the various Golay transform machines developed. A critique of Tse logic is presented, and recommendations for additional research are included.
A preliminary design of a general architecture for autonomous intelligent training systems was developed. The architecture integrates expert system technology with teaching/training methodologies to permit the production of systems suitable for use by NASA, other government agencies, industry, and academia in the training of personnel for the performance of complex, mission-critical tasks. The proposed architecture consists of five elements: a user interface, a domain expert, a training session manager, a trainee model, and a training scenario generator. The design of this architecture was guided and its efficacy tested through the development of a system for use by Mission Control Center Flight Dynamics Officers in training to perform Payload-Assist Module Deploys from the orbiter.
Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.
Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. However, with the modern approach of digital engineering and technological advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, mod-el-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in integrating DE and AI into an end-to-end system lifecycle management ecosystem safely and reliably. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world?s energy demands and build energy security.
This paper picks up where EVA Space Suit Architecture: Low Earth Orbit Vs. Moon Vs. Mars (Hill, Johnson, IEEEAC paper #1209) left off in the development of a space suit architecture that is modular in design and interfaces and could be reconfigured to meet the mission or during any given mission depending on the tasks or destination. This paper will walk though the continued development of a space suit system architecture, and how it should evolve to meeting the future exploration EVA needs of the United States space program. In looking forward to future US space exploration and determining how the work performed to date in the CxP and how this would map to a future space suit architecture with maximum re-use of technology and functionality, a series of thought exercises and analysis have provided a strong indication that the CxP space suit architecture is well postured to provide a viable solution for future exploration missions. Through the destination environmental analysis that is presented in this paper, the modular architecture approach provides the lowest mass, lowest mission cost for the protection of the crew given any human mission outside of low Earth orbit. Some of the studies presented here provide a look and validation of the non-environmental design drivers that will become every-increasingly important the further away from Earth humans venture and the longer they are away. Additionally, the analysis demonstrates a logical clustering of design environments that allows a very focused approach to technology prioritization, development and design that will maximize the return on investment independent of any particular program and provide architecture and design solutions for space suit systems in time or ahead of being required for any particular manned flight program in the future. The new approach to space suit design and interface definition the discussion will show how the architecture is very adaptable to programmatic and funding changes with minimal redesign effort required such that the modular architecture can be quickly and efficiently honed into a specific mission point solution if required.
Developing enhanced simulation capabilities has become a significant priority for the Space Communications and Navigation (SCaN) project at NASA as new space communications technologies are proposed to replace aging NASA communications assets, such as the Tracking and Data Relay Satellite System (TDRSS). When developing the architecture for these new space communications assets, it is important to develop updated modeling and simulation methodologies, such that competing architectures can be weighed against one another and the optimal path forward can be determined. There have been many simulation tools developed here at NASA for the simulation of single RF link budgets, or for the modeling and simulation of an entire network of spacecraft and their supporting SCaN network elements. However, the modeling capabilities are never fully complete and as new technologies are proposed, gaps are identified. One such gap is the ability to rapidly develop high fidelity simulation models of electronically steerable phased array systems. As future relay satellite architectures are proposed that include optical communications links, electronically steerable antennas will become more desirable due to the reduction in platform vibration introduced by mechanically steerable devices. In this research, we investigate how modeling of these antennas can be introduced into out overall simulation and modeling structure. The ultimate goal of this research is two-fold. First, to enable NASA engineers to model various proposed simulation architectures and determine which proposed architecture meets the given architectural requirements. Second, given a set of communications link requirements for a proposed satellite architecture, determine the optimal configuration for a phased array antenna. There is a variety of tools available that can be used to model phased array antennas. To meet our stated goals, the first objective of this research is to compare the subset of tools available to us, trading-off modeling fidelity of the tool with simulation performance. When comparing several proposed architectures, higher- fidelity modeling may be desirable, however, when iterating a proposed set of communication link requirements across ranges of phased array configuration parameters, the practicality of performance becomes a significant requirement. In either case, a minimum simulation - fidelity must be met, regardless of performance considerations, which will be discussed in this research. Given a suitable set of phased array modeling tools, this research then focuses on integration with current SCaN modeling and simulation tools. While properly modeling the antenna elements of a system are vital, this is only a small part of the end-to-end communication path between a satellite and the supporting ground station and/or relay satellite assets. To properly model a proposed simulation architecture, this toolset must be integrated with other commercial and government development tools, such that the overall architecture can be examined in terms of communications, reliability, and cost. In this research, integration with previously developed communication tools is investigated.
In traditional systems engineering practice, architecture, concept development, and requirements development are related but still separate activities. Concepts for operation, key technical approaches, and related proofs of concept are developed. These inform the formulation of an architecture at multiple levels, starting with the overall system composition and functionality and progressing into more detail. As this formulation is done, a parallel activity develops a set of English statements that constrain solutions. These requirements are often called "shall statements" since they are formulated to use "shall." The separation of requirements from design is exacerbated by well-meaning tools like the Dynamic Object-Oriented Requirements System (DOORS) that remained separated from engineering design tools. With the Europa Clipper project, efforts are being taken to change the requirements development approach from a separate activity to one intimately embedded in formulation effort. This paper presents a modeling approach and related tooling to generate English requirement statements from constraints embedded in architecture definition.
Rockwell International is conducting an ongoing program to develop avionics architectures that provide high intrinsic value while meeting all mission objectives. Studies are being conducted to determine alternative configurations that have low life-cycle cost and minimum development risk, and that minimize launch delays while providing the reliability level to assure a successful mission. This effort is based on four decades of providing ballistic missile avionics to the United States Air Force and has focused on the requirements of the NASA Cargo Transfer Vehicle (CTV) program in 1991. During the development of architectural concepts it became apparent that rendezvous strategy issues have an impact on the architecture of the avionics system. This is in addition to the expected impact on propulsion and electrical power duration, flight profiles, and trajectory during approach.
The NASA OPAD spectrometer system relies heavily on extensive software which repetitively extracts spectral information from the engine plume and reports the amounts of metals which are present in the plume. The development of this software is at a sufficiently advanced stage where it can be used in actual engine tests to provide valuable data on engine operation and health. This activity will continue and, in addition, the OPAD system is planned to be used in flight aboard space vehicles. The two implementations, test-stand and in-flight, may have some differing requirements. For example, the data stored during a test-stand experiment are much more extensive than in the in-flight case. In both cases though, the majority of the requirements are similar. New data from the spectrograph is generated at a rate of once every 0.5 sec or faster. All processing must be completed within this period of time to maintain real-time performance. Every 0.5 sec, the OPAD system must report the amounts of specific metals within the engine plume, given the spectral data. At present, the software in the OPAD system performs this function by solving the inverse problem. It uses powerful physics-based computational models (the SPECTRA code), which receive amounts of metals as inputs to produce the spectral data that would have been observed, had the same metal amounts been present in the engine plume. During the experiment, for every spectrum that is observed, an initial approximation is performed using neural networks to establish an initial metal composition which approximates as accurately as possible the real one. Then, using optimization techniques, the SPECTRA code is repetitively used to produce a fit to the data, by adjusting the metal input amounts until the produced spectrum matches the observed one to within a given level of tolerance. This iterative solution to the original problem of determining the metal composition in the plume requires a relatively long period of time to execute the software in a modern single-processor workstation, and therefore real-time operation is currently not possible. A different number of iterations may be required to perform spectral data fitting per spectral sample. Yet, the OPAD system must be designed to maintain real-time performance in all cases. Although faster single-processor workstations are available for execution of the fitting and SPECTRA software, this option is unattractive due to the excessive cost associated with very fast workstations and also due to the fact that such hardware is not easily expandable to accommodate future versions of the software which may require more processing power. Initial research has already demonstrated that the OPAD software can take advantage of a parallel computer architecture to achieve the necessary speedup. Current work has improved the software by converting it into a form which is easily parallelizable. Timing experiments have been performed to establish the computational complexity and execution speed of major components of the software. This work provides the foundation of future work which will create a fully parallel version of the software executing in a shared-memory multiprocessor system.
The Community Open Source Program Office (COSPO) has developed an architecture for the intelligence community's new Open Source Information System (OSIS). The architecture is a multi-phased program featuring connectivity, interoperability, and functionality. OSIS is based on a distributed architecture concept. The system is designed to function as a virtual entity. OSIS will be a restricted (non-public), user configured network employing Internet communications. Privacy and authentication will be provided through firewall protection. Connection to OSIS can be made through any server on the Internet or through dial-up modems provided the appropriate firewall authentication system is installed on the client.
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The Automation Hooks Architecture Trade Study for Flexible Test Orchestration sought a standardized data-driven alternative to conventional automated test programming interfaces. The study recommended composing the interface using multicast DNS (mDNS/SD) service discovery, Representational State Transfer (Restful) Web Services, and Automatic Test Markup Language (ATML). We describe additional efforts to rapidly mature the Automation Hooks Architecture candidate interface definition by validating it in a broad spectrum of applications. These activities have allowed us to further refine our concepts and provide observations directed toward objectives of economy, scalability, versatility, performance, severability, maintainability, scriptability and others.