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At least 685 records · Page 38

Demystification of Processes that Effect Prioritization of Space Radiation Element Research

In an effort to demystify how research funding priorities are established , the Space Radiation Element will present an introduction to the Human Space Risk Board (HSRB) framework that is that used to inform Human System Risk and can be found at https://humanresearchroadmap.nasa.gov/Risks/. These risks are based on the consequences of hazards (space radiation, altered gravity, isolation & confinement, distance from earth and hostile/closed environment) a human body is exposed to during spaceflight. The HSRB regularly evaluates risks to humans in space which includes updating the knowledge base to reflect emerging research, the development of effective countermeasures, and evolving operational approaches toward addressing those risks. To increase understanding and clarity, this talk will step through how risks (with the focus on Risk of Radiation Carcinogenesis) are assigned a rating (and color code) based on design reference missions, likelihood, and consequence. Further, The Space Radiation Element will discuss how risks, including the magnitude/rating, required technical deliverables, and expected products from current research efforts affect our element strategy and prioritization of research. In addition, navigation of the publicly available www.nasa.gov/hrp, will be demonstrated to inform principal investigators where this information can be readily accessed. Our primary objectives for this presentation/demonstration are to demystify The Space Radiation Element’s internal processes and to educate researchers concerning publicly available documents that can be used to better align their proposed objectives with Element priorities.

J A Zawaski↗

Microprocessor control and networking for the amps breadboard

Future space missions will require more sophisticated power systems, implying higher costs and more extensive crew and ground support involvement. To decrease this human involvement, as well as to protect and most efficiently utilize this important resource, NASA has undertaken major efforts to promote progress in the design and development of autonomously managed power systems. Two areas being actively pursued are autonomous power system (APS) breadboards and knowledge-based expert system (KBES) applications. The former are viewed as a requirement for the timely development of the latter. Not only will they serve as final testbeds for the various KBES applications, but will play a major role in the knowledge engineering phase of their development. The current power system breadboard designs are of a distributed microprocessor nature. The distributed nature, plus the need to connect various external computer capabilities (i.e., conventional host computers and symbolic processors), places major emphasis on effective networking. The communications and networking technologies for the first power system breadboard/test facility are described.

Floyd, Stephen A.↗

Design of launch systems using continuous improvement process

The purpose of this paper is to identify a systematic process for improving ground operations for future launch systems. This approach is based on the Total Quality Management (TQM) continuous improvement process. While the continuous improvement process is normally identified with making incremental changes to an existing system, it can be used on new systems if they use past experience as a knowledge base. In the case of the Reusable Launch Vehicle (RLV), the Space Shuttle operations provide many lessons. The TQM methodology used for this paper will be borrowed from the United States Air Force 'Quality Air Force' Program. There is a general overview of the continuous improvement process, with concentration on the formulation phase. During this phase critical analyses are conducted to determine the strategy and goals for the remaining development process. These analyses include analyzing the mission from the customers point of view, developing an operations concept for the future, assessing current capabilities and determining the gap to be closed between current capabilities and future needs and requirements. A brief analyses of the RLV, relative to the Space Shuttle, will be used to illustrate the concept. Using the continuous improvement design concept has many advantages. These include a customer oriented process which will develop a more marketable product and a better integration of operations and systems during the design phase. But, the use of TQM techniques will require changes, including more discipline in the design process and more emphasis on data gathering for operational systems. The benefits will far outweigh the additional effort.

Brown, Richard W.↗

An expert system based intelligent control scheme for space bioreactors

An expert system based intelligent control scheme is being developed for the effective control and full automation of bioreactor systems in space. The scheme developed will have the capability to capture information from various resources including heuristic information from process researchers and operators. The knowledge base of the expert system should contain enough expertise to perform on-line system identification and thus be able to adapt the controllers accordingly with minimal human supervision.

San, Ka-Yiu↗

Technical Language Processing of Nuclear Power Plants Equipment Reliability Data

Operating nuclear power plants (NPPs) generate and collect large amounts of equipment reliability (ER) element data that contain information about the status of components, assets, and systems. Some of this information is in textual form where the occurrence of abnormal events or maintenance activities are described. Analyses of NPP textual data via natural language processing (NLP) methods have expanded in the last decade, and only recently the true potential of such analyses has emerged. So far, applications of NLP methods have been mostly limited to classification and prediction in order to identify the nature of the given textual element (e.g., safety or non-safety relevant). In this paper, we target a more complex problem: the automatic generation of knowledge based on a textual element in order to assist system engineers in assessing an asset’s historical health performance. The goal is to assist system engineers in the identification of anomalous behaviors, cause–effect relations between events, and their potential consequences, and to support decision-making such as the planning and scheduling of maintenance activities. “Knowledge extraction” is a very broad concept whose definition may vary depending on the application context. In our particular context, it refers to the process of examining an ER textual element to identify the systems or assets it mentions and the type of event it describes (e.g., component failure or maintenance activity). In addition, we wish to identify details such as measured quantities and temporal or cause–effect relations between events. This paper describes how ER textual data elements are first preprocessed to handle typos, acronyms, and abbreviations, then machine learning (ML) and rule-based algorithms are employed to identify physical entities (e.g., systems, assets, and components) and specific phenomena (e.g., failure or degradation). A few applications relevant from an NPP ER point of view are presented as well.

97 MATHEMATICS AND COMPUTING↗

Cooperative analysis expert situation assessment research

For the past few decades, Rome Air Development Center (RADC) has been conducting research in Artificial Intelligence (AI). When the recent advances in hardware technology made many AI techniques practical, the Intelligence and Reconnaissance Directorate of RADC initiated an applications program entitled Knowledge Based Intelligence Systems (KBIS). The goal of the program is the development of a generic Intelligent Analyst System, an open machine with the framework for intelligence analysis, natural language processing, and man-machine interface techniques, needing only the specific problem domain knowledge to be operationally useful. The development of KBIS is described.

Mccown, Michael G.↗

Knowledge acquisition for autonomous systems

Knowledge-based capabilities for autonomous aerospace systems, such as the NASA Space Station, must encompass conflict-resolution functions comparable to those of human operators, with all elements of the system working toward system goals in a concurrent, asynchronous-but-coordinated fashion. Knowledge extracted from a design database will support robotic systems by furnishing geometric, structural, and causal descriptions required for repair, disassembly, and assembly. The factual knowledge for these databases will be obtained from a master database through a technical management information system, and it will in many cases have to be augmented by domain-specific heuristic knowledge acquired from domain experts.

Lum, Henry↗

How to help intelligent systems with different uncertainty representations cooperate with each other

In order to solve a complicated problem one must use the knowledge from different domains. Therefore, if one wants to automatize the solution of these problems, one has to help the knowledge-based systems that correspond to these domains cooperate, that is, communicate facts and conclusions to each other in the process of decision making. One of the main obstacles to such cooperation is the fact that different intelligent systems use different methods of knowledge acquisition and different methods and formalisms for uncertainty representation. So an interface f is needed, 'translating' the values x, y, which represent uncertainty of the experts' knowledge in one system, into the values f(x), f(y) appropriate for another one. The problem of designing such an interface as a mathematical problem is formulated and solved. It is shown that the interface must be fractionally linear: f(x) = (ax + b)/(cx + d).

Kreinovich, Vladik YA.↗

Factors shaping the evolution of electronic documentation systems

The main goal is to prepare the space station technical and managerial structure for likely changes in the creation, capture, transfer, and utilization of knowledge. By anticipating advances, the design of Space Station Project (SSP) information systems can be tailored to facilitate a progression of increasingly sophisticated strategies as the space station evolves. Future generations of advanced information systems will use increases in power to deliver environmentally meaningful, contextually targeted, interconnected data (knowledge). The concept of a Knowledge Base Management System is emerging when the problem is focused on how information systems can perform such a conversion of raw data. Such a system would include traditional management functions for large space databases. Added artificial intelligence features might encompass co-existing knowledge representation schemes; effective control structures for deductive, plausible, and inductive reasoning; means for knowledge acquisition, refinement, and validation; explanation facilities; and dynamic human intervention. The major areas covered include: alternative knowledge representation approaches; advanced user interface capabilities; computer-supported cooperative work; the evolution of information system hardware; standardization, compatibility, and connectivity; and organizational impacts of information intensive environments.

Dede, Christopher J.↗

Haughton-Mars Project (HMP)/NASA 2006 Lunar Medical Contingency Simulation: An Overview

Medical requirements are currently being developed for NASA's space exploration program. Lunar surface operations for crews returning to the moon will be performed on a daily basis to conduct scientific research and construct a lunar habitat. Inherent to aggressive surface activities is the potential risk of injury to crew members. To develop an evidence-base for handling medical contingencies on the lunar surface, a simulation project was conducted using the moon-Mars analog environment at Devon Island, Nunavut, high Canadian Arctic. A review of the Apollo lunar surface activities and personal communications with Apollo lunar crew members provided a knowledge base of plausible scenarios that could potentially injure an astronaut during a lunar extravehicular activity. Objectives were established to 1) demonstrate stabilization, field extraction and transfer an injured crew member to the habitat and 2) evaluate audio, visual and biomedical communication capabilities with ground controllers at multiple mission control centers. The simulation project s objectives were achieved. Among these objectives were 1) extracting a crew member from a sloped terrain by a two-member team in a 1-g analog environment, 2) establishing real-time communication to multiple space centers, 3) providing biomedical data to flight controllers and crew members, and 4) establishing a medical diagnosis and treatment plan from a remote site. The simulation project provided evidence for the types of equipment and methods needed for planetary space exploration. During the project, the crew members were confronted with a number of unexpected scenarios including environmental, communications, EVA suit, and navigation challenges. These trials provided insight into the challenges of carrying out a medical contingency in an austere environment. The knowledge gained from completing the objectives of this project will be incorporated into the exploration medical requirements involving an incapacited astronaut on the lunar surface.

Scheuring, R. A.↗

Techniques and potential capabilities of multi-resolutional information (knowledge) processing

A concept of nested hierarchical (multi-resolutional, pyramidal) information (knowledge) processing is introduced for a variety of systems including data and/or knowledge bases, vision, control, and manufacturing systems, industrial automated robots, and (self-programmed) autonomous intelligent machines. A set of practical recommendations is presented using a case study of a multiresolutional object representation. It is demonstrated here that any intelligent module transforms (sometimes, irreversibly) the knowledge it deals with, and this tranformation affects the subsequent computation processes, e.g., those of decision and control. Several types of knowledge transformation are reviewed. Definite conditions are analyzed, satisfaction of which is required for organization and processing of redundant information (knowledge) in the multi-resolutional systems. Providing a definite degree of redundancy is one of these conditions.

Meystel, A.↗

Human factors issues in the use of artificial intelligence in air traffic control. October 1990 Workshop

The objective of the workshop was to explore the role of human factors in facilitating the introduction of artificial intelligence (AI) to advanced air traffic control (ATC) automation concepts. AI is an umbrella term which is continually expanding to cover a variety of techniques where machines are performing actions taken based upon dynamic, external stimuli. AI methods can be implemented using more traditional programming languages such as LISP or PROLOG, or they can be implemented using state-of-the-art techniques such as object-oriented programming, neural nets (hardware or software), and knowledge based expert systems. As this technology advances and as increasingly powerful computing platforms become available, the use of AI to enhance ATC systems can be realized. Substantial efforts along these lines are already being undertaken at the FAA Technical Center, NASA Ames Research Center, academic institutions, industry, and elsewhere. Although it is clear that the technology is ripe for bringing computer automation to ATC systems, the proper scope and role of automation are not at all apparent. The major concern is how to combine human controllers with computer technology. A wide spectrum of options exists, ranging from using automation only to provide extra tools to augment decision making by human controllers to turning over moment-by-moment control to automated systems and using humans as supervisors and system managers. Across this spectrum, it is now obvious that the difficulties that occur when tying human and automated systems together must be resolved so that automation can be introduced safely and effectively. The focus of the workshop was to further explore the role of injecting AI into ATC systems and to identify the human factors that need to be considered for successful application of the technology to present and future ATC systems.

Hockaday, Stephen↗

Mission Engineering of a Rapid Cycle Spacecraft Logistics Fleet

The requirement for logistics re-supply of the International Space Station has provided a unique opportunity for engineering the implementation of NASA's first dedicated pressurized logistics carrier fleet. The NASA fleet is comprised of three Multi-Purpose Logistics Modules (MPLM) provided to NASA by the Italian Space Agency in return for operations time aboard the International Space Station. Marshall Space Flight Center was responsible for oversight of the hardware development from preliminary design through acceptance of the third flight unit, and currently manages the flight hardware sustaining engineering and mission engineering activities. The actual MPLM Mission began prior to NASA acceptance of the first flight unit in 1999 and will continue until the de-commission of the International Space Station that is planned for 20xx. Mission engineering of the MPLM program requires a broad focus on three distinct yet inter-related operations processes: pre-flight, flight operations, and post-flight turn-around. Within each primary area exist several complex subsets of distinct and inter-related activities. Pre-flight processing includes the evaluation of carrier hardware readiness for space flight. This includes integration of payload into the carrier, integration of the carrier into the launch vehicle, and integration of the carrier onto the orbital platform. Flight operations include the actual carrier operations during flight and any required real-time ground support. Post-flight processing includes de-integration of the carrier hardware from the launch vehicle, de-integration of the payload, and preparation for returning the carrier to pre-flight staging. Typical space operations are engineered around the requirements and objectives of a dedicated mission on a dedicated operational platform (i.e. Launch or Orbiting Vehicle). The MPLM, however, has expanded this envelope by requiring operations with both vehicles during flight as well as pre-launch and post-landing operations. These unique requirements combined with a success-oriented schedule of four flights within a ten-month period have provided numerous opportunities for understanding and improving operations processes. Furthermore, it has increased the knowledge base of future Payload Carrier and Launch Vehicle hardware and requirement developments. Discussion of the process flows and target areas for process improvement are provided in the subject paper. Special emphasis is also placed on supplying guidelines for hardware development. The combination of process knowledge and hardware development knowledge will provide a comprehensive overview for future vehicle developments as related to integration and transportation of payloads.

Holladay, Jon↗

An expert system to manage the operation of the Space Shuttle's fuel cell cryogenic reactant tanks

This paper describes a rule-based expert system to manage the operation of the Space Shuttle's cryogenic fuel system. Rules are based on standard fuel tank operating procedures described in the EECOM Console Handbook. The problem of configuring the operation of the Space Shuttle's fuel tanks is well-bounded and well defined. Moreover, the solution of this problem can be encoded in a knowledge-based system. Therefore, a rule-based expert system is the appropriate paradigm. Furthermore, the expert system could be used in coordination with power system simulation software to design operating procedures for specific missions.

Murphey, Amy Y.↗

DNA Sequence-Based Identification of Fusarium : A Work in Progress

Accurate species-level identification of an etiological agent is crucial for disease diagnosis and management because knowing the agent’s identity connects it with what is known about its host range, geographic distribution, and toxin production potential. This is particularly true in publishing peer-reviewed disease reports, where imprecise and/or incorrect identifications weaken the public knowledge base. This can be a daunting task for phytopathologists and other applied biologists that need to identify Fusarium in particular, because published and ongoing multilocus molecular systematic studies have highlighted several confounding issues. Paramount among these are: (i) this agriculturally and clinically important genus is currently estimated to comprise more than 400 phylogenetically distinct species (i.e., phylospecies), with more than 80% of these discovered within the past 25 years; (ii) approximately one-third of the phylospecies have not been formally described; (iii) morphology alone is inadequate to distinguish most of these species from one another; and (iv) the current rapid discovery of novel fusaria from pathogen surveys and accompanying impact on the taxonomic landscape is expected to continue well into the foreseeable future. To address the critical need for accurate pathogen identification, our research groups are focused on populating two web-accessible databases (FUSARIUM-ID v.3.0 and the nonredundant National Center for Biotechnology Information nucleotide collection that includes GenBank) with portions of three phylogenetically informative genes (i.e., TEF1, RPB1, and RPB2) that resolve at or near the species level in every Fusarium species. The objectives of this Special Report, and its companion in this issue ( Torres-Cruz et al. 2022 ), are to provide a progress report on our efforts to populate these databases and to outline a set of best practices for DNA sequence-based identification of fusaria.

Plant Sciences↗

Failure modes and effects analysis automation

A failure modes and effects analysis (FMEA) assistant was implemented as a knowledge based system and will be used during design of the Space Station to aid engineers in performing the complex task of tracking failures throughout the entire design effort. The three major directions in which automation was pursued were the clerical components of the FMEA process, the knowledge acquisition aspects of FMEA, and the failure propagation/analysis portions of the FMEA task. The system is accessible to design, safety, and reliability engineers at single user workstations and, although not designed to replace conventional FMEA, it is expected to decrease by many man years the time required to perform the analysis.

Kamhieh, Cynthia H.↗

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗

Automated cataloging and characterization of space-derived data

One of the most significant technical issues that NASA must address and resolve is the problem of managing the enormous amounts of scientific and engineering data that will be generated by the next generation of remote sensing systems such as the Hubble Space Telescope (HST) and the Earth Observing System (EOS). The amount of data these sensors are expected to produce will be orders of magnitude greater than NASA has ever experienced. Consequently, new solutions must be developed for managing, accessing, and automatically inputting the data into a database in some expressive fashion that will provide a meaningful understanding and effective utilization of this data in a multidisciplinary environment. Presently, scientific data provided by satellites and other sources are processed, cataloged, and archived according to narrow mission or project-specific requirements with little regard to the semantics of the overall research. Scientists therefore lack knowledge of or access to potentially valuable data outside their own field. What is needed is an innovative approach that will allow collected data to be automatically cataloged, characterized, and managed in a domain-community. A concept and design approach that employs expert system-based knowledge controllers combined with advanced spatial database systems and graphical data structures is discussed.

Campbell, William J.↗