SEARCH · Search NASA

Results for “knowledge encapsulation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

All sources NASA NTRS DOE OSTI

NASA NTRS2010

The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture that are informed by and consistent with SMAP observations. Such estimates are obtained by merging SMAP observations with estimates from a land surface model in a soil moisture data assimilation system. The land surface model component of the assimilation system is driven with observations-based surface meteorological forcing data, including precipitation, which is the most important driver for soil moisture. The model also encapsulates knowledge of key land surface processes, including the vertical transfer of soil moisture between the surface and root zone reservoirs. Finally, the model interpolates and extrapolates SMAP observations in time and in space. The L4_SM product thus provides a comprehensive and consistent picture of land surface hydrological conditions based on SMAP observations and complementary information from a variety of sources. The assimilation algorithm considers the respective uncertainties of each component and yields a product that is superior to satellite or model data alone. Error estimates for the L4_SM product are generated as a by-product of the data assimilation system.

Reichle, Rolf↗

NASA NTRS1991

A proven knowledge-based approach to prioritizing process information

Many space-related processes are highly complex systems subject to sudden, major transients. In any complex process control system, a critical aspect is rapid analysis of the changing process information. During a disturbance, this task can overwhelm humans as well as computers. Humans deal with this by applying heuristics in determining significant information. A simple, knowledge-based approach to prioritizing information is described. The approach models those heuristics that humans would use in similar circumstances. The approach described has received two patents and was implemented in the Alarm Filtering System (AFS) at the Idaho National Engineering Laboratory (INEL). AFS was first developed for application in a nuclear reactor control room. It has since been used in chemical processing applications, where it has had a significant impact on control room environments. The approach uses knowledge-based heuristics to analyze data from process instrumentation and respond to that data according to knowledge encapsulated in objects and rules. While AFS cannot perform the complete diagnosis and control task, it has proven to be extremely effective at filtering and prioritizing information. AFS was used for over two years as a first level of analysis for human diagnosticians. Given the approach's proven track record in a wide variety of practical applications, it should be useful in both ground- and space-based systems.

Corsberg, Daniel R.↗

NASA NTRS1991

The role of smart systems in rendezvous, close proximity operations and docking maneuvers

Various missions scenarios (Space Station logistics, LEO and GEO services, and SEI operation) will involve flexibility in mission management. This means operations will be one or a combination of the following: autonomous, supervised autonomous, and machine aided manual control. Smart Systems will likely play a significant role in making these missions successful from a safety/reliability perspective and less costly from an operations perspective. This does not imply that Smart Systems need to be super sophisticated. On the contrary, Smart Systems have been described as automated intelligence that if a person had done it wrong, it would be considered stupid. The first part of this paper will describe the types of Smart System techniques involved in AR and CC, their specifications, duties, and interactions. Next will be a discussion of the work performed under the auspice of the ALS Program to further Expert Systems applications imbedded in the control process, NASA/JSC CRAD, and other related IRAD projects. This will include issues pertaining to the following: integration, speed, knowledge encapsulation, and cooperative systems. Finally, a brief description will be offered to outline the major obstacles for the acceptance of Smart Systems in critical applications.

Szatkowski, Gerard P.↗

NASA NTRS1994

A fuzzy classifier system for process control

A fuzzy classifier system that discovers rules for controlling a mathematical model of a pH titration system was developed by researchers at the U.S. Bureau of Mines (USBM). Fuzzy classifier systems successfully combine the strengths of learning classifier systems and fuzzy logic controllers. Learning classifier systems resemble familiar production rule-based systems, but they represent their IF-THEN rules by strings of characters rather than in the traditional linguistic terms. Fuzzy logic is a tool that allows for the incorporation of abstract concepts into rule based-systems, thereby allowing the rules to resemble the familiar 'rules-of-thumb' commonly used by humans when solving difficult process control and reasoning problems. Like learning classifier systems, fuzzy classifier systems employ a genetic algorithm to explore and sample new rules for manipulating the problem environment. Like fuzzy logic controllers, fuzzy classifier systems encapsulate knowledge in the form of production rules. The results presented in this paper demonstrate the ability of fuzzy classifier systems to generate a fuzzy logic-based process control system.

Karr, C. L.↗

NASA NTRS2004

Realtime Knowledge Management (RKM): From an International Space Station (ISS) Point of View

We are developing automated methods to provide realtime access to spacecraft domain knowledge relevant a spacecraft's current operational state. The method is based upon analyzing state-transition signatures in the telemetry stream. A key insight is that documentation relevant to a specific failure mode or operational state is related to the structure and function of spacecraft systems. This means that diagnostic dependency and state models can provide a roadmap for effective documentation navigation and presentation. Diagnostic models consume the telemetry and derive a high-level state description of the spacecraft. Each potential spacecraft state description is matched against the predictions of models that were developed from information found in the pages and sections in the relevant International Space Station (ISS) documentation and reference materials. By annotating each model fragment with the domain knowledge sources from which it was derived we can develop a system that automatically selects those documents representing the domain knowledge encapsulated by the models that compute the current spacecraft state. In this manner, when the spacecraft state changes, the relevant documentation context and presentation will also change.

Robinson, Peter I.↗

NASA NTRS1991

Model-based task planning system for a space laboratory environment

This paper describes the design of a model-based autonomous planning system that will enable robots to manage a space-borne chemical laboratory. In a model-based planning system, knowledge is encapsulated in the form of models at the various layers to support the predefined system objectives. Thus the model-based approach can be considered as an extended planning paradigm which is able to base its planning, control, diagnosis, repair, and other activities on a variety of objectives-related models. A System Entity Structure/Model Base framework is employed to support autonomous system design through the ability to generate a family of planning alternatives as well as to build hierarchical event-based control structures. The model base is a multilevel, multiabstraction, and multiformalism system organized through the use of system morphisms to integrate related models.

Chi, Sung-Do↗

NASA NTRS1990

An application of object-oriented knowledge representation to engineering expert systems

The paper describes an object-oriented knowledge representation and its application to engineering expert systems. The object-oriented approach promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects and organized by defining relationships between the objects. An Object Representation Language (ORL) was implemented as a tool for building and manipulating the object base. Rule-based knowledge representation is then used to simulate engineering design reasoning. Using a common object base, very large expert systems can be developed, comprised of small, individually processed, rule sets. The integration of these two schemes makes it easier to develop practical engineering expert systems. The general approach to applying this technology to the domain of the finite element analysis, design, and optimization of aerospace structures is discussed.

D S Logie↗

NASA NTRS1990

Integration of object-oriented knowledge representation with the CLIPS rule based system

The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

Logie, David S.↗

NASA NTRS1993

Automated assembly of large space structures using an expert system executive

NASA LaRC has developed a unique testbed for investigating the practical problems associated with the assembly of large space structures using robotic manipulators. The testbed is an interdisciplinary effort which considers the full spectrum of assembly problems from the design of mechanisms to the development of software. This paper will describe the automated structures assembly testbed and its operation, detail the expert system executive and its development, and discuss the planned system evolution. Emphasis will be placed on the expert system development of the program executive. The executive program must be capable of directing and reliably performing complex assembly tasks with the flexibility to recover from realistic system errors. By employing an expert system, information pertaining to the operation of the system was encapsulated concisely within a knowledge base. This lead to a substantial reduction in code, increased flexibility, eased software upgrades, and realized a savings in software maintenance costs.

Allen, Cheryl L.↗

NASA NTRS1993

An expert system executive for automated assembly of large space truss structures

Langley Research Center developed a unique test bed for investigating the practical problems associated with the assembly of large space truss structures using robotic manipulators. The test bed is the result of an interdisciplinary effort that encompasses the full spectrum of assembly problems - from the design of mechanisms to the development of software. The automated structures assembly test bed and its operation are described, the expert system executive and its development are detailed, and the planned system evolution is discussed. Emphasis is on the expert system implementation of the program executive. The executive program must direct and reliably perform complex assembly tasks with the flexibility to recover from realistic system errors. The employment of an expert system permits information that pertains to the operation of the system to be encapsulated concisely within a knowledge base. This consolidation substantially reduced code, increased flexibility, eased software upgrades, and realized a savings in software maintenance costs.

Allen, Cheryl L.↗

NASA NTRS1988

Advanced piloted aircraft flight control system design methodology. Volume 1: Knowledge base

The development of a comprehensive and electric methodology for conceptual and preliminary design of flight control systems is presented and illustrated. The methodology is focused on the design stages starting with the layout of system requirements and ending when some viable competing system architectures (feedback control structures) are defined. The approach is centered on the human pilot and the aircraft as both the sources of, and the keys to the solution of, many flight control problems. The methodology relies heavily on computational procedures which are highly interactive with the design engineer. To maximize effectiveness, these techniques, as selected and modified to be used together in the methodology, form a cadre of computational tools specifically tailored for integrated flight control system preliminary design purposes. While theory and associated computational means are an important aspect of the design methodology, the lore, knowledge and experience elements, which guide and govern applications are critical features. This material is presented as summary tables, outlines, recipes, empirical data, lists, etc., which encapsulate a great deal of expert knowledge. Much of this is presented in topical knowledge summaries which are attached as Supplements. The composite of the supplements and the main body elements constitutes a first cut at a a Mark 1 Knowledge Base for manned-aircraft flight control.

Mcruer, Duane T.↗

NASA NTRS1991

Facing page test for the astronaut science advisor presentation

The goal of the Astronaut Science Advisor (ASA) project is to improve the scientific return of experiments performed in space by providing astronaut experimenters with an 'intelligent assistant' that encapsulates much of the domain- and experiment-related knowledge commanded by the Principal Investigator (PI) on the ground. By using expert systems technology and the availability of flight-qualified personal computers, it is possible to encode the requisite knowledge and make it available to astronauts as they perform experiments in space. The system performs four major functions: diagnosis and troubleshooting of experiment apparatus, data collection, protocol management, and detection of interesting data. The experiment used for development of the system measures human adaptation to weightlessness in the context of the neurovestibular system. This so-called 'Rotating Dome' experiment was flown on the recent Spacelab Life Sciences One (SLS-1) Mission. This mission was used as an opportunity to test some of the system's functionality. Experiment data was downlinked from the orbiter, and the system then captured the data and analyzed it in real time. The system kept track of the time being used by the experiment, recognized occurrences of interesting data, summarized data statistically and generated potential new protocols that could be used to optimize the course of the experiment.

Compton, Michael M.↗

NASA NTRS2008

Intelligent Integrated Health Management for a System of Systems

An intelligent integrated health management system (IIHMS) incorporates major improvements over prior such systems. The particular IIHMS is implemented for any system defined as a hierarchical distributed network of intelligent elements (HDNIE), comprising primarily: (1) an architecture (Figure 1), (2) intelligent elements, (3) a conceptual framework and taxonomy (Figure 2), and (4) and ontology that defines standards and protocols. Some definitions of terms are prerequisite to a further brief description of this innovation: A system-of-systems (SoS) is an engineering system that comprises multiple subsystems (e.g., a system of multiple possibly interacting flow subsystems that include pumps, valves, tanks, ducts, sensors, and the like); 'Intelligent' is used here in the sense of artificial intelligence. An intelligent element may be physical or virtual, it is network enabled, and it is able to manage data, information, and knowledge (DIaK) focused on determining its condition in the context of the entire SoS; As used here, 'health' signifies the functionality and/or structural integrity of an engineering system, subsystem, or process (leading to determination of the health of components); 'Process' can signify either a physical process in the usual sense of the word or an element into which functionally related sensors are grouped; 'Element' can signify a component (e.g., an actuator, a valve), a process, a controller, an actuator, a subsystem, or a system; The term Integrated System Health Management (ISHM) is used to describe a capability that focuses on determining the condition (health) of every element in a complex system (detect anomalies, diagnose causes, prognosis of future anomalies), and provide data, information, and knowledge (DIaK) not just data to control systems for safe and effective operation. A major novel aspect of the present development is the concept of intelligent integration. The purpose of intelligent integration, as defined and implemented in the present IIHMS, is to enable automated analysis of physical phenomena in imitation of human reasoning, including the use of qualitative methods. Intelligent integration is said to occur in a system in which all elements are intelligent and can acquire, maintain, and share knowledge and information. In the HDNIE of the present IIHMS, an SoS is represented as being operationally organized in a hierarchical-distributed format. The elements of the SoS are considered to be intelligent in that they determine their own conditions within an integrated scheme that involves consideration of data, information, knowledge bases, and methods that reside in all elements of the system. The conceptual framework of the HDNIE and the methodologies of implementing it enable the flow of information and knowledge among the elements so as to make possible the determination of the condition of each element. The necessary information and knowledge is made available to each affected element at the desired time, satisfying a need to prevent information overload while providing context-sensitive information at the proper level of detail. Provision of high-quality data is a central goal in designing this or any IIHMS. In pursuit of this goal, functionally related sensors are logically assigned to groups denoted processes. An aggregate of processes is considered to form a system. Alternatively or in addition to what has been said thus far, the HDNIE of this IIHMS can be regarded as consisting of a framework containing object models that encapsulate all elements of the system, their individual and relational knowledge bases, generic methods and procedures based on models of the applicable physics, and communication processes (Figure 2). The framework enables implementation of a paradigm inspired by how expert operators monitor the health of systems with the help of (1) DIaK from various sources, (2) software tools that assist in rapid visualization of the condition of the system, (3) analical software tools that assist in reasoning about the condition, (4) sharing of information via network communication hardware and software, and (5) software tools that aid in making decisions to remedy unacceptable conditions or improve performance.

Smith, Harvey↗

NASA NTRS1985

Glass breaking strength: The role of surface flaws and treatments

Although the intrinsic strength of silicon dioxide glass is of the order of 10 to the 6th power lb/sq in, the practical strength is roughly two orders of magnitude below this theoretical limit, and depends almost entirely on the surface condition of the glass, that is, the number and size of flaws and the residual surface compression (temper) in the glass. Glass parts always fail in tension when these flaws grow under sustained loading to some critical size. Research associated with glass encapsulated crystalline-Si photovoltaic (PV) modules has greatly expanded our knowledge of glass breaking strength and developed sizeable data base for commercially available glass types. A detailed design algorithm is developed for thickness sizing of rectangular glass plates subject to pressure loads. Additional studies examine the strength of glass under impact loading conditions such as that caused by hail. Although the fundamentals of glass breakage are directly applicable to thin film modules, the fracture strength of typical numerical glass must be replaced with data that reflect the high temperature tin oxide processing, laser scribing, and edge processing peculiar to thin film modules. The fundamentals of glass breakage applicable to thin film modules and preliminary fracture strength data for a variety of 1 ft square glass specimens representing preprocessed and post processed sheets from current amorphous-Si module manufacturers are presented.

Moore, D.↗

NASA NTRS2001

Case-Based Capture and Reuse of Aerospace Design Rationale

The goal of this project was to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project combined case-based reasoning (CBR) and concept maps (CMaps) to develop methods for capturing, organizing, and interactively accessing records of experiences encapsulating the methods and rationale underlying expert aerospace design, in order to bring the captured knowledge to bear to support future reasoning. The project's results contribute both principles and methods for effective design-aiding systems that aid capture and access of useful design knowledge. The project has been guided by the tenets that design-aiding systems must: (1) Leverage a designer's knowledge, rather than attempting to replace it; (2) Be able to reflect different designers' differing conceptualizations of the design task, and to clarify those conceptualizations to others; (3) Include capabilities to capture information both by interactive knowledge modeling and during normal use; and (4) Integrate into normal designer tasks as naturally and unobtrusive as possible.

Leake, David B.↗

NASA NTRS1994

Collaborative engineering-design support system

Designing engineering objects requires many engineers' knowledge from different domains. There needs to be cooperative work among engineering designers to complete a design. Revisions of a design are time consuming, especially if designers work at a distance and with different design description formats. In order to reduce the design cycle, there needs to be a sharable design describing the engineering community, which can be electronically transportable. Design is a process of integrating that is not easy to define definitively. This paper presents Design Script which is a generic engineering design knowledge representation scheme that can be applied in any engineering domain. The Design Script is developed through encapsulation of common design activities and basic design components based on problem decomposition. It is implemented using CLIPS with a Windows NT graphical user interface. The physical relationships between engineering objects and their subparts can be constructed in a hierarchical manner. The same design process is repeatedly applied at each given level of hierarchy and recursively into lower levels of the hierarchy. Each class of the structure can be represented using the Design Script.

Lee, Dong HO↗

NASA NTRS2007

Systems Modeling to Implement Integrated System Health Management Capability

ISHM capability includes: detection of anomalies, diagnosis of causes of anomalies, prediction of future anomalies, and user interfaces that enable integrated awareness (past, present, and future) by users. This is achieved by focused management of data, information and knowledge (DIaK) that will likely be distributed across networks. Management of DIaK implies storage, sharing (timely availability), maintaining, evolving, and processing. Processing of DIaK encapsulates strategies, methodologies, algorithms, etc. focused on achieving high ISHM Functional Capability Level (FCL). High FCL means a high degree of success in detecting anomalies, diagnosing causes, predicting future anomalies, and enabling health integrated awareness by the user. A model that enables ISHM capability, and hence, DIaK management, is denominated the ISHM Model of the System (IMS). We describe aspects of the IMS that focus on processing of DIaK. Strategies, methodologies, and algorithms require proper context. We describe an approach to define and use contexts, implementation in an object-oriented software environment (G2), and validation using actual test data from a methane thruster test program at NASA SSC. Context is linked to existence of relationships among elements of a system. For example, the context to use a strategy to detect leak is to identify closed subsystems (e.g. bounded by closed valves and by tanks) that include pressure sensors, and check if the pressure is changing. We call these subsystems Pressurizable Subsystems. If pressure changes are detected, then all members of the closed subsystem become suspect of leakage. In this case, the context is defined by identifying a subsystem that is suitable for applying a strategy. Contexts are defined in many ways. Often, a context is defined by relationships of function (e.g. liquid flow, maintaining pressure, etc.), form (e.g. part of the same component, connected to other components, etc.), or space (e.g. physically close, touching the same common element, etc.). The context might be defined dynamically (if conditions for the context appear and disappear dynamically) or statically. Although this approach is akin to case-based reasoning, we are implementing it using a software environment that embodies tools to define and manage relationships (of any nature) among objects in a very intuitive manner. Context for higher level inferences (that use detected anomalies or events), primarily for diagnosis and prognosis, are related to causal relationships. This is useful to develop root-cause analysis trees showing an event linked to its possible causes and effects. The innovation pertaining to RCA trees encompasses use of previously defined subsystems as well as individual elements in the tree. This approach allows more powerful implementations of RCA capability in object-oriented environments. For example, if a pressurizable subsystem is leaking, its root-cause representation within an RCA tree will show that the cause is that all elements of that subsystem are suspect of leak. Such a tree would apply to all instances of leak-events detected and all elements in all pressurizable subsystems in the system. Example subsystems in our environment to build IMS include: Pressurizable Subsystem, Fluid-Fill Subsystem, Flow-Thru-Valve Subsystem, and Fluid Supply Subsystem. The software environment for IMS is designed to potentially allow definition of any relationship suitable to create a context to achieve ISHM capability.

Figueroa, Jorge F.↗

NASA NTRS2015

Industrialization of Space: Microgravity Based Opportunities for Material and Life Science

Microgravity based commercial opportunities are broad, with applications ranging from fiber optics, device-grade semiconductor crystals, space beads, new materials, cell micro encapsulation, 3D tissues and cell cultures, genetic and molecular changes of immune suppression, protein and virus crystal growth, perfume and hair care. To date, primarily the knowledge gained from observing and understanding new end states of systems unraveled in microgravity has been translated into unique technologies and business opportunities on Earth. In some instances existing light qualified hardware is immediately available for commercial RD for small scale in-space manufacturing. Overall products manufactured in microgravity have key properties usually surpassing the best terrestrial counterparts. The talk will address the potential benefits of microgravity research for a variety of terrestrial markets. Our findings originate from discussions with 100+ non-aerospace private companies among the high-tech Silicon Valley ecosystem, show that the opportunities and benefits of using the ISS are largely not considered by experts, primarily due to a lack of awareness of the breadth of terrestrial applications that have been enabled or enhanced by microgravity RD. Based on this dialogue, the concept of microgravity verticals is developed to translate the benefits of the microgravity environment into blue ocean business opportunities for various key US commercial sectors.

technical risk↗