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At least 199 records · Page 11

Considerations on real-time processing of spaceborne synthetic aperture radar data

This paper comprises a description of Synthetic Aperture Radar (SAR) processing approaches and a discussion on the processor complexity measures. The objective of the paper is to provide basic system knowledge on the design of a real-time signal processor for spaceborne synthetic aperture radar. A review of SAR sensor performance capability and general electronic processing approaches will be given first. The discussion of SAR processor complexity is divided into two areas: the arithmetic complexity and the control complexity. A generalized treatment of these subjects is provided. The results could be readily extended to special cases.

Wu, C.↗

The design and application of a Transportable Inference Engine (TIE1)

A Transportable Inference Engine (TIE1) system has been developed by the author as part of the Interactive Experimenter Planning System (IEPS) task which is involved with developing expert systems in support of the Spacecraft Control Programs Branch at Goddard Space Flight Center in Greenbelt, Maryland. Unlike traditional inference engines, TIE1 is written in the C programming language. In the TIE1 system, knowledge is represented by a hierarchical network of objects which have rule frames. The TIE1 search algorithm uses a set of strategies, including backward chaining, to obtain the values of goals. The application of TIE1 to a spacecraft scheduling problem is described. This application involves the development of a strategies interpreter which uses TIE1 to do constraint checking.

Mclean, David R.↗

Training for 21st century space missions

Although specific recommendations are difficult to make about spacecraft and missions not yet designed, several general guidelines are presently formulated concerning the training of future, long-duration space mission crews. Training systems should be embedded in the normal controls and displays of the spacecraft used, so that critical maneuvers can be practiced as often as possible. Some system for computer-based training should be available onboard, in order to maintain the spacecraft system-knowledge of the crew at a high level and deepen understanding of malfunction responses.

Hughes, Frank E.↗

The design and application of a Transportable Inference Engine (TIE1)

A Transportable Inference Engine (TIE1) system has been developed by the author as part of the Interactive Experimenter Planning System (IEPS) task which is involved with developing expert systems in support of the Spacecraft Control Programs Branch at Goddard Space Flight Center in Greenbelt, Maryland. Unlike traditional inference engines, TIE1 is written in the C programming language. In the TIE1 system, knowledge is represented by a hierarchical network of objects which have rule frames. The TIE1 search algorithm uses a set of strategies, including backward chaining, to obtain the values of goals. The application of TIE1 to a spacecraft scheduling problem is described. This application involves the development of a strategies interpreter which uses TIE1 to do constraint checking.

Mclean, David R.↗

SHARP: Spacecraft Health Automated Reasoning Prototype

The planetary spacecraft mission OPS as applied to SHARP is studied. Knowledge systems involved in this study are detailed. SHARP development task and Voyager telecom link analysis were examined. It was concluded that artificial intelligence has a proven capability to deliver useful functions in a real time space flight operations environment. SHARP has precipitated major change in acceptance of automation at JPL. The potential payoff from automation using AI is substantial. SHARP, and other AI technology is being transferred into systems in development including mission operations automation, science data systems, and infrastructure applications.

Atkinson, David J.↗

Intelligent systems engineering methodology

An added challenge for the designers of large scale systems such as Space Station Freedom is the appropriate incorporation of intelligent system technology (artificial intelligence, expert systems, knowledge-based systems, etc.) into their requirements and design. This presentation will describe a view of systems engineering which successfully addresses several aspects of this complex problem: design of large scale systems, design with requirements that are so complex they only completely unfold during the development of a baseline system and even then continue to evolve throughout the system's life cycle, design that involves the incorporation of new technologies, and design and development that takes place with many players in a distributed manner yet can be easily integrated to meet a single view of the requirements. The first generation of this methodology was developed and evolved jointly by ISX and the Lockheed Aeronautical Systems Company over the past five years on the Defense Advanced Research Projects Agency/Air Force Pilot's Associate Program, one of the largest, most complex, and most successful intelligent systems constructed to date. As the methodology has evolved it has also been applied successfully to a number of other projects. Some of the lessons learned from this experience may be applicable to Freedom.

Fouse, Scott↗

Getting the Lowdown on Airborne Pollutants

Opto-Knowledge Systems, Inc. was founded in 1991 specifically to take advantage of the emergence of a new technology field related to spectral imaging. The technology has applications in diverse areas such as Earth remote sensing, agriculture, geology, medical diagnosis, manufacturing, forensics, and more. Under the NASA/Goddard Space Flight Center STTR project, OKSI developed several major aspects to further the state of the art, resulting in several commercial products.

Source record↗

A Data-Driven Solution for Performance Improvement

Marketed as the "Software of the Future," Optimal Engineering Systems P.I. EXPERT(TM) technology offers statistical process control and optimization techniques that are critical to businesses looking to restructure or accelerate operations in order to gain a competitive edge. Kennedy Space Center granted Optimal Engineering Systems the funding and aid necessary to develop a prototype of the process monitoring and improvement software. Completion of this prototype demonstrated that it was possible to integrate traditional statistical quality assurance tools with robust optimization techniques in a user- friendly format that is visually compelling. Using an expert system knowledge base, the software allows the user to determine objectives, capture constraints and out-of-control processes, predict results, and compute optimal process settings.

Source record↗

The Impact of Urbanization on the Precipitation Component of the Water Cycle: A New Perspective

It is estimated that by the year 2025, 60% of the world s population will live in cities (UNFP, 1999). As cities continue to grow, urban sprawl (e.g., the expansion of urban surfaces outward into rural surroundings) creates unique problems related to land use, transportation, agriculture, housing, pollution, and development. Urban expansion also has measurable impacts on environmental processes. Urban areas modify boundary layer processes through the creation of an urban heat island (UHI). The literature indicates that the signature of the urban heat island effect may be resolvable in rainfall patterns over and downwind of metropolitan areas. However, a recent U.S. Weather Research Program panel concluded that more observational and modeling research is needed in this area (Dabberdt et al. 2000). NASA and other agencies initiated programs such as the Atlanta Land-use Analysis: Temperature and Air Quality Project (ATLANTA) (Quattrochi et al. 1998) which aimed to identify and understand how urban heat islands impact the environment. However, a comprehensive assessment of the role of urban-induced rainfall in the global water and energy cycle (GWEC) and cycling of freshwater was not a primary focus of these efforts. NASA's Earth Science Enterprise (ESE) seeks to develop a scientific understanding of the Earth system and its response to natural or human-induced changes to enable improved prediction capability for climate, weather, and natural hazards (NASA, 2000). Within this mission, the ESE has three basic thrusts: science research to increase Earth system knowledge; an applications program to transfer science knowledge to practical use in society; and a technology program to enable new, better, and cheaper capabilities for observing the earth. Within this framework, a research program is underway to further address the co-relationship between land cover use and change (e.g. urban development) and its impact on key components of the GWEC (e.g., precipitation). This presentation discusses the feasibility of using the TRMM or GPM satellite to identify precipitation anomalies likely caused by urbanization (Shepherd et al. 2002). Recent results from analyses of TRMM data around several major U.S. cities (e.g. Dallas, Atlanta, Houston) will be discussed. The presentation also summarizes a NASA-funded research effort to investigate the phenomenon of urban-induced precipitation anomalies using TRMM (future GPM) satellite-based remote sensing, an intensive ground observation/validation effort near Atlanta, and coupled atmosphere-land numerical modeling techniques.

Shephard, J. Marshal↗

Sintering of Lunar and Simulant Glass

Most oxygen-extraction techniques are temperature-dependent, with higher temperatures resulting in higher oxygen yield. An example is hydrogen reduction, in which the optimum process temperature is 1050 C. However, glass-rich lunar soil begins to show the effects of sintering at temperatures of 900 C or lower. Sintering welds particles together due to viscous relaxation of the glass in the sample. One approach to avoid problems related to sintering, such as difficulty in removing waste material from the reactor, is to keep the soil in motion. One of several methods being studied to accomplish this is fluidized-bed processing techniques, in which the grains are kept in motion by the action of flowing reductant gas. The spent material can be removed from the chamber while still fluidized, or the fluidizing motion can continue until the material has cooled below approx. 500 C. Until end-to-end prototypes are built that can remove the heated soil, the most practical option is to keep the bed fluidized while cooling the waste material. As ISRU technology advances, another option will become valuable, which is to intentionally sinter the material to a great enough extent that it becomes a brick. The free iron in lunar soil is magnetic, and ferromagnetic bricks can be manipulated by robotic systems using electromagnetic end effectors. Finally, if an electromagnetic field is applied to the soil while the brick is being formed, the brick itself will become a magnet. This property can be used to create self-aligning bricks or other building materials that do not require fasteners. Although sintering creates a challenge for early lunar surface systems, knowledge gained during prototype development will be valuable for the advanced lunar outpost.

Cooper, Bonnie L.↗

Improving Computational Efficiency of Prediction in Model-Based Prognostics Using the Unscented Transform

Model-based prognostics captures system knowledge in the form of physics-based models of components, and how they fail, in order to obtain accurate predictions of end of life (EOL). EOL is predicted based on the estimated current state distribution of a component and expected profiles of future usage. In general, this requires simulations of the component using the underlying models. In this paper, we develop a simulation-based prediction methodology that achieves computational efficiency by performing only the minimal number of simulations needed in order to accurately approximate the mean and variance of the complete EOL distribution. This is performed through the use of the unscented transform, which predicts the means and covariances of a distribution passed through a nonlinear transformation. In this case, the EOL simulation acts as that nonlinear transformation. In this paper, we review the unscented transform, and describe how this concept is applied to efficient EOL prediction. As a case study, we develop a physics-based model of a solenoid valve, and perform simulation experiments to demonstrate improved computational efficiency without sacrificing prediction accuracy.

Daigle, Matthew John↗

Distributed Damage Estimation for Prognostics based on Structural Model Decomposition

Model-based prognostics approaches capture system knowledge in the form of physics-based models of components, and how they fail. These methods consist of a damage estimation phase, in which the health state of a component is estimated, and a prediction phase, in which the health state is projected forward in time to determine end of life. However, the damage estimation problem is often multi-dimensional and computationally intensive. We propose a model decomposition approach adapted from the diagnosis community, called possible conflicts, in order to both improve the computational efficiency of damage estimation, and formulate a damage estimation approach that is inherently distributed. Local state estimates are combined into a global state estimate from which prediction is performed. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the approach.

Daigle, Matthew↗

Bayesian Framework Approach for Prognostic Studies in Electrolytic Capacitor under Thermal Overstress Conditions

Electrolytic capacitors are used in several applications ranging from power supplies for safety critical avionics equipment to power drivers for electro-mechanical actuator. Past experiences show that capacitors tend to degrade and fail faster when subjected to high electrical or thermal stress conditions during operations. This makes them good candidates for prognostics and health management. Model-based prognostics captures system knowledge in the form of physics-based models of components in order to obtain accurate predictions of end of life based on their current state of heal th and their anticipated future use and operational conditions. The focus of this paper is on deriving first principles degradation models for thermal stress conditions and implementing Bayesian framework for making remaining useful life predictions. Data collected from simultaneous experiments are used to validate the models. Our overall goal is to derive accurate models of capacitor degradation, and use them to remaining useful life in DC-DC converters.

Kulkarni, Chetan S.↗

A Framework to Debug Diagnostic Matrices

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Model-based↗

Improving Decision-Making Activities for Meningitis and Malaria

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

parasitic diseases↗

User Needs and Assessing the Impact of Low Latency NASA Earth Observation Data Availability on Societal Benefit

Since the advent of NASA's Earth Observing System, knowledge of the practical benefits of Earth science data has grown considerably. The community using NASA Earth science observations in applications has grown significantly, with increasing sophistication to serve national interests. Data latency, or how quickly communities receive science observations after acquisition, can have a direct impact on the applications and usability of the information. This study was conducted to determine how users are incorporating NASA data into applications and operational processes to benefit society beyond scientific research, as well as to determine the need for data latency of less than 12 h. The results of the analysis clearly show the significant benefit to society of serving the needs of the agricultural, emergency response, environmental monitoring and weather communities who use rapidly delivered, accurate Earth science data. The study also showed the potential of expanding the communities who use low latency NASA science data products to provide new ways of transforming data into information. These benefits can be achieved with a clear and consistent NASA policy on product latency.

NASA↗

The SCIFLI Airborne Observation of Artemis 1 Ascent

SCIFLI, The Scientifically Calibrated In-Flight Imagery (https://scifli.larc.nasa.gov/), team at NASA Langley Research Center specializes in the collection of multispectral data for space vehicles during Ascent and Entry, Descent, and Landing (EDL) observations. Multispectral datasets are invaluable across the NASA Agency and to commercial stakeholders for evaluating the performance of launch and re-entry space vehicles and ensuring the safety of the scientific research community. The launch of Artemis 1 marked the initiation of NASA returning to lunar exploration. SCIFLI’s Airborne Multispectral Imager (SAMI) was deployed by the SCIFLI team to scientifically document the historic event and provide the NASA research community with aerial footage of the event in wavelength channels ranging from the ultraviolet (UV) to the visible (VIS) to mid-wave infrared (MWIR). SAMI was designed to spectrally image unique aerothermal phenomena during the Artemis 1 launch. The use of these datasets captured in-flight during the launch will provide insight to research organizations across the Agency; aiding in validation efforts for simulations and modeling that contributed to the kickoff of the Agency’s resurgence to lunar exploration. This presentation will focus on the imagery captured on SAMI by the WB-57 team on November 16th, 2022, during the observation. Imaging objectives were identified and considered beforehand to determine the configuration of the SAMI instrument for the imaging mission. SCIFLI and Opto-Knowledge Systems, Inc. (OKSI) performed a thorough review of the datasets collected to identify and characterize aerothermal phenomena occurring during the observation. Additional post-processing was completed to provide quantitatively calibrated temperature images of the rocket during the observation. Some of the candidates were not optimal for quantitative temperature extraction due to common degradation factors, but after various image enhancements they proved useful for qualitatively characterizing different phenomena during the observation.

Artemis1↗

Assessing the impact of modeling limits on intelligent systems

The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifying limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.

Rouse, William B.↗