REAL Knowledge at NASA: A Knowledge Services Model for the Modern Project Environment
REAL Knowledge at NASA: A Knowledge Services Model for the Modern Project Environment
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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.
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REAL Knowledge at NASA: A Knowledge Services Model for the Modern Project Environment
The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.
A description is given of user interface research aimed at bringing together multiple input and output modes in a way that handles mixed mode input (commands, menus, forms, natural language), interacts with a diverse collection of underlying software utilities in a uniform way, and presents the results through a combination of output modes including natural language text, maps, charts and graphs. The system, Integrated Interfaces, derives much of its ability to interact uniformly with the user and the underlying services and to build its presentations, from the information present in a central knowledge base. This knowledge base integrates models of the application domain (Navy ships in the Pacific region, in the current demonstration version); the structure of visual displays and their graphical features; the underlying services (data bases and expert systems); and interface functions. The emphasis is on a presentation planner that uses the knowledge base to produce multi-modal output. There has been a flurry of recent work in user interface management systems. (Several recent examples are listed in the references). Existing work is characterized by an attempt to relieve the software designer of the burden of handcrafting an interface for each application. The work has generally focused on intelligently handling input. This paper deals with the other end of the pipeline - presentations.
The development of structural design tools for Rotary Combustion Engines (RCE) using Finite Element Modeling (FEM) requires knowledge about the response of engine materials to various service conditions. This paper describes experimental work that studied housing deformation as a result of thermal, pressure and mechanical loads. The measurement of thermal loads, clamping pressure, and deformation was accomplished by use of high-temperature strain gauges, thermocouples, and a high speed data acquisition system. FEM models for heat transfer stress analysis of the rotor housing will be verified and refined based on these experimental results.
Federal involvement in simulating economic growth through the development and application of technology policy is currently the subject of serious debate. A recession and the recognition that an internationally competitive economy is a prerequisite for the attainment of national goals have fostered a number of technology policy initiatives aimed at improving the economic competitiveness of American industry. This paper suggests that the successful implementation of U.S. technology policy will require the adoption of a knowledge diffusion model, the development of user oriented information products and services, and a more 'activist' approach on the part of sci/tech librarians in the provision of scientific and technical information (STI). These changes will have a dramatic impact on the sci/tech library of the future and the preparation of sci/tech librarians.
Federal involvement in stimulating economic growth through the development and application of technology policy is currently the subject of serious debate. A recession and the recognition that an internationally competitive economy is a prerequisite for the attainment of national goals have fostered a number of technology policy initiatives aimed at improving the economic competitiveness of American industry. This paper suggests that the successful implementation of U.S. technology policy will require the adoption of a knowledge diffusion model, the development of user oriented information products and services, and a more 'activist' approach on the part of sci/tech librarians in the provision of scientific and technical information (STI). These changes will have a dramatic impact on the sci/tech library of the future and the preparation of sci/tech librarians.
There is a wide range of complexity in the various telerobotic servicing tasks performed in subsea, space, and hazardous material handling environments. Experience with telerobotic servicing has evolved into a knowledge base used to design tasks to be 'telerobot friendly.' This knowledge base generally resides in a small group of people. Written documentation and requirements are limited in conveying this knowledge base to serviceable equipment designers and are subject to misinterpretation. A mathematical model of task complexity based on measurable task parameters and telerobot performance characteristics would be a valuable tool to designers and operational planners. Oceaneering Space Systems and TRW have performed an independent research and development project to develop such a tool for telerobotic orbital replacement unit (ORU) exchange. This algorithm was developed to predict an ORU exchange degree of difficulty rating (based on the Cooper-Harper rating used to assess piloted operations). It is based on measurable parameters of the ORU, attachment receptacle and quantifiable telerobotic performance characteristics (e.g., link length, joint ranges, positional accuracy, tool lengths, number of cameras, and locations). The resulting algorithm can be used to predict task complexity as the ORU parameters, receptacle parameters, and telerobotic characteristics are varied.
Human collaboration in distributed knowledge sharing groups depends on the functionality of information and communication technologies (ICT) to support performance. Since many of these dynamic environments are constrained by time limits, knowledge must be shared efficiently by adapting the level of information detail to the specific situation. This paper focuses on the process of knowledge and context sharing with and without mediation by ICT, as well as issues to be resolved when determining appropriate ICT channels. Both technology-rich and non-technology examples are discussed.
The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.
The initiation of deep convection during the warm season is a forecast challenge in the relative high instability and low wind shear environment of the U.S. Deep South. Despite improved knowledge of the character of well known mesoscale features such as local sea-, bay- and land-breezes, observations show the evolution of these features fall well short in fully describing the location of first initiates. A joint collaborative modeling effort among the NWS offices in Mobile, AL, and Houston, TX, and NASA s Short-term Prediction Research and Transition (SPoRT) Center was undertaken during the 2012 warm season to examine the impact of certain NASA produced products on the Weather Research and Forecasting Environmental Modeling System. The NASA products were: a 4-km Land Information System data, a 1-km sea surface temperature analysis, and a 4-km greenness vegetation fraction analysis. Similar domains were established over the southeast Texas and Alabama coastlines, each with a 9 km outer grid spacing and a 3 km inner nest spacing. The model was run at each NWS office once per day out to 24 hours from 0600 UTC, using the NCEP Global Forecast System for initial and boundary conditions. Control runs without the NASA products were made at the NASA SPoRT Center. The NCAR Model Evaluation Tools verification package was used to evaluate both the forecast timing and location of the first initiates, with a focus on the impacts of the NASA products on the model forecasts. Select case studies will be presented to highlight the influence of the products.
When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.
The Ourika watershed is characterized by higher than average flood flows, a rugged topography, a sparse vegetation cover and a friable substrate that makes it vulnerable to soil erosion. Soil is an important non-renewable asset capital, providing several ecosystem services that sustain life through physical and biological regulation processes. The loss, or otherwise, redistribution of biota by soil erosion in the Ourika watershed has received little attention and thus constitutes a key knowledge gap that needs to be addressed. This study quantifies the level of erosion and maps its spatial distribution in the watershed using the Sediment Delivery Ratio (SDR) of the Integrated Valuation of Ecosystem Services and Tradeoffs model (InVEST3.6.0). The SDR maps the overland sediment generation and delivery to the stream at the watershed level using rainfall, soil properties, topography, cover management and cropping practices as predefined set of input variables. Recommended internal model calibration was used and results were compared to similar studies carried out in different parts of Morocco for validation. The results reveal that 93% of the watershed is subject to a strong rainfall aggressiveness greater than 50 MJ mm ha–1 h–1 yr1 under an average rainfall intensity of 541 mm/year, rainfall capacity to initiate the detachment and transport of soil particles by runoff, and only 11.5% of the watershed area is protected with vegetative cover. We find that overall, the Ourika watershed is losing its soil to erosion at an alarming average rate of 258.48 ton.ha–1.yr–1, a rate well above the tolerable threshold of 7ton.ha–1.yr–1. The spatial distribution of this loss shows areas that need to be urgently remedied. The primary factors for soil erosion in the Ourika watershed appear to be related to the aggressive nature of local rainfall and the inherent susceptibility of soils, which can be costly to this cash-crop region. Because rainfall intensity, soil properties, and topography are intrinsic characteristics of the watershed, we suggest that seasonally adapted cropping rotations that maintains conservative practices with a high cover management may reduce soil erosion in the Ourika watershed.
The contents include: 1) What do most KMS in use today assume?; 2) Assumptions are violated when KMS is used by EKP workers - Why?; 3) Current State of KMS for EKPs are inadequate; 4) What would an "adequate" KMS for EKPs look like?; 5) "User-as-Consumer" Analogue: Ecommerce/Eem ployee Services; 6) Why is an ideal KMS for EKPs hard to achieve?; 7) So, what type of KMS design would work?; 8) Human-Based KMS for EKP - Proposal Call Managers at R&DLAB; 9) Proposal Call Managers (PCMs); 10) Specific PCM tasks; 11) Why is a R&DLAB PCM a human metaphor for a KMS for EKP?; 12) Data Collection; 13) Finding #1; 14) Finding #2; 15) Finding #3; 16) Factors affecting How/when; 17) Finding #4; 18) Finding #5; 19) Implication#l for a KMS for EKP: From System to Service; 20) Implication #2: From technology or human-centric to Mixed Mode; 21) Implication #3: From Simple User Profiles to Dynamic Delivery Profiles; 22) Implication #4: Maintaining a trustworthy environment; 23) Implication #5: Constructing a dynamic delivery profile; 24) Implications for Research: Model; and 25) Example Research Qs on KMS Support for EKPs.
The NEXT ion thruster is a low specific mass, high performance thruster with a nominal throttling range of 0.5 to 7 kW. Numerous engineering model and one prototype model thrusters have been manufactured and tested. Of significant importance to propulsion system performance is thruster-to-thruster performance dispersions. This type of information can provide a bandwidth of expected performance variations both on a thruster and a component level. Knowledge of these dispersions can be used to more conservatively predict thruster service life capability and thruster performance for mission planning, facilitate future thruster performance comparisons, and verify power processor capabilities are compatible with the thruster design. This study compiles the test results of five engineering model thrusters and one flight-like thruster to determine unit-to-unit dispersions in thruster performance. Component level performance dispersion analyses will include discharge chamber voltages, currents, and losses; accelerator currents, electron backstreaming limits, and perveance limits; and neutralizer keeper and coupling voltages and the spot-to-plume mode transition flow rates. Thruster level performance dispersion analyses will include thrust efficiency.
This paper discusses the various approaches to measuring the value of information, first defining the meanings of information, economics of information, and value. It concludes that no general model of measuring the value of information is possible and that the usual approaches, such as cost/benefit equations, have very limited applications. It also concludes that in specific contexts with given goals for newly developed products and services or newly acquired information, there is a basis for its objective valuation. The axioms and inputs for such a model are described and directions for further verification and analysis are proposed.
This paper discusses the various approaches to measuring the value of information, first defining the meanings of information, economics of information, and value. It concludes that no general model of measuring the value of information is possible and that the usual approaches, such as cost/benefit equations, have very limited applications. It also concludes that in specific contexts with given goals for newly developed products and services or newly acquired information there is a basis for its objective valuation. The axioms and inputs for such a model are described and directions for further verification and analysis are proposed.
Numerous automated and semi-automated planning & scheduling systems have been developed for space applications. Most of these systems are model-based in that they encode domain knowledge necessary to predict spacecraft state and resources based on initial conditions and a proposed activity plan. The spacecraft state and resources as often modeled as a series of timelines, with a timeline or set of timelines to represent a state or resource key in the operations of the spacecraft. In this paper, we first describe a basic timeline representation that can represent a set of state, resource, timing, and transition constraints. We describe a number of planning and scheduling systems designed for space applications (and in many cases deployed for use of ongoing missions) and describe how they do and do not map onto this timeline model.
NASA’s Goddard Earth Science (GES) Data and Information Services Center (DISC) is one of twelve data centers in NASA's Science Mission Directorate (SMD), providing vital earth science data to a diverse user base. To enhance the discoverability of this data, GES DISC employs a keyword search system, which leverages scientific keywords embedded in dataset metadata. However, the evolving nature of scientific applications of our data necessitates regular review and augmentation of these keywords. To address this, we developed a service to automatically predict missing science keywords in the metadata. This service constructs a knowledge graph from the latest GES DISC metadata within NASA’s Common Metadata Repository (CMR). Using an open-source library, we trained a machine learning model to predict absent science keywords in the metadata. Our preliminary results indicate that the model has high levels of accuracy at predicting science keywords in the dataset metadata when exposed to data not included in its training. These predicted keywords were then evaluated by GES DISC data curation scientists and compared against other AI tools for metadata augmentation. We aim to enhance the overall usability and accessibility of NASA’s earth science data by implementing this tool in our data curation processes.