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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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The network was extensively tested for six months before Satloc began offering differential service to commercial users. During the 11 months that commercial service has been available we have gathered additional data to confirm the operating performance.
Abstract not provided.
Procedural modeling systems, rule based modeling systems, and a method for converting a procedural model to a rule based model are described. Simulation models are used to represent real time engineering systems. A real time system can be represented by a set of equations or functions connected so that they perform in the same manner as the actual system. Most modeling system languages are based on FORTRAN or some other procedural language. Therefore, they must be enhanced with a reaction capability. Rule based systems are reactive by definition. Once the engineering system has been decomposed into a set of calculations using only basic algebraic unary operations, a knowledge network of calculations and functions can be constructed. The knowledge network required by a rule based system can be generated by a knowledge acquisition tool or a source level compiler. The compiler would take an existing model source file, a syntax template, and a symbol table and generate the knowledge network. Thus, existing procedural models can be translated and executed by a rule based system. Neural models can be provide the high capacity data manipulation required by the most complex real time models.
The past decade has seen a rapid increase in availability and usage of near real-time data from satellite sensors. Applications have demonstrated the utility of timely data in a number of areas ranging from numerical weather prediction and forecasting, to monitoring of natural hazards, disaster relief, agriculture and homeland security. As applications mature, the need to transition from prototypes to operational capabilities presents an opportunity to improve current near real-time systems and inform future capabilities. This paper presents NASA s effort to implement a near real-time capability for land and atmosphere data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments on the Terra, Aqua, and Aura satellites. Index Terms- Real time systems, Satellite applications
This paper investigates implementations of process algebras which are suitable for modeling concurrent real-time systems. It suggests an approach for efficiently implementing real-time semantics using dynamic priorities. For this purpose a proces algebra with dynamic priority is defined, whose semantics corresponds one-to-one to traditional real-time semantics. The advantage of the dynamic-priority approach is that it drastically reduces the state-space sizes of the systems in question while preserving all properties of their functional and real-time behavior. The utility of the technique is demonstrated by a case study which deals with the formal modeling and verification of the SCSI-2 bus-protocol. The case study is carried out in the Concurrency Workbench of North Carolina, an automated verification tool in which the process algebra with dynamic priority is implemented. It turns out that the state space of the bus-protocol model is about an order of magnitude smaller than the one resulting from real-time semantics. The accuracy of the model is proved by applying model checking for verifying several mandatory properties of the bus protocol.
Many planned and proposed NASA science activities will benefit from precise real time positioning with wide area differential GPS (WADGPS). Future NASA users include orbital remote sensing instruments (altimeters, SARs, imagers) and a variety of airborne and Earth based investigations. Real time positioning requirements and goals range from a few meters to a few centimeters. Direct benefits will include the enabling of missions that are not now possible (such as precision remote sensing from the space shuttle and space station) and dramatic reduction of analysis costs for a diversity of current investigations.
A methodology for automatic mathematical modeling and generating simulation models is described. The models will be verified by running in a test environment using standard profiles with the results compared against known results. The major objective is to create a user friendly environment for engineers to design, maintain, and verify their model and also automatically convert the mathematical model into conventional code for conventional computation. A demonstration program was designed for modeling the Space Shuttle Main Engine Simulation. It is written in LISP and MACSYMA and runs on a Symbolic 3670 Lisp Machine. The program provides a very friendly and well organized environment for engineers to build a knowledge base for base equations and general information. It contains an initial set of component process elements for the Space Shuttle Main Engine Simulation and a questionnaire that allows the engineer to answer a set of questions to specify a particular model. The system is then able to automatically generate the model and FORTRAN code. The future goal which is under construction is to download the FORTRAN code to VAX/VMS system for conventional computation. The SSME mathematical model will be verified in a test environment and the solution compared with the real data profile. The use of artificial intelligence techniques has shown that the process of the simulation modeling can be simplified.
There are numberous definitions of real-time systems, the most stringent of which involve guaranteeing correct system response within a domain-dependent or situation-defined period of time.
The mobile range control center/range safety command destruct and real time instantaneous impact prediction system (MRCCS), designed for launching sounding rockets and expendable launch vehicles, is described. The MRCCS provides mission control and range safety support for remote launch sites and is equipped with telemetry and radar data acquisition systems, real time data computation systems, range safety display systems, and command destruct transmitters.
Not provided.
Excess stress caused by accumulation of misfolded proteins inside the endoplasmic reticulum (ER) lumen can cause cells to undergo apoptosis. Misfolded proteins exported from ER to cytoplasm are ubiquitinated and mostly degraded by the proteasome, but can also be destroyed by autophagy mediated by the docking proteins p62 and NBR1. When misfolded proteins accumulate beyond the capacity of these clearance systems, they are transported to the microtubule organization center to form aggresomes, which are also degraded by autophagy. Together, these phenomena suggest the existence of a coordinated intracellular network for coping with the accumulation of misfolded proteins. Thus, rational inhibition of this network system might enhance killing of cancer cells subjected to pronounced ER stress loading. Based on this rationale, we sought to establish a quantitative assay for monitoring ER stress loading. MDA-MB231 cells stably transfected with the ERAI-Venus vector exhibited a strong XBP1 splicing signal in response to ER stress. Using the IncuCyte cell imaging system, we monitored the fluorescence intensity of XBP1-Venus, normalized against cell density, as an ER stress indicator. This parameter correlated closely with other reporters of unfolded protein responses. Assessment of the XBP1-Venus signal during exposure to various drug combinations revealed that simultaneous inhibition of the proteasome, autophagy, and aggresome formation led to more effective ER stress loading and higher cytotoxicity than inhibition of only two components. Our data suggest that this monitoring system is a useful tool for designing effective drug combinations for ER stress loading in cancer therapy.
We report state estimation is a fundamental task in power systems. Although distribution systems are increasingly equipped with sensing devices and smart meters, measurements are typically reported at different rates and asynchronously; these aspects pose severe strains on workhorse state estimation algorithms, which are designed to process batches of data collected in a synchronous manner from all the measurement units. In this paper, we develop a novel state estimation algorithm to continuously update the estimate of the state based on measurements received in an asynchronous manner from measurement units. The synthesis of the algorithm hinges on a proximal-point type method, implemented in an online fashion, and capable of processing measurements received sequentially from sensors. A performance analysis is presented by providing bounds on the estimation error in terms of the mean and variance that hold at each iteration and asymptotically. The scheme is also compared with a more traditional Weighted Least Squares estimator that compensates for the lack of measurement data by using, as pseudo measurements, the measurement retrieved during a certain time window. Numerical simulations on the IEEE 37-bus feeder corroborate the analytical findings.
As electricity demand continues to grow and renewable energy increases its penetration in the power grid, realtime state estimation becomes essential for system monitoring and control. Recent development in phasor technology makes it possible with high-speed time-synchronized data provided by Phasor Measurement Units (PMU). In this paper we present a two-stage Kalman filter approach to estimate the static state of voltage magnitudes and phase angles, as well as the dynamic state of generator rotor angles and speeds. Kalman filters achieve optimal performance only when the system noise characteristics have known statistical properties (zero-mean, Gaussian, and spectrally white). However in practice the process and measurement noise models are usually difficult to obtain. Thus we have developed the Adaptive Kalman Filter with Inflatable Noise Variances (AKF with InNoVa), an algorithm that can efficiently identify and reduce the impact of incorrect system modeling and/or erroneous measurements. In stage one, we estimate the static state from raw PMU measurements using the AKF with InNoVa; then in stage two, the estimated static state is fed into an extended Kalman filter to estimate the dynamic state. Simulations demonstrate its robustness to sudden changes of system dynamics and erroneous measurements.
Model for HVAC system optimization in multi-family housing market.
Gemini and Apollo data transmission procedures and equipment for linking worldwide tracking sites and Cape Kennedy with Houston mission control center
The paper describes software techniques developed for the Unified Data System (UDS), a distributed processor network for control and data handling onboard a planetary spacecraft. These techniques include a structured language for specifying the programs contained in each module, and a small executive program in each module which performs scheduling and implements the module task.
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The rationale for system development is given along with reasons for not using vendor supplied operating systems. Although many system design and performance goals were dictated by problems with vendor supplied systems, other goals surfaced as a result of a design for a custom system able to span multiple projects. System development and management problems and areas that required redesign or major code changes for system implementation are examined as well as the relative successes of the initial projects. A generic description of the actual project is provided and the ongoing support requirements and future plans are discussed.