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Showing papers on "Modeling and simulation published in 1982"


Book
01 Jan 1982

22 citations



Proceedings Article
02 Nov 1982

9 citations



01 Jan 1982
TL;DR: A real time propulsion system modeling technique which provides the capabilities needed to evaluate propulsion system performance and aircraft system interaction on manned flight simulators was developed and demonstrated using flight simulator facilities at NASA Ames.
Abstract: The emphasis on increased aircraft and propulsion control system integration and piloted simulation has created a need for higher fidelity real time dynamic propulsion models. A real time propulsion system modeling technique which satisfies this need and which provides the capabilities needed to evaluate propulsion system performance and aircraft system interaction on manned flight simulators was developed and demonstrated using flight simulator facilities at NASA Ames. A piecewise linear state variable technique is used. This technique provides the system accuracy, stability and transient response required for integrated aircraft and propulsion control system studies. The real time dynamic model includes the detail and flexibility required for the evaluation of critical control parameters and propulsion component limits over a limited flight envelope. The model contains approximately 7.0 K bytes of in-line computational code and 14.7 K of block data. It has an 8.9 ms cycle time on a Xerox Sigma 9 computer. A Pegasus-Harrier propulsion system was used as a baseline for developing the mathematical modeling and simulation technique. A hydromechanical and water injection control system was also simulated. The model was programmed for interfacing with a Harrier aircraft simulation at NASA Ames. Descriptions of the real time methodology and model capabilities are presented.

6 citations


Journal ArticleDOI
TL;DR: This representation gives an overview about different aspects of modeling and simulation techniques applied in these tools in the design of IC's as an aid to optimize devices, reduce design time and costs.

5 citations



Proceedings ArticleDOI
Douglas G. Boike1, Edward H. Ernst1
17 Mar 1982
TL;DR: The applications are the optimization of performance parameters, subsystem requirements, tolerances, aging, and setpoints, as well as the examination of the performance of a population, which encompass customer utilization and service interactions.
Abstract: As part of the product development cycle, the Xerox Corporation has evolved a modeling and simulation methodology. This paper describes the approach, its use, and value in product development. To provide a common basis for understanding the modeling activities to be discussed, a brief overview of the xerographic process as used in our current duplicator copier products is described. Each of the functions is discussed in terms of how they contribute to the overall systems model and how they are linked together in this model. A brief description of the data acquisition system used for model validation is included.A discussion of the FORTRAN-based simulation language, analysis tools, and its flexibility is presented. The application of this modeling approach at Xerox is illustrated. The applications are the optimization of performance parameters, subsystem requirements, tolerances, aging, and setpoints, as well as the examination of the performance of a population. These population studies encompass customer utilization and service interactions. The advantages of this process will be discussed, including the design efficiencies enabled, service policy optimization, and field performance projection of the product population.

2 citations


Journal ArticleDOI
TL;DR: The aim of the proposed new system is to encourage experimental modeling and simulation of comlex real world problems and to gain an appropriate level of detail.
Abstract: Most simulation systems are able to cope with large 'white box' problems, but their application proves to be difficult in case of 'grey box' and 'black box' problems in the social sciences. Even recently developed interactive tools for simulation and structural modeling cannot manage large scale models without difficulties. A computer-aided method is missing for the modeling and simulation of large-scale real-world problems. At the Department of Medical Cybernetics of the University of Vienna Medical School simulation languages and 'modeling tools' are applied in different non-technical fields. First our experience with four systems (CSMP, QSIM3, SPIN, SISSY) is described. A methodological concept is presented for computer-assisted modeling and simulation of time oriented systems. It provides among other features: user defined types of structural elements and relations by means of a meta-definition language; relational networks for the structural representation; defined interfaces between structural representation and processes; support of top-down and bottom-up approaches by incorporation of ordering relationships within the model entities; communication, useability and documentation for the novice and advanced modeler. The aim of the proposed new system is to encourage experimental modeling and simulation of comlex real world problems and to gain an appropriate level of detail. The concepts for the realization are presented.

1 citations


01 Aug 1982
TL;DR: In this paper, a mathematical model characterizing the dynamic behavior of an engine at idle is first formulated and a number of simple on-vehicle tests are described and associated equations are derived to allow estimation of the model parameters.
Abstract: Idle speed control for automobiles performs two functions: it reduces the variation of engine speed at idle due to changes in accessory load usage and it allows a lowered idle speed giving a fuel economy improvement. This paper describes a modeling and simulation approach to designing an idle-speed control system. A mathematical model characterizing the dynamic behavior of an engine at idle is first formulated. A number of simple on-vehicle tests are described and associated equations are derived to allow estimation of the model parameters. With the aid of a computer simulation, a nonlinear control algorithm based upon the PID controller concept was developed. Finally, simulation and vehicle test results are compared to demonstrate the validity of this approach.

1 citations