An Agent-Based Netcentric Framework for Multidisciplinary Problem Solving Environments (MPSE).

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Title: An Agent-Based Netcentric Framework for Multidisciplinary Problem Solving Environments (MPSE).
Authors: Markus, S., Houstis, E. N., Catlin, A. C., Rice, J. R., Tsompanopoulou, P., Vavalis, E., Gottfried, D., Su, K., Balakrishnan, G.
Source: International Journal of Computational Engineering Science. Jun2000, Vol. 1 Issue 1, p33. 28p.
Subjects: Netcentric computing, Problem solving
Abstract: The process of prototyping is part of every scientific inquiry, product design, and learning activity. The new economic realities require the rapid prototyping of manufactured artifacts and rapid solutions to problems with numerous interrelated elements. This, in turn, requires the fast, accurate simulation of physical processes and design optimization using knowledge and computational models from multiple disciplines (multi-physics and multi-scale models) in science and engineering. Thus, the realization of rapid multidisciplinary prototyping is the new grand challenge. In this application scenario the natural computational resource is a "computational grid" that connects the needed distributed hardware and software resources used to simulate the elements of the artifact. Our research goal is to address this application scenario in the context of parallel computing, cluster computing (LAN based computational grids), and Intranet/Internet computational grids. In this document, we describe the initial design of a generic MPSE framework based on a network of computational agents assuming a net-centric run-time support environment. Moreover, we present the realization of this framework for designing a prototype MPSE (GasTurbnLab) for supporting simulations needed for the design of efficient gas turbine engines. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Computational Engineering Science is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Computational+Engineering+Science%22">International Journal of Computational Engineering Science</searchLink>. Jun2000, Vol. 1 Issue 1, p33. 28p.
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  Data: The process of prototyping is part of every scientific inquiry, product design, and learning activity. The new economic realities require the rapid prototyping of manufactured artifacts and rapid solutions to problems with numerous interrelated elements. This, in turn, requires the fast, accurate simulation of physical processes and design optimization using knowledge and computational models from multiple disciplines (multi-physics and multi-scale models) in science and engineering. Thus, the realization of rapid multidisciplinary prototyping is the new grand challenge. In this application scenario the natural computational resource is a "computational grid" that connects the needed distributed hardware and software resources used to simulate the elements of the artifact. Our research goal is to address this application scenario in the context of parallel computing, cluster computing (LAN based computational grids), and Intranet/Internet computational grids. In this document, we describe the initial design of a generic MPSE framework based on a network of computational agents assuming a net-centric run-time support environment. Moreover, we present the realization of this framework for designing a prototype MPSE (GasTurbnLab) for supporting simulations needed for the design of efficient gas turbine engines. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Computational Engineering Science is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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