The process of prot0!JPillg 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 me fast, accueate simulation of physical processes and design optimization using knowledge and computational models from !l1J(llip/e dircipliJJu (mllllj-p~sj(S OIld om/Ii-Hale IDO&/J) in science and engineering. Thus, the realization of rapid multidisciplinary prototyping is the new grrl/ld cballmge. In iliis application scenario the natural computational resource is a "computational grid" rnat connects the needed distributed hardware and somv:ue resources used w simulate the elements of the artifact. Our research goal is to address this application scenario in Ult: conte.xt of parallel computing, cluster computing (LAN based computational grids), and Intranet/Internet compurational grids. In this document, wc describe the initial design of a generic MPSE framework based on a ne[Work of computational agents assuming a net-centric nm-rimc support environment. Moreover, we prcsent thc realization of this framework for designing a prototype MPSE (GasTurbnLab) for supporting simul:ltions needed for the design of efficient gas turbine engines.

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Flow induced vibration of turbomachine blade rows is a coupled fluid-structure problem. Thus, rather than separate fluid and structural models, a coupled interacting fluid-structures analysis is needed. This research addresses this need by extending the finite element code ALE3D that solves the three-dimensional Euler equations to model the unsteady aerodynamics of turbomachine blade rows. The same finite element model is applied to both the blading and the fluid, resulting in consistency between the fluid and structure. This coupled interacting fluid-structure analysis enables the aerodynamic damping of multiple vibration modes to be predicted from a single time domain flow simulation. This novel approach to predict aerodynamic damping is demonstrated by considering a modem transonic compressor blade row. The blading is first impulsed in its first bending and first torsion modes in a vacuum. It is then immersed in the designpoint flow field and impulsed in its first bending and first torsion modes again. Signal processing tools applied to the predicted blade response time history extract the difference in the decay rate of both modes. spatial coordinate, i = I. 2, 3 nodal value. node number spatial coordinate, j = 1.2, 3 Descr;pl;on time step level node-centered element quantity

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