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      Parametric Model Order Reduction for Gas Flow Models

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      1 , 1 ,   1 , * ,
      ScienceOpen Posters
      ScienceOpen
      pMOR, Gas Transport, Empirical Gramians, DMD, POD
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            Abstract

            Planning the dispatch of contracted gas denominations requires various simulations of the involved gas transport infrastructure. Furthermore, due to the growing interplay of traditional gas transport and fluctuating demands related to renewable energies, the number of necessary simulations vastly increases. Mathematically, a system of Euler equations, which are coupled according to the underlying gas network topology, embodies the associated nonlinear and hyperbolic model. Repeated simulation of large networks for varying supply and demand scenarios often necessitates model order reduction. Yet, beyond these variable boundary conditions, further attributes of the network may be uncertain or need to be kept variable throughout simulations, which motivates parametric model order reduction (pMOR).

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            Author and article information

            Journal
            ScienceOpen Posters
            ScienceOpen
            27 April 2018
            Affiliations
            [1 ]Max Planck Institute for Dynamics of Complex Technical Systems
            [* ]Correspondence: himpe@ 123456mpi-magdeburg.mpg.de , Link to ScienceOpen Profile
            Article
            10.14293/P2199-8442.1.SOP-MATH.EJOCET.v1
            52caf0f5-0072-4a49-a233-1da7f34c5ef5
            Copyright © 2018

            This work has been published open access under Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com.

            History

            Applied mathematics,Applications,Statistics,Data analysis,Mathematics,Mathematical modeling & Computation
            DMD,Empirical Gramians,pMOR,POD,Gas Transport

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