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      Parametric Model Order Reduction for Gas Flow Models

      1 , 1 ,   , 1 , *

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      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
          10.14293/P2199-8442.1.SOP-MATH.EJOCET.v1
          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.

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