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  4. Numerical aspects of model order reduction for gas transportation networks
 
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2016
Conference Paper
Title

Numerical aspects of model order reduction for gas transportation networks

Abstract
The chapter focuses on the numerical solution of parametrized unsteady Eulerian flow of compressible real gas in pipeline distribution networks. Such problems can lead to large systems of nonlinear equations that are computationally expensive to solve by themselves, more so if parameter studies are conducted and the system has to be solved repeatedly. The stiffness of the problem adds even more complexity to the solution of these systems. Therefore, we discuss the application of model order reduction methods in order to reduce the computational costs. In particular, we apply two-sided projection via proper orthogonal decomposition with the discrete empirical interpolation method to exemplary realistic gas networks of different size. Boundary conditions are represented as inflow and outflow elements, where either pressure or mass flux is given. On the other hand, neither thermal effects nor more involved network components such as valves or regulators are considered. The numerical condition of the reduced system and the accuracy of its solutions are compared to the full-size formulation for a variety of inflow and outflow transients and parameter realizations.
Author(s)
Grundel, Sara
Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany
Hornung, Nils
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Roggendorf, Sarah
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Mainwork
Simulation-Driven Modeling and Optimization  
Conference
International Workshop on Advances in Simulation-Driven Optimization and Modeling (ASDOM) 2014  
DOI
10.1007/978-3-319-27517-8_1
Language
English
Fraunhofer-Institut für Algorithmen und Wissenschaftliches Rechnen SCAI  
Keyword(s)
  • gas network simulation

  • model order reduction

  • proper orthogonal decomposition

  • discrete empirical interpolation method

  • stiff initial-value problems

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