Abstract
CPU-intensive engineering problems such as networks of gas pipelines can be modelled as dynamical or quasi-static systems. These dynamical systems represent a map, depending on a set of control parameters, from an input signal to an output signal. In order to reduce the computational cost, surrogates based on linear combinations of translates of radial functions are a popular choice for a wide range of applications. Model order reduction, on the other hand, is an approach that takes the principal structure of the equations into account to construct low-dimensional approximations to the problem. We give an introductory survey of both methods, discuss their application to gas transport problems and compare both methods by means of a simple test case from industrial practice.
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Grundel, S., Hornung, N., Klaassen, B., Benner, P., Clees, T. (2013). Computing Surrogates for Gas Network Simulation Using Model Order Reduction. In: Koziel, S., Leifsson, L. (eds) Surrogate-Based Modeling and Optimization. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7551-4_9
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DOI: https://doi.org/10.1007/978-1-4614-7551-4_9
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