Adaptive refinement strategies for the simulation of gas flow in networks using a model hierarchy. ETNA - Electronic Transactions on Numerical Analysis
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6 avril 2018
- handle: 10670/1.43xcxb
- issn: 1068-9613
- doi: 10.1553/etna_vol48s97
info:eu-repo/semantics/openAccess
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Aseem Dua et al., « Adaptive refinement strategies for the simulation of gas flow in networks using a model hierarchy. ETNA - Electronic Transactions on Numerical Analysis », Elektronisches Publikationsportal der Österreichischen Akademie der Wissenschafte, ID : 10.1553/etna_vol48s97
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Résumé
A model hierarchy that is based on the one-dimensional isothermal Euler equations of fluid dynamics is used for the simulation and optimisation of natural gas flow through a pipeline network. Adaptive refinement strategies have the aim of bringing the simulation error below a prescribed tolerance while keeping the computational costs low. While spatial and temporal stepsize adaptivity is well studied in the literature, model adaptivity is a new field of research. The problem of finding an optimal refinement strategy that combines these three types of adaptivity is a generalisation of the unbounded knapsack problem. A refinement strategy that is currently used in gas flow simulation software is compared to two novel greedy-like strategies. Both a theoretical experiment and a realistic gas flow simulation show that the novel strategies significantly outperform the current refinement strategy with respect to the computational cost incurred.