Non-linear optimization of a 1-D shallow water model and integration into Simulink for operational use

Goffin, Louis; Dewals, Benjamin; Erpicum, Sébastien; Pirotton, Michel; Archambeau, Pierre

doi:10.1201/b21902-78

Cited by 1 publication

(3 citation statements)

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“…In this context, the dam operator needs a fast computation routine in order to operate its facilities in an optimized and safe way. To do so, an unsteady 1-D model was implemented in Fortran and integrated in a Simulink S-Function in order to be compatible with the operator model [7]. Our new algorithm was used for the fast computation of an initial condition.…”

Section: Real-world Applicationmentioning

confidence: 99%

“…The studied part of the Romanche River stretches over 9.5 km (Figure 14), from the new Livet Dam to Gavet. The geometry and the calibration of the friction coefficients are detailed in [7]. The river was discretized with 191 nodes (50 m-long meshes).…”

Section: Real-world Applicationmentioning

confidence: 99%

“…A 1-D model can still be used in the case of out-of-bank flooding, although they are unable to represent complex 2-D flow patterns in the floodplain [4]. Several practical cases have shown that flood mapping can be performed using 1-D models [5,6] and they can also be used in other fields, such as flood routing for hydropower plant operations [7] and mixed flows in pipes [8].…”

Section: Introductionmentioning

confidence: 99%

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An Optimized and Scalable Algorithm for the Fast Convergence of Steady 1-D Open-Channel Flows

Goffin

Dewals

Erpicum

et al. 2020

Water

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Calculating an open-channel steady flow is of main interest in many situations; this includes defining the initial conditions for the unsteady simulation or the computation of the water level for a given discharge. There are several applications that require a very short computation time in order to envisage a large number of runs, for example, uncertainty analysis or optimization. Here, an optimized algorithm was implemented for the fast and efficient computation of a 1-D steady flow. It merges several techniques: a pseudo-time version of the Saint-Venant equations, an evolutionary domain and the use of a non-linear Krylov accelerator. After validation of this new algorithm, we also showed that it performs well in scalability tests. The computation cost evolves linearly with the number of nodes. This was also corroborated when the execution time was compared to that obtained by the non-linear solver, CasADi. A real-world example using a 9.5 km stretch of river confirmed that the computation times were very short compared to a standard time-dependent computation.

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Section: Real-world Applicationmentioning

confidence: 99%

Section: Real-world Applicationmentioning

confidence: 99%