Technical Papers
Jul 12, 2016

Adaptive Hybrid Transient Formulation for Simulating Incompressible Pipe Network Hydraulics

Publication: Journal of Hydraulic Engineering
Volume 142, Issue 11

Abstract

Many studies have aimed to characterize pressurized transient hydraulics. However, it remains difficult to assess the importance of dynamic effects in a robust manner, and modeling is further complicated by the tension between computational efficiency and physical accuracy. To address such challenges for incompressible flows, this article presents an adaptive modeling approach that combines a novel hybrid formulation, termed the hybrid global gradient algorithm (HGGA), with a variable time step (VTS). The HGGA combines the generalized and rigid water column global gradient algorithms, so it can adapt to inertially-dominated flows and those without such effects. Computational efficiency and physical accuracy are balanced by adjusting the formulation according to the simulated hydraulics. Three physically-based indicators are then introduced to characterize unsteady flow: these actively inform the HGGA of how to model a system. Two pipe networks are used to demonstrate the current work. The first illustrates the utility of the inertial indicators, and the second comprises an extended period simulation with the VTS scheme. Although more computationally intensive than conventional modeling, the methodology is shown to provide a better representation of dynamic hydraulics.

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Acknowledgments

We thank the three reviewers for their helpful and stimulating comments. The financial support from the Natural Sciences and Engineering Research Council of Canada and FP&P HydraTek Inc. is also acknowledged and greatly appreciated.

References

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Go to Journal of Hydraulic Engineering
Journal of Hydraulic Engineering
Volume 142Issue 11November 2016

History

Received: Jul 30, 2015
Accepted: Apr 14, 2016
Published online: Jul 12, 2016
Published in print: Nov 1, 2016
Discussion open until: Dec 12, 2016

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J. D. Nault, S.M.ASCE [email protected]
Ph.D. Student, Univ. of Toronto, 35 St. George St., Toronto, ON, Canada M5S 1A4 (corresponding author). E-mail: [email protected]
B. W. Karney, M.ASCE [email protected]
Professor, Univ. of Toronto, 35 St. George St., Toronto, ON, Canada M5S 1A4. E-mail: [email protected]

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