2017
DOI: 10.1016/j.flowmeasinst.2017.09.011
|View full text |Cite
|
Sign up to set email alerts
|

Validation of computational fluid dynamics for deriving weir discharge relationships with scale model experiments and prototype measurements

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2017
2017
2022
2022

Publication Types

Select...
6

Relationship

0
6

Authors

Journals

citations
Cited by 6 publications
(2 citation statements)
references
References 20 publications
0
2
0
Order By: Relevance
“…It has suitable numerical solutions for the flow characteristics of physical problems such as steady and unsteady flow, laminar flow, and turbulence and achieves the best in terms of calculation speed, stability, and accuracy, so as to reveal its comprehensive performance. Daal-Rombouts et al combined lab experiments and field measurements to demonstrate that the complex hydraulic behavior, including a flow regime change, can be precisely simulated [15]. A similar conclusion is obtained by Dufresne et al [10], who employed particle image velocimetry and acoustic Doppler velocimetry to measure the flow field, and compared to the simulated results.…”
Section: Introductionmentioning
confidence: 74%
“…It has suitable numerical solutions for the flow characteristics of physical problems such as steady and unsteady flow, laminar flow, and turbulence and achieves the best in terms of calculation speed, stability, and accuracy, so as to reveal its comprehensive performance. Daal-Rombouts et al combined lab experiments and field measurements to demonstrate that the complex hydraulic behavior, including a flow regime change, can be precisely simulated [15]. A similar conclusion is obtained by Dufresne et al [10], who employed particle image velocimetry and acoustic Doppler velocimetry to measure the flow field, and compared to the simulated results.…”
Section: Introductionmentioning
confidence: 74%
“…The high temporal and spatial variability of pollution flow would require RTC to distinguish between highly polluted and less polluted flows. Pilot studies show promising results using conductivity and turbidity sensors as real-time surrogates for pollution potential . Such information coupled with RTC, in the near future, would allow stormwater discharge to be managed on the basis of the impact potential on the receiving water body. MPC is an advanced RTC technique, in which the optimization is based not only on the knowledge of the current state of the system but also on its forecast state.…”
Section: Approaches To Data-driven Uwmmentioning
confidence: 99%