Predicting Manhole Mixing Using a Compartmental Model
Publication: Journal of Hydraulic Engineering
Volume 147, Issue 12
Abstract
Manholes in combined sewers may become surcharged during storm events, resulting in complex mixing conditions. Although manhole hydrodynamics are reasonably well understood, predicting mixing across a surcharged manhole remains a challenge. An analytical compartmental mixing model for manholes, based on jet theory, has been further developed and applied to generate cumulative residence time distributions (CRTDs), which describe mixing. The modeled CRTDs were compared with the experimentally derived CRTDs of over 850 manhole configurations to evaluate how well the new compartmental model represents physical processes. The model underpredicts short-circuiting in manholes with manhole diameter to pipe diameter ratios greater than 4.4 and consequently overestimates mixing. Otherwise, the modeled CRTDs show good agreement with the experimental CRTDs. The new compartmental model represents key manhole hydrodynamics that are not represented in current software modeling packages, which assume manholes are instantaneously well-mixed. The compartmental model provides good predictions of the experimental downstream concentration profiles, although with reduced peak concentrations in those manhole configurations where short-circuiting is not well-predicted. Despite this, the compartmental model still predicts concentrations downstream of a manhole in closer agreement with the recorded data than the complete instantaneously well-mixed assumption. As an analytical model requiring no inputs other than manhole geometry, the new compartmental model applies to a wide range of manhole configurations, is robust, and is useful for predicting manhole mixing in practical applications.
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Data Availability Statement
Data and code used during this study are available in a repository online in accordance with funder data retention policies from Guymer, I., Stovin, V., O’Brien, R., Dennis, P., Saiyudthong, C., Lau, S.-T. D., and Sonnenwald, F. (2020). https://doi.org/10.15131/shef.data.13373039 and Sonnenwald, F., Mark, O., Stovin, V., and Guymer, I. (2021). https://doi.org/10.15131/shef.data.14160884.
Acknowledgments
This work was supported by the EPSRC (Grant No. EP/P012027/1).
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Published In
Journal of Hydraulic Engineering
Volume 147 • Issue 12 • December 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Mar 26, 2021
Accepted: Aug 9, 2021
Published online: Sep 23, 2021
Published in print: Dec 1, 2021
Discussion open until: Feb 23, 2022
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Cited by
- Fred Sonnenwald, Joe Shuttleworth, Olivia Bailey, Margaret Williams, James Frankland, Becky Rhead, Ole Mark, Matthew J. Wade, Ian Guymer, Quantifying Mixing in Sewer Networks for Source Localization, Journal of Environmental Engineering, 10.1061/JOEEDU.EEENG-7134, 149, 5, (2023).