Mixing at Cross Junctions in Water Distribution Systems. II: Experimental Study

Austin, R. G.; Waanders, Bart van Bloemen; McKenna, Sean Andrew; Choi, Christopher Y.

doi:10.1061/(asce)0733-9496(2008)134:3(295)

Cited by 55 publications

(20 citation statements)

References 4 publications

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“…Methodology for earlier experiments. A number of experiments have been performed to characterize the mixing behavior within individual pipe joints (Austin et al, 2008; McKenna et al, 2007; O'Rear et al, 2005). Pumps were used to supply water through pipes joined by a cross junction.…”

Section: Description Of Physical Mixing Processesmentioning

confidence: 99%

“…Water distribution analysis software such as EPANET (Rossman, 2000) typically assumes complete and instantaneous mixing within a junction such that the outlet concentrations are all equal. However, recent studies have shown that flow in cross junctions can result in incomplete mixing under a wide range of conditions (Austin et al, 2008; Ho, 2008; Romero‐Gomez et al, 2008; Ho et al, 2007, 2006; McKenna et al, 2007; Webb & van Bloemen Waanders, 2006; O'Rear et al, 2005; van Bloemen Waanders et al, 2005). Impinging flows within a cross junction tended to bifurcate and reflect off one another rather than mix completely.…”

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confidence: 99%

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Evaluation of solute mixing in water distribution pipe junctions

Ho¹,

Orear²

2009

Journal AWWA

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Growing public concern about potential contaminant transport in water distribution systems has increased the use of models to assess risk and detect sources of contamination. The movement and distribution of contaminants depend largely on mixing at pipe junctions, where different flow rates and contaminant concentrations can exist. This article presents experimental observations of solute mixing in various pipe junction configurations. Analytical models are derived for each configuration, and results are compared with experimental data. A key finding—that impinging fluid streams within a junction often do not mix completely—is contrary to the most common assumption of complete mixing in pipe junctions. This study finds that if concentrations of two incoming fluid streams differ, they tend to bifurcate and reflect off one another, affecting subsequent solute distribution and mixing of fluid streams. The authors introduce a new bulk‐advective mixing (BAM) model that has been shown to accurately represent this behavior and lead to more accurate water quality assessments.

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Section: Description Of Physical Mixing Processesmentioning

confidence: 99%

mentioning

confidence: 99%

Evaluation of solute mixing in water distribution pipe junctions

Ho¹,

Orear²

2009

Journal AWWA

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“…The conventional assumption of perfect mixing at junctions has been studied with measurements and Computational Fluid Dynamics modelling (Austin et al, 2008;Romero-Gomez et al, 2008a). The studies showed that at T-junctions, that are at least a few pipe diameters apart, perfect mixing can be assumed, while in cross junctions less than 10% mixing may occur.…”

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confidence: 99%

Importance of demand modelling in network water quality models: a review

Blokker

Vreeburg

Buchberger

et al. 2008

Drink. Water Eng. Sci.

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Abstract. Today, there is a growing interest in network water quality modelling. The water quality issues of interest relate to both dissolved and particulate substances. For dissolved substances the main interest is in residual chlorine and (microbiological) contaminant propagation; for particulate substances it is in sediment leading to discolouration. There is a strong influence of flows and velocities on transport, mixing, production and decay of these substances in the network. This imposes a different approach to demand modelling which is reviewed in this article.For the large diameter lines that comprise the transport portion of a typical municipal pipe system, a skeletonised network model with a top-down approach of demand pattern allocation, a hydraulic time step of 1 h, and a pure advection-reaction water quality model will usually suffice. For the smaller diameter lines that comprise the distribution portion of a municipal pipe system, an all-pipes network model with a bottom-up approach of demand pattern allocation, a hydraulic time step of 1 min or less, and a water quality model that considers dispersion and transients may be needed.Demand models that provide stochastic residential demands per individual home and on a one-second time scale are available. A stochastic demands based network water quality model needs to be developed and validated with field measurements. Such a model will be probabilistic in nature and will offer a new perspective for assessing water quality in the drinking water distribution system.

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“…They employed the simulator approach by Rossman [47] as a tool that assumes an idea mixing at all nodes. However, the investigation by Austin et al [136] revealed that the proposition generated an invalid result. This led to the development of an adjoint theory by Wang et al [137], which incorporates incomplete mixing at the junction.…”

Section: Simulation-optimisation Approachmentioning

confidence: 99%

Towards Development of an Optimization Model to Identify Contamination Source in a Water Distribution Network

Adedoja

Hamam

Khalaf

et al. 2018

Water

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Protection of the water system is paramount due to the negative consequences of contaminated water on the public health. Water resources are one of the critical infrastructures that must be preserved from deliberate and accidental attacks. Water qualities are examined at the treatment plant. However, its quality can substantially be contaminated during transportation from the plant to the consumers' taps. Contamination in water distribution networks (WDNs) is a danger that can have severe consequences on public health as well as an economic and social instability. Water distribution networks are immensely susceptible to deliberate or accidental attacks due to the complex nature of the system. Hence, contamination source identification (CSI) is a topical issue in water distribution systems that require immediate attention of researchers in order to protect mankind from the adverse effect of consuming contaminated water. Usually, a contaminant event can be detected by the water quality monitoring sensors or the contaminant warning system (CWS) installed on the network. Nevertheless, how to derive the source of the contamination from the collected information is a difficult task that must be tackled in order to evaluate the spread of the contamination and for immediate remedial strategies. In the past two decades, considerable efforts and advancement have been made by researchers applying various techniques in order to locate the source of the contamination in WDNs. Each of the techniques has certain limitations and applicability as reported in the literature. This paper presents a comprehensive review of the existing techniques with emphasis on their importance and technical challenges. Despite a series of investigations in this domain, the field is yet to be unified. Hence, open research areas are still available to explore. Consequently, improvement on the existing techniques is necessary and hereby suggested. More importantly, practical application of these techniques offer a major research gap that must be addressed.

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Mixing at Cross Junctions in Water Distribution Systems. II: Experimental Study

Cited by 55 publications

References 4 publications

Evaluation of solute mixing in water distribution pipe junctions

Evaluation of solute mixing in water distribution pipe junctions

Importance of demand modelling in network water quality models: a review

Towards Development of an Optimization Model to Identify Contamination Source in a Water Distribution Network

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