Experimental Verification of Incomplete Solute Mixing in a Pressurized Pipe Network with Multiple Cross Junctions

Abstract

Water quality models based on accurate mixing data at cross junctions are important for estimating concentrations of chemical species in municipal water distribution systems. Recent studies indicate that the instantaneous complete ͑thus "perfect"͒ mixing assumption potentially can result in an erroneous prediction of water quality. The present study examines the updated "incomplete" solute mixing model at cross junctions in a network having multiple cross junctions. The model performance in predicting solute transport was evaluated through a series of tracer experiments in a pressurized 5 ϫ 5 network with 9 cross junctions. The perfect mixing model consistently overestimated solute dilution at cross junctions and predicted evenly distributed solute concentration throughout the network. In contrast, the incomplete mixing model demonstrated uneven distribution patterns with a distinct solute plume, and the corresponding results were significantly more accurate than those based on the perfect mixing assumption. Average prediction errors in tracer concentrations were 15 and 66% using the updated and perfect mixing models, respectively, and the difference was statistically significant ͑P-value Ͻ0.001͒. Therefore, this study concludes that the incomplete mixing model can drastically improve the prediction of solute transport in pressurized pipe systems that have multiple cross junctions.

Incomplete Mixing Model at Cross-Junctions in Epanet by Polynomial Equations

“…Researchers from the University of Arizona, in collaboration with the University of Korea, assembled a laboratory pipe model to demonstrate the differences between simulations with complete and incomplete mixing [20,21]. They built a 5 × 5 square network with nine CJs and 32 pipes of 0.016 m diameter.…”

Impact of an incomplete solute mixing model on sensor network design

“…These solvers have been developed on the basis of the convenient but potentially erroneous assumption that solute mixing is complete and instantaneous at the pipe junctions. Figure 1 The performance of AZRED on a laboratory-scale water network has been experimentally examined and validated (Song et al 2009) and applied to a large-scale network ). The present study uses AZRED as the WQ modeling tool for providing the input data needed to carry out sensor network designs over two exemplary water networks.…”

Validation of a Computational Fluid Dynamics Model for a Novel Residence Time Distribution Analysis in Mixing at Cross-Junctions

“…where: i, link with flow leaving node k; I k , set of links with flow into k; L j , length of link; Q j , flow (volume/time) in link j; Q k,ext , external source flow entering the network at node k; and, C k , ext , concentration of the external source flow entering at node k. Several authors [25][26][27][28][29][30][31][32][33][34][35][36] have numerically and experimentally demonstrated that the mixing in these unions is far from being "complete and instantaneous". Most of these researches were based on physical experiments and simulations through Computational Fluid Dynamics (CFD) using tracers for the concentration distribution analysis.…”

“…Most of these researches were based on physical experiments and simulations through Computational Fluid Dynamics (CFD) using tracers for the concentration distribution analysis. Some researchers [26][27][28][31][32][33][34][35][36] implement experimental scale models of a cross-junction and tee junctions with different pipe diameters, which are driven by elevated tanks where tracer is injected into one of them. Once the mix of the flows was made, mixing coefficients were formulated based on their experimental measurements.…”

“…The lack of precision in water quality simulations can lead to erroneous projects of monitoring systems of the location of re-chlorination systems necessary for the control of disinfection [28]. The accuracy in these models is also necessary to simulate the spatial-temporal dispersion of chemical and microbial agents during accidental or intentional contamination events.…”