Experimental study on air pressure variation in a horizontal pipe of single-stack drainage system.

The water trap seal under the sanitary appliances is the primary defense against the ingress of foul gases and odors. However, research on air pressure variation in a horizontal pipe of a single-stack drainage system is very limited. Thus a physical model study was conducted to investigate the air pressure variation in a horizontal pipe. Four parameters were studied that affect the pressure variation; that is, water flow rate, inlet height, ventilation condition and outlet condition. When the top of the vertical drainage stack and the outlet were fully open to the atmosphere, the flow in the horizontal pipe changed from free surface flow to slug flow at certain times. The mean values and magnitudes of pressure fluctuation at measuring points on the horizontal pipe increased with Qw but decreased along the horizontal pipe. The inlet height had relatively small influence on the pressure variation. Three ventilation conditions; that is, top fully open, half open and sealed, were tested, and a choking flow was formed in the vertical drainage stack and the pressure in the horizontal pipe decreased under the top sealed condition. Three outlet conditions; that is, outlet fully open, half submerged and fully submerged, were tested. The pressure in the horizontal pipe increased significantly under the outlet fully-submerged condition, which should be avoided in the actual operation by careful designing.

A Greedy Sampling Design Algorithm for the Modal Calibration of Nodal Demand in Water Distribution Systems.

This paper presents a greedy optimization algorithm for sampling design to calibrate WDS hydraulic model. The proposed approach starts from the existing sensors and sequentially adds one new sensor at each optimization simulation step. In each step, the algorithm tries to minimize the calibration prediction uncertainty. The new sensor is installed in the location where the uncertainty is greatest but also sensitive to other nodes. The robustness of the proposed approach is tested under different spatial and temporal demand distribution. We found that both the number of sensors and the perturbation ratio affect the calibration accuracy as defined by the average nodal pressure deviation itself and its variability. The plot of the calibration accuracy versus the number of sensors can reasonably guide the trade-off between model calibration accuracy and number of sensors placed or the cost. This proposed approach is superior in calibration accuracy and modeling efficiency when compared to the standard genetic algorithm (SGA) and Monte Carlo Sampling algorithm (MCS).

The adsorption of Sb(III) in aqueous solution by Fe2O3-modified carbon nanotubes.

A novel kind of iron oxide supported on carbon nanotubes (CNTs) was prepared for adsorption of antimony (Sb)(III) in aqueous solution. The iron (III) oxide (Fe2O3)-modified CNTs were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, nitrogen adsorption-desorption and Fourier transform infrared spectrometer. Parameters affecting the adsorption efficiencies, including solution pH value, initial Sb(III) concentration, adsorbent dosage, adsorption time and temperature, were investigated. The results indicate that the removal rate of Sb(III) by Fe2O3-modified CNTs is 99.97% under the initial Sb(III) concentration of 1.5 mg/L, adsorbents dosage of 0.5 g/L, temperature of 25 (o)C and pH value of 7.00, which is 29.81% higher than that of the raw CNTs. The adsorption capacity increased correspondingly from 3.01 to 6.23 mg/g. The equilibrium adsorption data can be fitted to the Freundlich adsorption isotherm. In addition, it has been found that the solution pH values and adsorption temperatures have no significant influence on Sb(III) removal.

A noise adaptive approach for nodal water demand estimation in water distribution systems.

Hydraulic models have emerged as a powerful tool for simulating the real behavior of water distribution systems (WDSs). In using the models for estimating nodal water demands, measurement uncertainty must be considered. A common approach is to use the covariance of measurement noises to quantify the measurement uncertainty. The noise covariance is typically assumed constant and estimated a priori. However, such an assumption is frequently misleading as actual measurement accuracies are affected by measuring instruments and environmental noises. In this study, we develop a variational Bayesian approach for real-time estimation of noise covariance and nodal water demands. The approach can adaptively adjust the noise covariance with the variation of the noise intensity, thereby efficiently avoiding model overfitting. The measurement residual decomposition reveals that this new approach is effective in determining model structural errors caused by topological structure parameterization.

Numerical approach for water distribution system model calibration through incorporation of multiple stochastic prior distributions.

The use of water distribution system (WDS) hydraulic models facilitates the design and operation of such systems. For offline or online model applications, nodal water demands-variables with the highest levels of uncertainty-should be carefully calibrated because these can considerably affect the accuracy of model outputs in terms of hydraulics and water quality. With the increasing utilization of automatic water metering technology, nodal water demands can be modeled with high time resolution in certain forms of probability distributions. However, the fusion of various demand probability distributions with conventional measurements to improve the accuracy of WDS hydraulic models is a difficult problem. To resolve this, a numerical approach that incorporates various probability distributions and field measurements to calibrate nodal water demands based on Bayesian theory is proposed. In particular, the linearization of the exponential family prior distribution is well elaborated in this paper. The application of this proposed approach in two cases demonstrates that the technique is more accurate than methods that merely utilize measurements or prior information. Because this technique can avoid the overfitting of measurement noise and allow the retention of calibrated nodal water demands with stochastic nature, it is robust when errors or uncertainties exist in prior demand distribution or measurements. This method is expected to improve the WDS model accuracy relative to the increasing use of automatic water metering technology.

Real-Time Water Distribution System Hydraulic Modeling Using Prior Demand Information by Formal Bayesian Approach.

Real-time water distribution system (WDS) hydraulic models are used in water utilities to facilitate the planning and operation of the water distribution system. As a critical model input, spatiotemporally varying nodal water demands significantly affect the performance and applicability of such WDS models. Thus, real-time nodal demands must be calibrated for reliability before their use. The main difficulty for real-time calibration is the lack of observed data sufficient to determine thousands of nodal demands accurately in a network. To address the difficulty, this study proposes a formal Bayesian approach to determine nodal demands in WDS hydraulic modeling by explicitly taking prior water demand information into account and coupling more information to constrain the nodal water demand modeling. Application of the approach on a simple hypothetical network and a field network in a city of eastern Zhejiang Province, China demonstrates that by adding prior information, the nodal demand can be uniquely determined in real time. The approach limits uncertainty propagation and improves the robustness of the real-time model calibration and analysis.

Total and settling velocity-fractionated pollution potential of sewer sediments in Jiaxing, China.

Sewer sediments and their associated contaminant released along with wet-weather discharges pose potential pollution risks to environment. This paper presents total characteristics of sediments collected from Jiaxing, China. Size distribution and concentrations of volatile solids (VS) and four metals (Pb, Cu, Zn, Cr) of sediment samples from seven land use categories were analyzed. Then, the sediment samples were graded five fractions according to its settling velocity through the custom-built settling velocity-grading device. Sediment mass and pollution load distribution based on settling velocity were also assessed. The results show that there are relatively high level of heavy metal load in the sediment of separated storm drainage systems in Jiaxing, especially for the catchment of residential area (RA), road of developed area (RDA), and industrial area (IA). Although grain size follows a trend of increasing along with settling velocity, the methods of settling velocity grading are meaningful for stormwater treatment facilities with precipitation. For all land use categories, the pollution concentrations of the three lower settling velocity-fractionated sediment are relatively consistent and higher than others. Combined with mass distribution, the pollution percentage of fraction with different velocities for seven land use categories were also evaluated. Based on it, the statistical conclusion of design target settling velocity to different pollution load removal rates are drawn, which is helpful to guide design of on-site precipitation separation facilities.

Mixing at double-Tee junctions with unequal pipe sizes in water distribution systems.

Pipe flow mixing with various solute concentrations and flow rates at pipe junctions is investigated. The degree of mixing affects contaminant spread in a water distribution system, and many studies have focused on mixing at the cross junctions; however, only a few have focused on double-Tee junctions of unequal pipe diameters. To investigate the solute mixing at such junctions, a series of experiments was conducted in a turbulent regime (Re = 12,500-50,000) with different Reynolds number ratios and connecting pipe lengths. Dimensionless outlet concentrations were found to depend on mixing mechanism at the impinging interface of junctions, where junctions with a larger pipe diameter ratio were associated with more complete mixing. Further, the inlet Reynolds number ratio affected mixing more strongly than the outlet Reynolds number ratio. Finally, the dimensionless connecting pipe length in a double-Tee played an important and complicated role in the flow mixing. The results were used to develop two-dimensional isopleth maps for the calculation of normalized north outlet concentrations.

Experimental testing and modeling analysis of solute mixing at water distribution pipe junctions.

Flow dynamics at a pipe junction controls particle trajectories, solute mixing and concentrations in downstream pipes. The effect can lead to different outcomes of water quality modeling and, hence, drinking water management in a distribution network. Here we have investigated solute mixing behavior in pipe junctions of five hydraulic types, for which flow distribution factors and analytical equations for network modeling are proposed. First, based on experiments, the degree of mixing at a cross is found to be a function of flow momentum ratio that defines a junction flow distribution pattern and the degree of departure from complete mixing. Corresponding analytical solutions are also validated using computational-fluid-dynamics (CFD) simulations. Second, the analytical mixing model is further extended to double-Tee junctions. Correspondingly the flow distribution factor is modified to account for hydraulic departure from a cross configuration. For a double-Tee(A) junction, CFD simulations show that the solute mixing depends on flow momentum ratio and connection pipe length, whereas the mixing at double-Tee(B) is well represented by two independent single-Tee junctions with a potential water stagnation zone in between. Notably, double-Tee junctions differ significantly from a cross in solute mixing and transport. However, it is noted that these pipe connections are widely, but incorrectly, simplified as cross junctions of assumed complete solute mixing in network skeletonization and water quality modeling. For the studied pipe junction types, analytical solutions are proposed to characterize the incomplete mixing and hence may allow better water quality simulation in a distribution network.