scholarly journals Impact of Sediment Layer on Longitudinal Dispersion in Sewer Systems

Water ◽  
2021 ◽  
Vol 13 (22) ◽  
pp. 3168
Author(s):  
Marek Sokáč ◽  
Yvetta Velísková
Keyword(s):  
Reynolds Number ◽  
Layer Thickness ◽  
Dispersion Coefficient ◽  
Longitudinal Dispersion ◽  
Low Flow ◽  
Pipe Diameter ◽  
Sediment Layer ◽  
Pollution Transport ◽  
Sewer Pipes ◽  
Hydraulic Conditions

Experiments focused on pollution transport and dispersion phenomena in conditions of low flow (low water depth and velocities) in sewers with bed sediment and deposits are presented. Such conditions occur very often in sewer pipes during dry weather flows. Experiments were performed in laboratory conditions. To simulate real hydraulic conditions in sewer pipes, sand of fraction 0.6–1.2 mm was placed on the bottom of the pipe. In total, we performed 23 experiments with 4 different thicknesses of sand sediment layers. The first scenario is without sediment, the second is with sediment filling 3.4% of the pipe diameter (sediment layer thickness = 8.5 mm), the third scenario represents sediment filling 10% of the pipe diameter (sediment layer thickness = 25 mm) and sediment fills 14% of the pipe diameter (sediment layer thickness = 35 mm) in the last scenario. For each thickness of the sediment layer, a set of tracer experiments with different flow rates was performed. The discharge ranges were from (0.14–2.5)·10−3 m3·s−1, corresponding to the range of Reynolds number 500–18,000. Results show that in the hydraulic conditions of a circular sewer pipe with the occurrence of sediment and deposits, the value of the longitudinal dispersion coefficient Dx decreases almost linearly with decrease of the flow rate (also with Reynolds number) to a certain limit (inflexion point), which is individual for each particular sediment thickness. Below this limit the value of the dispersion coefficient starts to rise again, together with increasing asymmetricity of the concentration distribution in time, caused by transient (dead) storage zones.

Annulus Wall Boundary-Layer Measurements in a Four-Stage Compressor

1986 ◽  
Vol 108 (1) ◽  
pp. 2-6 ◽  
Author(s):  
N. A. Cumpsty
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Layer Thickness ◽  
Boundary Layers ◽  
Boundary Layer Thickness ◽  
Tip Clearance ◽  
The Other ◽  
Wall Boundary Layer ◽  
Multistage Compressors ◽  
Full Design

There are few available measurements of the boundary layers in multistage compressors when the repeating-stage condition is reached. These tests were performed in a small four-stage compressor; the flow was essentially incompressible and the Reynolds number based on blade chord was about 5 • 104. Two series of tests were performed; in one series the full design number of blades were installed, in the other series half the blades were removed to reduce the solidity and double the staggered spacing. Initially it was wished to examine the hypothesis proposed by Smith [1] that staggered spacing is a particularly important scaling parameter for boundary layer thickness; the results of these tests and those of Hunter and Cumpsty [2] tend to suggest that it is tip clearance which is most potent in determining boundary-layer integral thicknesses. The integral thicknesses agree quite well with those published by Smith.

scholarly journals Effect of soil textural characteristics on longitudinal dispersion in saturated porous media

2021 ◽  
Vol 69 (2) ◽  
pp. 161-170
Author(s):  
Mojtaba G. Mahmoodlu ◽  
Amir Raoof ◽  
Martinus Th. van Genuchten
Keyword(s):  
Particle Size ◽  
Dispersion Coefficient ◽  
Average Particle Size ◽  
Longitudinal Dispersion ◽  
Average Particle ◽  
Sand Sample ◽  
Average Pore ◽  
Advection Dispersion ◽  
Strong Positive Relationship

Abstract This study focuses on the effects of soil textural heterogeneity on longitudinal dispersion under saturation conditions. A series of solute transport experiments were carried out using saturated soil columns packed with two filter sands and two mixtures of these sands, having d50 values of 95, 324, 402, and 480 µm, subjected to four different steady flow rates. Values of the dispersion coefficient (D) were estimated from observed in-situ distributions of calcium chlo-ride, injected as a short nonreactive tracer pulse, at four different locations (11, 18, 25, 36 cm). Analyses of the observed distributions in terms of the standard advection-dispersion equation (ADE) showed that D increased nonlinearly with travel distance and higher Peclet numbers+. The dispersion coefficient of sand sample S1 with its largest average particle size (d 50) was more affected by the average pore-water velocity than sample S4 having the smallest d 50. Results revealed that for a constant velocity, D values of sample S1 were much higher than those of sample S4, which had the smallest d 50. A correlation matrix of parameters controlling the dispersion coefficient showed a relatively strong positive relationship between D and the Peclet number. In contrast, almost no correlation was evident between D and porosity as well as grain size. The results obtained with the four sandy matrices were consistent and proved that the dispersion coefficient depends mainly on the particle size.

scholarly journals Investigation of a parameter estimation method for contaminant transport in aquifers

2001 ◽  
Vol 3 (4) ◽  
pp. 203-213 ◽  
Author(s):  
Channa Rajanayaka ◽  
Don Kulasiri
Keyword(s):  
Experimental Data ◽  
Hydraulic Conductivity ◽  
Contaminant Transport ◽  
Dispersion Coefficient ◽  
Estimation Method ◽  
Longitudinal Dispersion ◽  
Longitudinal Dispersion Coefficient ◽  
System Noise ◽  
Estimated Parameters ◽  
Comparison Of The Results

Real world groundwater aquifers are heterogeneous and system variables are not uniformly distributed across the aquifer. Therefore, in the modelling of the contaminant transport, we need to consider the uncertainty associated with the system. Unny presented a method to describe the system by stochastic differential equations and then to estimate the parameters by using the maximum likelihood approach. In this paper, this method was explored by using artificial and experimental data. First a set of data was used to explore the effect of system noise on estimated parameters. The experimental data was used to compare the estimated parameters with the calibrated results. Estimates obtained from artificial data show reasonable accuracy when the system noise is present. The accuracy of the estimates has an inverse relationship to the noise. Hydraulic conductivity estimates in a one-parameter situation give more accurate results than in a two-parameter situation. The effect of the noise on estimates of the longitudinal dispersion coefficient is less compared to the effect on hydraulic conductivity estimates. Comparison of the results of the experimental dataset shows that estimates of the longitudinal dispersion coefficient are similar to the aquifer calibrated results. However, hydraulic conductivity does not provide a similar level of accuracy. The main advantage of the estimation method presented here is its direct dependence on field observations in the presence of reasonably large noise levels.

Reynolds Number and Roughness Effects on Turbocompressor Performance: Numerical Calculations and Measurement Data Evaluation

2020 ◽  
Author(s):  
Fabian Dietmann ◽  
Michael Casey ◽  
Damian M. Vogt
Keyword(s):  
Reynolds Number ◽  
Measurement Data ◽  
Theoretical Models ◽  
Design Flow ◽  
Flow Coefficient ◽  
Low Flow ◽  
Roughness Effects ◽  
Flow Channels ◽  
Compressor Performance ◽  
Low Flow Coefficient

Abstract Further validation of an analytic method to calculate the influence of changes in Reynolds number, machine size and roughness on the performance of axial and radial turbocompressors is presented. The correlation uses a dissipation coefficient as a basis for scaling the losses with changes in relative roughness and Reynolds number. The original correlation from Dietmann and Casey [6] is based on experimental data and theoretical models. Evaluations of five numerically calculated compressor stages at different flow coefficients are presented to support the trends of the correlation. It is shown that the sensitivity of the compressor performance to Reynolds and roughness effects is highest for low flow coefficient radial stages and steadily decreases as the design flow coefficient of the stage and the hydraulic diameter of the flow channels increases.

Chemotaxis under flow disorder shapes microbial dispersion in porous media 

2021 ◽  
Author(s):  
Pietro de Anna ◽  
Amir A. Pahlavan ◽  
Yutaka Yawata ◽  
Roman Stocker ◽  
Ruben Juanes
Keyword(s):  
Porous Media ◽  
Dispersion Coefficient ◽  
Pore Space ◽  
Low Flow ◽  
Pore Scale ◽  
Porous Rocks ◽  
Chemical Gradients ◽  
Deep Earth ◽  
Bacterium Bacillus Subtilis ◽  
Bacterium Bacillus

<div> <div> <div> <p>Natural soils are host to a high density and diversity of microorganisms, and even deep-earth porous rocks provide a habitat for active microbial communities. In these environ- ments, microbial transport by disordered flows is relevant for a broad range of natural and engineered processes, from biochemical cycling to remineralization and bioremediation. Yet, how bacteria are transported and distributed in the sub- surface as a result of the disordered flow and the associ- ated chemical gradients characteristic of porous media has remained poorly understood, in part because studies have so far focused on steady, macroscale chemical gradients. Here, we use a microfluidic model system that captures flow disorder and chemical gradients at the pore scale to quantify the transport and dispersion of the soil-dwelling bacterium Bacillus subtilis in porous media. We observe that chemotaxis strongly modulates the persistence of bacteria in low-flow regions of the pore space, resulting in a 100% increase in their dispersion coefficient. This effect stems directly from the strong pore-scale gradients created by flow disorder and demonstrates that the microscale interplay between bacterial behaviour and pore-scale disorder can impact the macroscale dynamics of biota in the subsurface.</p> </div> </div> </div>

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