Sediments in Storage Chambers

Dr Virginia Stovin

Department of Civil and Structural Engineering
The University of Sheffield

General Introduction

This website has primarily been established in order to report on the findings of a recently-completed research project, funded by EPSRC and entitled "The development of a simulation strategy for the prediction of sediment deposition in storage chambers" (EPSRC GR/L79205). The site also briefly outlines preceeding work, and will continue to be updated as the research develops in the future.


For further information please contact v.stovin@sheffield.ac.uk.


Structure of the website


Introduction

Storage chambers play an important role in urban pollution management. They are frequently used in conjunction with combined sewer overflow (CSO) structures, where they reduce the number and magnitude of CSO spill events. Detention tanks are also required to partition fine particles and gross solids between the continuation flow and the overflow discharge in order to minimise the discharge of pollutants. Flow velocities in storage chambers tend to be low, and partitioning is achieved through the settlement of sediments. However, one problem associated with the use of storage tanks is that sediment is then deposited on the bed of the chamber. Techniques that enable engineers to design new chambers for minimal deposition are required. A complementary objective is that urban drainage engineers should be able to predict where – and to what extent – deposition will occur within the large number of storage chambers that are already in use, in order to implement cost-effective maintenance programmes. Currently the design of storage chambers is based on the rather broad-based recommendations presented by WRc (Cant, 1991). These guidelines do not attempt to quantify the relative importance of different design aspects, or to give any indication of the actual performance characteristics of a particular design. This research project addresses both of these issues, through the development of simulation approaches for the quantification of storage chamber sediment deposition.


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Empirical Research

Two storage chamber test facilities have been constructed, one at the National CSO Test Facility (NCSOTF), Wigan and the second, a permanent facility, in the Water Engineering Laboratory at the University of Sheffield. The work at the NCSOTF was undertaken in collaboration with WRc. The newly-constructed laboratory facility has been designed in a flexible way to facilitate future work. The two facilities have both provided useful data on the sediment retention efficiency and the distribution of deposited sediments for a range of chamber configurations. In the case of the NCSOTF, chambers representative of typical full-scale installations were examined, whilst the preliminary laboratory tests have focused on simplified configurations, providing validation data for the computational approaches.

Field testing at the National CSO Test Facility, Wigan

The FWR National CSO Test Facility provides an opportunity for the full-scale evaluation of CSO chambers, screen devices and storage facilities. Raw sewage is diverted from the inlet works at Hoscar STW to a reinforced concrete test bed measuring approximately 16 m x 15 m, on which sewer ancillary structures may be constructed and tested. The computer-controlled inflow valve system is capable of delivering a flow of up to 500 l/s.

Tests at Wigan were completed in collaboration with WRc plc (Stovin et al., 1999). This work examined the effect of storage chamber configuration on gross solids' retention efficiency, and enabled observations of flow patterns and sediment deposition to be made. Looking downstream, the model storage chambers were constructed on the left-hand section of the test slab (Plate 1 and Plate 2).

Six chamber configurations were tested. All six chambers were 2.44 m wide, and either 15.86 m or 8.54 m in length. For each of the two chamber lengths, two different weir positions (upstream and downstream) were tested. Further tests were carried out in a chamber incorporating an inflow deflector. All were configured according to current design ‘good practice’ (Cant, 1991), with the following features: Inflow 475 mm in diameter; single DWF channel, 225 mm in diameter; continuation flow channel 225 mm diameter; benching at a transverse gradient of 1 in 12; longitudinal gradient of 1 in 200; overflow weir in the right-hand wall with the weir crest positioned at 0.8 D, and including a baffle/scumboard. Plate 1 and Plate 2 show the 15.86 m long chamber with the weir in the upstream position. The spilled flow was conveyed in the spill channel that ran parallel to the right-hand chamber wall.

Tests used a trapezoidal inflow hydrograph with a two hour spill duration. Inflow rates of 45, 67.5 and 90 l/s, with continuation flows of 0.1, 0.2 and 0.3 x Qmax were applied. Flow samples were collected at the inflow, continuation flow and the spill flow, and these were analysed for BOD and suspended solids. The separation of suspended solids and BOD between the continuation flow and the spill flow was very variable, with the efficiency generally being close to the flow split. This suggests that the settlement of fine sediments and the associated BOD during the spill phase of the tests was not significant.

Sketches of the surface flow pattern were prepared during each test (Figure 1), and photographs of sediments deposited on the chamber bed were taken once the chamber drained (for example, Plate 5). In these preliminary tests, no attempts to measure the velocity distribution within the chamber were made. All chambers experienced some sediment deposition, although it was not extensive. The pattern of deposition was related to the flow pattern observed at the flow surface. It was not possible to identify a configuration that significantly affected sediment deposition, and this probably reflected the fact that the benching design was constant for all chambers, and that all chambers also conformed to current ‘good practice’. This observation confirms the findings of a review of a major UK water utility undertaken by WRc, in which sedimentation was not identified as being a major problem in chambers designed to the current guidelines (Drinkwater, 2000).

The results of these preliminary collaborative tests provided useful validation data (flow patterns and sediment deposition patterns under steady flow conditions) for the development of the simulation strategy. However, the experience gained at the Wigan site was influential in modifying the plans for setting up a new long-term storage chamber test facility.

It became apparent during the tests that there were significant fluctuations in the composition of the sewage entering the facility, both on an hourly and a diurnal basis. Plate 3 and Plate 4 show how such variations affected the observed sediment deposition for a test that was repeated on two different days. The differences in the composition of the sewage are striking. Such fluctuations significantly impaired the comparative testing of chamber performance, apparently masking any differences in efficiency that arose in response to the configuration parameters that were varied. The intention to construct a permanent storage chamber test facility at the NCSOTF was consequently revised, and a laboratory facility was developed instead. Laboratory conditions are far more controllable than the field situation, with the advantage that a range of sediment types may be examined in isolation, and the behaviour of sediments close to the chamber bed may be observed during a test.

Laboratory-based experimental work

A storage chamber test bed has been constructed in the Water Engineering Laboratory at The University of Sheffield. The test bed (2.44 x 4.88 m) is formed from steel I-beams, raised 0.5 m above ground level (Plate 6). The flow in the laboratory is circulated via a sump, pumps and a header tank. Inflow to the test bed is computer controlled, up to a maximum of approximately 100 l/s. The length of the inflow pipe, and its lateral position, are both flexible, enabling a chamber of any size and position to be accommodated on the test bed. At the downstream end is a continuation flow collection channel, from which flow is directed into a volumetric flow measuring tank. The test bed has been positioned such that spill discharges may be directed to the right hand side of the chamber into a separate return channel with an independent flow measurement tank. The chambers themselves are constructed from GRP Hydroglass panels that may be bolted together into any configuration. Additional fabrication, using aluminium sheet or plywood, for benching or weir baffles is straightforward. Using this approach a highly flexible test ‘kit’ has been assembled. The ‘kit’ has been applied within the context of the current project to collect data on three simple chambers. However it should be stressed that a permanent facility has now been established, which will be available for subsequent research requiring model testing of storage chambers, CSOs or other sewer ancillary devices.

Following discussions with colleagues at K. U. Leuven, Bakelite was selected as the model sediment (Luyckx et al., 1999). The size fraction 0.6 to 1.18 mm was selected for the preliminary experimental work. Bakelite has several advantages over other potential materials, the most significant of which being that it is inert. Also of relevance is the fact that particles are irregularly shaped (and therefore do not roll artificially along the bed). The selected size fraction was sufficiently large to be collected from the continuation flow using a wire mesh collection basket, and then dried and weighed to obtain the mass passed through the chamber. Deposited sediments were also washed from the chamber bed into a sieve for drying and weighing.

Three chamber configurations were examined, each having a plan area of 3 m2. The chambers had length to breadth ratios of 2:1, 1:2 and 8:1. A penstock on the outflow was used to regulate the flow depth to 0.25 m. Each chamber had an inlet diameter of 0.19 m and an outlet diameter of 0.15 m. None of the chambers had a spill weir. In each case the invert was level with the chamber base, which was laid level.

Sediment deposition efficiency was defined as the ratio of mass deposited on the bed to mass input. The efficiency of each chamber was established under steady flow conditions for a range of discharge values (between 5 and 20 l/s). In each test 100 g of Bakelite particles was input into the inflow pipe a minimum of 5 m upstream from the chamber inlet. Sediment was input in small batches to give a constant load over a 10 minute period. Steady flow continued for a further 10 minutes without sediment input, with the sieve then being removed from the continuation flow and sediments retrieved. The sieve was then positioned in the continuation flow once again and sediments that had deposited on the chamber bed were flushed through to be collected, dried and weighed. Deposition efficiencies are compared in Figure 3. The 1:2 chamber represents a rather unusual configuration, but a very low efficiency (i.e. significantly lower deposition than in either of the more conventional chambers) was observed.

The flow patterns for the three chambers are of interest, with the basic flow pattern in each being similar at all flowrates (see Figure 2). In the 2:1 chamber the flow was asymmetric, with a single clockwise circulation occupying the main body of the flow, and a lesser anti-clockwise circulation in the upstream left corner of the chamber. In the 1:2 chamber twin recirculations developed. The majority of the flow appeared to move directly across the chamber from the inlet to the outlet. The 8:1 chamber was characterised by a recirculatory section at the upstream end and reasonably uniform flow across the entire chamber width in the downstream portion of the chamber.

The flow pattern in each chamber accounts for the observed sediment deposition efficiencies. In the 8:1 chamber the efficiency was observed to fall suddenly at inlet velocities in excess of 0.6 m/s, above which the mean cross-sectional velocity was sufficient to sustain most of the sediment in suspension throughout the chamber length. At lower velocities the efficiency of the 2:1 chamber was found to be marginally lower than the 8:1 chamber, as the asymmetric circulation provided a jet of comparatively high-velocity flow that moved sediments directly from the inlet to the outlet. At the higher velocities the correspondingly higher turbulence in this chamber ensured that a significant portion of the sediment transferred into the stagnant zones in the flow, and deposition in excess of the long chamber occurred. It is believed that the central jet of flow in the 1:2 chamber was responsible for the fact that only a small proportion of the incoming sediment was transported into the quiescent side portions of the chamber, where flow velocities were sufficiently low to allow deposition. It is thought that, as the mean inlet velocity increased, the effects of increasing turbulent transfer into the side sections and increasingly rapid transport across the central body of the chamber were working in opposition. The peak in efficiency that occurred at the mean inlet velocity of 0.5 m/s therefore represents the point at which the short-circuiting of the inlet jet started to outweigh the turbulent transfer into the side sections. These three data sets highlight the fact that the comparative assessment of chamber geometries is highly dependent upon the velocity.

In addition to the efficiency data, observations of sediment deposition location were also made (Plates 8, 9 and 10). In all three cases it appeared that the deposits occurred beneath regions of the flow field that had been observed to have low velocities. The observed correlation between flow patterns, efficiency and sediment deposition patterns clearly reinforces the assumption underlying this research, that the key to predicting sediment behaviour lies in the prediction of flow behaviour.


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CFD-based approaches to the simulation of sediment deposition

Introduction

Previous research undertaken by the investigators (Stovin and Saul, 1996; 1998; 2000) demonstrated the potential that existed to apply Lagrangian particle tracking to the prediction of sediment transport in storage chambers. Realistic sediment tracks have been observed, and effective simulations of the division of particles between the continuation flow and the spill flow of a CSO structure have also been reported. However, problems were encountered with the definition of deposition criteria. The approach adopted by Stovin and Saul was based on the assumption that a particle ‘bouncing’ on any specific bed cell for a sufficiently large number of time steps could be assumed to have deposited. This approach was not entirely satisfactory, being disconnected from deterministic physical processes and being found to be sensitive to simulation parameters. They argued that a better approach would involve the application of a critical bed shear stress criterion in determining whether or not a particle deposits. The following section outlines how this approach has been implemented, and demonstrates that good comparisons between simulation results and laboratory observations have been obtained.

An alternative approach to particle tracking is multiphase modelling, in which the proportions of sediment and liquid in each computational cell are calculated. One objective of the current research was to investigate the applicability of the range of multiphase modelling tools available as part of the Fluent simulation software to the storage chamber deposition problem. Originally it was proposed that the granular multiphase model be applied. However, initial work on the feasibility of applying this approach was inconclusive, as numerous problems with solution stability arose. Discussions with collaborators at Fluent resulted in the decision to work instead with a newly-implemented modelling approach, the Algebraic Slip Model (ASM). Work with this model is described here.

Modified Particle Tracking

The particle tracking approach described by Stovin and Saul (1996, 1998) has been modified through the implementation of a critical bed shear stress criterion for sediment deposition. This represents a substantial theoretical advance over previous approaches, as it is based upon the well-reported observation (Stovin and Saul, 1994) that deposition is a function of the bed shear stress distribution.

The bed shear stress-based boundary condition is not a standard component of the commercial CFD code. It was written specifically for this research project by the principal investigator as a 'User Defined Subroutine', which was 'merged' with the FLUENT code. The approach has the advantage of facilitating very rapid and computationally robust comparisons between chamber configurations.

The files required to operate the user defined subroutines may be downloaded here.

Each of the laboratory chambers has been simulated at 0.2 m/s, 0.5 m/s and 0.8 m/s. All simulations were undertaken using Fluent 4 (structured mesh), with the k/e turbulence model. Each model geometry incorporated a 1 m section of inlet pipe and a 1 m section of outlet pipe. All solutions were perturbed (asymmetric ‘nudge’) prior to full convergence being obtained, in order to ensure stability in the flow field. Initial work with the modified particle tracking approach employed sediment with a density of 1500 kg/m3 and a diameter of 1 x 10-4 m. A critical bed shear stress of 0.04 Pa was adopted. These values correspond to sediments used in previous laboratory work (Stovin, 1996). Regardless of the differences between the sediment characteristics applied in the simulation and those employed in the current series of laboratory tests, the simulated efficiencies (Figure 4) compare favourably with the trends in the observed efficiency data (Figure 3). In common with the observed comparisons, the simulation results identify 1:2 as the least efficient chamber and indicate that this chamber exhibits a peak efficiency in the middle of the velocity range. Simulations applying the characteristics of the Bakelite sediment have also been completed, and, for example, the results of simulations for the 8:1 chamber are presented in Figure 4. In this case there is an almost perfect match to the observed data.

In general it was observed that the flow field at all levels of inlet velocity was similar, and that the bed shear stresses fell as the mean inlet velocity decreased. For each chamber three figures have been produced to illustrate the flow field, the computed bed shear stress distribution and the distribution of deposited particles respectively (Figure 5). Comparison with the laboratory flow fields (Figure 2) and the observed sediment deposition patterns (Plates 8, 9 and 10) suggests that these are both replicated effectively in the simulations.

Extensive parametric assessment of this modelling approach has been completed in collaboration with Åsa Adamsson, visiting Research Scholar at Sheffield from Chalmers University in Sweden. This work has highlighted the importance of the selection of appropriate sediment physical characteristics, and a journal paper is currently in preparation (Adamsson et al., in press).

Application of the modified particle tracking technique to the chambers tested at Wigan (Stovin et al., 1999) revealed difficulties in matching the simulated flow patterns to the observed surface flow patterns for the three long chambers (Figure 1). In each case the flow was characterised by multiple low velocity recirculations. However, improved simulations were obtained following further investigations into the relevance of mesh configuration, choice of turbulence model and wall functions. The inlet boundary conditions were also refined from a uniform velocity to a velocity distribution obtained through simulation of the entire inlet pipe. Simulated surface flow patterns for the long chamber with an upstream weir at a discharge of 90 l/s are presented in Figure 6. In this case the main features of the observed flow pattern are well represented. The bed shear stress distribution is presented in Figure 7, while the observed pattern of sediment deposition for the corresponding test is shown in Plate 5. The observed deposition appears to correlate with the zones of low bed shear stress, except in the right-hand section of the chamber downstream from the weir. Here the bed shear stress was computed to be reasonably high, yet deposition may clearly be seen. Unfortunately the simulated flow field could only be partially validated (against observed flow patterns at the surface), and the particle tracking methodology was not, therefore, applied to the Wigan chambers.

Overall, it may be concluded that the particle tracking approach provides good efficiency predictions and deposition patterns for simple laboratory model cases. The approach is fast, stable and robust. It follows that the approach may be applied to compare the performance of alternative chamber designs.

Multiphase Modelling

The ASM is only implemented in Fluent 5, which, unlike Fluent 4, employs an unstructured solution technique. New model meshes were generated to take advantage of this feature. It should be appreciated that the application of any multiphase model requires a time-dependent solution, and that the computational effort required is significantly greater when compared with the particle tracking approach.

Figure 8, Figure 9 and Figure 10 present results from the application of the ASM multiphase model to a chamber with a length to breadth ratio of 2:1. The inlet velocity was 0.2 m/s (Q = 5.6 l/s), and the sediment particles had a diameter of 0.1 mm and a density of 1500 kg/m3. These values were selected as being representative of data collected during a previous series of laboratory studies (Stovin, 1996). Sediment was injected at a volume fraction of 1 x 10-3, equivalent to 8.4 g/s.

Figure 8 shows contours of sediment volume fraction 4 minutes and 20 minutes after the start of sediment injection. It may be seen that the highest volume fractions occur closest to the bed, and that the sediment preferentially settled in specific zones. These zones may be seen more clearly in Figure 9, in which contours of sediment volume fraction at 5 mm above the bed are plotted. The predicted locations of sediment deposition closely match both the previous laboratory findings (Plate 7) and the laboratory data collected during the present research programme (Plate 8). The plots presented in Figure 9 are extracted from a time-dependent animation.

Although these results suggest that the ASM model is potentially suited to modelling sediment deposition in storage chambers, the research has also revealed that the stability of the model is affected by the quality of the mesh, the time step used and the characteristics of the sediment phase. Sensitivity analysis of these parameters, and their influence on predicted deposition patterns and rates, is consequently underway. It was therefore not felt to be appropriate at this stage to apply this methodology to the comparative assessment of alternative chamber geometries.

Sediment build-up rates may be estimated by comparing the sediment fluxes through the inlet and outlet over time (see Figure 10). In this example, from a total input load of 10.1 kg sediment, 0.67 kg deposited. This represents an efficiency of only 7%. The data in Figure 10 are consistent with the results obtained for other chamber configurations, flow rates and sediment sizes, in that after a period of time the sediment exits the chamber at the same rate it enters. An equilibrium, in which the rate of deposition is zero, is reached. The existence of a depositional equilibrium is not wholly unanticipated, given that the inverts of both the inlet and outlet pipes of the modelled chambers are flush with the chamber bed, and that any reduction in flow depth as a result of sedimentation will result in increased shear stresses acting on the chamber bed. There is also some field evidence that deposition reaches an equilibrium. The investigators have observed that the extent of sediment deposition in storage chambers does not vary substantially between return visits, irrespective of intervening flow conditions, and work currently being conducted in collaboration with Yorkshire Water will enable the deposition on the bed of an operational tank to be monitored at regular intervals. The investigators also propose to seek funding to investigate the depositional equilibrium further, through a combination of field observations and the use of the newly-developed laboratory storage chamber test bed. Long duration, high loading tests would require only minor modifications to be made to the sediment input and retrieval systems currently in place.

Overall it may be concluded that the ASM appears to have the potential to be applied in this type of situation. However, the need to use time-dependent simulations and the stability problems encountered mean that it proved not to be an approach that could, at this stage, be used to undertake comparative tests.


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Simulation Strategy

The modified particle tracking approach to the quantification of storage chamber efficiency was found to provide a stable and rapid tool for the comparative assessment of chamber performance. This forms the basis of the simulation strategy, which is divided into three steps as described below.

Hydraulic Model

The first step is to obtain a simulation of the flow field for each chamber under consideration at the appropriate design flowrate (a range of flows may be selected to give a comparison of chambers over the full range of discharge conditions likely to be experienced). The hydraulic model must be three dimensional. Confidence in the flow field should be obtained through appropriate attention to mesh generation issues, particularly to the density of the mesh close to the boundaries. Under most circumstances it is appropriate to use turbulence modelling, and to apply appropriate wall roughness values. The RNG k/e turbulence model in Fluent 4 is recommended. The position of the free surface may be obtained experimentally, from HydroWorks or by storage routing with standard weir and orifice flow equations. (Note that it may also be determined independently in Fluent if the Volume Of Fluid model is applied to determine the position of the air-water interface).

Boundary Conditions

The bed shear stress-based boundary condition is not a standard component of the commercial CFD code. It was written specifically for this research project by the principal investigator as a 'User Defined Subroutine', which needs to be 'merged' with the Fluent code. Notes on this can be obtained here.

Wall boundaries should be set to reflect, except the bed of the chamber which should be defined as User Defined.

Particle Injection

In setting up particle tracking, it is recommended that particle injections are distributed across the entire inlet cross-section. Particle size and density should, ideally, be identified in the field, although ‘default’ values of f = 1 mm and r = 1500 kg/m3 are felt to provide reasonable values for comparative tests. A critical value for bed shear stress must be defined, and experience has shown that a value of 0.1 N/m2 is appropriate for full scale structures, although this might be modified if site-specific information is available. The number of time steps must be sufficiently large to ensure that particles either deposit or exit the chamber. As particle tracking simulations are stochastic, a number of repeat simulations should be performed for each group of injected particles. It has been found that if the injected group contains 50+ particles, 10 repeat runs are sufficient to obtain a statistically significant result with 2% confidence limits.


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Publications/References

Adamsson, Å, Stovin, V.R., et al., in preparation, A critical bed shear stress criterion for the prediction of sediment deposition in storage chambers.

Cant, J., 1991, Detention tank design and maintenance, Report UM1233, WRc, Swindon, UK.

Drinkwater, A., 2000, Research project discussions.

Luycks, G., Vaes, G. and Berlamont, J., 1999, Experimental investigation on the efficiency of a high side weir overflow, Water Science and Technology, Vol. 39, No. 2, 61-68.

Stovin, V.R. and Saul, A.J., 1994, Sedimentation in storage tank structures, Wat. Sci. Tech., Vol. 29, No. 1-2, 363-372.

Stovin, V.R. and Saul, A.J., 1996, Efficiency prediction for storage chambers using computational fluid dynamics, Water, Science and Technology, Vol. 33, No. 9, 163-170.

Stovin, V.R., 1996, The prediction of sediment deposition in storage chambers based on laboratory observations and numerical simulation, PhD thesis, Department of Civil and Structural Engineering, University of Sheffield.

Stovin, V.R. and Saul, A.J., 1998, A Computational Fluid Dynamics (CFD) particle tracking approach to efficiency prediction, Water Science and Technology, Vol. 37, No. 1, 285-293.

Stovin, V.R., Saul, A.J., Drinkwater, A and Clifforde, I, 1999, Field testing CFD-based predictions of storage chamber gross solids separation efficiency, Water Science and Technology, Vol. 39, No. 9, 161-168.

Stovin, V.R. and Saul, A.J., 2000, Computational Fluid Dynamics and the Design of Sewage Storage Chambers, Journal of the Chartered Institution of Water and Environmental Management, 14, 103-110.


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Picture Gallery

This section contains selected images and animations from the research.

List of photographs

Plate 1 The test slab at the National CSO Test Facility, viewed from upstream.
Plate 2 The storage chamber, viewed from downstream
Plate 3 Sediment deposition close to the inlet following 90 l/s test (a)
Plate 4 Sediment deposition close to the inlet following 90 l/s test (b)
Plate 5 Sediment deposition on the chamber bed following 90 l/s test
Plate 6 The laboratory storage chamber test bed, with the 2:1 chamber
Plate 7 Sediment deposition pattern from previous laboratory test programme (Stovin, 1996)
Plate 8 Sediment deposition in 2:1 chamber (Q = 14 l/s) (inflow right)
Plate 9 Sediment deposition in 1:2 chamber (Q = 14 l/s) (inflow bottom)
Plate 10 Sediment deposition in 8:1 chamber (Q = 14 l/s) (inflow right)

List of Figures

Figure 1 Comparison between observed and simulated surface flow patterns (Wigan chambers)
Figure 2 Basic flow patterns for the three laboratory chambers
Figure 3 Observed laboratory efficiency results for three storage chambers
Figure 4 Efficiency simulated with the modified particle tracking approach
Figure 5 Results from particle tracking
Figure 6 Simulated surface flow patterns for the long chamber tested at Wigan, with Q = 90 l/s and an upstream weir
Figure 7 Simulated bed shear stress patterns for the long chamber tested at Wigan, with Q = 90 l/s and an upstream weir
Figure 8 Contours of volume fraction of sand
Figure 9 Contours of volume fraction of sand 5 mm above the bed of the chamber
Animation of time-dependent contours of volume fraction of sand 5 mm above the bed
Figure 10 Sediment transport rates in the inflow to and outflow from the chamber

 

Plate 1 The test slab at the National CSO Test Facility, viewed from upstream.
The storage chamber is on the left.


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Plate 2 The storage chamber, viewed from downstream


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Plate 3 Sediment deposition close to the inlet following 90 l/s test (a)


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Plate 4 Sediment deposition close to the inlet following 90 l/s test (b)

Plates 3 and 4 (corresponding to identical test conditions) highlight the effect that diurnal variations in the composition of the sewage have on the apparent sediment deposition efficiency.


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Plate 5 Sediment deposition on the chamber bed following 90 l/s test


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Plate 6 The laboratory storage chamber test bed, with the 2:1 chamber


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Plate 7 Sediment deposition pattern from previous laboratory test programme (Stovin, 1996)

In this instance the discharge was 15.9 l/s and the sediment used was crushed olive stone, which has a mean diameter of 47 mm and a density of 1500 kg/m3. The inflow is on the left of the picture.


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Plate 8 Sediment deposition in 2:1 chamber (Q = 14 l/s) (inflow right)


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Plate 9 Sediment deposition in 1:2 chamber (Q = 14 l/s) (inflow bottom)


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(a) downstream section

(b) upstream section

Plate 10 Sediment deposition in 8:1 chamber (Q = 14 l/s) (inflow right)


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Figure 1 Comparison between observed and simulated surface flow patterns (Wigan chambers)


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(a) 2:1 chamber

(b) 1:2 chamber

(c) 8:1 chamber

Figure 2 Basic flow patterns for the three laboratory chambers


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Figure 3 Observed laboratory efficiency results for three storage chambers

Figure 4 Efficiency simulated with the modified particle tracking approach

Note that the solid lines represent particles of 0.1 mm in diameter (comparable with previous experimental work in which crushed olivestone was used) whilst the dashed line depicts the results of simulations carried out with particles 0.9 mm in diameter (comparable with bakelite model sediment).


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a) Velocity vectors, bed shear stress contours and particle destinations for the 2:1 chamber

Figure 5 Results from particle tracking


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b) Velocity vectors, bed shear stress contours and particle destinations for the 1:2 chamber

Figure 5 Results from particle tracking


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c) Velocity vectors, bed shear stress contours and particle destinations for the 8:1 chamber

Figure 5 Results from particle tracking

For the flow field and the bed shear stress, only the results of the 0.8 m/s inlet velocity simulation are illustrated. In both plots high values are represented by red colouring, with low values being represented by blue colouring. In the case of the bed shear stress plot, the boundary of the 0.04 Pa contour is indicated by the boundary of the pale blue and pale green shading.


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Figure 6 Simulated surface flow patterns for the long chamber tested at Wigan, with Q = 90 l/s and an upstream weir


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Figure 7 Simulated bed shear stress patterns for the long chamber tested at Wigan, with Q = 90 l/s and an upstream weir


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a) 4 minutes after the start of sediment injection

b) 20 minutes after the start of sediment injection

Figure 8 Contours of volume fraction of sand

The results presented in Figures 9 to 11 are from the Fluent ASM model, for a chamber with length to breadth ratio 2:1, an inflow velocity of 0.2 m/s, a sediment diameter of 0.1 mm and a sediment density of 1500 kg/m3. The simulation time step was 1 second.


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a) 4 minutes after the start of sediment injection

b) 20 minutes after the start of sediment injection

Figure 9 Contours of volume fraction of sand 5 mm above the bed of the chamber

Animation of time-dependent contours of volume fraction of sand 5 mm above the bed


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Figure 10 Sediment transport rates in the inflow to and outflow from the chamber


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Acknowledgements

The work described in this website has been undertaken by Dr Virginia Stovin. I would like to show my appreciation to the following:

EPSRC for their financial support, which has enabled the construction of a permanent storage chamber test facility in the Water Engineering Laboratory, Department of Civil and Structural Engineering, The University of Sheffield.

My collaborators, in particular Dr Ferit Boysan of Fluent Europe, Ian Clifforde and Andy Drinkwater of WRc and Dennis Dring of Yorkshire Water.

Åsa Adamsson, from Chalmers University in Sweden, who collaborated on work involving the modified particle tracking routine during three months as a visiting postgraduate student.

John Grimm, research student at the University of Sheffield, for assisstance in the laboratory.

My academic colleagues and the technical staff in the Department of Civil and Structural Engineering at the University of Sheffield.


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