Sediment flow simulation Result

When the models were run for 30000 seconds with time step of 50 seconds following result were obtained. After the sediment simulation, result file are read on Tecplot program. Sediment distribution and concentration is plotted. With the help of distribution and concentration pictures, a visual inspection has made for discussion and comparison of sediment simulation results. Distribution of sediment concentration of plan and cross section view are listed in Annexure-C.

6.3.1 Sediment distribution on one settling basin

This model does not have any effect of approach geometry. So concentration is distributed uniformly. Concentration level is higher at entrance and bottom level.

Concentration level goes down on downstream and upper level. Figure 6.3 show the sediment concentration distribution on one settling chamber model.

Figure 6.3 Sediment concentration distribution on one settling chamber 6.3.2 Sediment distribution on proposed layout settling basin

Sediment concentration is not equally distributed over four chamber of settling chamber. Effect of approach geometry is clearly seen on distribution of sediment concentration. More sediment is concentrated on inner chamber than outer chamber of two approach bends. Figure 6.4 shows sediment concentration distribution on proposed layout.

Figure 6.4 Sediment concentration distribution on proposed layout

6.3.3 Sediment distribution on alternative layout settling basin

Sediment concentration is not equally distributed over four chamber of settling chamber. Effect of approach geometry is clearly seen on distribution of sediment concentration. More sediment is concentrated on inner chamber than outer chamber of two approach bends. As comparing with proposed layout

concentration is even more on inner chambers. Figure 6.5 shows sediment concentration distribution on alternative layout.

Figure 6.5Sediment concentration distribution on alternative layout

6.3.4 Sediment distribution on modification layouts

Results show modifications on approach geometry, improve in uniformity of distribution of sediment concentration.

Modification 1

Modification 1 show more uniform distribution of sediment concentration over four chambers. With visual inspection chamber four has little less sediment concentration than other chamber however, it seems more uniform than propose layout. Figure 6.6 shows sediment distribution over settling chamber due to modification 1.

Figure 6.6 Sediment concentration distribution on modification 1

Modification 2

Sediment concentration distribution is more similar with proposed layout however, distribution can be said quite more uniform than proposed layout.

Figure 6.7 shows distribution of sediment concentration due to modification 2.

Figure 6.7Sediment concentration distribution on modification 2 Modification 3

Sediment concentration distribution is uniformly distributed on all four chambers due to modification 3. Figure 6.8 shows distribution of sediment concentration due to modification 3.

Figure 6.8Sediment concentration distribution on modification 3 Modification 4

Sediment concentration distribution is uniformly distributed on all four chambers due to modification 4. Figure 6.9 shows distribution of sediment concentration due to modification 4.

Figure 6.9 Sediment concentration distribution on modification 4

As comparing result of sediment distribution due to modifications on approach geometry, distribution is more uniform and Modification 3 and 4 give more uniformly distribution of sediment concentration.

6.3.5 Sediment distribution on closing of chambers

During closing of one chamber for full operation of plant, sediment concentration also not uniform on remaining chambers. Also sediment concentration is more at downstream of settling chamber than operation of four chambers. Figure 6.10 to Figure 6.13 shows the concentration of sediment distribution on closing of first to fourth.

Closing of first chambers

Figure 6.10Sediment concentration distribution on closing of first chamber

Closing of second chambers

Figure 6.11Sediment concentration distribution on closing of second chamber

Closing of third chamber

Figure 6.12Sediment concentration distribution on closing of third chamber

Closing of fourth chamber

Figure 6.13 Sediment concentration distribution on closing of fourth chamber 6.4 Trap efficiency

6.4.1 Trap efficiency evaluation by Analytical Method

For one settling chamber trap efficiency is evaluated by Vetter’s Method and Camp’s Method. Trapping efficiency for different size of sediment is presented on Figure 6.14.

Camp’s method seems more conservative because trapping efficiency for particle size greater than 0.15mm is 100% while from Vetter’s method trapping efficiency 100% for particle size greater than 0.3mm.

Figure 6.14 Trapping Efficiency by Analytical Method

6.4.2 Trap efficiency evaluation by SSIIM model

Trapping efficiency is evaluated for during high sediment band of inflow shown in Figure 6.1 and Figure 6.2 above and SSIIM was run only for five finest particle sizes. In SSIIM model trapping efficiency is calculated by sediment inflow flux and outflow flux, written in boogie file during the simulation.

One settling chamber was modeled with high sediment band and inflow and outflow of sediment concentration flux is evaluated with respect to time. Trap percentage for respected time is evaluated with inflow and out flow flux. Trap percentage is considered as trapping efficiency. When the model was run for 66000 second with time step of 20 second following results were obtained which is shown in Figure 6.15

Figure 6.15 shows trap percentage with respect to time of computation and sediment concentration inflow shown in Figure 6.2. It shows percentage of trap goes down with time of computation it may be due to high flow of sediment concentration with respect to time. When sediment flow to settling basin most of coarse particle settle down at entrance of basin and deposition may reduce the flow depth. Due to reduced flow depth fine particle may not settle down because of higher velocities. Settle fine particle may be become suspension and flow toward the outlet.

Figure 6.15 Trap percentage with time of computation

Comparison with analytical method

In Figure 6.16, trapping efficiency of SSIIM model is compared with trapping efficiency by analytical method. For fine particle SSIIM model gives lower trap value while for larger sediment particle SSIIM model gives higher trap value.

Figure 6.16 Comparison of trapping efficiency by SSIIM and Vetter Method Trap percentage for proposed, alternative and modifications

SSIIM model were run for 65050 seconds with time step of 50 seconds Trap percentage are found as Table 6.2. It was assumed that there is no bed erosion.

Table 6.2 Trap percentage by SSIIM Model Layouts 

SC  PL  AL  M1  M2  M3  M4 

Size,mm 

0.3  100.00  100.00  100.00  100.00 100.00 100.00  100.00

0.2  99.95  99.37  97.56  99.65 99.66 99.60  99.53

0.15  97.61  94.02  87.57  95.60 95.30 95.12  94.69

0.1  77.14  72.32  66.09  75.85 74.20 74.36  73.55

0.06  42.61  41.57  40.29  44.58 43.03 43.08  42.60

Average 

Trap %  83.46  81.45  78.19  83.14 82.44 82.43  82.07

SC- Settling chamber PL- Proposed layout AL- Alternative layout M1- Modification 1 M2- Modification 2 M3- Modification 3 M4- Modification 4

From the Table 6.2 trap efficiency is more for settling basin chamber model it may be due to no effect of approach geometry and for other models trap percentage near to equal and modifications also increase trap percentage.

Trap percentage during closing of one chamber

Table 6.3 Trap percentage by SSIIM Model Layouts 

C1  C2  C3  C4 

Size,mm 

0.3  99.96  99.95  99.94  99.91 

0.2  96.60  96.59  96.86  97.70 

0.15  84.53  84.86  86.17  88.19 

0.1  57.95  58.72  61.84  63.86 

0.06  31.56  32.13  35.40  36.11 

Average Trap %  74.12  74.45  76.04  77.15 

C1- Closing of first chamber C2- Closing of second chamber C3- Closing of Third chamber C4- Closing of Fourth chamber From Table 6.2 and 6.3 it is clearly seen that trap percentage reduces with closing one chamber and operation of remaining chambers with full design discharge.

All the calculation tables are presented on Appendix –C.

6.4.3 Sensitivity of control file parameters 6.4.3.1 Effect of Sediment pick-up rate, F 37 2

SSIIM model was run with F 37 2 data set and trap percentage is find out as on Table 6.4. Comparing trap percentage of F 37 2 data set with F 37 1 data set on Table 6.4 trap percentage is also most similar for coarse particle. However, for fine particle, F 37 2 data set has higher trap percentage. It may be due to F 37 1 data set is used for re-suspension of sediment at a constant rate and while F 37 2 data set is used re-suspension become function of flux. In both cases all other parameter are same.

Table 6.4 Trap efficiency variation due to F 37 data set F 37 data set 

F 37 1  F 37 2 

Size,mm 

0.3  100.00%  100.00% 

0.2  99.95%  99.95% 

0.15  97.61%  97.70% 

0.1  77.14%  78.15% 

0.06  42.61%  45.03% 

Average Trap %  83.46%  84.17% 

6.4.3.2 Effect of change of F 16 data set

When model was run varying F 16 data set following result were obtained. It has very minor effect on trap percentage. The result is presented on Table 6.5.

Table 6.5 Trap percentage with variation of F 16 data set

Size mm F 16 data set values

0.021  0.019  0.017  0.014 

0.3   100.00%  100.00%  100.00% 100.00%

0.2  99.95%  99.95%  99.95% 99.95%

0.15  97.61%  97.61%  97.61% 97.62%

0.1  77.14%  77.15%  77.16% 77.19%

0.06  42.61%  42.60%  42.61% 42.61%

6.4.3.3 Effect of shield’s coefficient F 11 data set

When model was run with shield’s coefficient 0.04 following result was obtained.

With comparing with result on Table 6.6 the result all most same so effect of Shield’s coefficient is very minor. Defect percentage also reduces with shield coefficient 0.04. Trap percentage with F 11 2.65 0.04 is shown in Table 6.6.

Table 6.6Trap percentage with changing F 11 data set F 11 data set 

0.047  0.040 

Size,mm 

0.3  100.00%  100.00%

0.2  99.95%  99.95%

0.15  97.61%  97.60%

0.1  77.14%  77.05%

0.06  42.61%  42.40%

Average Trap %  83.46%  83.40% 

6.4.3.4 Effect of thickness of the upper active sediment layer

To achieve a reduced defect SSIIM model was run providing F 106 data set. It overrides the original value which is equal to maximum particle diameter. It reduced defect percentage. The figure has very low difference. Trap percentage with F 106 data set is presented on Table 6.7.

Table 6.7 Trap percentage with changing F 106 data set F 106 data set 

Without F 106  With F 106  Size,mm 

0.3  100.00%  100.00%

0.2  99.95%  99.94%

0.15  97.61%  97.61%

0.1  77.14%  77.13%

0.06  42.61%  42.59%

Average Trap %  83.46%  83.45%