Pneumatic Conveying Design - Report Example

Table of contents Introduction Assumptions Design of spreadsheet Design steps and the logic sequences Results Discussion of results Reference List Introduction Pneumatic conveying design is a system for transporting bulk materials using pressurised gas in pipes. This system enables the materials move from one point to another for industrial use. In this design, materials that are transported in pipes should be able to be compressed or made into fluid so that they can be transported in non-suspension flow. However in order for them to be transported easily, the system capability and characteristics of the materials plays. In designing the pneumatic conveying system three variables are involved mass flow rate of the conveying gas( mf), flow rate of materials(ms) and resulting pressure required to drive the gas-solid mixture. The distance to be covered by materials during the transportation is important in design the system as this will enable one understand the minimum transport capability. The rate of flow of materials will be affected by static pressure in the pipeline that is conveying the materials. The pick-up velocity of the materials is critical in the analysis of the system as it will determine the amount of materials to be transport. This becomes critical when designing the Pneumatic conveying system. Assumptions: The following are the assumptions made in relation to the design of the Pneumatic conveying system; Assumption table Item Measurement Unit 1. Length of Pipe 176 [m] 2. Vertical Length of Pipe 29 [m] 3. Diameter 0.05 [m] 4. Rair 287.058 J/(Kg K) 5. To 288.2 K 6. Standard Temperature 293 [K] 7. Roughness factor (ε) 4.60E-05 8. Standard Pressure 101300 [Pa] 9. Number of Bends 24 10. Bend factor 0.6 11. μ0 0.00001783 12. B -1.9552285 13. C 11.2787611 Pneumatic Conveying Design Methods (Steps) Step 1; identify the material to be transported Step 2: identify pick-up conveying velocity Step 3: determine air flow rate, material flow rate and pipe pressure Step 4: determine the ability of materials to be fluidized Step 5: determine the diameter of the conveying pipeline and maximum pressure for transporting the materials. Step 6: determine the relationship between pick-up velocity and m*. In the excel calculation the various methods has been employed to determine conveying capability of the system proposed. We begun by first employing the following formulae to determine the diameter of the pipe D= Whereas Vf = the superficial gas velocity (m/s) ms = solids mass flow rate and and ρf = the gas density (kg/m3).where ms is found using the following formulae ms= mf x m* Whereas mf = gas mass flow rate and m*= solids loading ratio The relationship between these variables is determined by the following Whereas mf = gas mass flow, R =gas constant, T = absolute temperature, vf = superficial gas velocity, d =pipeline internal temperature, Vf = gas volumetric flow rate (m3/s) Predicting the way pneumatic conveying system will work is important to design process. Design of spreadsheet Iteration Ms m*a m*s ΔP_Guess m* P0 Pi Pm ρ0 ρi ρm μ c0 ci cm Re Δf Fr λs Δpair ΔPBends ΔPSolids ΔPvertical ΔPConv [t/h] [kg/s] [kg/s] [kPa] [Pa] [Pa] [Pa] [kg/m^3] [kg/m^3] [kg/m^3] [m/s] [m/s] [m/s] [Pa] [Pa] [Pa] [Pa] [kPa] 1 25 0.0801 6.94 377 86.70 101300.00 478300.00 289800.00 1.20 5.69 3.45 1.80523E-05 33.87 7.17 11.84 112990.27 0.019231946 16.91 0.004811 16348.58 304973.63 354533.30 675.86 14 25 0.0801 6.94 774.45 86.70 101300.00 875749.98 488524.99 1.20 10.41 5.81 1.80523E-05 33.87 3.92 7.02 112990.27 0.019231946 10.03 0.013354 9698.21 180914.71 583837.23 774.45                                                               Stepped Pipe Ms m*a m*s ΔP_Guess Diameter Length Bends Bend factor m* P0 Pi Pm ρ0 ρi ρm μ c0 ci cm Re λf Fr λs Δpair ΔPBends ΔPSolids ΔPvertical ΔPConv [t/h] [kg/s] [kg/s] [kPa] [m] [m] [Pa] [Pa] [Pa] [kg/m^3] [kg/m^3] [kg/m^3] [m/s] [m/s] [m/s] [Pa] [Pa] [Pa] [Pa] [kPa] 1 25 0.45 6.94 1105   0.125 40 2 1.52 15.43 101300.00 1206300.00 653800.00 1.20 14.34 7.77 1.80523E-05 30.45 2.56 4.72 253910.72 0.01560046 4.26 0.168817 431.77 4320.50 72104.10 76.86 25 0.45 6.94 40.04 0.125 40 2 1.52 15.43 101300.00 141338.10 121319.05 1.20 1.68 1.44 1.80523E-05 30.45 21.82 25.42 253910.72 0.01560046 22.96 0.006268 2326.86 23283.60 14427.63   40.04 2 25 0.45 6.94 699.84 0.1 455 5 1.2 15.43 141338.10 841178.10 491258.10 1.68 10.00 5.84 1.80523E-05 34.10 5.73 9.81 317388.40 0.01638426 9.90 0.032434 20949.86 27706.85 640001.33 688.66 25 0.45 6.94 673.74 0.1 455 5 1.2 15.43 141338.10 815078.97 478208.53 1.68 9.69 5.69 1.80523E-05 34.10 5.91 10.08 317388.40 0.01638426 10.17 0.030771 21521.55 28462.92 623752.02   673.74 3 25 0.45 6.94 699.84 0.04 100 5 0.5 15.43 815078.97 1514918.97 1164998.97 9.69 18.01 13.85 1.80523E-05 36.95 19.88 25.85 793471.01 0.0203127 41.27 0.001991 235068.69 190160.40 355579.07 780.81 25 0.45 6.94 778.38 0.04 100 5 0.5 15.43 815078.97 1593461.53 1204270.25 9.69 18.95 14.32 1.80523E-05 36.95 18.90 25.01 793471.01 0.0203127 39.93 0.002124 227403.09 183959.27 367020.20   778.38 4 25 0.45 6.94 699.84 0.036 100 5 0.5 15.43 1593461.53 2293301.53 1943381.53 18.95 27.27 23.11 1.80523E-05 23.34 16.21 19.13 881634.46 0.02085322 32.20 0.003235 244993.77 173747.08 586598.05 1005.34 25 0.45 6.94 1019.52 0.036 100 5 0.5 15.43 1593461.53 2612981.22 2103221.37 18.95 31.07 25.01 1.80523E-05 23.34 14.23 17.68 881634.46 0.02085322 29.75 0.003776 226374.82 160542.71 632602.16   1019.52 5 25 0.45 6.94 699.84 0.033 180 5 0.5 15.43 2612981.22 3312821.22 2962901.22 31.07 39.39 35.23 1.80523E-05 16.94 13.36 14.94 961783.04 0.02131603 26.25 0.004823 456819.37 161403.39 1595150.07 2213.37 25 0.45 6.94 2536.37 0.033 180 5 0.5 15.43 2612981.22 5149352.54 3881166.88 31.07 61.22 46.15 1.80523E-05 16.94 8.59 11.40 961783.04 0.02131603 20.04 0.008177 348738.08 123216.12 2064417.13   2536.37 6 25 0.45 6.94 699.84 0.03 170 5 0.5 15.43 5149352.54 5849192.54 5499272.54 61.22 69.54 65.38 1.80523E-05 10.40 9.15 9.74 1057961.35 0.02184089 17.95 0.010143 383583.83 127319.62 2748995.19 3259.90 25 0.45 6.94 3905.37 0.03 170 5 0.5 15.43 5149352.54 9054727.38 7102039.96 61.22 107.66 84.44 1.80523E-05 10.40 5.91 7.54 1057961.35 0.02184089 13.90 0.016724 297017.76 98586.50 3509770.58   3905.37 Table 1:- data Table 1                                 ΔP guess Pmean Pi Po ρ-mean Ci Co C-mean Re λf Fr λs ΔP air ΔP bend ΔP friction ΔP total ΔPm/ΔPc a.Fr^b λs.(m*^0.5) 396.06 289.50 101.38 101.38 3.56 30.42 30.42 10.30 107659.21 0.00018 14.77 0.008142 11.90 123.78 260.38 396.06 0.951879 0.00517 0.000507 352.94 272.50 101.34 101.38 3.30 22.00 30.42 8.03 77849.99 0.00026 11.35 0.012902 6.70 83.81 262.43 352.94 0.971828 0.00866 0.001307 324.73 267.00 101.33 101.38 3.13 30.47 30.42 11.71 107792.29 0.00016 16.04 0.008675 13.54 108.97 202.22 324.73 1.022373 0.00441 0.00042 340.39 264.50 101.33 101.38 3.23 24.56 30.42 9.17 86899.22 0.00022 13.05 0.010379 8.55 92.33 239.51 340.39 0.960671 0.00659 0.000811 318.21 258.00 101.31 101.38 3.10 27.31 30.42 10.63 96613.83 0.00018 14.87 0.009115 11.01 97.91 209.29 318.21 0.986776 0.00510 0.000534 322.94 259.50 101.32 101.38 3.12 17.34 30.42 6.69 61348.45 0.00036 9.39 0.018068 4.40 60.38 258.16 322.94 0.9816 0.01254 0.002617 299.18 254.50 101.31 101.38 2.98 28.74 30.42 11.61 101670.75 0.00016 15.87 0.009071 12.66 97.99 188.53 299.18 1.026132 0.00450 0.000447 312.04 255.00 101.31 101.38 3.06 12.75 30.42 5.02 45113.07 0.00058 7.03 0.029621 2.43 39.08 270.54 312.04 0.987054 0.02211 0.007511 283.2 241.00 101.28 101.38 2.89 19.27 30.42 8.04 68135.37 0.00028 11.23 0.014384 5.87 63.76 213.57 283.20 0.988702 0.00884 0.001455 307.47 255.00 101.31 101.38 3.03 10.80 30.42 4.29 38193.07 0.00076 5.95 0.040059 1.76 30.22 275.49 307.47 1.001731 0.03061 0.013824 271.94 236.00 101.27 101.38 2.82 13.59 30.42 5.80 48040.76 0.00048 8.09 0.024756 2.99 40.06 228.90 271.94 0.992862 0.01680 0.004737 226.59 217.00 101.23 101.38 2.55 22.63 30.42 10.68 79979.22 0.00020 14.64 0.01108 9.16 64.47 152.96 226.59 1.023881 0.00526 0.000643 248.28 227.50 101.25 101.38 2.68 18.94 30.42 8.51 66937.68 0.00027 11.69 0.014734 6.11 57.47 184.71 248.28 1.018991 0.00818 0.001334 247.78 226.50 101.25 101.38 2.68 14.98 30.42 6.74 52964.61 0.00039 9.29 0.020888 3.83 43.32 200.64 247.78 1.01299 0.01281 0.002982 255.29 226.50 101.25 101.38 2.72 11.26 30.42 4.98 39789.99 0.00063 6.98 0.03221 2.12 29.57 223.60 255.29 0.98318 0.02241 0.008308 257.64 231.00 101.26 101.38 2.74 9.67 30.42 4.26 34200.76 0.00082 5.88 0.043991 1.56 23.56 232.51 257.64 1.009169 0.03131 0.015408 275.08 240.00 101.28 101.38 2.84 8.32 30.42 3.53 29409.99 0.00112 4.87 0.05982 1.11 19.02 254.95 275.08 1.010616 0.04532 0.030266 269.63 248.00 101.29 101.38 2.81 7.49 30.42 3.21 26482.30 0.00133 4.24 0.080975 0.91 15.83 252.88 269.63 1.090388 0.05932 0.049177 297.54 259.50 101.32 101.38 2.97 6.73 30.42 2.73 23820.76 0.00172 3.65 0.100693 0.70 13.70 283.15 297.54 1.065404 0.07972 0.084161 185.77 199.50 101.20 101.38 2.31 21.39 30.42 11.15 75587.68 0.00021 15.05 0.012156 9.04 51.93 124.80 185.77 1.060457 0.00499 0.000648 257.86 225.00 101.25 101.38 2.74 7.08 30.42 3.11 25018.46 0.00143 4.42 0.070762 0.83 14.11 242.92 257.86 0.961754 0.05480 0.045716 202.29 194.00 101.19 101.38 2.41 8.40 30.42 4.20 29676.15 0.00094 6.08 0.042897 1.34 16.48 184.47 202.29 0.919489 0.02938 0.015435 Control correlation table Table 2 ma (kg/s) ms (kg/s) ΔP kPa m* (Ms/Ma) Po Pmean Ci Cmean Co ρ-mean Re λf ΔPair ΔPbend λs Fr λs-(M*)^.5 0.0809 3.6 377 44.50 377 299.33 30.42 10.65 41.07 3.56 107659.21 0.000177 0.01 0.123777 0.008142 14.77 -6.663 0.0585 3.14 343 53.68 343 277.77 22.00 8.18 30.19 3.30 77849.99 0.000262 0.01 0.083811 0.012902 11.35 -7.313 0.081 2.77 332 34.20 332 263.67 30.47 11.56 42.03 3.13 107792.29 0.000157 0.01 0.108972 0.008675 16.04 -5.839 0.0653 3.02 327 46.25 327 271.5 24.56 9.41 33.97 3.23 86899.22 0.000218 0.01 0.092328 0.010379 13.05 -6.790 0.0726 2.75 314 37.88 314 260.41 27.31 10.73 38.04 3.10 96613.83 0.00018 0.01 0.097909 0.009115 14.87 -6.145 0.0461 2.72 317 59.00 317 262.77 17.34 6.77 24.11 3.12 61348.45 0.000358 0.00 0.060378 0.018068 9.39 -7.663 0.0764 2.51 307 32.85 307 250.89 28.74 11.44 40.19 2.98 101670.75 0.000163 0.01 0.097992 0.009071 15.87 -5.723 0.0339 2.35 308 69.32 308 257.32 12.75 5.07 17.82 3.06 45113.07 0.000577 0.00 0.039075 0.029621 7.03 -8.296 0.0512 2.38 280 46.48 280 242.9 19.27 8.10 27.37 2.89 68135.37 0.000281 0.01 0.06376 0.014384 11.23 -6.804 0.0287 2.13 308 74.22 308 255.04 10.80 4.29 15.09 3.03 38193.07 0.000759 0.00 0.030225 0.040059 5.95 -8.575 0.0361 2.08 270 57.62 270 237.27 13.59 5.83 19.42 2.82 48040.76 0.000478 0.00 0.040058 0.024756 8.09 -7.566 0.0601 1.79 232 29.78 232 214.6 22.63 10.56 33.19 2.55 79979.22 0.000202 0.01 0.064467 0.01108 14.64 -5.446 0.0503 2.02 253 40.16 253 225.44 18.94 8.43 27.36 2.68 66937.68 0.000271 0.01 0.057472 0.014734 11.69 -6.322 0.0398 1.93 251 48.49 251 225.19 14.98 6.70 21.68 2.68 52964.61 0.000389 0.00 0.043315 0.020888 9.29 -6.943 0.0299 1.79 251 59.87 251 228.95 11.26 5.03 16.29 2.72 39789.99 0.000632 0.00 0.029572 0.03221 6.98 -7.705 0.0257 1.67 260 64.98 260 230.12 9.67 4.24 13.91 2.74 34200.76 0.000824 0.00 0.023562 0.043991 5.88 -8.017 0.0221 1.63 278 73.76 278 238.84 8.32 3.51 11.83 2.84 29409.99 0.001117 0.00 0.01902 0.05982 4.87 -8.528 0.0199 1.49 294 74.87 294 236.12 7.49 3.06 10.55 2.81 26482.30 0.00133 0.00 0.015833 0.080975 4.24 -8.572 0.0179 1.52 317 84.92 317 250.07 6.73 2.63 9.36 2.97 23820.76 0.001719 0.00 0.013696 0.100693 3.65 -9.114 0.0568 1.37 197 24.12 197 194.19 21.39 10.85 32.25 2.31 75587.68 0.000206 0.01 0.051926 0.012156 15.05 -4.899 0.0188 1.37 248 72.87 248 230.23 7.08 3.18 10.26 2.74 25018.46 0.001434 0.00 0.01411 0.070762 4.42 -8.466 0.0223 1.18 186 52.91 186 202.45 8.40 4.38 12.78 2.41 29676.15 0.000938 0.00 0.016478 0.042897 6.08 -7.231 Results From the results of the regression, the regression coefficient is found to be equal to 11.39 as it is the graph 1 below. It implies that if pick-up velocity increases by 1 unit, the other variable will change 11.39 times. This regression coefficient indicates towards a close association between the two variables. This finding is further reinforced by the value of R squared. Very high value of r squared, 0.998, suggests that variation in the given data of M* is capable of explaining 99.8 percent of total variation in other variable around its average value. It implies that the regression model is a good fit in the given data. Graph 1 Graph 2 below shows solids loading ratio and relative velocity. The graph depicts that when there is a higher solid loading ratio the relative velocity tends to be lower. This means the flow of the materials in the system are affected by the relative within the system Graph 2 The graph 3 below shows that when the pipe length increases the velocity decreases. This means that the distance to be covered affects the speed of transmission of materials. Graph 3 From the graph 4 it can be noted that changes triggers minimal changes in pick-up velocity. The changes are minimal to the point that it can be said that the ΔP_Measured/ΔPConv remains constant as the pick-up velocity increases. Graph 4 From the graph5 below it can stated that the pattern of the plotted points on the graph slopes from right to left of the scatter plot suggesting a positive relationship between the two variables. This kind of association simply implies that as the m* rises, changes slightly. This kind of findings simply goes with the general expectation. The finding through the scatter diagram is further reinforced by the value of the correlation coefficient between the two variables under consideration. The positive sign of the coefficient indicates a positive relationship while the very low absolute value of the coefficient, 0.001, simply implies minimum relationship. Graph 4 The system selected in our cases is as follows Discussion of Results As required, the pick-up velocity, mass flow rate of materials, distance conveying, gas mass flow rate, gas mass flow, gas constant, absolute temperature, pipeline internal diameter, and gas volumetric flow rate was determined. These were used to calculate Minimum Conveying Capability which has been highlighted in the graph1 and two above. Graphs 1 & 4 shown above are those that were plotted based on the data recorded and calculations done to validate Pneumatic Conveying Design. The design was done successfully to understand the methods of flow measurement and the concepts of flow process that happens inside a pipe. Determining the velocities along a conveyor was done by the measurement of pressure heads and the application of the Streeter model in determining the air and solid friction. Reference List Jones, M. and Peter Wypych, P. ( 2007). Introduction to Pneumatic Conveying. Centre for Bulk Solids and Particulate Technologies, The Universities of Newcastle and Wollongong. Lewin, D.R., Seider, W. D. & Seade, J.D. (2002). ‘Integrated process design instruction’, Computers and Chemical Engineering, vol. 26, no.2, pp. 295-306. Mondie, S. (2005). System, structure and control 2004. Oxford: Elsevier-IFAC. Pan, R. (1999). Material properties and flow modes in pneumatic conveying. Powder Technology, 104, 157–163. Shah, L. S. & MacGregor, F. J. (2005). Dynamics and control of process systems 2004, Oxford: Elsevier-IFAC. Williams, K.C., (2008). Dense phase pneumatic conveying of powders: Design aspects and phenomena. Doctoral dissertation, University of Newcastle, Australia. Williams, K. C.,& Jones, M. G. (2003). Classification diagrams for dense-phase pneumatic conveying. Powder Handling and Processing, 15(6), 368–373. Read More