datacomsol for heat transfer

datacomsol for heat transfer - SUMMARYOUTPUT MultipleR 1...

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SUMMARY OUTPUT Regression Statistics Multiple R 1 R Square 1 Adjusted R 1 Standard E 0.82 Observatio 3 ANOVA df SS MS F ignificance F Regression 1 332.82 332.82 499.23 0.03 Residual 1 0.67 0.67 Total 2 333.49 Coefficients tandard Err t Stat P-value Lower 95%Upper 95% Lower 95.0%pper 95.0% Intercept 472.82 3.5 135.24 0 428.4 517.24 428.4 517.24 X Variable  -505.88 22.64 -22.34 0.03 -793.57 -218.2 -793.57 -218.2
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SUMMARY OUTPUT Regression Statistics Multiple R 1 R Square 1 Adjusted R 1 Standard E 0.67 Observatio 3 ANOVA df SS MS F ignificance F Regression 1 337.28 337.28 742.54 0.02 Residual 1 0.45 0.45 Total 2 337.74 Coefficients tandard Err t Stat P-value Lower 95%Upper 95% Lower 95.0%pper 95.0% Intercept 450.96 4.29 105.1 0.01 396.44 505.49 396.44 505.49 X Variable  -509.23 18.69 -27.25 0.02 -746.68 -271.78 -746.68 -271.78
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position (m) Temp © Temp (K) -505.88 1 0.13 135.5 408.65 22.64 2 0.15 121.6 394.75 1 3 0.18 109.7 382.85 499.23 4 0.2 74.71 347.86 332.82 5 0.23 60.65 333.8 #N/A 6 0.25 48.75 321.9 #N/A #N/A q (W/m^2) 130845 24.67 #1) #2) dT/dx (K/m) error k (W/m/k) error Left -505.88 22.64 258.65 16.19 4.4669E-04 Right -509.23 18.69 256.95 13.25 4.4829E-04 resist. (m^2K/W): del 0.1 0.12 270 290 310 330 350 370 390 410 430 f(x) = R² = f(x) = R² = Tem p(K)
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199.67 #N/A -509.23 177.81 3.5 #N/A 18.69 4.29 0.82 #N/A 1 0.67 1 #N/A 742.54 1 0.67 #N/A 337.28 0.45 #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A error Temp (K)@x=.19 1/h error h (W/m^2/K) error 4.4335E-06 376.7 1.719E-04 1.124E-06 5.816E+03 3.802E+01 5.5672E-07 354.21 Left 1 2 3 Right 4 5 6 k(W/m/K) Ac (m2) P (m) 2 0.14 0.16 0.18 0.2 0.22 0.24 0.26 = -509.23x + 450.96 1 = -505.88x + 472.82 1 Temp vs x Column D Linear Regres- sion for Column D Column D Linear Regres- sion for Column D Position (m)
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#3) Q_water (W) Q_heater ( heat loss (%) 25.81 66.5 61.19 #6) T © position (m) (T-Te)(Tb- beta hc 135.5 0.13 0.81 2.42 0.81 4.12 121.6 0.15 0.71 2.97 0.71 6.23 109.7 0.18 0.63 3.36 0.63 7.97 ave 2.92 74.71 0.2 0.38 5.29 0.38 19.69 60.65 0.23 0.28 6.07 0.28 25.93 48.76 0.25 0.19 6.95 0.19 34.06 111 0 0.08
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4 scfm 1 scfm x (m) T © T (K) x (m) T © 0.13 139.2 412.35 0.13 141.4 0.15 136 409.15 0.15 139.8 0.18 132.5 405.65 0.18 138.3 3 scfm 8 scfm x (m) T © T (K) x (m) T © 0.13 140.5 413.65 0.13 138.4 0.15 137.7 410.85 0.15 134.1 0.18 134.7 407.85 0.18 129.1 #1) Air Vel (scfm) T @ x=L (K) error dT/dx @ x=L error hc () 1 410.76 0 -60.38 ? 57.9 2 408.53 0 -85.79 ? 83.88 3 406.58 0 -112.62 ? 112.04 4 404.23 0 -129.76 ? 131.86 8 400.32 0 -179.34 ? 189.01 0.64 435.89 #N/A 0.02 0 #N/A 1 0 #N/A #2) 0.12 0.14 0.16 0.18 396 398 400 402 404 406 408 410 412 414 416 f(x) = 422.39·0.86^x f(x) = 429.65·0.73^x Chart Title Column E Exponential Regression for Column E Column I Exponential Regression for Column I Column M Column E Column I x (m) T (K)
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1 scfm 2 scfm 3 scfm x z T T T 0.01 407.72 406.1 404.86 0.02 409.21 407.67 406.5 0.03 410.71 409.24 408.13 0.04 412.21 410.83 409.78
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This note was uploaded on 03/11/2011 for the course CHEM ENG 154 taught by Professor Maboudian during the Spring '11 term at Berkeley.

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datacomsol for heat transfer - SUMMARYOUTPUT MultipleR 1...

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