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4.34 Cooling method for gas turbines. Refer to the Journal of Engineering for Gas Turbines and...

4.34 Cooling method for gas turbines. Refer to the Journal of Engineering for Gas Turbines and Power (January 2005) study of a high-pressure inlet fogging method for a gas turbine engine, Exercise 4.15 (p. 190). Recall that you fit a first-order model for heat rate (y) as a function of speed (x1), inlet temperature (x2), exhaust temperature (x3), cycle pressure ratio (x4), and air flow rate (x5) to data saved in the GASTURBINE file.

a, Researchers hypothesize that the linear relationship between heat rate (y) and temperature (both inlet and exhaust) depends on air flow rate. Write a model for heat rate that incorporates the researchers’ theories.

b. Use statistical software to fit the interaction model, part a, to the data in the GASTURBINE file. Give the least squares prediction equation.

c. Conduct a test (at α = .05) to determine whether inlet temperature and air flow rate interact to affect heat rate.

d, Conduct a test (at α = .05) to determine whether exhaust temperature and air flow rate interact to affect heat rate.

e. Practically interpret the results of the tests, parts c and d.

Homework Answers

Answer #1

(a) The model for heat rate is:

Heart rate = 16,569.8271 - 14.1293*inlet temperature + 20.6848*exhaust temperature

0.795
Adjusted R² 0.788
R   0.891
Std. Error   733.823
n   67
k   2
Dep. Var. HeatRate
ANOVA table
Source SS   df   MS F p-value
Regression 13,34,33,406.1993 2   6,67,16,703.0997 123.89 9.87E-23
Residual 3,44,63,802.2484 64   5,38,496.9101
Total 16,78,97,208.4478 66  
Regression output confidence interval
variables coefficients std. error    t (df=64) p-value 95% lower 95% upper
Intercept 16,569.8271
Inlettemp -14.1293 0.9592 -14.730 3.10E-22 -16.0456 -12.2131
exhtemp 20.6848 2.9865 6.926 2.51E-09 14.7185 26.6510

(b) The model for heat rate is:

Heart rate = 13,696.6672 - 11.7055*inlet temperature + 26.0407*exhaust temperature - 0.0045*inlet temperature*exhaust temperature

0.795
Adjusted R² 0.785
R   0.892
Std. Error   739.111
n   67
k   3
Dep. Var. HeatRate
ANOVA table
Source SS   df   MS F p-value
Regression 13,34,81,260.9118 3   4,44,93,753.6373 81.45 1.20E-21
Residual 3,44,15,947.5360 63   5,46,284.8815
Total 16,78,97,208.4478 66  
Regression output confidence interval
variables coefficients std. error    t (df=63) p-value 95% lower 95% upper
Intercept 13,696.6672
Inlettemp -11.7055 8.2462 -1.419 .1607 -28.1843 4.7733
exhtemp 26.0407 18.3441 1.420 .1607 -10.6172 62.6985
Inlettemp*exhtemp -0.0045 0.0152 -0.296 .7682 -0.0348 0.0258

(c) The hypothesis being tested is:

H0: β3 = 0

H1: β3 ≠ 0

The p-value from the output is 0.0002.

Since the p-value (0.0002) is less than the significance level (0.05), we can reject the null hypothesis.

Therefore, we can conclude that inlet temperature and air flow rate interact to affect heat rate.

0.751
Adjusted R² 0.739
R   0.866
Std. Error   815.350
n   67
k   3
Dep. Var. HeatRate
ANOVA table
Source SS   df   MS F p-value
Regression 12,60,15,126.8500 3   4,20,05,042.2833 63.18 5.64E-19
Residual 4,18,82,081.5977 63   6,64,794.9460
Total 16,78,97,208.4478 66  
Regression output confidence
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