EGR100 The Temperature Values in Celsius
Plot the average temperature values in a scatter plot in triangles (y-axis), and the average resistance values on a secondary y-axis in a scatter plot as squares. Feel free to change the color of the data points, but make sure to graph the time on the x-axis.(30 pts) Time (min) Expt Resistance-1 (Ohms) Expt Resistance-2 (Ohms)
0.50 800 850
1.00 1000 1100
1.50 1200 1280
2.00 1400 1450
2.50 1450 1520
3.00 1450 1550
3.50 1450 1550
4.00 1470 1570
4.50 1500 1600
5.00 1500 1600
The standard deviation of the each set of values should be used as error bars in each data set, and add a trendline as well for each data set. The regression equations and R-squared values for the trendlines should be displayed on the figure. Make sure to follow the figure rules for formatting in EGR 100.
Create a table of all of your calculations. Make sure to label your table and format it according to the EGR 100 guidelines.
Make a word document and paste your figure and table into the document as pictures with titles. In the same document, type the equations for the answer to the problem below.
Draw a basic turbine with four blades. Add a figure title.
Finally, make the whole document (answers for questions 1 and 2) a pdf for submission on D2L. Your Excel file should also be uploaded as part of your midterm submission.Print your pdf and attach your signature page (page one of this document) to your final hard copy submission.
Answer:
- Calculate the temperature values in Celsius - C for the resistance values below using the above equation.
Experiment 1
1/T0 |
1/B |
R for Experiment 1 |
R0 |
(R/R0) |
ln(R/R0) |
1/T |
T (K) |
T (0C) |
0.00335402 |
0.00025316 |
800 |
10000 |
0.08 |
-2.5257 |
0.002715 |
368.3786 |
95.22857 |
0.00335402 |
0.00025316 |
1000 |
10000 |
0.1 |
-2.3026 |
0.002771 |
360.8702 |
87.72017 |
0.00335402 |
0.00025316 |
1200 |
10000 |
0.12 |
-2.1203 |
0.002817 |
354.9584 |
81.80839 |
0.00335402 |
0.00025316 |
1400 |
10000 |
0.14 |
-1.9661 |
0.002856 |
350.107 |
76.95701 |
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 |
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 |
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 |
0.00335402 |
0.00025316 |
1470 |
10000 |
0.147 |
-1.9173 |
0.002869 |
348.5992 |
75.44919 |
0.00335402 |
0.00025316 |
1500 |
10000 |
0.15 |
-1.8971 |
0.002874 |
347.9788 |
74.82884 |
0.00335402 |
0.00025316 |
1500 |
10000 |
0.15 |
-1.8971 |
0.002874 |
347.9788 |
74.82884 |
Experiment 2
1/T0 |
1/B |
R for Experiment 2 |
R0 |
(R/R0) |
ln(R/R0) |
1/T |
T (K) |
T (0C) |
0.00335402 |
0.00025316 |
850 |
10000 |
0.085 |
-2.4651 |
0.00273 |
366.3084 |
93.15835 |
0.00335402 |
0.00025316 |
1100 |
10000 |
0.11 |
-2.2073 |
0.002795 |
357.7553 |
84.60535 |
0.00335402 |
0.00025316 |
1280 |
10000 |
0.128 |
-2.0557 |
0.002834 |
352.9097 |
79.7597 |
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 |
0.00335402 |
0.00025316 |
1520 |
10000 |
0.152 |
-1.8839 |
0.002877 |
347.5747 |
74.42466 |
0.00335402 |
0.00025316 |
1550 |
10000 |
0.155 |
-1.8643 |
0.002882 |
346.9762 |
73.82624 |
0.00335402 |
0.00025316 |
1550 |
10000 |
0.155 |
-1.8643 |
0.002882 |
346.9762 |
73.82624 |
0.00335402 |
0.00025316 |
1570 |
10000 |
0.157 |
-1.8515 |
0.002885 |
346.5865 |
73.43654 |
0.00335402 |
0.00025316 |
1600 |
10000 |
0.16 |
-1.8326 |
0.00289 |
346.0127 |
72.86273 |
0.00335402 |
0.00025316 |
1600 |
10000 |
0.16 |
-1.8326 |
0.00289 |
346.0127 |
72.86273 |
R for Experiment 1 |
R for Experiment 2 |
Average R values |
800 |
850 |
825 |
1000 |
1100 |
1050 |
1200 |
1280 |
1240 |
1400 |
1450 |
1425 |
1450 |
1520 |
1485 |
1450 |
1550 |
1500 |
1450 |
1550 |
1500 |
1470 |
1570 |
1520 |
1500 |
1600 |
1550 |
1500 |
1600 |
1550 |
Table showing the calculation of standard deviation
Average R values |
Variance |
s.d | ||||
825 |
-539.5 |
291060.3 |
61485.83 |
247.9634 | ||
1050 |
-314.5 |
98910.25 | ||||
1240 |
-124.5 |
15500.25 | ||||
1425 |
60.5 |
3660.25 | ||||
1485 |
120.5 |
14520.25 | ||||
1500 |
135.5 |
18360.25 | ||||
1500 |
135.5 |
18360.25 | ||||
1520 |
155.5 |
24180.25 | ||||
1550 |
185.5 |
34410.25 | ||||
1550 |
185.5 |
34410.25 | ||||
Total |
13645 |
553372.5 | ||||
mean |
1364.5 | |||||
n |
10 |
Table of average temperatures in degree Celsius
T (0C) |
T (0C) |
Average temperature values (0C) |
95.22857 |
93.15835 |
94.19346 |
87.72017 |
84.60535 |
86.16276 |
81.80839 |
79.7597 |
80.78405 |
76.95701 |
75.87117 |
76.41409 |
75.87117 |
74.42466 |
75.14792 |
75.87117 |
73.82624 |
74.84871 |
75.87117 |
73.82624 |
74.84871 |
75.44919 |
73.43654 |
74.44287 |
74.82884 |
72.86273 |
73.84579 |
74.82884 |
72.86273 |
73.84579 |
Table showing the calculation of standard deviation
Average temperature values (0C) |
( |
Variance |
s.d | |||
94.19346 |
15.74005 |
247.749 |
45.80363 |
6.767838 | ||
86.16276 |
7.709345 |
59.434 | ||||
80.78405 |
2.330635 |
5.43186 | ||||
76.41409 |
-2.03932 |
4.158846 | ||||
75.14792 |
-3.30549 |
10.9263 | ||||
74.84871 |
-3.6047 |
12.9939 | ||||
74.84871 |
-3.6047 |
12.9939 | ||||
74.44287 |
-4.01054 |
16.08447 | ||||
73.84579 |
-4.60762 |
21.23021 | ||||
73.84579 |
-4.60762 |
21.23021 | ||||
Total |
784.53415 |
412.2327 | ||||
mean |
78.453415 | |||||
n |
10 |
Graph of average temperature – average resistance against time
The standard deviation of the each set of values should be used as error bars in each data set, and add a trendline as well for each data set. The regression equations and R-squared values for the trendlines should be displayed.
Graph of average temperature – average resistance against time
- Create a table of all of your calculations.
1/T0 |
1/B |
R for Experiment 1 |
R0 |
(R/R0) |
ln(R/R0) |
1/T |
T (K) |
T (0C) | |||||
0.00335402 |
0.00025316 |
800 |
10000 |
0.08 |
-2.5257 |
0.002715 |
368.3786 |
95.22857 | |||||
0.00335402 |
0.00025316 |
1000 |
10000 |
0.1 |
-2.3026 |
0.002771 |
360.8702 |
87.72017 | |||||
0.00335402 |
0.00025316 |
1200 |
10000 |
0.12 |
-2.1203 |
0.002817 |
354.9584 |
81.80839 | |||||
0.00335402 |
0.00025316 |
1400 |
10000 |
0.14 |
-1.9661 |
0.002856 |
350.107 |
76.95701 | |||||
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 | |||||
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 | |||||
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 | |||||
0.00335402 |
0.00025316 |
1470 |
10000 |
0.147 |
-1.9173 |
0.002869 |
348.5992 |
75.44919 | |||||
0.00335402 |
0.00025316 |
1500 |
10000 |
0.15 |
-1.8971 |
0.002874 |
347.9788 |
74.82884 | |||||
0.00335402 |
0.00025316 |
1500 |
10000 |
0.15 |
-1.8971 |
0.002874 |
347.9788 |
74.82884 | |||||
1/T0 |
1/B |
R for Experiment 2 |
R0 |
(R/R0) |
ln(R/R0) |
1/T |
T (K) |
T (0C) | |||||
0.00335402 |
0.00025316 |
850 |
10000 |
0.085 |
-2.4651 |
0.00273 |
366.3084 |
93.15835 | |||||
0.00335402 |
0.00025316 |
1100 |
10000 |
0.11 |
-2.2073 |
0.002795 |
357.7553 |
84.60535 | |||||
0.00335402 |
0.00025316 |
1280 |
10000 |
0.128 |
-2.0557 |
0.002834 |
352.9097 |
79.7597 | |||||
0.00335402 |
0.00025316 |
1450 |
10000 |
0.145 |
-1.931 |
0.002865 |
349.0212 |
75.87117 | |||||
0.00335402 |
0.00025316 |
1520 |
10000 |
0.152 |
-1.8839 |
0.002877 |
347.5747 |
74.42466 | |||||
0.00335402 |
0.00025316 |
1550 |
10000 |
0.155 |
-1.8643 |
0.002882 |
346.9762 |
73.82624 | |||||
0.00335402 |
0.00025316 |
1550 |
10000 |
0.155 |
-1.8643 |
0.002882 |
346.9762 |
73.82624 | |||||
0.00335402 |
0.00025316 |
1570 |
10000 |
0.157 |
-1.8515 |
0.002885 |
346.5865 |
73.43654 | |||||
0.00335402 |
0.00025316 |
1600 |
10000 |
0.16 |
-1.8326 |
0.00289 |
346.0127 |
72.86273 | |||||
0.00335402 |
0.00025316 |
1600 |
10000 |
0.16 |
-1.8326 |
0.00289 |
346.0127 |
72.86273 | |||||
R for Experiment 1 |
R for Experiment 2 |
Average R values |
Average R values |
Variance |
s.d | ||||||||
800 |
850 |
825 |
825 |
-539.5 |
291060.3 |
61485.83 |
247.9634 | ||||||
1000 |
1100 |
1050 |
1050 |
-314.5 |
98910.25 | ||||||||
1200 |
1280 |
1240 |
1240 |
-124.5 |
15500.25 | ||||||||
1400 |
1450 |
1425 |
1425 |
60.5 |
3660.25 | ||||||||
1450 |
1520 |
1485 |
1485 |
120.5 |
14520.25 | ||||||||
1450 |
1550 |
1500 |
1500 |
135.5 |
18360.25 | ||||||||
1450 |
1550 |
1500 |
1500 |
135.5 |
18360.25 | ||||||||
1470 |
1570 |
1520 |
1520 |
155.5 |
24180.25 | ||||||||
1500 |
1600 |
1550 |
1550 |
185.5 |
34410.25 | ||||||||
1500 |
1600 |
1550 |
1550 |
185.5 |
34410.25 | ||||||||
Total |
13645 |
553372.5 | |||||||||||
mean |
1364.5 | ||||||||||||
n |
10 | ||||||||||||
T (0C) |
T (0C) |
Average temperature values (0C) |
|
Average temperature values (0C) |
|
|
Variance |
s.d | |||||
95.22857 |
93.15835 |
94.19346 | |||||||||||
87.72017 |
84.60535 |
86.16276 |
94.19346 |
15.74005 |
247.749 |
45.80363 |
6.767838 | ||||||
81.80839 |
79.7597 |
80.78405 |
86.16276 |
7.709345 |
59.434 | ||||||||
76.95701 |
75.87117 |
76.41409 |
80.78405 |
2.330635 |
5.43186 | ||||||||
75.87117 |
74.42466 |
75.14792 |
76.41409 |
-2.03932 |
4.158846 | ||||||||
75.87117 |
73.82624 |
74.84871 |
75.14792 |
-3.30549 |
10.9263 | ||||||||
75.87117 |
73.82624 |
74.84871 |
74.84871 |
-3.6047 |
12.9939 | ||||||||
75.44919 |
73.43654 |
74.44287 |
74.84871 |
-3.6047 |
12.9939 | ||||||||
74.82884 |
72.86273 |
73.84579 |
74.44287 |
-4.01054 |
16.08447 | ||||||||
74.82884 |
72.86273 |
73.84579 |
73.84579 |
-4.60762 |
21.23021 | ||||||||
73.84579 |
-4.60762 |
21.23021 | |||||||||||
Total |
784.5342 |
412.2327 | |||||||||||
mean |
78.45342 | ||||||||||||
n |
10 |
Water possess energy by the virtue of its flow
The factors that determine the power output depend on
- The velocity V (m/s)
- The cross-section area A
- The overall conversion efficiency (?)
- The principle of converting kinetic energy to mechanical energy and then electrical energy
K.E = ½ *m*v2……………………………………..1
M = mass of water
M = A * ………….2
Where,
A = cross-section area
Combining equation 1 and 2
K.E =
K.E energy per second is equivalent to power
Power in water =
Power developed =
Representation of units
Power unit =
If we divide like terms
But, Energy =
Time = s
Power = Energy / time
Power =
KAPLAN TURBINE
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