Complete the following in MatLAB: A thermocouple held in room-temperature air is suddenly immersed into a beaker of cold water. Its temperature asa function of time is recorded. Determine the thermocouple's time constant by plotting the data listed in Table attached, assuming that the thermocouple behaves as a first-order system. A more accurate method of determining the time constant is by performing a least-squares linear regression analysis after transforming the temperatures into their appropriate non-dimensional variables. Time(ms) Temperature (°C) 0 24.8 40 22.4 120 19.1 200 15.5 240 13.1 400 9.76 520 8.15 800 6.95 970 6.55 1100 6.15 1400 5.75 1800 5.30 2000 5.20 2200 5.00 3000 4.95 4000 4.95 5000 4.95 6000 4.95 7000 4.95
Complete the following in MatLAB: A thermocouple held in room-temperature air is suddenly immersed into a beaker of cold water. Its temperature asa function of time is recorded. Determine the thermocouple's time constant by plotting the data listed in Table attached, assuming that the thermocouple behaves as a first-order system. A more accurate method of determining the time constant is by performing a least-squares linear regression analysis after transforming the temperatures into their appropriate non-dimensional variables. Time(ms) Temperature (°C) 0 24.8 40 22.4 120 19.1 200 15.5 240 13.1 400 9.76 520 8.15 800 6.95 970 6.55 1100 6.15 1400 5.75 1800 5.30 2000 5.20 2200 5.00 3000 4.95 4000 4.95 5000 4.95 6000 4.95 7000 4.95
Elements Of Electromagnetics
7th Edition
ISBN:9780190698614
Author:Sadiku, Matthew N. O.
Publisher:Sadiku, Matthew N. O.
ChapterMA: Math Assessment
Section: Chapter Questions
Problem 1.1MA
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Complete the following in MatLAB: A thermocouple held in room-temperature air is suddenly immersed into a beaker of cold water. Its temperature as
a function of time is recorded.
Determine the thermocouple's time constant by plotting the data listed in Table attached, assuming that the thermocouple behaves as a first-order system.
A more accurate method of determining the time constant is by performing a least-squares linear regression analysis after transforming the temperatures into their appropriate non-dimensional variables.
Time(ms) | Temperature (°C) |
0 | 24.8 |
40 | 22.4 |
120 | 19.1 |
200 | 15.5 |
240 | 13.1 |
400 | 9.76 |
520 | 8.15 |
800 | 6.95 |
970 | 6.55 |
1100 | 6.15 |
1400 | 5.75 |
1800 | 5.30 |
2000 | 5.20 |
2200 | 5.00 |
3000 | 4.95 |
4000 | 4.95 |
5000 | 4.95 |
6000 | 4.95 |
7000 | 4.95 |
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