Numerical on temperature rise time relationAsif Jamadar
This video contains the numerical on temperature rise time relation under heating cooling and ventilation of electrical machines to better understanding of concepts.
Learning Objective: Use the Arrhenius equation and linear regression analysis to calculate the frequency factor and activation energy from temperatures and reaction rate constants. This exercise will develope your habits and skills to analyse temperature and rate data using linear regression.
Climate change model forecast global temperature out to 2100Gaetan Lion
This study is leveraging a VAR model introduced in an earlier presentation to forecast global temperature out to 2100, and assess how likely are we to keep such temperatures at or under the + 1.5 degree Celsius threshold.
Numerical on temperature rise time relationAsif Jamadar
This video contains the numerical on temperature rise time relation under heating cooling and ventilation of electrical machines to better understanding of concepts.
Learning Objective: Use the Arrhenius equation and linear regression analysis to calculate the frequency factor and activation energy from temperatures and reaction rate constants. This exercise will develope your habits and skills to analyse temperature and rate data using linear regression.
Climate change model forecast global temperature out to 2100Gaetan Lion
This study is leveraging a VAR model introduced in an earlier presentation to forecast global temperature out to 2100, and assess how likely are we to keep such temperatures at or under the + 1.5 degree Celsius threshold.
FORTRAN is used as a numerical and scientific computing language. The main objective of the lab work is to understand FORTRAN language using which we solve simple numerical problems and compare different methodologies. Through this project we make use of various functions of FORTRAN and solve a FDM simple heat equation problem applying different conditions viz. Dirichlet and Von Neumann. The given problems are solved analytically then built and compiled using a free integrated development environment called CODE::BLOCKS [1] which is an open source platform for FORTRAN and C.
The results of an experiment can be presented as a data table or as an equation that represents them. In the case of adjusting a polynomial, Excel allows us to change its degree and calculates the R2 of the adjusted equation. It is considered that if it is 1 the equation goes through all the experimental points. By adjusting Tungsten resistivity data, it is found that the equations do not go through all the points (even with R2 = 1), which is verified by calculating the differences for each point. In those cases, the best fit is the linear interpolation between consecutive points. The equation adjusted by Excel, Matlab or Origin requires checking if it corresponds to the minimum in the sum of squared differences, it is possible that it can be reduced by changing the coefficients values.
The results of an experiment can be presented as a data table or as an equation that represents them. In the case of adjusting a polynomial, Excel allows us to change its degree and calculates the R2 of the adjusted equation. It is considered that if it is 1 the equation goes through all the experimental points. By adjusting Tungsten resistivity data, it is found that the equations do not go through all the points (even with R2 = 1), which is verified by calculating the differences for each point. In those cases, the best fit is the linear interpolation between consecutive points. The equation adjusted by Excel, Matlab or Origin requires checking if it corresponds to the minimum in the sum of squared differences, it is possible that it can be reduced by changing the coefficients values.
The results of an experiment can be presented as a data table or as an equation that represents them.
In the case of adjusting a polynomial, Excel allows us to change its degree and calculates the R2 of the
adjusted equation. It is considered that if it is 1 the equation goes through all the experimental points.
By adjusting Tungsten resistivity data, it is found that the equations do not go through all the points
(even with R2 = 1), which is verified by calculating the differences for each point. In those cases, the
best fit is the linear interpolation between consecutive points. The equation adjusted by Excel, Matlab
or Origin requires checking if it corresponds to the minimum in the sum of squared differences, it is
possible that it can be reduced by changing the coefficients values.
LabQuest 7 Chemistry with Vernier 7 - 1 Pressure.docxMARRY7
LabQuest
7
Chemistry with Vernier 7 - 1
Pressure - Temperature
Relationship in Gases
Gases are made up of molecules that are in constant motion and exert pressure when they collide
with the walls of their container. The velocity and the number of collisions of these molecules are
affected when the temperature of the gas increases or decreases. In this experiment, you will
study the relationship between the temperature of a gas sample and the pressure it exerts. Using
the apparatus shown in Figure 1, you will place an Erlenmeyer flask containing an air sample in
four water baths of varying temperature. Pressure will be monitored with a Pressure Sensor and
temperature will be monitored using a Temperature Probe. The volume of the gas sample and the
number of molecules it contains will be kept constant. Pressure and temperature data pairs will
be collected during the experiment and then analyzed. From the data and graph, you will
determine what kind of mathematical relationship exists between the pressure and absolute
temperature of a confined gas. You may also do the extension exercise and use your data to find a
value for absolute zero on the Celsius temperature scale.
OBJECTIVES
In this experiment, you will
Study the relationship between the temperature of a gas sample and the pressure it exerts.
Determine from the data and graph, the mathematical relationship between pressure and
absolute temperature of a confined gas.
Find a value for absolute zero on the Celsius temperature scale.
Figure 1
MATERIALS
LabQuest plastic tubing with two connectors
LabQuest App 125 mL Erlenmeyer flask
Vernier Gas Pressure Sensor rubber stopper assembly
Temperature Probe ring stand and utility clamp
ice two 600 mL beakers
hot plate glove or cloth
beaker tongs
LabQuest 7
7 - 2 Chemistry with Vernier
PROCEDURE
1. Obtain and wear goggles.
2. Prepare a hot-water bath. Put about 400 mL of hot tap water into a 600 mL beaker and place
it on a hot plate. Turn the hot plate to a high setting. NOTE: Submerge Erlenmeyer flask to
neck to ensure that the water does not overflow. See Figure 3.
3. Prepare an ice-water bath. Fill a second 600 mL beaker with ice, ~ 1/3 full. Add cold tap
water to fill to the 400 mL mark.
4. Prepare the Temperature Probe and Gas Pressure Sensor for data collection.
a. Connect the Gas Pressure Sensor to Channel 1 of LabQuest and the
Temperature Probe to Channel 2. Choose New from the File menu.
If you have older sensors that do not auto-ID, manually set up the
sensors.
b. Obtain a rubber-stopper assembly with a piece of heavy-wall plastic
tubing connected to one of its two valves. Attach the connector at
the free end of the plastic tubing to the open stem of the Gas
Pressure Sensor with a clockwise turn. Leave its two-way valve on
the rubber stopper open (lined up with the valve stem as shown in Figure 2) until Step 4d.
c. Insert the rubber-stopper assembly ...
6th International Conference on Machine Learning & Applications (CMLA 2024)ClaraZara1
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Understanding Inductive Bias in Machine LearningSUTEJAS
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The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
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ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
1. ME 416 MECHANICAL ENGINERING LABORATORY
DEPARTMENT OF MECHANICAL
ENGINEERING
UNIVERSITY OF GAZIANTEP
TEMPERATURE MEASUREMENT
Submitted to: Res. Assist. İBRAHİM HALİL YILMAZ
Submitted by: (GROUP 7)
HALİL İBRAHİM GÜLMEZ
MESUT GÜNGÖR
FIRAT GÜNYEL
YAŞAR GÜRBÜZ
HACER İLHAN
EMRE KARACA
ERDİ KARAÇAL
DECEMBER 2013
2. INTRODUCTION
Temperature measurement experiment was done for the junior engineers to show that
how is temperature measured in the real life?This experiment zoom us to real life.
Important point is when measuring temperatures, which device is preferable and which
one has better measurements.This is the another point of which must be considered when
doing experiment.
Another important point is in our educational life we have seen lots of parameter on
the Formula sheets and at the books.But when we are doing something at the laboratory This
will be not forgotten during our life.
Our calculations were done by using Excel program and coefficient of determination
square of r was found by used directly from Excel program.We have also know how we can
find the square of r but the using of Excel easier way to find.
There are lots of devices which measures the temperatures.At this experiment we have
measured the temperature by using thermocouple.We have also used the liquid in glass
temperature.There are lots of thermocouple and it has a standarts.We have used T type copper
constantan.
Before the experiment we have predict that there will be lots of error.When we look at
the assembly of experiment it is not hard to predict that…The junctions of the cables are not
suitable.We didnot take care of when we did the experiment.
3. Firstly we draw the voltage/temperature curve on the Excel program to find the thermocouple
constant K.
Figure 1 Thermocouple Constant
K=25,76
If we apply this Formula we can understand our curve is perfectly work.
Formula is -> T=K*V
So the thermocouple constant is 25,76 found at Figure 1.
y = 25,76x
0
10
20
30
40
50
60
70
80
90
0 1 2 3 4
TEMPERATURE
VOLT
Volt / Temperature
Volt / Temperature
Doğrusal (Volt /
Temperature)
4. Secondly We seek to fit a straight line of the for Y=Ax+B through the datas.
We would like to obtain values of the constans ‘’a’’ and ‘’b’’.If we have only two
pairs of data,the solution is simple since the points completely determine straight line.Linear
approximation of the datas.So we should use ‘’the least-square linear fit’’ method for best
fit.Calculations are at table 1.
xi xi*xi yi xi*yi yi*yi
0 0 0 0 0
0,9 0,81 25 22,5 625
1,2 1,44 33 39,6 1089
1,5 2,25 42 63 1764
1,8 3,24 47 84,6 2209
2,1 4,41 55 115,5 3025
2,4 5,76 62 148,8 3844
2,7 7,29 70 189 4900
3 9 76 228 5776
3,3 10,89 82 270,6 6724
total xi total xi*xi total yi total xi*yi
total
yi*yi
18,9 45,09 492 1161,6 29956
Table : 1
= 24,733 + 2,455
24,733
)(
))((
22
ii
iiii
xxn
yxyxn
a
.2,455
)(
))(())((
22
2
ii
iiiii
xxn
xyxxy
b
5. We have found that = 24,733 + 2,455 and If we put our datas in the Formula,There
will be some mistakes.As we learned that from our course, There is a value that shows how our
equation fit the datas.Correlation coefficient is the exactly name of this value.We can find this value
from the formulation which is given in the course book but it is simple way that Excel program can
give this value easily.
Figure 2 :Graph of Least square method
At figure 2 there is a value of = 0,996 .This value should be as closest to unity ‘’1’’
This shows that our experimental datas and theoretical datas did not match.There is some mistake on
the formulation of least square method.We can find unceartainy for the y=ax+b equation.At course
book from equation (6.71a)
∗
= (ax + )+ , ∗ / , セ√( + 1)/ + ( ∗
−
_
) / − ∗
But we dont have to find this uncertainty because there is another error which comes from the given
experimental data sheet.Thermocouple calibration datas are not match with the experimental datas.
This situation makes another errors.The measured values are not correct with respect to calibration
datas.
y = 24,73x + 2,455
R² = 0,996
0
10
20
30
40
50
60
70
80
90
0 1 2 3 4
TEMPERATURE
VOLT
Volt / Temperature
Volt / Temperature
Doğrusal (Volt /
Temperature)
6. As we said that there are some errors due to making a least square methods.After this point we
will calculate the errors which come from least square methods.
The Formula was found as
= 24,733 + 2,455
at this Formula x refers to Volt
y refers to temperature.
The temperature values have been written to this Formula and we find the voltage value from the
Formula.This is our x values.
Experimental Values From Formulation
ERROR
%
Volt Temperature Volt
0,9 25 0,912 1,28
1,2 33 1,235 2,84
1,5 42 1,599 6,20
1,8 47 1,801 0,07
2,1 55 2,125 1,16
2,4 62 2,408 0,32
2,7 70 2,731 1,15
3 76 2,974 -0,88
3,3 82 3,217 -2,59
Table 2: Error from formulation
As it seen at table 2 we have datas from experiment and we have some error from the
formulation of this datas.
7. Finally we compare the experimental datas and calibration table.As it seen that in the table 3
errors are seen in each measured values.We can say that our thermocouple primarly measure the
values incorrectly.We dont have the actual values of each measurement.We mean that we dont have
the correct value and after this point we have done some mistake.
Measured Values
From Table for T type
Thermocouple
ERROR
%
Temperature Volt Temperature Volt
25 0,9 25 0,992 9,27
33 1,2 33 1,320 9,09
42 1,5 42 1,696 11,56
47 1,8 47 1,908 5,66
55 2,1 55 2,251 6,71
62 2,4 62 2,556 6,10
70 2,7 70 2,909 7,18
76 3 76 3,177 5,57
82 3,3 82 3,448 4,29
Table 3:Comparing the datas
8. CONCLUSION
As we said that at the introduction part of this experiment.We predicted that there will be lots
of error through out the experiment.Junctions of the cables were not suitable to measure the correct
voltage.
And another important point is when we were doing the experiment we have seen that liquid
in glass temperature of mercury temperature has good accuracy and it protects its calibration thought
years.
Also thermocouple has some errors We think it has lost its calibration.
We took 10 measurements by increments of 0,3 volt.We found the thermocouple constant and
after that point we calculate the linear equations coefficients ‘’a’’ and ‘’b’’.The formulation was
written and some errors were predicted when doing the linear equations.This errors were compared
with the experimental values.
Also there were another errors which were seen.For this point we compared our experimental
values with the calibration curves of thermocouples.
Finally we can say that when doing some experiment There will be lots of parameter which
the experimenter take care.’’Errors begets error.’’ ın turkish mean ‘’hata hatayı doğurur.’’