Lab 6 Pre Lab 1
.pdf
keyboard_arrow_up
School
University Of Connecticut *
*We aren’t endorsed by this school
Course
3263
Subject
Mechanical Engineering
Date
Dec 6, 2023
Type
Pages
2
Uploaded by andreweschang on coursehero.com
ME-3283 Lab Section 012, Station 02
Andrew Chang
11/8/2023
Lab 6, Pre-Lab 1
1.
Using MATLAB or Python, perform a multiple linear regression on the above data to find
thickness as a function of the changes in the first three natural frequencies. (4 points)
Thickness (t) function:
𝑡 = − 7. 93∆ω
1
− 86. 05∆ω
2
+ 29. 25∆ω
3
2.
Collected frequency data for an unknown coating thickness show frequency changes of
∆
𝜔
1=-1.34 kHz,
∆
𝜔
2 = -7.71 kHz, and
∆
𝜔
3 = -21.27 kHz. What is the thickness of the gold
coating? (2 points)
3.
From the lab manual, the material we discussed in class, and your knowledge from previous
labs, develop a hypothesis for what you expect to see in Lab 6. What will be the relationship
between our controlled variables (the location and size of the added mass) and our measured
variables (the beam’s natural frequencies). Make a prediction that we do not know a priori to
be true. (3 points).
Since we know that mass has a direct function relating to the change of natural frequency eg.
, which is derived from Ghatkesar’s findings. From that same
𝑚 = ?∆ω
1
+ ?∆ω
2
+ ?∆ω
3
article we saw that a uniform deposition, otherwise, a uniformly distributed load across the
cantilever beam, showed that increase in mass sensitivity was linear with the square of the
mode number. This implies that the equivalent point load at exactly half of the cantilever’s
length would also have the same relationship. In Lab 6, I expect to see a linear relationship
between mass and change in frequency when regression is applied when the point load is
applied at half the cantilever’s length. I believe that variation from this location specifically may
interfere with the cantilever’s natural frequencies in an unexpected way. I also believe that the
existence of a potential second point load at the end of the beam due to the mounting of the
beam may also have an adverse effect on the results, skewing the data or adding unnecessary
noise. Ghatkesar et al also discussed the effect the medium the beam is vibrating in having an
effect so I expect to see a 0.5% deviation from the theoretical/guessed data. I also believe that
applying a point mass to a node may have very little effect on the resonant frequency due to the
nature of a node being a natural point of little to no oscillation. However I also believe that this
only holds true for masses with small moment of Inertia as we see from Euler-Lagrange Dynamic
beam equation that moment of inertia affects the resonant frequency, so if the moment of
inertia of the applied mass is too large to no longer be negligible, then due to parallel axis
theorem, the effect on the beam will be considerable.
Your preview ends here
Eager to read complete document? Join bartleby learn and gain access to the full version
- Access to all documents
- Unlimited textbook solutions
- 24/7 expert homework help
Related Questions
Please help Matlab, as well needs to be on excel data sheet.
P14.19 You perform experiments and determine the following values of heat capacity cat various temperatures T for a gas:I) For c, determine (a) the mean, (b) median, (c) mode, (d) range, (e) standarddeviation, (f) variance, and (g) coefficient of variation.II) Using linregr given function, fit the data using a straight line (determine a1,a0, r2). Plot the data and the regression curve.III) Using polyfit command, fit the data using a quadratic curve (determine a2, a1, a0).Plot the data and the regression curve.IV) Using linregr given function, fit the data using exponential model (determineα, β, r2). Plot the data and the regression curve in the T-c space (not the T-log(c)space)
T -50 -30 0 60 90 110
C 1250 1280 1350 1480 1580 1700
arrow_forward
A one-fortieth-scale model of a ship’s propeller is tested in a tow tank at 1250 r/min and exhibits a power output of 1.9 ft·lbf/s.
According to Froude scaling laws, what should the revolutions per minute of the prototype propeller be under dynamically similar conditions?
According to Froude scaling laws, what should the horsepower output of the prototype propeller be under dynamically similar conditions?
arrow_forward
The processing of raw coal involves “washing,” in which coal ash (nonorganic, incombustible material) is removed. The article “Quantifying Sampling Precision for Coal Ash Using Gy’s Discrete Model of the Fundamental Error” (Journal of Coal Quality, 1989:33–39) provides data relating the percentage of ash to the volume of a coal particle.
The average percentage of ash for six volumes of coal particles was measured. The data are as follows:
Volume (cm3)
0.01
0.06
0.58
2.24
15.55
276.02
Percent ash
3.32
4.05
5.69
7.06
8.17
9.36
Using the most appropriate model, predict the percent ash for particles with a volume of 48 cm3. Round answer to three decimal places.
* the answer i got was of 6.260 was wrong
arrow_forward
Use dimentional analysis to evaluate that in a problem involving shallow water waves (figure 6), both the Froude number and the Reynold's number are relevant dimensionless parameters. The wave speed, c of waves on the surface of a liquid is a function of depth h, gravitational acceleration g, fluid density, p and fluid viscosity μ. Manipulate your II's to get the parameters into the following form:
Fr = c/(gh)1/2= f(Re) , where Re = pch/μ
arrow_forward
The heat transfer between a solid body and a fluid medium is determined by the equation Q=h·A·(Ts-Tf). Here; Q is the amount of heat transferred, h is the heat transfer coefficient, A is the heat transfer surface area, Ts is the temperature of the surface and Tf is the temperature of the fluid. These parameters were measured as h=250±1.75 W/m2ºC, A=20±0.75 m2, Ts =100±0.75ºC and Tf =25±0.75ºC, including error levels. What is the total uncertainty in the amount of heat transferred, in ±%?
a. 3.98
b. 4.07
c. 2.73
d. 2.95
e. 3.88
arrow_forward
About supervised machine learning, in the context of Linear Regression; Decision tree; Logistics Regresion; Randon forest and neural network, which metrics should be used to know if a classification model is good and why use them? What about regression, what metrics are used to say how good the model is? What is the best for each case?
arrow_forward
4) If two variables are highly correlated, does this imply that changes in one cause changes in the other? If not, give at least one example from the real world-that illustrates what else could cause a high correlation.
arrow_forward
Materials of Interest: CuFeS, in a silica matrix, 1.5% Cu (4.3318% CuFeS,); Top Size = 1.5 cm; CuFeS, grain size = 0.01 cm Desired sampling accuracy: +0.02% Cu, certainty of 0.99 (2.576 standard deviations) CuFeS, specific gravity=4.2: Overall specific gravity 2.8 Broad size distribution. Determine the minimum sample weight (in grams) needed for testing.
arrow_forward
Cardiologists use the short-range scaling exponent α1, which measures the randomness of heart rate patterns, as a tool to assess risk of heart attack. The article “Applying Fractal Analysis to Short Sets of Heart Rate Variability Data” compared values of α1 computed from long series of measurements (approximately 40,000 heartbeats) with those estimated from the first 300 beats to determine how well the long-term measurement (y) could be predicted the short-term one (x). Following are the data (obtained by digitizing a graph).
Short
Long
0.54
0.55
1.02
0.79
1.4
0.81
0.88
0.9
1.68
1.05
1.16
1.05
0.82
1.05
0.93
1.07
1.26
1.1
1.18
1.19
0.81
1.19
0.81
1.2
1.28
1.23
1.18
1.23
0.71
1.24
Note: This problem has a reduced data set for ease of performing the calculations required. This differs from the data set given for this problem in the text.
Compute the least-squares line for predicting the long-term measurement from the short-term measurement.…
arrow_forward
As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.
arrow_forward
A _____system uses measurements
of disturbance variables to position the manipulated variable in such a way as to minimize any resulting deviation. The disturbance variables could be either measured loads or the set point, the former being more common.
arrow_forward
Hello Sir.Good night.Permission, i have a question in my homework related numerical methods lesson. The following bellow is question. Please advice. Thank you so much
Regards,Irfan
Mention the types of problems that exist in the field of engineering, especially mechanical engineering that can be solved by the linear regression method
arrow_forward
The variables do not vary with respect to time is called as ___________________
a.
Dynamic characteristics
b.
Random Error
c.
Systematic Error
d.
Static characteristics
arrow_forward
Forecast sales for the 7th period. For leveling, use exponential smoothing 0.20 and moving average 3 for averaging; and linear and exponential functions for trend data. Assume an initial exponential forecast of 60 units in period 2 if you decide to use it (i.e., no forecast for period 1).
Period
Demand
1
67
2
72
3
68
4
20
5
70
6
66
7
68
arrow_forward
Pierce (1948) mechanically measured the frequency (the number of wing vibrations per second) of chirps (or pulses of sound) made by a striped ground cricket, at various ground temperatures. Since crickets are ectotherms (cold-blooded), the rate of their philosophical processes and their overall metabolism are influenced by temperature. Consequently, there is a reason to believe that temperature would have a profound affect on aspects of their behavior, such as chirp frequency. In general, it was found that crickets did not sing at temperatures colder than 60°F or warmer than 100°F. In the following data let X= chirps/sec for the striped ground cricket and Y= temperature in degrees of Fahrenheit.
X 19 19.8 18.4 17.1 15.5 14.7 17.1 15.4 16.2 15 17.2 16 17 14.4
Y 71.6 93.3 84.3 80.6 75.2 69.7 82 69.4 83.3 79.6 82.6 80.6 83.5 76.3
a. use two decimal places: Y bar =?
b. use two decimal…
arrow_forward
11.8 The functional frequency η of a stretched string is a function of the string length L, its diameter D, the mass density ⍴, and the applied tensile force T. Suggest a set of dimensionless parameters relating these variables.
arrow_forward
1) To ensure complete similarity, the model and prototype must be
a)
same material
b)
similar geometric and all independent groups are match
c)
same geometric
d)
in same fluid
2) Temperature is a dimension, kelvin is a unit. True or False
arrow_forward
Multiple choice questions. Choose correct answer
1. Sampling is used because
A) it increases the data quality B) the processing of entire data can be time-consuming C) it reduces dimensionality D) it helps find missing data
Answer:
2) Correlation coefficient is always in the range
A) 0 to 1 B) -1 to 1 C) 0 to 100 D) 1 to 2
Answer:
True or False. Choose correct answer
3. Regression analysis is used to predict a value of a continuous valued variable.
Answer:
arrow_forward
The following table presents the highway gasoline mileage performance and engine displacement for Audi vehicles for model year 2005.
a) (5 Pts.) Fit simple linear model. Test for significance of the regression using alpha=0.05. Find the p-value for this test. What conclusions you can reach? b) (5 Pts.) Test Ho: P₁= -0.05 versus H₁: ₁
arrow_forward
A dam spillway is to be tested using Froude scaling with a 1:20 model. The model flow has an average velocity of 0.7 m/s. What is the velocity of prototype?
arrow_forward
Q=What is the importance of regression analysis in transportation engineering?
ANSWER in word fomat
arrow_forward
For the calibration data of given below, (a) determine the static sensitivity of the system, (b) find the maximum nonlinearity, (c) find the value of the threshold. X (cm) 0.5 1.0 (cm) 0.4 1.0 5.0 10 15 20 25 30 35 40 45 50 6.9 15.8 24.7 36.4 49.9 60.3 75.1 87.0 98.9 110.1
arrow_forward
The fuel gage for a gasoline tank in a car reads proportional to its bottom gage. The tank is 35 cm deep and accidentally contaminated with 3 cm of water. Specific gravity of gasoline is 0.68. If the tank has a uniform horizontal cross-sectional area of 0.45 m2, how many liters of gasoline are required to fill the tank?
Select the correct response:
9.53 L
7.41 L
6.35L
8.47L
The fuel gage for a gasoline tank in a car reads proportional to its bottom gage. The tank is 35 cm deep and accidentally contaminated with 3 cm of water. Specific gravity of gasoline is 0.68. What is the gage reading when the tank is filled with gasoline?
Select the correct response
2.87 kPa
2.11 kPa
2.56 kPa
2.34 kPa
arrow_forward
In the field of air pollution control, one often needs to sample the quality of a moving airstream. In such measurements a sampling probe is aligned with the flow as sketched in Fig. A suction pump draws air through the probe at volume flow rate V· as sketched. For accurate sampling, the air speed through the probe should be the same as that of the airstream (isokinetic sampling). However, if the applied suction is too large, as sketched in Fig, the air speed through the probe is greater than that of the airstream (super iso kinetic sampling). For simplicity consider a two-dimensional case in which the sampling probe height is h = 4.58 mm and its width is W = 39.5 mm. The values of the stream function corresponding to the lower and upper dividing streamlines are ?l = 0.093 m2/s and ?u = 0.150 m2/s, respectively. Calculate the volume flow rate through the probe (in units of m3/s) and the average speed of the air sucked through the probe.
arrow_forward
SEE MORE QUESTIONS
Recommended textbooks for you
Elements Of Electromagnetics
Mechanical Engineering
ISBN:9780190698614
Author:Sadiku, Matthew N. O.
Publisher:Oxford University Press
Mechanics of Materials (10th Edition)
Mechanical Engineering
ISBN:9780134319650
Author:Russell C. Hibbeler
Publisher:PEARSON
Thermodynamics: An Engineering Approach
Mechanical Engineering
ISBN:9781259822674
Author:Yunus A. Cengel Dr., Michael A. Boles
Publisher:McGraw-Hill Education
Control Systems Engineering
Mechanical Engineering
ISBN:9781118170519
Author:Norman S. Nise
Publisher:WILEY
Mechanics of Materials (MindTap Course List)
Mechanical Engineering
ISBN:9781337093347
Author:Barry J. Goodno, James M. Gere
Publisher:Cengage Learning
Engineering Mechanics: Statics
Mechanical Engineering
ISBN:9781118807330
Author:James L. Meriam, L. G. Kraige, J. N. Bolton
Publisher:WILEY
Related Questions
- Please help Matlab, as well needs to be on excel data sheet. P14.19 You perform experiments and determine the following values of heat capacity cat various temperatures T for a gas:I) For c, determine (a) the mean, (b) median, (c) mode, (d) range, (e) standarddeviation, (f) variance, and (g) coefficient of variation.II) Using linregr given function, fit the data using a straight line (determine a1,a0, r2). Plot the data and the regression curve.III) Using polyfit command, fit the data using a quadratic curve (determine a2, a1, a0).Plot the data and the regression curve.IV) Using linregr given function, fit the data using exponential model (determineα, β, r2). Plot the data and the regression curve in the T-c space (not the T-log(c)space) T -50 -30 0 60 90 110 C 1250 1280 1350 1480 1580 1700arrow_forwardA one-fortieth-scale model of a ship’s propeller is tested in a tow tank at 1250 r/min and exhibits a power output of 1.9 ft·lbf/s. According to Froude scaling laws, what should the revolutions per minute of the prototype propeller be under dynamically similar conditions? According to Froude scaling laws, what should the horsepower output of the prototype propeller be under dynamically similar conditions?arrow_forwardThe processing of raw coal involves “washing,” in which coal ash (nonorganic, incombustible material) is removed. The article “Quantifying Sampling Precision for Coal Ash Using Gy’s Discrete Model of the Fundamental Error” (Journal of Coal Quality, 1989:33–39) provides data relating the percentage of ash to the volume of a coal particle. The average percentage of ash for six volumes of coal particles was measured. The data are as follows: Volume (cm3) 0.01 0.06 0.58 2.24 15.55 276.02 Percent ash 3.32 4.05 5.69 7.06 8.17 9.36 Using the most appropriate model, predict the percent ash for particles with a volume of 48 cm3. Round answer to three decimal places. * the answer i got was of 6.260 was wrongarrow_forward
- Use dimentional analysis to evaluate that in a problem involving shallow water waves (figure 6), both the Froude number and the Reynold's number are relevant dimensionless parameters. The wave speed, c of waves on the surface of a liquid is a function of depth h, gravitational acceleration g, fluid density, p and fluid viscosity μ. Manipulate your II's to get the parameters into the following form: Fr = c/(gh)1/2= f(Re) , where Re = pch/μarrow_forwardThe heat transfer between a solid body and a fluid medium is determined by the equation Q=h·A·(Ts-Tf). Here; Q is the amount of heat transferred, h is the heat transfer coefficient, A is the heat transfer surface area, Ts is the temperature of the surface and Tf is the temperature of the fluid. These parameters were measured as h=250±1.75 W/m2ºC, A=20±0.75 m2, Ts =100±0.75ºC and Tf =25±0.75ºC, including error levels. What is the total uncertainty in the amount of heat transferred, in ±%? a. 3.98 b. 4.07 c. 2.73 d. 2.95 e. 3.88arrow_forwardAbout supervised machine learning, in the context of Linear Regression; Decision tree; Logistics Regresion; Randon forest and neural network, which metrics should be used to know if a classification model is good and why use them? What about regression, what metrics are used to say how good the model is? What is the best for each case?arrow_forward
- 4) If two variables are highly correlated, does this imply that changes in one cause changes in the other? If not, give at least one example from the real world-that illustrates what else could cause a high correlation.arrow_forwardMaterials of Interest: CuFeS, in a silica matrix, 1.5% Cu (4.3318% CuFeS,); Top Size = 1.5 cm; CuFeS, grain size = 0.01 cm Desired sampling accuracy: +0.02% Cu, certainty of 0.99 (2.576 standard deviations) CuFeS, specific gravity=4.2: Overall specific gravity 2.8 Broad size distribution. Determine the minimum sample weight (in grams) needed for testing.arrow_forwardCardiologists use the short-range scaling exponent α1, which measures the randomness of heart rate patterns, as a tool to assess risk of heart attack. The article “Applying Fractal Analysis to Short Sets of Heart Rate Variability Data” compared values of α1 computed from long series of measurements (approximately 40,000 heartbeats) with those estimated from the first 300 beats to determine how well the long-term measurement (y) could be predicted the short-term one (x). Following are the data (obtained by digitizing a graph). Short Long 0.54 0.55 1.02 0.79 1.4 0.81 0.88 0.9 1.68 1.05 1.16 1.05 0.82 1.05 0.93 1.07 1.26 1.1 1.18 1.19 0.81 1.19 0.81 1.2 1.28 1.23 1.18 1.23 0.71 1.24 Note: This problem has a reduced data set for ease of performing the calculations required. This differs from the data set given for this problem in the text. Compute the least-squares line for predicting the long-term measurement from the short-term measurement.…arrow_forward
- As an industrial engineer, you intend to use linear trend (or linear regression) method to solve a forecasting problem. You have decided to use the equation of y = m(x) + c to establish the relationship between the sales (y) and the related month (x). It is known that 8 consecutive months data (Jan to Aug) were used and they resulted to the following parameter values of m = 320 and c = 1017. Using the regression technique, estimate the percentage of sales improvement from December this year to June next year.arrow_forwardA _____system uses measurements of disturbance variables to position the manipulated variable in such a way as to minimize any resulting deviation. The disturbance variables could be either measured loads or the set point, the former being more common.arrow_forwardHello Sir.Good night.Permission, i have a question in my homework related numerical methods lesson. The following bellow is question. Please advice. Thank you so much Regards,Irfan Mention the types of problems that exist in the field of engineering, especially mechanical engineering that can be solved by the linear regression methodarrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Elements Of ElectromagneticsMechanical EngineeringISBN:9780190698614Author:Sadiku, Matthew N. O.Publisher:Oxford University PressMechanics of Materials (10th Edition)Mechanical EngineeringISBN:9780134319650Author:Russell C. HibbelerPublisher:PEARSONThermodynamics: An Engineering ApproachMechanical EngineeringISBN:9781259822674Author:Yunus A. Cengel Dr., Michael A. BolesPublisher:McGraw-Hill Education
- Control Systems EngineeringMechanical EngineeringISBN:9781118170519Author:Norman S. NisePublisher:WILEYMechanics of Materials (MindTap Course List)Mechanical EngineeringISBN:9781337093347Author:Barry J. Goodno, James M. GerePublisher:Cengage LearningEngineering Mechanics: StaticsMechanical EngineeringISBN:9781118807330Author:James L. Meriam, L. G. Kraige, J. N. BoltonPublisher:WILEY
Elements Of Electromagnetics
Mechanical Engineering
ISBN:9780190698614
Author:Sadiku, Matthew N. O.
Publisher:Oxford University Press
Mechanics of Materials (10th Edition)
Mechanical Engineering
ISBN:9780134319650
Author:Russell C. Hibbeler
Publisher:PEARSON
Thermodynamics: An Engineering Approach
Mechanical Engineering
ISBN:9781259822674
Author:Yunus A. Cengel Dr., Michael A. Boles
Publisher:McGraw-Hill Education
Control Systems Engineering
Mechanical Engineering
ISBN:9781118170519
Author:Norman S. Nise
Publisher:WILEY
Mechanics of Materials (MindTap Course List)
Mechanical Engineering
ISBN:9781337093347
Author:Barry J. Goodno, James M. Gere
Publisher:Cengage Learning
Engineering Mechanics: Statics
Mechanical Engineering
ISBN:9781118807330
Author:James L. Meriam, L. G. Kraige, J. N. Bolton
Publisher:WILEY