Lab 05 Force and Motion Part I
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Lab 05: Force and Motion Part I
I.
Develop an experimental mathematical model to describe the behavior of a system
a.
Brainstorm
Mass of the system, hanging mass, force of gravity, air resistance
b.
Select an IV to test
Experimental Design Template
Research Question:
How does the acceleration of a system change when hanging mass changes?
Dependent variable (DV):
Acceleration of a system
Independent variable (IV):
Hanging mass
Control variables (CV):
Mass of the system: 0.3044kg, length of the string: 1.04m, starting point: 0.85m
Testable Hypothesis:
There is a positive correlation between the hanging mass and the acceleration of a system.
Prediction:
c.
Complete the experimental design.
x-axis
y-axis
Air track
Glider system
Hanging mass hook
Weights
Meter stick
Scale
We will be doing 8 trials and will use values of 0.0094kg, 0.0144kg, 0.0194kg, 0.0244kg
d.
Conduct the experiment.
The uncertainty of the measured values for acceleration is ±0.001m/s2 due to the rotary motion sensor’s estimated scale uncertainty, given in this lab.
The uncertainty of the measured values for the length of the string and position of the system is ±0.0005m due to the meter stick’s estimated uncertainty, given in a previous lab.
The uncertainty of the masses is ±0.001kg due to the scale’s estimated uncertainty, given in a previous lab.
Hanging mass
(kg)
Trial 1
(m/s
2
)
Trial 2
(m/s
2
)
Trial 3
(m/s
2
)
Average
(m/s
2
)
0.0094
0.288 ± 5.2*10
-4
0.289 ± 2.8*10
-4
0.290 ± 2.2*10
-4
0.289
0.0114
0.349 ± 3.0*10
-4
0.346 ± 6.2*10
-4
0.349 ± 5.1*10
-4
0.348
0.0134
0.407 ± 3.4*10
-4
0.407 ± 4.2*10
-4
0.404 ± 1.1*10
-3
0.406
0.0154
0.467 ± 5.0*10
-4
0.467 ± 5.3*10
-4
0.466 ± 4.9*10
-4
0.467
0.0174
0.525 ± 2.8*10
-4
0.526 ± 6*10
-4
0.524 ± 6.4*10
-4
0.525
0.0194
0.575 ± 7.1*10
-4
0.574 ± 5.7*10
-4
0.575 ± 5.5*10
-4
0.575
0.0214
0.630 ± 5.3*10
-4
0.630 ± 6.5*10
-4
0.630 ± 6.9*10
-4
0.630
0.0234
0.683 ± 6.8*10
-4
0.684 ± 9.4*10
-4
0.677 ± 2.8*10
-3
0.681
e.
Enter collected data into Excel
f.
Consider the mathematical model provided by Excel
a
=
2.8663
F
+
0.0295
2.8663 (1/kg) and 0.0295 (m/s
2
)
A causal relationship exists between the acceleration (a) and the gravitational force (F) if the mass of the system, length of the string, starting point is held constant, indicating a positive linear function.
II.
Developing a second experimental mathematical model to describe the behavior of the system.
a.
Select a second IV.
Mass of the system
b.
Repeat all steps in Part I.
Experimental Design Template
Research Question:
How does the acceleration of a system change when the mass of the system changes?
Dependent variable (DV):
Acceleration of a system
Independent variable (IV):
Mass of the system
Control variables (CV):
Hanging mass: 0.0234kg, length of the string: 1.04m, starting point: 0.85m
Testable Hypothesis:
There is a negative correlation between the mass of the system and the acceleration of a system.
Prediction:
c.
Complete the experimental design.
8 trials, values of 0.3044kg, 0.3544kg, 0.4044kg, 0.4544kg, 0.5044kg, 0.5544kg, 0.6044kg, 0.6544kg
d.
Conduct the experiment.
The uncertainty of the measured values for acceleration is ±0.001m/s2 due to the rotary motion sensor’s estimated scale uncertainty, given in this lab.
The uncertainty of the measured values for the length of the string and position of the system is ±0.0005m due to the meter stick’s estimated uncertainty, given in a previous lab.
x-axis
y-axis
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The uncertainty of the masses is ±0.001kg due to the scale’s estimated uncertainty, given in a previous lab.
System mass
(kg)
Trial 1
(m/s
2
)
Trial 2
(m/s
2
)
Trial 3
(m/s
2
)
Average
(m/s
2
)
0.3044
0.687 ± 4.8*10
-4
0.688 ± 5.6*10
-4
0.687 ± 1.3*10
-4
0.687
0.3544
0.596 ± 9.5*10
-4
0.595 ± 1.0*10
-4
0.597 ± 3.4*10
-4
0.595
0.4044
0.528 ± 6.7*10
-4
0.528 ± 5.2*10
-4
0.528 ± 5.6*10
-4
0.528
0.4544
0.473 ± 4.4*10
-4
0.472 ± 4.8*10
-4
0.471 ± 8.1*10
-4
0.472
0.5044
0.428 ± 4.6*10
-4
0.429 ± 4.1*10
-4
0.428 ± 4.7*10
-4
0.428
0.5544
0.391 ± 4.1*10
-4
0.392 ± 2.2*10
-4
0.392 ± 5.8*10
-4
0.392
0.6044
0.361 ± 4.0*10
-4
0.362 ± 4.0*10
-4
0.361 ± 3.3*10
-4
0.361
0.6544
0.335 ± 2.5*10
-4
0.335 ± 3.9*10
-4
0.335 ± 3.1*10
-4
0.335
e.
Enter collected data into Excel
f.
Consider the mathematical model provided by Excel
a
=
0.2252
m
−
0.938
0.2252 (N) and -0.938
A causal relationship exists between the acceleration (a) and the system mass (F) if the hanging mass, length of the string, starting point is held constant, indicating a negative power function.
III.
Connecting Experimental Model to Established Scientific Model
a.
Define established scientific model for the acceleration of a system.
a
∝
F
net
, hanging mass vs. acceleration of a system
a
∝
1
m
, mass of a system vs. acceleration of a system
b.
Compare your experimental model with the established scientific model.
a
=
2.8663
F
+
0.0295
, hanging mass vs acceleration of system
a
=
0.2252
m
0.938
, mass of system vs acceleration of system
The relationships represented in our mathematical models and the scientific equation are very similar to the established models for the acceleration of a system in relation to the hanging mass, as the hanging mass and the acceleration of a system are proportional, while the mass of the system is inversely proportional to the acceleration of the system. The only difference in the models is that the mass value in the equation for the mass of a system vs. acceleration of a system has an exponential value of 0.938, which may be partially attributed to the uncertainty values of the data.
c.
Create an Experimental Outcomes Organizer
IV.
Final Wrap-Up Questions
a.
Summarize the group’s findings into a general conclusion.
The results of the experiment for hanging mass vs. the acceleration of a system indicated a positive linear relationship when the mass of the system, string length, and starting point held constant. We conducted 3 trials for each of 8 masses, taking the average acceleration of each mass and using that result in the
graph. The R^2 value of the trend line for this data was 0.999, indicating a very Hanging mass (IV 1)
Mass of the system (IV 2)
Acceleration of system (DV)
Experimental Relationship: a=2.8663F+0.0295 found when the length of the string, starting point, and mass of the system held constant
Experimental Relationship: a=0.2252/(m^(0.938)) found when the length of the string, starting point, and hanging mass held constant
Established relationship: a
∝
Fnet
Mechanism explained: There is no mechanism to describe here
Mechanism explained: There is no mechanism to describe here
Established relationship: a1/m
∝
strong fit. The results for the experiment for the mass of a system vs. the acceleration of a system indicated a negative power relationship when the hanging mass, string length, and starting point held constant. We conducted 3 trials for each of 8 masses, taking the average acceleration of each mass and using that result in the graph. The R^2 value of the trend line for this data was 1, indicating a perfect fit. Therefore, we found that the hanging mass is directly proportional to the acceleration of a system and the mass of a system is inversely proportional to the acceleration of a system.
b.
Evaluate the evidence and resulting experimental model using the questions below as a guide.
Should the measurements collected when testing each IV be trusted? Would you expect similar numbers and/or a similar pattern if the experiment were repeated? Provide justification. Consider the ranges of measurement uncertainty and how closely the plotted points follow a pattern or trend
1.
Yes, the measurements collected when testing each IV should be trusted, and we would expect similar numbers and/or a similar pattern if the experiment were repeated, as the uncertainty values of all measurements were significantly small, the equations
for both IVs match the established equations well, and the range of values for each independent variable tested was large, as we did 8 different values with 3 trials for each, then took the average for each value for the graphs.
Should the equation determined using Excel be trusted for making accurate predictions for the acceleration of a system for masses and applied forces different from those tested in lab? Provide justification. Possibly include fit of the trendline, R^2 value, range of IV values tested and plotted on graph, and how well the experimental equation matches the established equation.
1.
Yes, the equation determined using Excel should be trusted for making accurate predictions for the acceleration of a system for masses and applied forces different from those tested in lab, as the trendline fits the data very well, the graphs have an R^2 value of 1 and 0.999, we did three trials for 8 values each for the hanging mass and the mass of the system, and the experimental equation matches the established equation well for both independent variables.
c.
Identify limitations by stating conditions for which claims hold.
Include the CV values, range of values used for IV. For each IV, state conditions for which the resulting claim holds
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1.
The limitations for these experiments are that the mass of the system, length of the string, and starting position must remain constant when testing the hanging mass in relation to the acceleration of a system, and the hanging mass, length of the string, and starting position must remain constant when testing the mass of the system in relation to the acceleration. Also, the range of values for the mass of the system must not be too large, as the system will not move if the mass exceeds a certain amount.
d.
Consider a hypothetical scenario
e.
A physics student claims that Newton's second law (
= ) can be used to 𝐹
𝑚𝑎
predict the net force necessary to obtain a desired acceleration. What relationship, correlational or causal, exists between net force and acceleration if mass is constant? Explain
If the mass is constant, there is a causal relationship between the net force and acceleration if the mass is constant because as the acceleration increases, so too does the net force, and the acceleration is the only factor that is changing/would affect the net force. A change in acceleration would have a direct impact on the net force.
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%3D
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0.3
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- please show work answer is Darrow_forwardProblem 1 (15 points) (Core Course Outcome 5)/MatlabGrader Write a function mySecond Derivative Order 3 that calculates the second derivative d²y/dx² of a data set (x, y) with at least third order accuracy at each data point. The data is equidistant in x with spacing h. The function input shall be ⚫y: one-dimensional column vector of y values ⚫h: scalar value of spacing h The function output shall be • d2y: column vector of the same size as y containing d²y/dx² Calculate d²y/dx² using only the following formulas that use the nomenclature of Table 8-1 and the lecture notes, but are different from the formulas listed there: f" (xi) 164f(xi) — 465f(xi+1) + 460ƒ (xi+2) − 170ƒ (xi+3) + 11f (xi+5) + O(h³) = 60h2 56f(xi−1) − 105f(xi) +40f(xi+1) + 10f(xi+2) − f(x+4) + O(h³) 60h² −5f(xi−2) +80f(xi−1) − 150f(xi) + 80f(xi+1) − 5ƒ(xi+2) (1) f"(xi) = (2) f"(xi) = +0(h) (3) 60h2 f"(xi) -2f(x-4)+5f(xi-3)+50f(xi-1) — 110f(xi) +57f(xi+1) = +0(h³) (4) 60h² f"(xi) = 57f(x-5) 230f(xi-4) + 290 f (xi-3)-235…arrow_forwardThe governing equation of motion for a base motion system is given by (assume the units are Newton) mä(t)+ci(t)+kx(t) =cY@, cos(@,t) +kY sin(@t) %3D Given that m = 180 kg, c = 30 kg/s, Y = 0.02 m, and о, — 3.5 rad/s %3| 1. Use Excel or Matlab to find the largest value of the stiffness, k that makes the transmissibility ratio less than 0.85 2. Using the value of the stiffness obtained in part (1), determine the transmitted force to the base motion system using Matlab or Excel. 3. Display and discuss your results.arrow_forward
- lail - Ahmed Amro Hussein Ali A x n Course: EN7919-Thermodynamic x Homework Problerns(First Law)_S x noodle/pluginfile.php/168549/mod_resource/content/1/Homework%20Problems%28First%20Law%29_SOLUTIONS.pdf UTIONS.pdf 4 / 4 100% Problem-4: When a system is taken from a state-a to a state-b, the figure along path a-c-b, 84 kJ of heat flow into the system, and the system does 32 kJ of work. (i) How much will the heat that flows into the system along the path a-d-b be, if the work done is 10.5 kJ? (Answer: 62.5 kJ) (ii) When the system is returned from b to a along the curved path, the work done on the system is 21 kJ. Does the system absorb or liberate heat, and how much? (Answer:-73 k]) (iii) If Ua = 0 andU, = 42kJ , find the heat absorbed in the processes ad and db. (Answer: 52.5 kJ, 10 kJ)arrow_forwardI want to run the SGP4 propagator for the ISS (ID = 25544) I got from spacetrack.org in MATLAB. I don't know where to get the inputs of the function. Where do I get the inFile and outFile that is mentioned in the following function. % Purpose: % This program shows how a Matlab program can call the Astrodynamic Standard libraries to propagate % satellites to the requested time using SGP4 method. % % The program reads in user's input and output files. The program generates an % ephemeris of position and velocity for each satellite read in. In addition, the program % also generates other sets of orbital elements such as osculating Keplerian elements, % mean Keplerian elements, latitude/longitude/height/pos, and nodal period/apogee/perigee/pos. % Totally, the program prints results to five different output files. % % % Usage: Sgp4Prop(inFile, outFile) % inFile : File contains TLEs and 6P-Card (which controls start, stop times and step size) % outFile : Base name for five output files %…arrow_forward1. For the following concentration expressions, indicate whether they are uniform or nonuniform and in how many dimensions (OD, 1D, 2D, or 3D), and steady or unsteady. Then for the following control volume and origin, and table of constants, use Excel or Matlab to graph profiles that show how concentration changes within the control volume and over time to a limit of 20 for the following: C(x,0,0,0), C(0,y,0,0), C(0,0,z,0) and C(0,0,0,t). On each graph, show which parameters are held constant, the CV boundaries, and the point where all four plots overlap. 20 C(x=0) 10 a 0.0001 b 0.001 | 20 0.01 k 0.1 100 All of the following functions are C(space, time) and so not necessarily just x as suggested. a. C,(x)= C,(x = 0)x exp{- ax}arrow_forward
- You are part of a car accident investigative team, looking into a case where a car drove off a bridge. You are using the lab projectile launcher to simulate the accident and to test your mathematical model (an equation that applies to the situation) before you apply the model to the accident data. We are assuming we can treat the car as a projectile.arrow_forwardPlease help me Matlabarrow_forwardMotiyo Add explanationarrow_forward
- I want to run several shocks in my calibrated DSGE model. I want the shock “a” to happen at period 0, shock “b” at period 2 and shock “c” at period 5. Also, I want to run a shock of 1 % to the variable “a”, 2 % to variable “b” and 10 % to variable “c”. How would I write it in the Dynare code? The model is log-linearized around the steady state and all endogenous variables are set at 0 at the steady state.arrow_forwardA Do Now- Work and Energy Tran: x + ure.com/courses/44384/assignments/1494085 Al. O Google Drive LTI TumingPoint-Parti.. 4 Roots, Multi, and Fu.. A Roots, Multi, and Fu. A Roots, Multi, and Fu. O https://student.pas. y = 0 h Write down an equation for the total energy in the system at point 1 and point 2, before and after the change in height and speed. Part 2- Complete the Table using the image above: Use the tables below to calculate the kinetic energy of the cart at point 2 for the following values: m=2,000 kg, h; = 30 m, hf= 16 m Point 1 (initial) Point 2 (final) Ep (J) Ex (J) Ep (J) Ek (J) ETotal J) ETotal (1)arrow_forwardManufacturing process with two variables x1,x2 described by the empirical model: y=bo +b1 x1 + b2 x2 + b12 x1 x2 + b3 (x1)^2 +b4 (x2)^2 please refere to the image attachedarrow_forward
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