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University Physics I · unit UPI-12

Static Equilibrium & Elasticity

Connect the ideas, make your working visible, and test the result. Use the hints when you need a starting point; open the full solution after your attempt.

Extra challenging questions

A selection from this pathway. Open a topic below for its complete practice and challenge set.

Extra challenging · 01

Translational & Rotational Equilibrium: infer an input with uncertainty

A rigid body is in equilibrium when the external forces on it add to zero and their torques about a point add to zero, so neither its centre of mass nor its rotation accelerates; static equilibrium also requires it to start at rest. Use the supplied topic model Y_out = fa+fb-600, where Y_out is NET FORCE ΣF_y (N). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793. fa is Lift F₁ at end A, measured in N. Keep fb (Lift F₂ at end B) = 300 N; p (Axis position p from A) = 1 m fixed. For this exercise use only 189.75 N ≤ fa ≤ 410.25 N on this continuous branch. A grid of test settings is an input restriction for this exercise, not by itself a claim of physical quantisation. This calculation retains the topic model's stated assumptions; it does not extend them to a different physical setup. A reading gives Y_out = 24.255 N, with a bounded reading uncertainty ±12.899 N. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown fa by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.02205 N, using a numerical bracket if required. Find the full input interval consistent with the bounded reading uncertainty and compare it with a symmetric input-error assumption. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

NET FORCE ΣF_y against fa

Predictions from the supplied Translational & Rotational Equilibrium model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): NET FORCE ΣF_y / N

NET FORCE ΣF_y against faPredictions from the supplied Translational & Rotational Equilibrium model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: fa: Lift F₁ at end A / N. Vertical axis: NET FORCE ΣF_y / N. Exact values are available in the data table below.-119.1-59.53059.53119.1180.9240.5300359.5419.1xy

Horizontal axis (x): fa: Lift F₁ at end A / N

Axes show the supplied calibration interval; the origin may lie outside the plot.

Reading 1fa: Lift F₁ at end A / N: 189.8NET FORCE ΣF_y / N: -110.3
Read the exact data as a table
NET FORCE ΣF_y against fa — supplied values
fa: Lift F₁ at end A / NNET FORCE ΣF_y / N
189.75-110.25
244.875-55.125
3000
355.12555.125
410.25110.25

These are the supplied values, not a worked answer. No fitted trend is drawn.

Show a hint

The model's endpoint predictions bracket the reading. Solve Y_out(fa) = Y_measured and then solve again at Y_measured − u and Y_measured + u; a nonlinear inverse can give unequal input deviations.

Reveal the worked solution
  1. Endpoint predictions are Y_out(189.75) = -110.25 N and Y_out(410.25) = 110.25 N. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives fa_line = 189.75 + (24.255 − -110.25)(410.25 − 189.75)/(110.25 − -110.25) = 324.255 N. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Use the actual equation, not the chord, and bracket its root. Evaluating the midpoint and retaining the sign-changing half-interval gives fa = 324.255 N; substituting back gives Y_out = 24.255 N.
  4. The interpolation error in the input is |fa_line − fa| = 0 N. This is within the requested numerical tolerance.
  5. Invert both limits Y_out = 11.356 N and 37.154 N. Sort the roots even if the response decreases: 311.356 N ≤ fa ≤ 337.154 N.
  6. The lower and upper input deviations are 12.899 N and 12.899 N. They agree on this branch; this does not establish linearity for changes in other inputs or outside the interval. This interval includes reading uncertainty only, not model error or uncertainty in fixed inputs.

Answer fa ≈ 324.255 N; compatible interval [311.356, 337.154] N. Endpoint interpolation gives 324.255 N.

Compare the assumptions, method and units with your attempt. Explain any correction before trying another question.

Extra challenging · 02

Center of Mass & Center of Gravity: infer an input with uncertainty

The center of gravity is the point where a body's entire weight can be taken to act when computing torques; in a uniform gravitational field it coincides with the center of mass, the mass-weighted average position r_cm = Σ mᵢrᵢ / M. Use the supplied topic model Y_out = deg(atan(0.3*(20+load)/(15+load*shelf))), where Y_out is TIPPING ANGLE θ_c (°). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; deg converts radians to degrees; unmarked trigonometric functions use radians. load is Load mass m, measured in kg. Keep tilt (Tilt about the edge θ) = 15 °; shelf (Height of the load's center) = 1.2 m fixed. For this exercise use only 6.375 kg ≤ load ≤ 53.625 kg on this continuous branch. A grid of test settings is an input restriction for this exercise, not by itself a claim of physical quantisation. This calculation retains the topic model's stated assumptions; it does not extend them to a different physical setup. A reading gives Y_out = 16.135698 °, with a bounded reading uncertainty ±0.08713 °. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown load by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.004725 kg, using a numerical bracket if required. Find the full input interval consistent with the bounded reading uncertainty and compare it with a symmetric input-error assumption. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

TIPPING ANGLE θ_c against load

Predictions from the supplied Center of Mass & Center of Gravity model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): TIPPING ANGLE θ_c / °

TIPPING ANGLE θ_c against loadPredictions from the supplied Center of Mass & Center of Gravity model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: load: Load mass m / kg. Vertical axis: TIPPING ANGLE θ_c / °. Exact values are available in the data table below.15.4116.4117.4118.419.44.48517.243042.7655.51xy

Horizontal axis (x): load: Load mass m / kg

Axes show the supplied calibration interval; the origin may lie outside the plot.

Reading 1load: Load mass m / kg: 6.375TIPPING ANGLE θ_c / °: 19.26
Read the exact data as a table
TIPPING ANGLE θ_c against load — supplied values
load: Load mass m / kgTIPPING ANGLE θ_c / °
6.37519.25623592318662
18.187517.28090729149899
29.99999999999999616.389540334034788
41.8124999999999915.882242083630004
53.6249999999999915.554830345290936

These are the supplied values, not a worked answer. No fitted trend is drawn.

Show a hint

The model's endpoint predictions bracket the reading. Solve Y_out(load) = Y_measured and then solve again at Y_measured − u and Y_measured + u; a nonlinear inverse can give unequal input deviations.

Reveal the worked solution
  1. Endpoint predictions are Y_out(6.375) = 19.2562 ° and Y_out(53.625) = 15.5548 °. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives load_line = 6.375 + (16.1357 − 19.2562)(53.625 − 6.375)/(15.5548 − 19.2562) = 46.21 kg. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Use the actual equation, not the chord, and bracket its root. Evaluating the midpoint and retaining the sign-changing half-interval gives load = 35.1975 kg; substituting back gives Y_out = 16.135698 °.
  4. The interpolation error in the input is |load_line − load| = 11.0125 kg. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 16.048568 ° and 16.222828 °. Sort the roots even if the response decreases: 33.2775 kg ≤ load ≤ 37.2836 kg.
  6. The lower and upper input deviations are 1.91996 kg and 2.08615 kg. They differ because the inverse response is nonlinear; a symmetric error bar would only be a local approximation. This interval includes reading uncertainty only, not model error or uncertainty in fixed inputs.

Answer load ≈ 35.1975 kg; compatible interval [33.2775, 37.2836] kg. Endpoint interpolation gives 46.21 kg.

Compare the assumptions, method and units with your attempt. Explain any correction before trying another question.

Extra challenging · 03

Moments & Couples: infer an input with uncertainty

A couple is a pair of equal and opposite forces whose lines of action are a perpendicular distance d apart; it exerts no net force, and its moment C = F d is the same about every point. Use the supplied topic model Y_out = f*(d/2+p)+f*(d/2-p), where Y_out is NET M₁ + M₂ (N m). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793. f is Force magnitude F, measured in N. Keep d (Separation of the lines d) = 0.5 m; p (Position of P from the midpoint) = -0.8 m fixed. For this exercise use only 13.1875 N ≤ f ≤ 36.8125 N on this continuous branch. A grid of test settings is an input restriction for this exercise, not by itself a claim of physical quantisation. This calculation retains the topic model's stated assumptions; it does not extend them to a different physical setup. A reading gives Y_out = 13.799375 N m, with a bounded reading uncertainty ±0.69103 N m. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown f by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.0023625 N, using a numerical bracket if required. Find the full input interval consistent with the bounded reading uncertainty and compare it with a symmetric input-error assumption. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

NET M₁ + M₂ against f

Predictions from the supplied Moments & Couples model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): NET M₁ + M₂ / N m

NET M₁ + M₂ against fPredictions from the supplied Moments & Couples model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: f: Force magnitude F / N. Vertical axis: NET M₁ + M₂ / N m. Exact values are available in the data table below.6.1219.31112.515.6918.8812.2418.622531.3837.76xy

Horizontal axis (x): f: Force magnitude F / N

Axes show the supplied calibration interval; the origin may lie outside the plot.

Reading 1f: Force magnitude F / N: 13.19NET M₁ + M₂ / N m: 6.594
Read the exact data as a table
NET M₁ + M₂ against f — supplied values
f: Force magnitude F / NNET M₁ + M₂ / N m
13.18756.59375
19.093759.546875000000002
2512.499999999999998
30.9062515.453125
36.812518.40625

These are the supplied values, not a worked answer. No fitted trend is drawn.

Show a hint

The model's endpoint predictions bracket the reading. Solve Y_out(f) = Y_measured and then solve again at Y_measured − u and Y_measured + u; a nonlinear inverse can give unequal input deviations.

Reveal the worked solution
  1. Endpoint predictions are Y_out(13.1875) = 6.59375 N m and Y_out(36.8125) = 18.4063 N m. The target lies between them. On the selected branch the response is strictly increasing.
  2. Endpoint interpolation gives f_line = 13.1875 + (13.7994 − 6.59375)(36.8125 − 13.1875)/(18.4063 − 6.59375) = 27.5987 N. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Use the actual equation, not the chord, and bracket its root. Evaluating the midpoint and retaining the sign-changing half-interval gives f = 27.5987 N; substituting back gives Y_out = 13.799375 N m.
  4. The interpolation error in the input is |f_line − f| = 3.55271e-15 N. This is within the requested numerical tolerance.
  5. Invert both limits Y_out = 13.108345 N m and 14.490405 N m. Sort the roots even if the response decreases: 26.2167 N ≤ f ≤ 28.9808 N.
  6. The lower and upper input deviations are 1.38206 N and 1.38206 N. They agree on this branch; this does not establish linearity for changes in other inputs or outside the interval. This interval includes reading uncertainty only, not model error or uncertainty in fixed inputs.

Answer f ≈ 27.5987 N; compatible interval [26.2167, 28.9808] N. Endpoint interpolation gives 27.5987 N.

Compare the assumptions, method and units with your attempt. Explain any correction before trying another question.

Extra challenging · 04

Beams, Supports & Reactions: infer an input with uncertainty

A support reaction is the force or couple a support exerts on a structure, with one component for each motion the support prevents: one for a roller or a cable, two for a pin, three for a fixed end. Use the supplied topic model Y_out = 6*x*sqrt(d*d+h*h)/(d*h), where Y_out is CABLE TENSION T (kN). The output symbol Y_out is distinct from all input symbols. ^ denotes a power; π = 3.141592653589793; sqrt(x) means √x. h is Anchor height h of D above A, measured in m. Keep d (Cable attachment E at distance d) = 4 m; x (Load position x from A) = 2.75 m fixed. For this exercise use only 1.2125 m ≤ h ≤ 2.7875 m on this continuous branch. A grid of test settings is an input restriction for this exercise, not by itself a claim of physical quantisation. This calculation retains the topic model's stated assumptions; it does not extend them to a different physical setup. A reading gives Y_out = 8.6405371 kN, with a bounded reading uncertainty ±0.21386 kN. Treat the model and all fixed inputs as exact for this exercise; the bound is not a standard deviation. First estimate the unknown h by straight-line interpolation between the two endpoint predictions. Then solve the actual model on the stated branch to an absolute input tolerance of 0.0001575 m, using a numerical bracket if required. Find the full input interval consistent with the bounded reading uncertainty and compare it with a symmetric input-error assumption. Do not assume that the supplied calibration points prove monotonicity outside this branch.

Explore the question data

CABLE TENSION T against h

Predictions from the supplied Beams, Supports & Reactions model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law.

Vertical axis (y): CABLE TENSION T / kN

CABLE TENSION T against hPredictions from the supplied Beams, Supports & Reactions model, with all other inputs fixed as stated in the question. 5 calibration points support a trend comparison; they are not measured data or a straight-line law. Horizontal axis: h: Anchor height h of D above A / m. Vertical axis: CABLE TENSION T / kN. Exact values are available in the data table below.6.9358.82610.7212.6114.51.1491.57522.4252.85xy

Horizontal axis (x): h: Anchor height h of D above A / m

Axes show the supplied calibration interval; the origin may lie outside the plot.

Reading 1h: Anchor height h of D above A / m: 1.212CABLE TENSION T / kN: 14.22
Read the exact data as a table
CABLE TENSION T against h — supplied values
h: Anchor height h of D above A / mCABLE TENSION T / kN
1.212514.219705444097219
1.606249999999999711.069655964070389
1.99999999999999989.223780407186634
2.393758.032956498181582
2.78749999999999967.2148132649102985

These are the supplied values, not a worked answer. No fitted trend is drawn.

Show a hint

The model's endpoint predictions bracket the reading. Solve Y_out(h) = Y_measured and then solve again at Y_measured − u and Y_measured + u; a nonlinear inverse can give unequal input deviations.

Reveal the worked solution
  1. Endpoint predictions are Y_out(1.2125) = 14.2197 kN and Y_out(2.7875) = 7.21481 kN. The target lies between them. On the selected branch the response is strictly decreasing.
  2. Endpoint interpolation gives h_line = 1.2125 + (8.64054 − 14.2197)(2.7875 − 1.2125)/(7.21481 − 14.2197) = 2.46694 m. This estimates the inverse of the endpoint chord, rather than assuming that chord is the physical model.
  3. Use the actual equation, not the chord, and bracket its root. Evaluating the midpoint and retaining the sign-changing half-interval gives h = 2.17325 m; substituting back gives Y_out = 8.6405371 kN.
  4. The interpolation error in the input is |h_line − h| = 0.293686 m. This is larger than the requested numerical tolerance.
  5. Invert both limits Y_out = 8.4266771 kN and 8.8543971 kN. Sort the roots even if the response decreases: 2.10598 m ≤ h ≤ 2.24551 m.
  6. The lower and upper input deviations are 0.0672722 m and 0.0722557 m. They differ because the inverse response is nonlinear; a symmetric error bar would only be a local approximation. This interval includes reading uncertainty only, not model error or uncertainty in fixed inputs.

Answer h ≈ 2.17325 m; compatible interval [2.10598, 2.24551] m. Endpoint interpolation gives 2.46694 m.

Compare the assumptions, method and units with your attempt. Explain any correction before trying another question.

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