22 of 22 ideas
A.3 Work, energy and power: 22 ideas
Basketball pressure and bounce efficiency
Research question. How does the coefficient of restitution of a basketball, found from drop heights of 1.20 m, change when its gauge pressure is varied from 30 kPa to 80 kPa in 6 to 8 steps?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Common: on 2 sites
My take. Less crowded (listed on 2 sites) and easy to run. Choose it if you play basketball, and add multiple drop heights to turn it into a gradient measurement.
Method, physics and where marks are lost+
- Independent variable
- Gauge pressure, 30 to 80 kPa in 10 kPa steps (6 values), set with a hand pump and a pressure gauge, with 5 drops at each.
- What you measure
- Rebound height from a phone video filmed against a metre rule, or a sound-based method with a microphone timing successive bounces. The coefficient of restitution e is found from the ratio of rebound to drop height, then square-rooted.
- Controlled variables
- Drop height fixed with a release rig. Same ball and the same hard floor. The ball released without spin. Temperature of the ball stable, since air pressure depends on it.
- Physics and graph
- e = vafter / vbefore = √(h₂/h₁). Plot h₂ against h₁ for a fixed pressure to find e² from the gradient. Then plot e against pressure. Discuss energy loss as ΔE = mg(h₁ − h₂) and the ball's gas and rubber wall deformation.
- SL and HL
- SL students calculate e at each pressure and discuss the trend. To reach the top band, vary drop height at each pressure to get e from a gradient, and consider whether e levels off. HL can link to the gas laws for the pressure change during impact.
- Where marks are lost
- Research design: pressure changing as the ball is checked or pumped, or reading heights from a video without calibration. Data analysis: only one drop height. Conclusion: a trend claimed over too few pressures. Evaluation: air resistance and parallax not discussed.
- Data
- Needs a ball, a pump with a gauge and a phone camera; parallax reading of height is the main uncertainty.
Rebound of a bouncing ball from freezer to hot water
Research question. How does the starting temperature of a tennis ball, varied from 5 °C to 60 °C in six steps, change its coefficient of restitution when it is dropped from 1.00 m onto a concrete floor?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Common: on 2 sites
My take. Popular with two sites listing it, so it needs a personal angle: I would push a student to compare a pressurised ball with a pressureless one, or to test a ball type they actually play with, so the physics explanation is tested and not just quoted. It works well because the equipment is cheap and the range of e is large enough to beat the noise.
Method, physics and where marks are lost+
- Independent variable
- Core temperature of the ball: about 5, 15, 25, 35, 45 and 60 °C (six values). Cool in a fridge or freezer, warm in a water bath or oven set low. Use one ball per temperature, or the same ball re-equilibrated, and do at least five drops at each value.
- What you measure
- Rebound height after the first bounce, read from a video recorded at 120 fps or 240 fps against a metre rule, or from sound timing between the first and second impacts with a microphone and Audacity. Coefficient of restitution e is calculated as the square root of rebound height divided by drop height. Ball temperature is checked with a digital or infrared thermometer just before release.
- Controlled variables
- Drop height fixed with a clamp-held release point and a plumb line. Same floor tile or slab for every drop, checked for cleanliness. Ball cooling during the transfer is limited by timing each drop within 10 s of removal and by logging the temperature immediately before release. The same ball, or balls from the same tube, are used to avoid differences in wear and internal pressure.
- Physics and graph
- For a ball hitting a fixed surface, e = vafter / vbefore = √(h / H), because speed comes from energy conservation during free fall. Plot h against H for a fixed temperature to check that the relationship is linear, with gradient e squared. Then plot e against temperature, or e squared against temperature, and comment on the trend. Link the trend to the gas pressure inside the ball, which rises with temperature according to the pressure law, and to the softening of the rubber, which increases energy loss as internal friction in the material.
- SL and HL
- At SL, a clean e against temperature graph with uncertainty bars and a sensible explanation using energy dissipated in the collision is enough for a good mark. To reach the top band, repeat at several drop heights to show that e does not depend on H, then separate the pressure effect from the rubber effect, for example by comparing a pressurised ball with a pressureless one or by drilling a small hole in a sacrificial ball. An HL student can add a model of the energy lost per bounce as a fraction of the initial energy, and estimate the change in gas pressure from the pressure law with T in kelvin.
- Where marks are lost
- Research design: temperature of the ball surface is measured but the core is at a different temperature, so the real IV is unclear. Data analysis: only one drop per temperature, or rebound height read by eye from a rule with no frame by frame video, producing large unquantified uncertainty. Conclusion: claiming a linear trend from too narrow a temperature range without a fitted line, or explaining the trend with 'more energy' without discussing the ball's rubber and gas. Evaluation: ignoring how quickly a hot or cold ball returns to room temperature, and not discussing systematic error from slow motion video frame rate or parallax.
- Data
- A phone with slow motion video, a metre rule, a thermometer and a water bath are enough, but the ball cools or warms between the bath and the drop, so the real core temperature is the main uncertainty.
Rolling time of a can down ramps of different heights
Research question. How does the height h of the top end of a 1.00 m ramp, varied from 5 cm to 25 cm in 5 cm steps, affect the time for a solid metal cylinder to roll down it, and is the result consistent with energy conservation including rotational energy?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Common: on 2 sites
My take. Fine as a base but the raw question is too thin. Twist it by comparing a solid and a hollow cylinder, so the moment of inertia gives you a real prediction to test.
Method, physics and where marks are lost+
- Independent variable
- Height of the raised end above the bench, 5, 8, 11, 14, 17, 20, 25 cm, each run five times.
- What you measure
- Time to roll a fixed 1.00 m distance, measured with two light gates or by slow motion video. Calculated: acceleration a = 2s/t², and final speed v.
- Controlled variables
- Same cylinder and same ramp surface. Distance travelled fixed at 1.00 m. Release from rest with a ruler held across the top. Ramp checked flat so the cylinder does not drift sideways.
- Physics and graph
- For a solid cylinder, mgh = ½mv² + ½Iω² gives v² = (4/3)gh, and a = (2/3) g sinθ. Plot a (y) against sinθ (x), where sinθ = h/L. The gradient should be 2g/3, about 6.5 m/s², independent of mass.
- SL and HL
- SL students can use energy transfer with the fraction of kinetic energy that is rotational and compare the gradient with theory. HL students can derive it with the moment of inertia and compare a solid cylinder with a hollow one.
- Where marks are lost
- Research design: the question asks about time, which is not linear in h, so no useful graph is planned. Data analysis: uncertainty in h at a shallow ramp not propagated to sinθ. Conclusion: no comparison with the predicted gradient. Evaluation: slipping and ramp flex not considered.
- Data
- Needs a ramp, metre rule and stopwatch or light gates, and the main uncertainty is starting exactly at rest and timing short runs.
Ball size and rebound elasticity on a hard floor
Research question. How does the outer diameter of a solid rubber ball, varied from 20 mm to 60 mm in six steps, change the ratio of rebound speed to impact speed (e = √(hrebound/hdrop)) after a single bounce from a release height of 1.00 m onto a concrete floor?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. A sound and easy investigation, but the topic is common, so it only stands out if the design tackles the confound between size, mass and material. Personalise it by choosing an unusual but consistent ball family, such as sports balls of one material, and by using audio timing as a second measurement of e.
Method, physics and where marks are lost+
- Independent variable
- Ball diameter: six balls from 20 mm to 60 mm in roughly 8 mm steps, measured with vernier calipers at three orientations and averaged. Ideally the same material for all (for example solid rubber or steel-free bouncy balls from one supplier). 5 drops per ball, 30 drops in total.
- What you measure
- Rebound height read from a slow motion video (240 fps phone camera) filmed against a metre rule, using the frame where the ball reaches its top. Coefficient of restitution calculated as e = √(hrebound/hdrop). Optionally, a microphone and audio software can time the gap between the first two impacts to get e from the flight time.
- Controlled variables
- Release height fixed at 1.00 m to the bottom of the ball using a clamped release point and a rule with a set square. Same floor surface for every drop, marked with tape. Ball material and temperature kept the same by using balls from one batch stored in the same room. Release without spin by holding the ball between two fingers or using a small clamp.
- Physics and graph
- Conservation of energy before and after impact gives v = √(2gh), so e = vafter/vbefore = √(hrebound/hdrop). Plot e against diameter to test for a trend. Alternatively plot hrebound against hdrop for one ball, whose gradient is e squared. Also consider mass, since a larger ball of the same material is heavier, and compare the fractional energy lost, 1 - e squared.
- SL and HL
- An SL student can find e for each diameter, plot it with error bars and describe the trend and any link to mass. To reach the top band, the student should separate the effect of size from mass and material (for example by comparing a hollow ball and a solid one), analyse the energy lost as sound and heat, and judge whether any trend is larger than the spread of repeats. HL students can add a model of the ball as a nonlinear spring with damping, or examine the contact time.
- Where marks are lost
- Research design: diameter is confounded with mass, wall thickness and material when different types of ball are mixed, so the comparison is not fair. Data analysis: reading the top of the bounce by eye gives uncertainties of several centimetres, and students often ignore them or propagate them wrongly through the square root. Conclusion: claiming a trend when the differences in e are smaller than the repeat spread. Evaluation: not discussing air resistance, spin, non-vertical bounces, or the fact that the balls are not identical in composition.
- Data
- Needs vernier calipers, a metre rule and a phone with slow motion video; the main uncertainty is reading the peak height from video frames, plus real variation between balls.
Ball speed at the foot of a ramp against release height
Research question. How does the release height, varied from 5 cm to 30 cm in 5 cm steps, affect the speed of a steel ball at the bottom of a 1.0 m ramp, and what fraction of gravitational potential energy becomes translational kinetic energy?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. Easy and widely done, so the interest is in the rolling energy split. Twist: compare a solid ball, a hollow ball and a can to test how mass distribution changes the fraction.
Method, physics and where marks are lost+
- Independent variable
- Vertical release height from 5 cm to 30 cm, 6 values, with 5 repeats at each.
- What you measure
- Speed at the bottom from a light gate placed across the ball's diameter (±0.01 m s⁻¹) or from video analysis. Kinetic energy is found from the speed and the mass on a balance.
- Controlled variables
- Ball mass and diameter, using one steel ball. Track surface, using the same groove or rail. Release method, letting go without pushing, for instance with a ruler stop. Light gate position, kept at the same point on the track.
- Physics and graph
- For a solid sphere rolling without slipping, mgh = ½mv² + ½Iω² gives v² = (10/7)gh. Plot v² against h, with a gradient of (10/7)g ≈ 14.0 m s⁻². Compare with the value found to find energy lost.
- SL and HL
- SL students get the v² against h line and compare the gradient to 10/7 g. Top band work tests the rolling assumption, for example by using a hollow sphere or cylinder to compare moments of inertia. HL students can build the moment of inertia analysis rigorously.
- Where marks are lost
- Research design: the input says ramp angle is controlled, but changing height at a fixed length changes the angle, so the variables need a clear plan. Data analysis: plotting v against h and missing the square relationship. Conclusion: ignoring rotational energy so that 'lost energy' appears large. Evaluation: not measuring the diameter for the light gate speed.
- Data
- Needs a ramp, a light gate or a phone camera, and a steel ball. The main uncertainty is the gate's timing over the ball's width and slipping.
Bounce height and impact force for cushioning materials
Research question. How does the thickness of a foam layer (5, 10, 15, 20, 25, 30 mm) affect the peak deceleration of a 200 g steel ball dropped from 0.50 m onto it?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. Worth choosing if you fix one material and vary thickness, because comparing several unlike materials gives you nothing to linearise. Twist: test the foam from a real helmet or a parcel you own.
Method, physics and where marks are lost+
- Independent variable
- Foam thickness from 5 mm to 30 mm in six steps, stacking identical 5 mm sheets so the material stays the same. Five drops per thickness.
- What you measure
- Peak acceleration read from a phone accelerometer taped to the ball holder or a force sensor plate, converted to peak force with F = ma. Optionally rebound height from slow motion video against a ruler.
- Controlled variables
- Drop height fixed with a clamp and marked release point. Mass of the falling object fixed by weighing it. Same foam type and density, cut from one sheet. Rigid bench surface under the foam, same for every trial.
- Physics and graph
- Energy transfer mgh to kinetic energy, impulse F·Δt = Δp, and the fraction of energy returned e = hrebound/hdrop. Plot peak force against 1/thickness, or rebound fraction against thickness. If the deceleration distance d is compressive, Favg ≈ mgh/d gives a testable link.
- SL and HL
- SL students can plot force against thickness and explain with impulse and energy. Top band work compares a model of average force with measured peak force and discusses why they differ. HL students can add a force-time curve integrated to check the impulse equals the momentum change.
- Where marks are lost
- Research design: comparing 'materials' with no way to hold thickness and density equal. Data analysis: reading the peak from one noisy trace without repeats or uncertainty. Evaluation: ignoring that phone sampling rates can miss the true peak.
- Data
- Needs a phone accelerometer app or force sensor; the main uncertainty is the sampling rate missing the peak and the ball tilting on impact.
DC motor efficiency across a range of lifted loads
Research question. How does the mass lifted by a small DC motor, varied from 20 g to 200 g in 20 g steps, affect its efficiency at a fixed supply voltage of 3.0 V?
- A.3 Work, energy and power
- SL
- Needs care
- Rarely listed
My take. Sound and easy to run, and the efficiency peak gives a clear result. Make it yours by explaining the peak with a loss model rather than just plotting it.
Method, physics and where marks are lost+
- Independent variable
- Lifted mass, 20 g to 200 g in steps of 20 g (10 values), each lifted 3 times.
- What you measure
- Voltmeter and ammeter readings give input power Pin = VI. Metre rule and stopwatch give the time to raise the mass through a fixed height (about 0.80 m), so Pout = mgh/t. Efficiency = Pout/Pin.
- Controlled variables
- Supply voltage: stabilised power supply checked with a voltmeter during each lift. Lift height: marked on a rule and the same start and end points used. String and pulley: the same thread and a low-friction pulley throughout. Motor temperature: pause between runs so the motor does not warm up.
- Physics and graph
- Efficiency = useful power out / power in, with P = VI and P = mgh/t. Plot efficiency against lifted mass and find the load at maximum efficiency. A second graph of Pout against m helps show why the curve peaks. Note that current varies during the lift, so read it at steady speed.
- SL and HL
- SL: measure, plot the efficiency curve and describe the peak. Top band: model motor losses (resistive heating I²R, friction) and compare the predicted peak with the measured one. HL students can link the back emf of the motor to induction ideas from D.4.
- Where marks are lost
- Research design: too few masses near the peak, or voltage not held constant. Data analysis: reading current while the motor is accelerating, and no uncertainty on t for short lifts. Conclusion: claiming a rise then fall without comparing to a model. Evaluation: ignoring pulley friction and string stretch.
- Data
- A cheap hobby motor, two multimeters and a stopwatch are enough; lifts of about 2 s make timing uncertainty large, so use a longer lift height or video timing.
Drop height of water and power from a small turbine
Research question. How does the vertical drop height of water (0.20 to 1.00 m in 0.20 m steps) affect the electrical power delivered by a small hobby generator to a fixed resistor?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. A solid energy conversion project if efficiency is the focus. Test a second turbine design to make it your own.
Method, physics and where marks are lost+
- Independent variable
- Drop height of the water outlet above the turbine, 0.20 to 1.00 m, five or six values, 5 repeats each.
- What you measure
- Voltage across a fixed load resistor with a voltmeter or data logger, giving P = V²/R in W; water flow rate from a measuring cylinder and stopwatch.
- Controlled variables
- Volume of water released, using a fixed bucket with a valve; outlet nozzle diameter; load resistance; distance and angle of the jet onto the turbine.
- Physics and graph
- Water gains kinetic energy mgh, so the available power is ρQgh. Plot electrical power against height, expecting a line through the origin. The gradient gives ρQg times efficiency. Compare with the input power to obtain efficiency.
- SL and HL
- SL: power against height with efficiency calculated. Top band: note that flow rate also depends on height, and use Bernoulli to correct for it. HL adds nothing essential.
- Where marks are lost
- Research design: flow rate changes with height and is not controlled. Data analysis: only peak voltage is read from a fluctuating signal. Evaluation: splash losses and turbine friction not discussed.
- Data
- Needs a hobby DC motor as generator, a tube, a logger; the main uncertainty is the fluctuating output, so record V against time and average.
Efficiency of a pulley system when lifting loads
Research question. How does the efficiency of a two-pulley block and tackle change as the load is increased from 0.20 kg to 1.00 kg in steps of 0.20 kg, when lifted through 0.30 m?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. A decent choice if you focus on efficiency, since simple work done equals mgh is not really a question. The rise of efficiency with load is a good personal finding.
Method, physics and where marks are lost+
- Independent variable
- Load lifted: 5 to 6 values from 0.20 to 1.00 kg, each lift repeated 3 times, with an optional second series with different numbers of supporting strings.
- What you measure
- Effort measured with a force sensor or newton meter as the load rises slowly, and distances moved by the load and by the effort measured with a rule; work input is Feffort times the effort distance, work output is mgh, and efficiency is output divided by input.
- Controlled variables
- Lifting height: fixed at 0.30 m with markers. Lifting speed: slow and steady, timed to about 0.05 m/s. Pulleys and string: same set and lubrication. Number of supporting strings: kept the same for the load series.
- Physics and graph
- Work W = F s, useful work mgh, efficiency = (mgh) / (Feffort s). Plot work output against work input; the gradient is efficiency. The energy lost by friction and pulley weight explains the shortfall from 100 percent.
- SL and HL
- SL students find efficiency for each load and describe the trend. Stronger work models the constant friction plus the pulley weight, and predicts why efficiency rises with load towards a limit.
- Where marks are lost
- Research design: only measuring force on a stationary load, missing friction. Data analysis: reading a bouncing newton meter. Evaluation: not linking energy loss to friction and the weight of the moving pulley.
- Data
- Pulleys, string, masses and a force sensor; the main uncertainty is jerky force reading while the load moves.
Efficiency of a small DC motor lifting a load
Research question. How does the electrical input power, varied from 0.5 to 3.0 W by changing supply voltage, affect the efficiency of a small DC motor lifting a 50 g mass?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. A solid, safe choice with clear energy conversions. Make it your own by extracting the winding resistance and testing whether it explains the losses.
Method, physics and where marks are lost+
- Independent variable
- Supply voltage to the motor, 1.0 to 6.0 V in steps of 1.0 V (six values), three trials each. Input power found from voltage times current.
- What you measure
- Efficiency = useful output power divided by input power. Output power = mgh/t, using a stopwatch or video for the time to lift the mass through a measured height with a metre rule. Voltage and current from two multimeters.
- Controlled variables
- Lifted mass: 50 g throughout. Lift height: fixed at 0.80 m. Motor and string: the same motor with the same spool. Motor temperature: rest between runs so resistance stays similar.
- Physics and graph
- Efficiency = mgh/(VIt). Energy losses come from Joule heating I²R in the windings and friction. Plot efficiency against input power, and also plot output power against input power. A model of Pout = Pin minus I²R minus friction can be tested.
- SL and HL
- SL: measure and plot efficiency, discuss losses qualitatively. Top band: estimate winding resistance from a stalled test and fit a loss model quantitatively. HL: link to back emf in the motor, if induction is covered.
- Where marks are lost
- Research design: no clear method for output power, or lifting speed not constant. Data analysis: uncertainty in short lift times ignored. Evaluation: not commenting on the mass being too small for the higher voltages, which pushes efficiency down.
- Data
- Two multimeters, a motor, a pulley and a stopwatch are enough; the main uncertainty is the lift time at high voltage, so use video timing.
Energy lost by a trolley on different ramp surfaces
Research question. How does the surface material of a 1.00 m ramp inclined at 15° (sandpaper, carpet, plastic, wood, felt, foil: 6 values) affect the percentage of gravitational potential energy converted to kinetic energy at the base?
- A.3 Work, energy and power
- SL
- Easy data
- Rarely listed
My take. Fine, but the IV is categorical, which limits the analysis. Twist it by using several release distances per surface and finding μ from graphs.
Method, physics and where marks are lost+
- Independent variable
- Ramp surface material, 6 types glued on the same board. Each tested 5 times.
- What you measure
- Speed at the bottom from a light gate with a card of known width. Kinetic energy ½mv² is compared with mgΔh, and the fraction dissipated is 1 − KE/PE.
- Controlled variables
- Ramp angle: set with the same height blocks and checked with a protractor. Trolley mass: measured on a balance. Release position: from the same mark with no push. Wheels: same trolley, or a sliding block with the same contact area.
- Physics and graph
- Energy conservation: mgh = ½mv² + work against friction. Then fraction lost = 1 − v²/(2gh). With a sliding block, work against friction is μmg cosθ × d, giving μ. Plot v² against distance down the slope for each material; the gradient gives the acceleration and thus μ.
- SL and HL
- SL students can compare fractions and connect them to friction. To reach the top band, extract μ from the gradient of v² against distance and discuss rotational KE for the wheels. HL depth is less natural here.
- Where marks are lost
- Research design: only one release distance, so no trend is available. Data analysis: rolling wheel energy is ignored when the trolley is said to lose energy. Evaluation: surface wear and dust between repeats.
- Data
- A ramp, a light gate and a balance are enough; the main uncertainty is the speed from a light gate and the ramp angle.
Energy lost when a pendulum bob strikes a wall
Research question. How does the mass of a steel ball, from 10 g to 60 g in 5 steps, affect the fraction of kinetic energy lost when it swings from a fixed release height into a rigid block?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. A decent idea if you expect and test a null result. Vary the wall material as well to make it your own.
Method, physics and where marks are lost+
- Independent variable
- Ball mass, 5 to 6 values (steel or brass spheres of the same radius are not possible, so use drilled or different material balls and record diameter), 5 repeats each.
- What you measure
- Release height and rebound height read from a video frame against a ruler, with the tracker software. Fraction lost = 1 − hrebound/hrelease, with propagated uncertainty.
- Controlled variables
- Release height (fixed with a clamp stop). String length and type. Wall material and its rigidity (clamped steel block). Ball diameter, or note its change and its effect on air drag.
- Physics and graph
- Gravitational potential energy mgh converts to kinetic energy and back. Fraction lost = 1 − h2/h1. Plot fraction lost against mass; if the collision is independent of mass the gradient is zero, which is a testable prediction.
- SL and HL
- SL: measure and compare with a flat line. Top band: relate the result to the coefficient of restitution e = √(h2/h1), and consider air drag and string losses separately.
- Where marks are lost
- Research design: masses that also change diameter, so more than one variable is changing. Data analysis: reading rebound heights from a video with large uncertainty. Conclusion: claiming a trend when values overlap within error bars.
- Data
- Needs a phone camera at 120 fps or more; reading the rebound height is the main uncertainty.
Paddle area of a small waterwheel and its efficiency
Research question. How does the paddle area of a hand built waterwheel, from 4 cm² to 20 cm² in 5 steps, affect its efficiency in lifting a 50 g mass or turning a small motor as generator, at a fixed water flow rate?
- A.3 Work, energy and power
- SL and HL
- Hard data
- Rarely listed
My take. Messy but personal, and it can score if you keep the flow rate under control. Build your own wheel and measure output at several load resistances to find the best.
Method, physics and where marks are lost+
- Independent variable
- Paddle area, 5 values (card or plastic cut to 4, 8, 12, 16, 20 cm²), 3 or more repeats each.
- What you measure
- Electrical output power from a small DC motor used as a generator, P = V²/R, with a voltmeter across a load resistor. Input power from water flow rate (measuring cylinder and stopwatch) and drop height, P = ρQgh. Efficiency = Pout/Pin.
- Controlled variables
- Water flow rate (constant head tank with a fixed tap). Drop height. Number of paddles and the wheel radius. Load resistor value.
- Physics and graph
- Input power P = ρQgh; output power P = V²/R. Efficiency = Pout/Pin. Plot efficiency against paddle area and find where the curve peaks, then explain with momentum transfer from the water.
- SL and HL
- SL: collect and plot the data, and comment on the trend. Stronger: explain the peak with a momentum model of the jet hitting the paddle, and account for splash losses and friction.
- Where marks are lost
- Research design: flow rate not held constant, and too few areas. Data analysis: not propagating uncertainty into efficiency. Evaluation: not measuring friction or splash losses.
- Data
- Needs a motor, a voltmeter and a steady water supply; the flow rate stability and generator efficiency are the main uncertainties.
Peak lifting speed of a hand-held load against mass
Research question. How does the mean speed of lifting a load through 0.50 m vary as the mass is increased from 1.0 kg to 6.0 kg in 1.0 kg steps?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. Fine if you replace the stopwatch with video and go for peak power. Get teacher approval for the human-participant risk.
Method, physics and where marks are lost+
- Independent variable
- Lifted mass: 1.0, 2.0, 3.0, 4.0, 5.0 and 6.0 kg (6 values), using slotted masses on a hanger, 5 repeats each with rests between.
- What you measure
- Time to raise the load through a marked 0.50 m, taken from a video recorded at 120 frames per second or a ultrasonic motion sensor. Mean speed = 0.50 m divided by time; power = mgv.
- Controlled variables
- Lifting distance: fixed with tape marks at 0.50 m. Person: one participant, with a warm-up. Technique: same posture, elbow starting angle and instruction to lift as fast as possible. Rest time: 2 minutes between lifts to avoid fatigue.
- Physics and graph
- Muscle force-velocity behaviour is usually modelled by the Hill relation, and mechanical power is P = mgv. Plot v (y) against mass m (x) to see the curve, and P against m to find the peak power. A straight line of 1/v against m is a simple test of a linear model.
- SL and HL
- SL students plot v against m and calculate power and work. Stronger work compares the curve with a simple model and separates constant-speed from accelerating phases. The original heavier-is-slower claim is obvious, so the quantitative shape is the point.
- Where marks are lost
- Research design: human participant, fatigue and ethics are not controlled or discussed. Data analysis: stopwatch timing with reaction error of about 0.2 s on a lift of under 1 s. Evaluation: not commenting on the acceleration phase.
- Data
- Needs a phone camera or motion sensor and slotted masses; the main uncertainty is timing a short lift and one person's fatigue.
Power from a model wind turbine at different blade lengths
Research question. How does the electrical power delivered by a model turbine to a fixed 10 ohm load change when the blade length is varied from 6 cm to 16 cm in steps of 2 cm?
- A.3 Work, energy and power
- SL and HL
- Needs care
- Rarely listed
My take. Fine and practical, but common as a theme. Make it personal by measuring the wind speed map across the fan face and deriving efficiency rather than just plotting power.
Method, physics and where marks are lost+
- Independent variable
- Blade length: 6, 8, 10, 12, 14 and 16 cm (6 values), with 3 or more repeats each. Blades are cut from the same card or plastic sheet and trimmed.
- What you measure
- Voltage across a fixed load resistor measured with a voltmeter or logger, giving P = V²/R. Wind speed at the rotor is checked with an anemometer.
- Controlled variables
- Wind speed: same fan setting and distance, checked at the rotor with an anemometer. Blade number, pitch angle and width: use a template and a protractor. Load resistance: same resistor. Generator: same small DC motor used as a generator.
- Physics and graph
- Power in the wind through the swept area is P = ½ρAv³ with A = πL², so power should be proportional to L² if efficiency is constant. Plot P (y) against L² (x); gradient = ½ρπv³ × efficiency, so efficiency can be estimated. A non-linear plot shows tip losses or a stalled rotor.
- SL and HL
- SL students test P against L² and find the efficiency. HL or top band work also examines the non-uniform wind profile from a fan, and compares the power coefficient with the Betz limit of 59 percent.
- Where marks are lost
- Research design: fan wind is not uniform across large blades, so the wind speed is not truly controlled. Data analysis: ignoring that power is not simply V×I of a loaded motor. Evaluation: not commenting on friction in the generator or turbulence.
- Data
- Needs a fan, a small DC motor and an anemometer; the main uncertainty is the uneven airflow across the rotor.
Ramp angle and the run-out distance of a rolling ball
Research question. How does ramp angle from 5 to 35 degrees affect the distance a steel ball rolls on a flat wooden track after it leaves a ramp with a release length of 0.50 m?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. Easy to run and easy to make trivial. It becomes solid work if you linearise with sin(θ) and check the rolling energy split against the measured speeds.
Method, physics and where marks are lost+
- Independent variable
- Ramp angle, 7 values from 5 to 35 degrees in 5 degree steps, set by a fixed release length and adjusted height, 5 runs each.
- What you measure
- Run-out distance on the flat track from the base of the ramp, measured with a tape and marked by a small tab. Speed at the base from a light gate or video analysis to see the energy conversion.
- Controlled variables
- Same ball, same release length along the ramp so that it starts at the same point. Ramp surface and flat track kept the same and cleaned. A smooth transition curve at the ramp base. Ball released without push, by a ruler held at the top.
- Physics and graph
- For a rolling ball, mgh = 1/2 m v2 + 1/2 I w2 (for a solid sphere, v2 = (10/7) g h). Constant deceleration on the flat gives d = v2 / (2a). Plot d (y) against sin(θ) (x) with h = L sin(θ): expect a straight line through the origin.
- SL and HL
- SL students plot d against sin(θ) and comment on the trend. Better work extracts the deceleration on the flat track and compares v from the light gate with (10/7) g h. HL depth can treat rotational kinetic energy and rolling resistance.
- Where marks are lost
- Research design: kink at the ramp base, so the ball bounces and loses energy. Data analysis: plotting distance against angle rather than sin(θ) and assuming linear. Conclusion: claiming a trend without a physical reason from the energy split.
- Data
- Needs a ramp, ball, tape and optionally a light gate or phone video; main uncertainty is the base transition and the point where the ball stops.
Rebound efficiency of a ball on different surfaces
Research question. How does the fraction of gravitational potential energy retained after one bounce of a tennis ball change with drop height from 0.20 m to 1.20 m in steps of 0.20 m, on a hard laboratory floor?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. Simple and cheap, and easy to do well, but examiners have seen bouncing balls. Drop the muscle comparison and add a twist, for example your own sport ball or a surface such as a gym mat. This is a measurable version, but it is not a biological study.
Method, physics and where marks are lost+
- Independent variable
- Drop height h0 from 0.20 to 1.20 m in steps of 0.20 m (6 values), with 5 drops at each height. A second run could repeat this on a different surface.
- What you measure
- Rebound height h1 read from slow motion video (120 fps or more) filmed against a metre rule, using a phone. Efficiency is calculated as h1/h0, since mass cancels in mgh1/mgh0.
- Controlled variables
- Same ball, checked with a balance before and after. Same surface, taped down and level. Release with no spin, using a clamp or a marked release point. Ball temperature and room temperature kept steady, with drops in one session so the ball does not warm up.
- Physics and graph
- Gravitational potential energy Ep = mgh, with efficiency = Ep(after)/Ep(before) = h1/h0. Plot h1 against h0. The gradient is the efficiency, or the square of the coefficient of restitution. A straight line through the origin supports a constant fraction. Curvature would suggest speed dependent losses. Comparing with muscle efficiency of about 25 % is a side comment, not the core of the investigation.
- SL and HL
- SL students give a clear h1 against h0 graph with the gradient and uncertainty. To reach top band, link efficiency to the coefficient of restitution e = √(h1/h0), explain where the energy goes (sound, heat, deformation), and test a second surface or ball. HL students can add the time between successive bounces and check consistency with a geometric series of rebound heights.
- Where marks are lost
- Research design: the original muscle comparison is not measurable with balls, so the question must stay on the bounce itself. Data analysis: reading the rebound height by eye gives large uncertainty, so use video and propagate it. Conclusion: claiming a constant efficiency without checking the fit residuals. Evaluation: ignoring parallax on the ruler and air resistance at large heights.
- Data
- Needs a metre rule, a ball and a phone with slow motion. The main uncertainty is reading the peak of the rebound from video frames, about ±1 cm.
Rebound energy loss of a ball on different floor materials
Research question. How does the type of flat surface (glass, wood, rubber mat, carpet tile, cork, concrete slab; 6 materials) affect the coefficient of restitution e of a squash ball dropped from 1.00 m, found from rebound height using e = √(h/H)?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. A safe, doable idea but very common, so it only scores well with a proper h against H gradient and honest uncertainties. Personalise it by choosing materials from your own home or school, such as a gym mat or a sports court sample, and by testing the speed dependence.
Method, physics and where marks are lost+
- Independent variable
- Surface material, 6 different flat samples of similar thickness, all laid on the same rigid floor. A second run can vary drop height (0.40 to 1.60 m in 5 steps) on one material to test whether e depends on impact speed.
- What you measure
- Rebound height h after the first bounce, read from a video recorded at 120 fps or more beside a fixed metre rule, measured to ±0.5 cm. e is calculated as √(h/H) for each drop. 5 repeat drops per material give a mean and a spread.
- Controlled variables
- Same ball, kept at room temperature and checked for pressure or wear, so ball properties do not drift. Release height fixed with a clamp and a release method that gives no spin, such as a light suction or a two-finger release. Camera position and distance fixed, with the ruler in the same plane as the ball to limit parallax. Sample resting on the same solid base, so the base does not absorb energy differently.
- Physics and graph
- Energy before and after impact: v = √(2gH) on arrival and √(2gh) on leaving, so e = vout/vin = √(h/H). Plot h against H for one surface: the gradient equals e², so e = √gradient. For the material comparison, a bar chart of mean e with error bars. Extension: e against impact speed to see if e is constant, and energy lost as a fraction 1 − e².
- SL and HL
- SL students can compare materials with a clear method, uncertainties and a bar chart of e. Top band work uses the h against H gradient to get e for each material, propagates uncertainty properly and discusses why e may vary with speed. HL depth can come from modelling the contact as a damped spring, or from using contact time or sound to estimate energy going into vibration and heat.
- Where marks are lost
- Research design: listing materials without saying why they differ, and not controlling spin or release. Data analysis: using one drop per material, or reporting e without an uncertainty from the h readings and the square root. Conclusion: claiming a ranking when the error bars overlap. Evaluation: ignoring that thin samples on a floor behave as a layered system, and that parallax and frame rate limit the height reading.
- Data
- Needs a ball, metre rule, phone camera with slow motion and clamp stand; the main uncertainty is reading the peak height from video, about ±1 cm.
Rebound height of a ball: which factor matters
Research question. How does the drop height of a tennis ball (0.20 to 1.20 m in 6 steps) affect its coefficient of restitution on a concrete floor?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. Very common as an idea, so it needs a twist. Try temperature of a squash ball (5 to 60 °C in a water bath) to make it your own.
Method, physics and where marks are lost+
- Independent variable
- Drop height from 0.20 to 1.20 m, 6 values, each repeated 5 times. Choose one factor only; the others below stay constant.
- What you measure
- Rebound height measured from 240 fps video beside a metre rule. Coefficient of restitution e = √(hrebound/hdrop), or the speeds either side of the bounce from a microphone or Tracker.
- Controlled variables
- Surface: same floor tile throughout. Ball: same ball, kept at room temperature (checked with a thermometer). Inflation: sealed ball, not changed between runs. Release: from rest by hand, checked on video for spin.
- Physics and graph
- Speed just before impact is v = √(2gh) and after is √(2gh'), so e = √(h'/h). Plot h' against h; the gradient is e². A non-linear graph would show that e depends on speed. Energy lost per bounce is mg(h − h').
- SL and HL
- SL students can plot h' against h and interpret the gradient. To reach the top band, compare several bounces on one drop and discuss deformation and air drag. HL students may use a model of the ball as a damped spring.
- Where marks are lost
- Research design: several variables are changed together so no conclusion is possible. Data analysis: rebound height is read by eye with large uncertainty. Evaluation: ignores parallax and the ball's spin.
- Data
- A ball, a metre rule and a phone camera are enough; the main uncertainty is reading the rebound peak.
Stored energy in springs of different stiffness and construction
Research question. How does the spring constant k of five helical steel springs (k about 5 to 60 N/m) affect the elastic energy stored, found from the area under the force-extension graph, when each is stretched to a fixed extension of 0.100 m?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. Sound and easy, but basic unless you add series and parallel prediction or hysteresis. Pick it if you want a clean, well-controlled dataset, and add a loading-unloading loop to make it yours.
Method, physics and where marks are lost+
- Independent variable
- Spring identity, five to six springs of different stiffness (different wire diameter or coil number), each characterised by its own k. Alternatively vary the number of identical springs in series or parallel, giving 5+ effective values of k.
- What you measure
- Extension measured with a metre rule (or a marker and camera) for at least six hanging masses per spring, three repeats each. Force from mg. Stored energy from the area under the F-x graph and compared with ½kx².
- Controlled variables
- Final extension fixed at 0.100 m using a marked stop position. Stay within the elastic limit by checking the spring returns to its original length. Same rule and reading height to limit parallax. Mass values from one balance.
- Physics and graph
- F = kx and E = ½kx². Plot F against x for each spring, gradient is k. Then plot E against k for the fixed extension, which should be a straight line through the origin with gradient ½x².
- SL and HL
- SL students find k for each spring and compare ½kx² with the graph area. Top band work tests the linearity limit, compares series and parallel prediction of k, and estimates energy lost when a spring is released and oscillates.
- Where marks are lost
- Research design: the original question is vague about 'spring type', so define exactly what changes. Data analysis: forgetting uncertainty in gradient and propagation to E. Conclusion: not comparing stored energy with the prediction. Evaluation: ignoring spring mass and hysteresis.
- Data
- Springs, slotted masses, hanger and metre rule are enough; the main uncertainty is reading the extension to about 1 mm.
Water drop release height and rebound from a water surface
Research question. How does the release height of a 50 microlitre water drop (10 to 60 cm, 6 heights) affect the height of the small secondary droplet that jumps up from a water surface?
- A.3 Work, energy and power
- SL and HL
- Hard data
- Rarely listed
My take. Interesting but risky because rebound can be rare and scattered. Choose it only if you have slow-motion video; a safer twist is measuring the crater or splash height instead.
Method, physics and where marks are lost+
- Independent variable
- Release height of the drop measured from the surface, 10 to 60 cm in 10 cm steps, 5 drops per height, delivered by a burette or syringe with a fixed tip.
- What you measure
- Rebound height of the droplet read from high-speed video (slow-motion phone, 240 fps) against a ruler in the frame. Impact speed calculated from height, and the ratio of rebound to fall height found.
- Controlled variables
- Drop size, by using the same tip and counting the mass of 20 drops. Depth and width of the water tray. Lighting and camera position, fixed with a clamp. Water temperature and any surface film or dust, by using fresh water each set.
- Physics and graph
- Impact speed v = √(2 g h), so kinetic energy at impact is proportional to h. Plot rebound height against fall height and see if the line is straight; the gradient gives the efficiency of energy return. Consider surface tension energy of the droplets formed.
- SL and HL
- SL: rebound versus fall height graph and an energy efficiency estimate. Top band: compare with surface energy 4 pi r2 sigma and explain why the rebound is not a single simple bounce and may only occur in a limited height range. HL adds nothing needed.
- Where marks are lost
- Research design: not stating how the rebound is defined. Data analysis: reading a fast event by eye with no video. Conclusion: claiming energy conservation when the result shows a small fraction returned. Evaluation: the rebound only appears at certain heights, and scatter is large.
- Data
- Needs slow-motion video and good lighting; the main uncertainty is the small secondary droplet, which is irregular and may not occur at every height.
Where a rubber cord stops obeying Hooke's law
Research question. How does the elastic energy stored in a rubber cord differ from the value predicted by Hooke's law as the extension increases from 2 cm to 30 cm in 2 cm steps?
- A.3 Work, energy and power
- SL and HL
- Easy data
- Rarely listed
My take. Good if you use rubber, where the physics is interesting. Personalise it by comparing two different cords or a band and a spring.
Method, physics and where marks are lost+
- Independent variable
- Extension of a rubber cord or elastic band, 2 cm to 30 cm in 2 cm steps (15 values), during loading and again during unloading.
- What you measure
- Force from a force sensor or a set of slotted masses, extension from a fixed metre rule. Stored energy is found from the area under the force against extension graph by the trapezium rule, then compared with ½kx² using the initial gradient.
- Controlled variables
- Cord sample: the same piece and original length for every run. Temperature: room conditions, and rest between cycles to limit hysteresis. Rate of loading: slow, steady steps with a fixed 10 s wait before each reading. Zero position: the unstretched length is checked before each run.
- Physics and graph
- Hooke's law F = kx and elastic energy E = ½kx² = area under the F-x graph. Plot F against x and compare with the straight-line extrapolation. The difference between loading and unloading areas is the energy dissipated as thermal energy.
- SL and HL
- SL: plot F-x, find the limit of proportionality and compare energies. Top band: quantify the hysteresis loop and relate it to energy lost, with a proper uncertainty on the area. HL adds nothing syllabus-wise but can use a fitted non-linear model.
- Where marks are lost
- Research design: a steel spring is chosen, which stays linear over the range, so there is nothing to investigate. Data analysis: area from crude graph counting with no uncertainty. Conclusion: an unsupported limit value. Evaluation: not commenting on time dependence (creep) of rubber.
- Data
- Slotted masses, a rule and a stand are enough; the main uncertainty is creep, so readings drift with waiting time.
Ideas were collected from public lists and published IA titles, merged when they are the same investigation, and rewritten from scratch. “On N sites” counts how many public lists carry the same investigation. How this list was made.
Frequently asked questions
What are good IB Physics IA ideas on work, energy and power?
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Good starting points with easy data that few sites list are ball speed at the foot of a ramp against release height, energy lost by a trolley on different ramp surfaces and ramp angle and the run-out distance of a rolling ball. Each one gives a straight-line graph from school equipment, which is what the Data analysis and Conclusion criteria need.
Which work, energy and power IA ideas are overdone?
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None of the 22 ideas on this page appears on three or more public lists, so any of them is less likely to look like a copy.
Can I do a work, energy and power IA at SL?
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Yes. All 22 ideas on this page use physics from the SL syllabus. HL students can take the same ideas further, and each idea says how.