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A Level · Cambridge (CIE) · 9709

Use vertical height in gravitational potential energy

Calculate mgΔh, distinguish height from distance along a slope and keep energy differences unchanged when the reference level changes.

Mechanics · Energy, work and power · 4.5
Exam scope and assessment notes

Mechanics (Paper 4, AS & A Level) · Mathematics 9709, 2026–2027, section 4.5. Use g = 10 m s⁻² throughout these problems. Masses are positive and constant. Work by a constant force is Fd cos θ, with θ between force and displacement; scalar-product notation is not required. Kinetic energy is ½mv² and gravitational potential-energy change is mgΔh. State the system and count gravitational work or potential-energy change once, not both. Mechanical energy is conserved only under the stated loss-free model; friction and supplied resistance transfer mechanical energy to other forms. Smooth curved-slide examples use overall energy changes and assume contact throughout, rather than requiring a normal-reaction calculation. Average power is work divided by elapsed time; P = Fv applies to a force along the motion. Constant driving power generally gives variable force and acceleration; instantaneous calculations do not justify constant-acceleration formulae over a whole journey. Check string, contact and motion-state changes before continuing a model. Written practice is self-checked; human subject-teacher review remains pending.

Before you begin

  • Find vertical height from slope distance and sine.
  • Calculate signed changes between two levels.

Work on paper. Try each question before revealing help, and explain why your method works.

Quick readiness check

A particle travels distance s up a plane inclined at θ to horizontal. What height change enters mgΔh?

What you will learn

  • Use vertical height change in gravitational potential-energy calculations.
  • Relate gravitational work to potential-energy change without double counting.

Potential-energy differences depend on vertical height

In a uniform gravitational field, potential energy relative to a chosen reference level is U = mgh. Its change is mg(h₂ − h₁). For a 4 kg particle moved 5 m up a 30° slope, the vertical rise is 5 sin 30° = 2.5 m, so ΔU = 4 × 10 × 2.5 = 100 J. Using 5 m directly would confuse distance along the plane with vertical height.

Rising gives positive ΔU; falling gives negative ΔU. A 2 kg particle falling 4 m has ΔU = −80 J. Gravity then does +80 J of work. For any change in this field, gravitational work is −ΔU. The path shape does not alter this height-based gravitational contribution, though friction or other forces can add path-dependent work.

Choose a datum but do not count gravity twice

A 5 kg particle rises from height 2 m to 5 m above ground. With ground as datum, U changes from 100 to 250 J, giving +150 J. Choosing a datum 3 m above ground instead gives heights −1 and +2 m, so U changes from −50 to +100 J. The same +150 J difference is physically relevant; negative reference potential energy is allowed.

In a kinetic-energy work balance, include gravitational work with its sign. In a mechanical-energy balance using K + U, put gravity into ΔU and include only the other work terms on the work side. Including both −mgΔh as work and +mgΔh as potential change in the same balance counts gravity twice. State the chosen form and system before inserting numbers.

Pause and explain

A particle gains potential energy 100 J. What work does gravity do?

Put the idea to work

Worked example

A 4 kg particle moves 5 m up a 30° plane. Find potential-energy change and work by gravity using g = 10.

Show the worked solution
  1. Vertical rise is Δh = 5 sin 30° = 2.5 m.
  2. Potential-energy change is ΔU = 4 × 10 × 2.5 = +100 J.
  3. Gravity does the opposite signed work, −100 J.

Answer ΔU = +100 J; gravitational work −100 J.

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From guided practice to a new situation

Write your answer and reasoning first. Use a hint only if you are stuck. The model solution is for self-checking; your written work is not automatically marked.

1 · Guided

A 3 kg particle rises vertically by 2 m. Find its potential-energy change and work by gravity.

Give me a hint

Use the signed vertical change and opposite signs for potential change and gravity work.

Compare my reasoning
  1. Δh = +2 m, so ΔU = 3 × 10 × 2 = +60 J.
  2. Gravitational work is −ΔU = −60 J.
  3. The rise increases stored gravitational energy while gravity opposes the displacement.

ΔU = +60 J; gravitational work −60 J.

Look for these in your work

  • Use g = 10 as supplied.
  • Keep the two quantities equal in magnitude and opposite in sign.
2 · Independent

A 2 kg particle falls from one level to another 4 m lower. Find potential-energy change and work by gravity.

Give me a hint

A fall gives a negative final-minus-initial height change.

Compare my reasoning
  1. Δh = −4 m.
  2. ΔU = 2 × 10 × (−4) = −80 J.
  3. Gravity does +80 J of work as the particle moves down.

ΔU = −80 J; gravitational work +80 J.

Look for these in your work

  • Use signed height change.
  • Do not report a positive potential gain for a fall.
3 · Transfer

A 5 kg particle rises from 2 m to 5 m above ground. Calculate both endpoint potential energies and their difference using first ground, then a level 3 m above ground, as the datum.

Give me a hint

Subtract the same reference height from both endpoints.

Compare my reasoning
  1. Ground datum gives energies 5 × 10 × 2 = 100 J and 5 × 10 × 5 = 250 J, difference 150 J.
  2. The higher datum gives heights −1 and +2, energies −50 J and +100 J.
  3. Their difference is again +150 J; the reference choice changes endpoint values, not this change.

Ground: 100 to 250 J; higher datum: −50 to +100 J; ΔU = +150 J in both.

Look for these in your work

  • Use the same datum for both endpoints in each calculation.
  • Retain negative relative height where appropriate.

Common mistakes

  • Use vertical height rather than slope distance.
  • Negative reference potential energy is possible.
  • Count gravity as work or potential-energy change once.
Recall without your notes

What can you explain now?

Does changing the potential-energy datum change the energy difference between the same two positions?

Compare with the explanation

No; the additive reference shift cancels from the difference.

Both endpoint values change by the same constant for the same mass.

After trying it yourself, choose your next review. This is your self-assessment.

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Make it stick

Find vertical height change, calculate mgΔh and include the gravitational contribution exactly once in the balance.

If you needed the solution, close it and solve the problem again from a blank page. A correct answer is stronger when you can explain the reason for each step.

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Course scope and assessment

312 sequenced lessons provide 936 guided, independent and application problems covering the 160 objectives in sections 1.1–1.8, 2.1–2.6, 3.1–3.9, 4.1–4.5, 5.1–5.5 and 6.1–6.5. The map lists all 38 sections across six alternative components; all eight Pure Mathematics 1 sections and all six Pure Mathematics 2 sections, from Paper 2 Algebra through Numerical solution of equations, currently have full teaching sequences. Paper 3 Algebra, section 3.1, links the six shared foundation lessons plus six lessons on partial fractions and rational binomial expansions; Paper 3 logarithms, trigonometry and numerical equations use the shared lessons, with the Paper 1 graph foundation linked into trigonometry. Paper 3 differentiation combines the shared methods with its inverse-tangent derivative lesson. Paper 3 Integration links four shared standard and identity lessons plus seven advanced lessons, covering all six section 3.5 requirements. Eight Vectors lessons cover all six section 3.7 requirements, with 2D and 3D line and solid applications. Nine Differential equations lessons cover all four section 3.8 requirements, including Paper 3 integration techniques, initial conditions, equilibrium solutions and conditional model interpretations. Eleven Complex numbers lessons cover all eight section 3.9 requirements, with seven Argand diagrams and explicit argument and boundary checks. All nine Pure Mathematics 3 sections now have teaching linked to every mapped requirement. Nine Forces and equilibrium lessons cover all seven section 4.1 requirements, with six force diagrams, signed incline-friction intervals, reaction-dependent pull and push limits and separate-body third-law checks. Nine Kinematics lessons cover the four official section 4.2 requirements, with the graph requirement mapped to three relationships. Six motion diagrams support directed quantities, graph slopes and signed areas, Paper 1 time-calculus methods, reversal distances, constant-acceleration stages and shared-clock particle meetings. Six Momentum lessons cover both section 4.3 requirements, including signed system totals, conservation assumptions, outgoing velocities, coalescence, unknown masses and successive impacts. Four diagrams show system momentum through the stipulated events, and supplied kinetic-energy checks distinguish conservation of momentum from changes in kinetic energy. Twelve Newton’s laws lessons cover all four section 4.4 requirements, with vertical support and release stages, rough horizontal and incline motion, inferred parameters, hanging and surface pulley systems, rigid tow-bar thrust and slack-string transitions. Seven force diagrams support the separate-particle balances. Nine Energy, work and power lessons cover all five section 4.5 requirements, with angle-dependent work, kinetic and reference potential energy, signed net-work balances, smooth curved slides, rough and driven slopes, ideal connected-system energy and instantaneous power on hills. Five diagrams distinguish the energy inputs, losses and valid positive-speed force model. All five Mechanics sections now have teaching and staged practice linked to their mapped requirements. Thirteen Representation of data lessons cover all five section 5.1 requirements, including choice and limitations of displays, ordered and back-to-back stems, raw summaries and box plots, unequal-width density histograms, cumulative-frequency interpolation, descriptive moment calculations, grouped estimates, coding, combining two datasets and correcting totals. Six accessible diagrams retain repeated observations and distinguish numerical spread, frequency area and estimated readings. Ten Permutations and combinations lessons cover both official section 5.2 requirements, with selection and ordered roles, repeated objects, adjacency blocks, non-adjacency gaps, leading-zero cases, labelled multi-row seating and mixed restrictions. Six accessible diagrams show outcome trees, ordered versus unordered choices, repeated copies, blocks, gaps and distinct row seats. Eleven Probability lessons cover all four section 5.3 requirements, with equiprobable elementary outcomes, selection-based probabilities, complements and disjoint regions, independence tests, restricted sample spaces, two-way tables, replacement and removal trees, reversed conditions and unknown parameters. Seven accessible diagrams show dice outcomes, random subsets, event regions, a conditioned grid, a count table and two probability trees. Twelve Discrete random variables lessons cover all three official section 5.4 requirements, with complete probability tables, moment and parameter checks, binomial assumptions, exact probabilities and moments, geometric first-success probabilities, tails, expectation and integer reliability thresholds. Six accessible diagrams distinguish outcome grouping, weighted moments, fixed trials, discrete probability bars, waiting conventions and integer tail deadlines. Twelve Normal distribution lessons cover all three official section 5.5 requirements, with continuous-area interpretation, MF19 cumulative tables, full standardisation, tail and interval regions, conditional probabilities, percentiles, one- and two-parameter inference, binomial suitability, continuity corrections and approximate integer thresholds. Seven accessible diagrams show model areas, table reading, aligned scales, intervals, quantiles, matched binomial and normal shapes and whole integer cells. All five Statistics 1 sections now have teaching and staged practice linked to their mapped requirements. Fourteen Poisson distribution lessons cover all five official section 6.1 requirements, with homogeneous event-count assumptions, exposure scaling, exact masses and tails, conditional count events, moments, parameter inference, probability duration targets, disjoint and overlapping windows, rare-count binomial approximations, matched normal approximations and continuity corrections. Nine accessible diagrams show event exposures, unit conversions, discrete bars, complete tail complements, population moments, shared windows, approximate count models and integer cells. Exact checks distinguish approximate and exact close-target decisions. Fourteen Linear combinations lessons cover the six listed results in official section 6.2, with affine moments, signed scales and constant cases, expectation without independence, independent squared variance contributions, fixed and random fees, independent copies versus reused values, affine normal events, independent normal sums and differences, weighted and conditional areas, coefficient inference, exact independent Poisson sums and overlapping exposure limits. Nine accessible diagrams distinguish scale changes, variance contributions, component costs, copy mechanisms, aligned normal scales, summed areas, Poisson count pairs and unsupported distribution claims. Fourteen Continuous random variables lessons cover both official section 6.3 requirements, with density validity and units, support-aware intervals, complements and conditional regions, first and second moments, percentiles by direct density areas, symmetry checks, parameter inference, infinite-support power and exponential integrals, divergent-moment limits and combined applications. Nine accessible diagrams distinguish density height from probability, normalisation, negative-density failures, central and conditional areas, mean versus median, percentile locations and partial infinite tails. Explicit cumulative distribution function knowledge is not required. Eighteen Sampling and estimation lessons cover all eight official section 6.4 requirements, with population and frame definitions, random-number selection, sampling-quality limits, independent sample-mean moments, normal means, CLT conditions, SE scaling, raw, summarised and coded unbiased estimates, known-variance and large-sample mean intervals, repeated-sampling interpretation, precision planning, proportion intervals, sparse-outcome limits and contextual applications. Ten accessible diagrams distinguish selection frames, number rejection, repeated sample means, population versus mean density, CLT models, variance divisors, interval targets, illustrative coverage, integer size checks and proportion margins. Eighteen Hypothesis tests lessons cover all five official section 6.5 requirements, with pre-specified alternatives, inclusive count tails, explicit equal-tail conventions, integer critical regions and actual significance, exposure-aware Poisson tests, continuity-corrected count approximations, normal and large-sample mean tests, confidence-interval connections, error classifications, fixed-region binomial, Poisson and normal error probabilities and sample-size power comparisons. Nine accessible diagrams show the testing procedure, exact count regions, unequal Poisson tails, discrete significance jumps, corrected count boundaries, matching mean intervals and alternative error distributions. All shared lessons are counted once in the course total. All 38 sections now link teaching and practice. Eight earlier overview lessons remain available, but do not count as full section coverage. This is a content-availability measure, not full programme completion or exam readiness. Written practice is self-checked, not officially marked. Check the 2028–2030 syllabus separately if sitting an examination from 2028; this teaching map uses 2026–2027 requirements.

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