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A Level · Cambridge (CIE) · 9709

Join constant acceleration stages without resetting velocity

Carry final velocity and position into the next stage, use local stage durations and check a complete journey with velocity–time areas.

Section 4.2 · Kinematics of motion in a straight line

Mechanics · Straight-line kinematics · 4.2
Exam scope and assessment notes

Mechanics (Paper 4, AS & A Level) · Mathematics 9709, 2026–2027, section 4.2. Motion is restricted to one dimension. Choose a positive direction; distance and speed are scalars, while displacement, velocity and acceleration carry a direction. Deceleration means decreasing speed, not necessarily negative acceleration. Calculus uses Paper 1 techniques only. Constant-acceleration formulae require constant acceleration on the stated interval; use a new interval and its initial velocity when conditions change. Where vertical motion occurs, use the supplied g = 10 m s⁻² and the stated no-air-resistance model. Written practice is self-checked; human subject-teacher review remains pending.

Before you begin

  • Use the constant-acceleration equations.
  • Calculate signed areas and split at velocity zeros.

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

Quick readiness check

A particle reaches 6 m s⁻¹ after 2 s, then continues uniformly for 4 s. What displacement belongs to that uniform stage?

What you will learn

  • Solve a journey with successive constant-acceleration and uniform-velocity stages.
  • Track velocity continuity and account for a reversal inside a stage.
From rest, acceleration +2 m s⁻² for 4 s reaches velocity 8 m s⁻¹. Uniform motion lasts 3 s, then acceleration −4 m s⁻² reaches the first stop after another 2 s. The continuous graph joins (0, 0), (4, 8), (7, 8) and (9, 0). Stage areas are 16, 24 and 8 m, giving distance and displacement 48 m over 9 s. Each stage begins at the preceding stage’s final velocity, while its acceleration can change at a join.Carry velocity between stagesStage durations: 4 s, 3 s, 2 sv (m s⁻¹)t (s)0479v = 816 m24 m8 mOne-dimensional motion · labelled units
From rest, acceleration +2 m s⁻² for 4 s reaches velocity 8 m s⁻¹. Uniform motion lasts 3 s, then acceleration −4 m s⁻² reaches the first stop after another 2 s. The continuous graph joins (0, 0), (4, 8), (7, 8) and (9, 0). Stage areas are 16, 24 and 8 m, giving distance and displacement 48 m over 9 s. Each stage begins at the preceding stage’s final velocity, while its acceleration can change at a join.

Each stage has its own duration and initial velocity

When acceleration changes, begin a new interval with the previous stage’s final velocity. Keep an elapsed-time record separately from each stage’s local duration. A particle starts from rest, accelerates at 2 m s⁻² for 4 s, travels at its reached velocity for 3 s, then accelerates at −4 m s⁻² until it first stops. The first stage ends with v = 8 m s⁻¹ and s = 16 m; the uniform stage adds 8 × 3 = 24 m.

The stopping stage starts with u = 8, not zero, and 0 = 8 − 4τ gives duration τ = 2 s. Its displacement is ½(8 + 0) × 2 = 8 m. Total time is 4 + 3 + 2 = 9 s and displacement is 48 m. All velocities are non-negative, so distance is also 48 m. A velocity graph joins (0, 0), (4, 8), (7, 8) and (9, 0); the two triangles and rectangle provide a separate check.

A stage need not end at the first stop unless the problem says so

If a particle starts with u = 6 and a = −2 for a fixed 4 s interval, it stops at 3 s but then reverses during the remaining second. Its final velocity is −2 m s⁻¹, its displacement is 8 m and its distance is 9 + 1 = 10 m. A later uniform stage must start at that negative velocity; do not silently stop the model at the first velocity zero when the duration is fixed.

Use a supplied first-stop condition to select a stopping time; use a supplied duration to continue through any reversal. Add stage displacements with signs to obtain the whole-journey displacement, and split inside stages when adding distance. Idealised acceleration changes give corners in a continuous velocity graph; they do not reset velocity instantaneously. The model describes the stated intervals only, and extending a deceleration past a stop requires explicit ongoing-motion assumptions.

Pause and explain

For u = 6 and constant a = −2 over a fixed 4 s, what final velocity must pass into the next stage?

Put the idea to work

Worked example

From rest, a particle accelerates at 2 m s⁻² for 4 s, continues uniformly for 3 s, then has a = −4 m s⁻² until its first stop. Find total time and distance.

Show the worked solution
  1. Stage 1 gives v = 8 m s⁻¹ and displacement 16 m; stage 2 adds 24 m in 3 s.
  2. Stage 3 starts at 8 m s⁻¹ and stops after 2 s, adding 8 m.
  3. Total time is 9 s and distance is 16 + 24 + 8 = 48 m, matching the non-negative velocity-graph area.

Answer Total time 9 s; distance and displacement 48 m.

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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

From rest, a particle accelerates at 3 m s⁻² for 2 s, travels uniformly for 4 s, then has a = −2 m s⁻² until it first stops. Find total time and distance.

Give me a hint

Find each stage’s reached velocity, duration and area before adding totals.

Compare my reasoning
  1. The first stage reaches 6 m s⁻¹ and adds ½ × 3 × 2² = 6 m; uniform travel adds 6 × 4 = 24 m.
  2. The stopping stage takes 6/2 = 3 s and adds ½ × 6 × 3 = 9 m.
  3. Total time is 2 + 4 + 3 = 9 s and distance is 6 + 24 + 9 = 39 m.

Total time 9 s; distance and displacement 39 m.

Look for these in your work

  • Carry the velocity 6 m s⁻¹ into both later stages.
  • Add durations and non-negative areas separately.
2 · Independent

A particle initially moves at 10 m s⁻¹, has a = −2 m s⁻² for 3 s, then continues at its reached velocity for 5 s. Find final velocity, total time and total displacement.

Give me a hint

The first stage does not last long enough to stop the particle.

Compare my reasoning
  1. After 3 s, v = 10 − 2 × 3 = 4 m s⁻¹, and displacement is 10 × 3 − 3² = 21 m.
  2. The uniform stage adds 4 × 5 = 20 m and retains v = 4 m s⁻¹.
  3. Total time is 8 s and displacement is 21 + 20 = 41 m; distance is also 41 m because no reversal occurs.

Final velocity +4 m s⁻¹; total time 8 s; displacement and distance 41 m.

Look for these in your work

  • Use 4 m s⁻¹ for the second stage rather than the original 10.
  • Check velocity remains positive through the first stage.
3 · Transfer

A particle starts with v = +6 m s⁻¹, has constant a = −2 m s⁻² for 4 s, then continues uniformly for another 3 s. Find final velocity, whole-journey displacement and distance.

Give me a hint

The first stage contains a reversal, so split its distance at the zero velocity.

Compare my reasoning
  1. First-stage velocity reaches zero at 3 s and ends at −2 m s⁻¹ after 4 s.
  2. Its displacement is 6 × 4 − 4² = 8 m; its distance is 9 + 1 = 10 m.
  3. The uniform stage adds displacement −2 × 3 = −6 m and distance 6 m, giving total displacement +2 m and distance 16 m.

Final velocity −2 m s⁻¹; displacement +2 m; distance 16 m over 7 s.

Look for these in your work

  • Continue through rest because the first-stage duration is fixed.
  • Preserve negative velocity into uniform travel and add path lengths separately.

Common mistakes

  • Use stage duration rather than total elapsed time in a stage’s equations.
  • Carry the reached velocity into the next stage.
  • A fixed acceleration interval can continue through rest and reverse direction.
Recall without your notes

What can you explain now?

If stage 1 ends with v = −2 m s⁻¹ and stage 2 is uniform motion, what is stage 2’s initial velocity?

Compare with the explanation

−2 m s⁻¹.

Uniform motion retains the signed velocity unless an explicitly modelled event changes it.

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Make it stick

Carry velocity between stages, use local durations and split reversals before adding whole-journey distance.

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Keep learning Mathematics

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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