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A Level · Cambridge (CIE) · 9709

Respect physical boundaries and singular times in changing-quantity models

Use separation on the permitted interval, stop a model at an empty vessel or pole and check whether an algebraic continuation still satisfies the original law.

Pure Mathematics 3 · Differential equations · 3.8
Exam scope and assessment notes

Pure Mathematics 3 (Paper 3, A Level) · Mathematics 9709, 2026–2027, section 3.8. Paper 1 calculus and Paper 3 Integration are assumed. This pathway uses first-order separable equations, including Paper 3 integration methods, with all context assumptions supplied. Second-order equations and integrating-factor methods are beyond this mapped requirement. Check factors before dividing, retain equilibrium solutions, and state the interval and physical meaning of an initial-value solution. Written practice is self-checked; human subject-teacher review remains pending.

Before you begin

  • Integrate powers and logarithmic composites after separation.
  • Check non-negative quantities, original denominators and elapsed-time bounds.

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

Quick readiness check

If √V = 3 − t with V ≥ 0, what restriction follows?

What you will learn

  • Solve changing-quantity equations with square-root or variable-denominator terms.
  • Identify a physical boundary or singular time and interpret a solution only on its valid interval.
Stop the draining branch at emptyV = (3 − t)², 0 ≤ t ≤ 3369V (L)t (min)Invalid refill012345No inflow: V = 0 after 3 min
The blue draining branch solves V′ = −2√V, V(0) = 9 L: V = (3 − t)² only for 0 ≤ t ≤ 3 min. The marked point at t = 3 has V = 0. With no inflow, the green continuation stays at zero after emptying and satisfies the original law. The dashed red curve is the invalid continuation of the same polynomial past 3 min: it increases and violates the negative rate law for positive V. Squaring √V = 3 − t must not remove its non-negative right-hand-side restriction. The plot extends to 5 min to make this distinction visible.

Squaring can hide the end of a physical branch

Suppose a supplied vessel model is V′ = −2√V, V(0) = 9 L, with t in minutes and V ≥ 0. For V > 0, separation gives 2√V = −2t + C, so √V = 3 − t. The square-root relation requires t ≤ 3. Thus V = (3 − t)² on 0 ≤ t ≤ 3, reaching an empty vessel at 3 min. The coefficient has units √L per minute so the right-hand side is a volume rate.

The same squared expression at t > 3 increases and no longer satisfies V′ = −2√V: its derivative is positive, while the original right-hand side is negative for a positive volume. If the model has no inflow, staying at V = 0 after emptying satisfies the original rate law. Check this boundary directly, since dividing by √V excluded zero. A convenient polynomial formula is not permission to interpret a vessel as refilling.

A pole and an undefined physical denominator are different boundaries

For y′ = y² and y(0) = 1, integration gives y = 1/(1 − t). The interval through the initial point is t < 1, and forward time uses 0 ≤ t < 1. The solution grows without bound as t approaches 1 from below. The negative formula value at t = 2 lies beyond an undefined pole; it is not a finite continuation of the same initial-value solution. The singularity also warns against indefinite interpretation of a supplied physical model.

In a well-mixed vessel losing 2 L/min with no inflow, an initial 20 L gives V = 20 − 2t. If the amount of dissolved material is S grams, the supplied uniform concentration is S/V g/L, so the loss law is S′ = −2S/(20 − 2t). It is defined only while liquid remains, 0 ≤ t < 10. Starting at 10 g gives S = 10 − t, and the concentration is 1/2 g/L before emptying. At t = 10 the ratio is 0/0, so the concentration formula is undefined even though its limit is 1/2.

Pause and explain

For y = 1/(1 − t), y(0) = 1, is the value at t = 2 a continuation through t = 1?

Put the idea to work

Worked example

Solve V′ = −2√V, V(0) = 9 L, and explain the valid draining interval and what happens at its end.

Show the worked solution
  1. For positive V, integrate dV/√V = −2dt to obtain √V = 3 − t.
  2. Non-negativity of the square root gives V = (3 − t)² for 0 ≤ t ≤ 3; the vessel empties at 3 min.
  3. Beyond that time the same squared formula violates the original rate sign; with no inflow, V = 0 is a valid continuation.

Answer V = (3 − t)² for 0 ≤ t ≤ 3; empty at 3 min, then stays zero under the no-inflow law.

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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

V′ = −3√V, V(0) = 16 L, with time in minutes. Find the draining solution, V(2) and the emptying time.

Give me a hint

Integrate for V > 0 and keep the non-negative square-root relation.

Compare my reasoning
  1. Separation gives 2√V = −3t + 8, so √V = 4 − 3t/2.
  2. Thus V = (4 − 3t/2)² on 0 ≤ t ≤ 8/3; at t = 2 the volume is 1 L.
  3. The vessel empties at 8/3 min; continuing the squared polynomial past that boundary would reverse the rate sign.

V = (4 − 3t/2)², 0 ≤ t ≤ 8/3; V(2) = 1 L; empty at 8/3 min.

Look for these in your work

  • Check the coefficient in the square-root primitive.
  • Keep the physical interval when evaluating and interpreting the result.
2 · Independent

Solve y′ = y² with y(0) = 1. State its forward interval and behaviour near the singular time, and explain why evaluating the same formula at 2 does not continue this solution.

Give me a hint

Integrate −1/y = t + C before applying the condition.

Compare my reasoning
  1. The initial condition gives y = 1/(1 − t).
  2. The forward solution has 0 ≤ t < 1 and grows without bound as t approaches 1 from below.
  3. At t = 1 the formula is undefined; its value −1 at t = 2 belongs to a separate branch beyond the pole.

y = 1/(1 − t), 0 ≤ t < 1; diverges as t approaches 1 from below and cannot continue finitely through it.

Look for these in your work

  • Use the initial condition with the correct reciprocal sign.
  • State the interval and distinguish a separate algebraic branch from continuation.
3 · Transfer

A vessel starts with 20 L containing 10 g of dissolved material, uniformly mixed. No liquid enters; 2 L/min leaves. Concentration is S/V g/L. Form and solve the amount equation, find S(8) and state what is undefined at emptying.

Give me a hint

Outflow of material equals liquid outflow times its uniform concentration.

Compare my reasoning
  1. V = 20 − 2t, so S′ = −2S/(20 − 2t) for 0 ≤ t < 10.
  2. Integration gives ln S = ln(20 − 2t) + C; the initial condition gives S = (20 − 2t)/2 = 10 − t.
  3. At 8 min, S = 2 g and V = 4 L, so concentration is 1/2 g/L. At emptying the amount tends to zero, but S/V is 0/0 and undefined.

S′ = −2S/(20 − 2t); S = 10 − t for 0 ≤ t < 10; S(8) = 2 g; concentration is undefined at the empty vessel.

Look for these in your work

  • Use the amount-to-volume ratio in the stated loss law.
  • Retain the pre-emptying interval and distinguish a ratio limit from its endpoint value.

Common mistakes

  • Preserve a square-root sign condition after squaring.
  • An initial-value solution cannot pass through an undefined pole.
  • A concentration ratio is undefined when both the amount and liquid volume are zero.
Recall without your notes

What can you explain now?

Why is (3 − t)² invalid as the same draining solution for t > 3?

Compare with the explanation

Its derivative becomes positive while −2√V is negative for positive V.

Check the original equation and the non-negative square-root relation, not the squared expression alone.

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

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Make it stick

Solve a changing-quantity model, identify the first physical or mathematical boundary and check the original rate law before continuing an algebraic expression past it.

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.

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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