Models & Qualitative Behavior

Study Sheet

Models & Qualitative Behavior

Growth, cooling, mixing, and equilibria

The Classic Models

Tip
Logistic growth
PP′510−112fastest at K/2
The growth rate P′=P(1−P/10)P' = P(1 - P/10): zero at 00 and K=10K = 10, largest at P=5P = 5; arrows show the flow toward KK.

dPdt=rP(1−PK)\tfrac{dP}{dt} = rP\left(1 - \tfrac{P}{K}\right): growth is proportional to both the population and the remaining room. The rate is a downward parabola in PP, fastest exactly at half capacity P=K/2P = K/2, and every positive solution flows to the carrying capacity KK.

Why this form: a population far below capacity grows like rPrP, as if resources were unlimited; the factor 1−PK1 - \tfrac PK is the fraction of room still available, which throttles growth to 00 as PP reaches KK and makes it negative above KK. The rate f(P)=rP(1−PK)f(P) = rP\left(1 - \tfrac PK\right) is a parabola with zeros at 00 and KK, so its vertex is midway, at P=K2P = \tfrac K2, where the rate is rK4\tfrac{rK}{4}. With r=1r = 1 and K=10K = 10 the fastest growth is 2.52.5 per unit time, at P=5P = 5.

Tip
Newton cooling & mixing tanks

Cooling: the excess over ambient decays exponentially — if the excess halves in 10 minutes it halves again in the next 10. Mixing: dSdt=(rate in)−SV(flow out)\tfrac{dS}{dt} = (\text{rate in}) - \tfrac{S}{V}(\text{flow out}); the equilibrium is where inflow balances outflow, always equal to incoming concentration times tank volume.

Why the excess: Newton's law says heat flows at a rate proportional to the temperature difference, T′=−k(T−Tamb)T' = -k(T - T_{\text{amb}}). The difference u=T−Tambu = T - T_{\text{amb}} satisfies u′=−kuu' = -ku, so it — not TT — decays exponentially, and equal times multiply it by equal factors. For a tank, bookkeeping gives the equation: salt enters at (concentration in)×\times(flow in) and leaves at (current concentration S/VS/V)×\times(flow out). With equal flows, the equilibrium S′=0S' = 0 is where the tank's concentration matches the incoming one, so S=(incoming concentration)×VS = (\text{incoming concentration})\times V.

Example
Euler’s method, honestly
ty0.2545666.256.594eᵗ
One Euler step of 0.50.5 (dashed) and two steps of 0.250.25 (faint) both fall below 4et4e^t at t=0.5t = 0.5.

One step of size hh: yn+1=yn+h f(yn)y_{n+1} = y_n + h\,f(y_n) — follow the tangent line briefly, then re-aim. On y′=yy' = y from y(0)=4y(0)=4 with h=0.5h = 0.5: estimate 66 vs. the true 4e0.5≈6.594e^{0.5} \approx 6.59; Euler undershoots convex solutions, and halving hh halves the error.

Why it undershoots here: the solution 4et4e^t bends upward, so its tangent line at t=0t = 0 lies below it, and one step along the tangent ends below the curve: 4+0.5⋅4=64 + 0.5\cdot4 = 6 against 4e0.5≈6.594e^{0.5} \approx 6.59, an error of about 0.590.59. Two steps of h=0.25h = 0.25 re-aim halfway: 4→5→6.254 \to 5 \to 6.25, error about 0.340.34. The error has not quite halved; it approaches exact halving as hh shrinks, because Euler's error is proportional to hh only for small hh (see the proof below).

Side note
Significance: the same equation, twelve costumes

Newton cooling = drug elimination = RC discharge = mixing = depreciation: all u′=−kuu' = -ku about the right variable. Recognizing the archetype is the modeling skill — once you see "rate proportional to amount (or excess)," you already know the solution, the half-life, and the long-run behavior.

Try it
Try it: build then solve

Coffee at 90∘90^\circ in a 20∘20^\circ room cools to 70∘70^\circ in 55 minutes. When does it reach 45∘45^\circ?

Show the answer

Work with the excess over the room, u=T−20u = T - 20: it starts at u(0)=70u(0) = 70 and satisfies u′=−kuu' = -ku, so u=70e−ktu = 70e^{-kt}. At t=5t = 5 the excess is 5050: e−5k=57e^{-5k} = \tfrac57, so k=15ln⁡75≈0.0673k = \tfrac15\ln\tfrac75 \approx 0.0673 per minute. The target 45∘45^\circ is an excess of 2525: 70e−kt=2570e^{-kt} = 25 gives t=ln⁡(70/25)k=5ln⁡2.8ln⁡1.4≈15.3t = \dfrac{\ln(70/25)}{k} = \dfrac{5\ln 2.8}{\ln 1.4} \approx 15.3 minutes. Sanity check: each 55 minutes multiplies the excess by 57\tfrac57, so 70→50→35.7→25.570 \to 50 \to 35.7 \to 25.5 after 1515 minutes — just above 2525, and 15.315.3 minutes finishes the job.

Building a Model from Rates

Tip
Rate in, rate out

A first-order model is a sentence about rates: d(amount)dt=(rate in)−(rate out)\dfrac{d(\text{amount})}{dt} = (\text{rate in}) - (\text{rate out}). Write each rate with units, find the equilibrium where they balance, and look for the archetype: whenever the rate is proportional to the distance from an equilibrium EE, the model is u′=−kuu' = -ku for u=y−Eu = y - E, with solution y=E+(y0−E)e−kty = E + (y_0 - E)e^{-kt}.

Why units first: every term must have units of amount per time (grams per minute, degrees per minute); a term that does not is a modelling error, caught before any calculus. Why the equilibrium: it is the one number the model announces without solving, and the exponential archetype then says exactly how the gap to it closes — by the factor e−ke^{-k} per unit time, with time constant 1k\tfrac1k.

Example
Worked: a thermometer carried outdoors
ty246810510152025(2, 15)(8.64, 24)room 25°
The reading closes half the gap to the room every 22 minutes; 24∘24^\circ arrives at t≈8.64t \approx 8.64.

A thermometer reading 5∘5^\circ is taken from a fridge into a 25∘25^\circ room. After 22 minutes it reads 15∘15^\circ. When does it read 24∘24^\circ?

Model the excess u=T−25u = T - 25 (negative here, since the thermometer is colder than the room): u(0)=−20u(0) = -20, u(2)=−10u(2) = -10, and u′=−kuu' = -ku.

Step 1 — the excess went from −20-20 to −10-10 in 22 minutes: it halves every 22 minutes, so u=−20⋅2−t/2u = -20\cdot2^{-t/2} and T=25−20⋅2−t/2T = 25 - 20\cdot2^{-t/2}. No need to compute kk — the halving time carries the same information (k=ln⁡22≈0.347k = \tfrac{\ln 2}{2} \approx 0.347 per minute).

Step 2 — 24∘24^\circ is an excess of −1-1: 20⋅2−t/2=120\cdot2^{-t/2} = 1, so 2t/2=202^{t/2} = 20 and t=2log⁡220≈8.64t = 2\log_2 20 \approx 8.64 minutes.

Step 3 — check by halvings: 20→10→5→2.5→1.2520 \to 10 \to 5 \to 2.5 \to 1.25 takes 88 minutes, and 1.25→11.25 \to 1 needs a bit under half of another 22-minute period.

Step 4 — the last degree takes longest: going from 15∘15^\circ to 20∘20^\circ took 22 minutes, but 20∘20^\circ to 24∘24^\circ takes more than 44 more, because the driving difference keeps shrinking.

Example
Worked: a tank that fills while it mixes
ty102030405050100150200(50, 177.5)2VS
Salt S(t)S(t) (solid) climbing toward 2V2V, the amount at the incoming concentration (dashed).

A tank holds 5050 L of water with 1010 g of salt dissolved. Brine with 22 g/L enters at 33 L/min; the mixed solution leaves at 22 L/min. How much salt is in the tank when it holds 100100 L?

The volume grows by 11 L/min: V=50+tV = 50 + t. Salt enters at 2⋅3=62\cdot3 = 6 g/min and leaves at SV⋅2\dfrac{S}{V}\cdot2 g/min, so

S′=6−2S50+t.S' = 6 - \frac{2S}{50 + t}.

Step 1 — the equation is linear: S′+250+tS=6S' + \dfrac{2}{50 + t}S = 6. Its integrating factor is e∫2/(50+t) dt=(50+t)2e^{\int 2/(50+t)\,dt} = (50 + t)^2.

Step 2 — multiply through: ((50+t)2S)′=6(50+t)2\big((50+t)^2S\big)' = 6(50+t)^2, so (50+t)2S=2(50+t)3+C(50+t)^2S = 2(50+t)^3 + C.

Step 3 — the start: 2500⋅10=2⋅125000+C2500\cdot10 = 2\cdot125000 + C gives C=−225000C = -225000, so S=2(50+t)−225000(50+t)2S = 2(50 + t) - \dfrac{225000}{(50+t)^2}.

Step 4 — the tank holds 100100 L at t=50t = 50: S=200−22500010000=177.5S = 200 - \dfrac{225000}{10000} = 177.5 g, a concentration of 1.7751.775 g/L.

Step 5 — read the formula: 2(50+t)=2V2(50 + t) = 2V is the salt the tank would hold at the incoming concentration 22 g/L; the second term is the initial deficit, fading as 1V2\tfrac{1}{V^2}. Treating VV as constant here (using S50\tfrac{S}{50} for the outflow concentration) would be wrong — see the sidenote.

Example
Worked: falling against air resistance

A skydiver's velocity obeys v′=9.8−0.2vv' = 9.8 - 0.2v (gravity minus a drag proportional to speed), v(0)=0v(0) = 0. Find the terminal velocity and the time to reach 90%90\% of it.

Equilibrium first: v′=0v' = 0 when v=9.80.2=49v = \dfrac{9.8}{0.2} = 49 m/s — the speed at which drag balances gravity.

Step 1 — the excess over equilibrium, w=v−49w = v - 49, satisfies w′=−0.2ww' = -0.2w, the same archetype as cooling. So w=−49e−0.2tw = -49e^{-0.2t} and v=49(1−e−0.2t)v = 49\left(1 - e^{-0.2t}\right).

Step 2 — 90%90\% of terminal: 1−e−0.2t=0.91 - e^{-0.2t} = 0.9, so e−0.2t=0.1e^{-0.2t} = 0.1 and t=5ln⁡10≈11.5t = 5\ln 10 \approx 11.5 s.

Step 3 — read the time constant 10.2=5\tfrac{1}{0.2} = 5 s: each 55 s closes 63%63\% of the remaining gap, and each 5ln⁡105\ln 10 s closes 90%90\%.

Step 4 — the model says terminal velocity is approached, never reached; a real skydiver is within a fraction of a percent after about 3030 s (e−6≈0.25%e^{-6} \approx 0.25\%).

Side note
Where it goes wrong: exponentials in the wrong variable

For the thermometer, a tempting model is T=5ektT = 5e^{kt}, fitted to T(2)=15T(2) = 15: e2k=3e^{2k} = 3. It predicts T(4)=45∘T(4) = 45^\circ and unlimited growth — in a 25∘25^\circ room. The exponential belongs to the difference from the room, which shrinks: 25−T=20⋅2−t/225 - T = 20\cdot2^{-t/2}, giving T(4)=20∘T(4) = 20^\circ. The same slip in the filling tank uses S50\tfrac{S}{50} as the outflow concentration; with the volume growing to 100100 L that overstates the outflow and gives the wrong answer 150−140e−0.04⋅50≈131150 - 140e^{-0.04\cdot 50} \approx 131 g instead of 177.5177.5 g.

Try it
Try it: terminal velocity

A falling object obeys v′=9.8−0.1vv' = 9.8 - 0.1v, v(0)=0v(0) = 0. Find its terminal velocity and the time at which it reaches half of it.

Show the answer

Terminal velocity is the equilibrium: 9.8−0.1v=09.8 - 0.1v = 0 gives v=98v = 98 m/s. The excess w=v−98w = v - 98 satisfies w′=−0.1ww' = -0.1w with w(0)=−98w(0) = -98, so v=98(1−e−0.1t)v = 98\left(1 - e^{-0.1t}\right). Half of terminal: e−0.1t=12e^{-0.1t} = \tfrac12, so t=10ln⁡2≈6.93t = 10\ln 2 \approx 6.93 s — the half-life of the gap, the same number whether the gap is in speed, temperature or salt.

Logistic Growth in Numbers

Tip
The logistic solution and its landmarks

The solution of P′=rP(1−PK)P' = rP\left(1 - \tfrac PK\right), P(0)=P0P(0) = P_0, is

P(t)=K1+Ae−rt,A=K−P0P0.P(t) = \frac{K}{1 + Ae^{-rt}}, \qquad A = \frac{K - P_0}{P_0}.

For 0<P0<K20 < P_0 < \tfrac K2 the curve is an S: it passes K2\tfrac K2 at t∗=ln⁡Art^* = \tfrac{\ln A}{r}, where the growth rate is largest (rK4\tfrac{rK}{4}), and it is symmetric about that point.

Why AA has that value: at t=0t = 0 the formula gives K1+A=P0\dfrac{K}{1 + A} = P_0. Why the midpoint is the inflection: P′′=f′(P) P′P'' = f'(P)\,P', and f(P)=rP(1−P/K)f(P) = rP(1 - P/K) has f′(P)=0f'(P) = 0 exactly at P=K2P = \tfrac K2, so the curve switches from bending up to bending down there. Why the symmetry: 1P−1K\tfrac1P - \tfrac1K is a pure exponential, so the curve's shape depends only on t−t∗t - t^*.

Example
Worked: a logistic population, start to finish
ty246810125001000(4.39, 500)(10, 942.8)KP₀ = 1500
Logistic solutions with K=1000K = 1000, r=0.5r = 0.5 from P0=100P_0 = 100 and P0=1500P_0 = 1500; the lower curve is steepest at (4.39,500)(4.39, 500).

A population follows P′=0.5P(1−P1000)P' = 0.5P\left(1 - \tfrac{P}{1000}\right) with P(0)=100P(0) = 100. When does it reach 500500, and what is P(10)P(10)?

The solution is P(t)=K1+Ae−rtP(t) = \dfrac{K}{1 + Ae^{-rt}} with K=1000K = 1000, r=0.5r = 0.5, and A=K−P0P0=900100=9A = \dfrac{K - P_0}{P_0} = \dfrac{900}{100} = 9 (from P(0)=K1+AP(0) = \tfrac{K}{1 + A}).

Step 1 — half capacity: 10001+9e−0.5t=500\dfrac{1000}{1 + 9e^{-0.5t}} = 500 needs 9e−0.5t=19e^{-0.5t} = 1, so t=2ln⁡9≈4.39t = 2\ln 9 \approx 4.39. This is the inflection point, where growth is fastest (P′=rK4=125P' = \tfrac{rK}{4} = 125 per unit time).

Step 2 — P(10)=10001+9e−5≈942.8P(10) = \dfrac{1000}{1 + 9e^{-5}} \approx 942.8.

Step 3 — the S-shape is symmetric about the inflection point: PP rises from 100100 to 500500 in 4.394.39 time units, and from 500500 to 900900 in another 4.394.39 (solve 9e−0.5t=199e^{-0.5t} = \tfrac19: t=8ln⁡3≈8.79=2⋅4.39t = 8\ln 3 \approx 8.79 = 2\cdot 4.39).

Step 4 — a population started above capacity, say P(0)=1500P(0) = 1500, has A=−13A = -\tfrac13 and decreases toward 10001000; one started at exactly 10001000 never moves.

Example
Worked: finding K and r from three counts
ty1234550100prediction 75exponentialK = 100
The three counts (dots), the logistic fit through them, and the exponential guess (dashed) that overshoots.

A culture is counted at equal intervals: 1010, 2525, 5050. Assuming logistic growth, find the carrying capacity and predict the next count.

The key: for P=K1+Ae−rtP = \dfrac{K}{1 + Ae^{-rt}}, the reciprocal is 1P=1K+AKe−rt\dfrac1P = \dfrac1K + \dfrac AKe^{-rt} — a constant plus a pure exponential. So with q=e−rq = e^{-r} (one interval), the gaps 1Pn−1K\tfrac1{P_n} - \tfrac1K shrink by the factor qq each interval.

Step 1 — the reciprocals are 110\tfrac1{10}, 125\tfrac1{25}, 150\tfrac1{50}. Their successive differences are 125−110=−350\tfrac1{25} - \tfrac1{10} = -\tfrac3{50} and 150−125=−150\tfrac1{50} - \tfrac1{25} = -\tfrac1{50}, and these also shrink by qq, so q=13q = \tfrac13.

Step 2 — find 1K\tfrac1K from 125−1K=q(110−1K)\tfrac1{25} - \tfrac1K = q\left(\tfrac1{10} - \tfrac1K\right): multiplying by 33, 325−3K=110−1K\tfrac3{25} - \tfrac3K = \tfrac1{10} - \tfrac1K, so 2K=325−110=150\tfrac2K = \tfrac3{25} - \tfrac1{10} = \tfrac1{50} and K=100K = 100.

Step 3 — the rate per interval is r=ln⁡3r = \ln 3, and A=KP0−1=9A = \tfrac{K}{P_0} - 1 = 9.

Step 4 — predict: 1P3=1100+q3⋅9100=1100(1+927)\dfrac1{P_3} = \dfrac1{100} + q^3\cdot\dfrac{9}{100} = \dfrac1{100}\left(1 + \dfrac{9}{27}\right), so P3=75P_3 = 75. The counts 10,25,50,7510, 25, 50, 75 then approach 100100, the next ones being 9090 and 96.496.4.

Side note
Where it goes wrong: extrapolating the early growth

From the counts 1010 and 2525 — a factor of 2.52.5 per interval — an exponential model predicts 62.562.5 and then 156.25156.25. The logistic fit gives 5050 and 7575. Early logistic growth looks exponential because 1−PK≈11 - \tfrac PK \approx 1 when PP is small (here 1−10100=0.91 - \tfrac{10}{100} = 0.9), but the brake tightens with every count. Two data points cannot distinguish the models; the third count, 5050 rather than 62.562.5, is what reveals the carrying capacity.

Try it
Try it: time to half capacity

A fish population in a lake follows the logistic model with K=600K = 600, r=ln⁡2r = \ln 2 per year and P(0)=100P(0) = 100. When does it reach 300300?

Show the answer

First A=K−P0P0=500100=5A = \dfrac{K - P_0}{P_0} = \dfrac{500}{100} = 5, so P(t)=6001+5⋅2−tP(t) = \dfrac{600}{1 + 5\cdot2^{-t}} (since e−tln⁡2=2−te^{-t\ln 2} = 2^{-t}). Reaching 300=K2300 = \tfrac K2 needs 5⋅2−t=15\cdot2^{-t} = 1, so 2t=52^t = 5 and t=log⁡25≈2.32t = \log_2 5 \approx 2.32 years. This is the inflection time ln⁡Ar=ln⁡5ln⁡2\tfrac{\ln A}{r} = \tfrac{\ln 5}{\ln 2}: from then on the population still grows, but ever more slowly.

Proofs & Why It Matters

Tip
Proof: solving the logistic equation

Separate dPP(1−P/K)=r dt\tfrac{dP}{P(1 - P/K)} = r\,dt and split by partial fractions: 1P(1−P/K)=1P+1/K1−P/K\tfrac{1}{P(1-P/K)} = \tfrac1P + \tfrac{1/K}{1 - P/K}. Integrating gives ln⁡PK−P=rt+C\ln\tfrac{P}{K-P} = rt + C, and solving for PP: P(t)=K1+Ae−rtP(t) = \dfrac{K}{1 + Ae^{-rt}} — an S-curve rising to KK. Every positive start flows to the carrying capacity because e−rt→0e^{-rt} \to 0. ■\blacksquare

Tip
Proof: Newton cooling is exponential in the excess

The law says T′=−k(T−Tamb)T' = -k(T - T_{\text{amb}}). Let u=T−Tambu = T - T_{\text{amb}} (the excess); since TambT_{\text{amb}} is constant, u′=T′=−kuu' = T' = -ku — the pure exponential equation, so u=u0e−ktu = u_0e^{-kt}.

Halving in equal time intervals is exactly the property of exponentials, which is why the "excess halves every 10 minutes" phrasing works. ■\blacksquare

Tip
Proof sketch: Euler's error halves with h

One Euler step commits error ≈h22y′′\approx \tfrac{h^2}{2}y'' (the first Taylor term the tangent line misses). Reaching a fixed time TT takes T/hT/h steps, so the accumulated error is on the order of Th⋅h22max⁡∣y′′∣=O(h)\tfrac{T}{h}\cdot\tfrac{h^2}{2}\max|y''| = O(h) — proportional to hh. Halve the step, halve the error: Euler is a first-order method. ■\blacksquare

Going Deeper: Explanations & Worked Problems

Concept
Equilibria and stability: the phase-line shortcut

For an autonomous equation y′=f(y)y' = f(y), enormous insight costs one sketch. Find the zeros of ff — the equilibria, where the system sits still. Between consecutive zeros, ff keeps one sign: yy moves right (up) where f>0f > 0, left (down) where f<0f < 0.

Mark arrows on a number line and stability is visible: arrows converging on an equilibrium make it stable (perturb, return), diverging make it unstable (perturb, flee). Logistic growth y′=ry(1−y/K)y' = ry(1 - y/K): zeros at 00 and KK; f>0f > 0 between them, so arrows point from 00 toward KK — the origin is unstable, the carrying capacity stable, and every positive solution S-curves to KK, all without solving the equation. The phase line is the qualitative theory in miniature: solve only when you need numbers; sketch when you need understanding.

Example
Worked: half-life to dosage, a complete exponential-decay problem

A drug has half-life 66 hours; a dose raises blood concentration by 1010 units. When does a single dose drop below 11 unit?

Step 1 — model: y′=kyy' = ky with y=10ekty = 10e^{kt}.

Step 2 — pin kk from the half-life: y(6)=5y(6) = 5 gives e6k=12e^{6k} = \tfrac12, so k=−ln⁡26≈−0.1155k = -\tfrac{\ln2}{6} \approx -0.1155.

Step 3 — solve 10ekt=110e^{kt} = 1: ekt=110e^{kt} = \tfrac1{10}, so t=ln⁡10ln⁡2⋅6=6log⁡210≈19.9t = \dfrac{\ln 10}{\ln 2}\cdot6 = 6\log_2 10 \approx 19.9 hours.

Step 4 — sanity check in halvings: 10→5→2.5→1.2510 \to 5 \to 2.5 \to 1.25 after three half-lives (1818 h), and 1.25→11.25 \to 1 needs about a third more of one half-life — 18+2≈2018 + 2 \approx 20 h ✓.

Step 5 — the modeling lesson: the answer depended only on the ratio 10:110:1, so every decade of decay costs the same log⁡210≈3.32\log_2 10 \approx 3.32 half-lives, whatever the starting dose.

Example
Worked: a mixing tank, from setup to equilibrium

A 100100 L tank starts with pure water. Brine at 22 g/L flows in at 55 L/min; the well-mixed tank drains at 55 L/min. Find the salt S(t)S(t).

Step 1 — build the equation from bookkeeping: rate in =2⋅5=10= 2 \cdot 5 = 10 g/min; rate out == (concentration)(flow) =S100⋅5=S20= \tfrac{S}{100}\cdot5 = \tfrac{S}{20}; so S′=10−S20S' = 10 - \tfrac{S}{20}.

Step 2 — equilibrium first: S′=0S' = 0 at S=200S = 200 g — which is just (incoming concentration)(volume) =2⋅100= 2\cdot100, as it must be.

Step 3 — solve: linear with μ=et/20\mu = e^{t/20}: (et/20S)′=10et/20(e^{t/20}S)' = 10e^{t/20}, so et/20S=200et/20+Ce^{t/20}S = 200e^{t/20} + C, and S(0)=0S(0) = 0 gives C=−200C = -200: S(t)=200(1−e−t/20)S(t) = 200\left(1 - e^{-t/20}\right).

Step 4 — read the time scale: the "time constant" is 2020 min; after 2020 min the tank is at 200(1−e−1)≈126200(1 - e^{-1}) \approx 126 g, after an hour ≈190\approx 190 g — the exponential approach to equilibrium that governs tanks, cooling coffee, and charging capacitors alike.