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Further Modelling with Functions Simplified Revision Notes

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2.13.1 Further Modelling with Functions

Further modelling with functions involves tackling more complex scenarios where relationships between variables might not be straightforward. This often requires combining different types of functions, interpreting piecewise functions, or working with non-linear models. Let's dive into some advanced aspects of function modelling:

1. Piecewise Functions

In some cases, a situation can be best described using different functions over different intervals. This is where piecewise functions come into play.

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Example: A taxi company charges £3 for the first mile and £2 for each additional mile. Model the cost C(x)C(x) as a function of the distance xx (in miles) travelled. Solution:

  • For  0<x1\ 0 < x \leq 1 , the cost is £3.
  • For  x>1,\ x > 1 , the cost is  3+2(x1).\ 3 + 2(x - 1) . The piecewise function is: C(x)={3if 0<x13+2(x1)if x>1C(x) = \begin{cases} 3 & \text{if } 0 < x \leq 1 \\ 3 + 2(x - 1) & \text{if } x > 1 \end{cases}

Interpretation: This function reflects how the cost changes after the first mile, combining a flat rate with a linear increase.

2. Exponential Growth and Decay

Exponential functions are frequently used to model situations where a quantity grows or decays at a rate proportional to its current value.

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Example: The population of a town grows at a rate of 5% per year. If the current population is 20,000, model the population P(t)P(t) as a function of time  t\ t (in years) and predict the population after 10 years. Solution: The model follows the exponential growth function: P(t)=P0ertP(t) = P_0 \cdot e^{rt} Where:

  •  P0=20000\ P_0 = 20000 (initial population)
  •  r=0.05\ r = 0.05 (growth rate)
  •  t=10\ t = 10 years Substituting the values: P(10)=20000e0.05×1020000e0.5200001.6487=32974P(10) = 20000 \cdot e^{0.05 \times 10} \approx 20000 \cdot e^{0.5} \approx 20000 \cdot 1.6487 = 32974

Interpretation: After 10 years, the population is predicted to be approximately 32,974.

3. Quadratic Modelling

Quadratic functions are ideal for modelling situations involving acceleration, projectile motion, or any scenario where a relationship involves a squared term.

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Example: A ball is thrown upwards from a height of 5 meters with an initial velocity of 10 m/sm/s. Model the height  h(t)\ h(t) of the ball as a function of time  t,\ t , considering the acceleration due to gravity  g=9.8m/s2.\ g = 9.8 \, \text{m/s}^2 . Solution: The height function is quadratic, given by: h(t)=h0+v0t12gt2h(t) = h_0 + v_0t - \frac{1}{2}gt^2 Where:

  •  h0=5\ h_0 = 5 meters (initial height)
  •  v0=10\ v_0 = 10 m/sm/s (initial velocity)
  • g=9.8m/s2 g = 9.8 m/s^2 Substitute the values: h(t)=5+10t4.9t2h(t) = 5 + 10t - 4.9t^2

To find when the ball hits the ground (h(t)=0)( h(t) = 0 ): 0=5+10t4.9t20 = 5 + 10t - 4.9t^2

This is a quadratic equation: 4.9t210t5=04.9t^2 - 10t - 5 = 0 Use the quadratic formula: t=(10)±(10)24(4.9)(5)2(4.9)t = \frac{-(-10) \pm \sqrt{(-10)^2 - 4(4.9)(-5)}}{2(4.9)}

Simplifying: t=10±100+989.8=10±1989.810±14.079.8t = \frac{10 \pm \sqrt{100 + 98}}{9.8} = \frac{10 \pm \sqrt{198}}{9.8} \approx \frac{10 \pm 14.07}{9.8}

This gives two solutions:  t=24.079.82.46 seconds(valid)\ t = \frac{24.07}{9.8} \approx 2.46 \text{ seconds} \quad \text{(valid)}  t=4.079.8(not valid, as time cannot be negative)\ t = \frac{-4.07}{9.8} \quad \text{(not valid, as time cannot be negative)}

Interpretation: The ball hits the ground approximately 2.46 seconds after it is thrown.

4. Logarithmic Modelling

Logarithmic functions model situations where growth slows down over time, like the pHpH of a solution or the Richter scale for earthquakes.

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Example: The pHpH of a solution is defined as  pH=log[H+]\ pH = -\log[H^+] , where  [H+]\ [H^+] is the hydrogen ion concentration in moles per litre. If the concentration decreases exponentially, model the pH as a function of time  t.\ t . Solution: Given  [H+]=[H+]0ekt\ [H^+] = [H^+]_0 e^{-kt} , the pH function is: pH(t)=log([H+]0ekt)=log[H+]0+ktlogepH(t) = -\log([H^+]_0 e^{-kt}) = -\log[H^+]_0 + kt\log e

This logarithmic model shows how pH increases as hydrogen ion concentration decreases over time.

Practice Problem:

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A company manufactures electronic devices. The cost  C(x)\ C(x) to produce  x\ x units is given by  C(x)=500+20x\ C(x) = 500 + 20x , and the revenue  R(x)\ R(x) from selling  x\ x units is  R(x)=50x0.1x2.\ R(x) = 50x - 0.1x^2 . Determine the number of units the company must produce and sell to maximize profit.

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Solution: Profit function  P(x)=R(x)C(x):\ P(x) = R(x) - C(x) :

P(x)=(50x0.1x2)(500+20x)P(x) = (50x - 0.1x^2) - (500 + 20x)

Simplify: P(x)=0.1x2+30x500P(x) = -0.1x^2 + 30x - 500

To maximize profit, differentiate and set to zero: P(x)=0.2x+30=0x=150P'(x) = -0.2x + 30 = 0 \quad \Rightarrow \quad x = 150

Verify with the second derivative: P(x)=0.2(Negative, so a maximum)P''(x) = -0.2 \quad (\text{Negative, so a maximum})

Answer: The company should produce and sell 150 unitsunits to maximize profit.


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