Applications of the Derivative

Applications of the Derivative

Learning Objectives

Use derivatives to find tangent lines, normal lines, and angles of intersection between curves.
Apply related rates to solve problems involving multiple variables changing with respect to time.
Analyze rectilinear motion and compute velocity, speed, and acceleration.
Use first and second derivative tests to find absolute and relative extrema for optimization and curve sketching.
Apply marginal analysis to economic functions and use L'Hopital's Rule to evaluate indeterminate limits.

Calculus is not just about computing derivatives; it's about using them to understand how quantities change. We use derivatives to optimize systems (finding max profit, min cost), analyze motion (velocity, acceleration), calculate marginal analysis in economics, and solve related rates problems.

Tangent and Normal Lines

Tangent Line

The tangent line to a curve $y = f(x)$ at $x = c$ is the best linear approximation of the curve at that point. Its slope is $m = f'(c)$ . Equation: $y - f(c) = f'(c)(x - c)$

Normal Line

The normal line is perpendicular to the tangent line at the point of tangency. Its slope is the negative reciprocal: $-1/f'(c)$ . Equation: $y - f(c) = -\frac{1}{f'(c)}(x - c)$

Angle of Intersection Between Curves

When two curves intersect, the angle

\theta

between them is defined as the angle between their respective tangent lines at the point of intersection.

How to Find the Angle of Intersection

STEP-BY-STEP

Find the intersection point(s) of the two curves.
Calculate the slopes $m_1 = f'(x)$ and $m_2 = g'(x)$ at the point of intersection.
Use the tangent addition formula to find the acute angle $\theta$ .

Angle of Intersection Formula

Angle between two intersecting curves.

\tan \theta = \left| \frac{m_1 - m_2}{1 + m_1 m_2} \right|

Variables

Symbol	Description	Unit
$\theta$	Acute angle of intersection	-
$m_1, m_2$	Slopes of the tangent lines	-

Rates of Change and Rectilinear Motion

Rectilinear Motion

Motion that occurs along a straight line.

s(t)

represents the position of an object moving along a straight line at time

t

Kinematic Equations

The fundamental equations relating position, velocity, speed, and acceleration in rectilinear motion.

v(t) = s'(t)

a(t) = v'(t) = s''(t)

\text{Speed} = |v(t)|

Variables

Symbol	Description	Unit
$s(t)$	Position function with respect to time	-
$v(t)$	Velocity function (Instantaneous rate of change of position)	-
$a(t)$	Acceleration function (Rate of change of velocity)	-
$\|v(t)\|$	Speed (Magnitude of velocity)	-

Marginal Analysis in Economics

In economics, the term "marginal" refers to a derivative. It represents the approximate change in a quantity resulting from a one-unit increase in production or sales.

Cost Function $C(x)$

The total cost of producing $x$ units.

Marginal Cost $C'(x)$

The instantaneous rate of change of cost, roughly approximating the cost of producing the next unit.

Revenue Function $R(x)$

The total revenue from selling $x$ units.

Marginal Revenue $R'(x)$

The instantaneous rate of change of revenue.

Profit Optimization

Maximum profit occurs when Marginal Revenue equals Marginal Cost.

P(x) = R(x) - C(x)

R'(x) = C'(x)

Variables

Symbol	Description	Unit
$P(x)$	Profit function	-
$R(x)$	Revenue function	-
$C(x)$	Cost function	-
$R'(x)$	Marginal revenue	-
$C'(x)$	Marginal cost	-

Related Rates

In related rates problems, we relate the rates of change of two or more variables that are changing with respect to time. The key is to differentiate implicitly with respect to time

t

Common Strategy for Related Rates

STEP-BY-STEP

Draw a picture and label variables.
Write an equation relating the variables.
Differentiate implicitly with respect to time ( $t$ ).
Substitute known values after differentiating.
Solve for the unknown rate.

Interactive Simulation

Interact with the simulation below to explore related rates using a sliding ladder context.

Related Rates: Sliding Ladder

Distance from Wall (x)

Length (L)10 m

x6.00 m

y8.00 m

Assume dx/dt = 2 m/s

dy/dt-1.50 m/s

Notice how dy/dt (speed of top of ladder) increases dramatically as x approaches L (bottom pulls away).

Interactive Simulation

Interact with the simulation below to explore related rates using a conical hydraulic reservoir context.

Hydraulic Related Rates: Conical Reservoir

A standard civil engineering application: analyze how depth $h$ changes over time as water flows into a conical tank at a constant rate $dV/dt$ .

Tank Total Height (

H

): 10 m

Tank Top Radius (

R

): 5 m

Inflow Rate (

Q = dV/dt

): 1.5 m³/min

Current Water Depth (

h

): 4.00 m

0.1m10m (Full)

Governing Equation

\frac{dh}{dt} = \frac{dV/dt}{\pi r^2}

Current Radius $r$:

2.00 m

Water Volume $V$:

16.8 m³

Rate dh/dt:0.1194 m/min

Reservoir Geometry Cross-Section

Depth vs. Depth Rate (dh/dt)

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Key Insight: Observe how the green curve decreases exponentially. As the depth

h

increases, the cross-sectional area expands, meaning the rate of vertical rise

dh/dt

slows down drastically for the same constant inflow!

Optimization: Maxima and Minima

Finding the best (optimal) value is a core engineering task, such as finding the maximum volume or minimum cost. It involves analyzing the critical points of a function.

Absolute vs. Relative Extrema

Absolute (Global) Maximum: The absolute highest value of $f(x)$ over its entire domain.
Absolute (Global) Minimum: The absolute lowest value of $f(x)$ over its entire domain.
Relative (Local) Maximum: A peak in the graph. The value $f(c)$ is higher than all nearby values in an open interval containing $c$ .
Relative (Local) Minimum: A valley in the graph. The value $f(c)$ is lower than all nearby values in an open interval containing $c$ .

Finding Extrema

STEP-BY-STEP

Critical Points: Find where $f'(c) = 0$ or $f'(c)$ is undefined.

First Derivative Test: Check if $f'$ changes sign.

Positive to Negative implies a Relative Maximum.
Negative to Positive implies a Relative Minimum.

Second Derivative Test: Check concavity at critical points.

$f''(c) > 0$ (Concave Up) implies a Minimum.
$f''(c) < 0$ (Concave Down) implies a Maximum.

Interactive Simulation

Interact with the simulation below to explore a classic optimization problem: constructing an open-top box with maximum volume from a flat sheet.

Box Optimization Problem

Cut Size (x): 2.00

Length16.00

Width16.00

Height (x)2.00

Volume512.0

Max Volume occurs at x ≈ 3.33

Current % of Max: 86.4%

Curve Sketching

Derivatives provide powerful tools for understanding the shape of a graph without plotting points manually.

First and Second Derivative Tests

Increasing/Decreasing: If $f'(x) > 0$ , the curve is increasing. If $f'(x) < 0$ , it is decreasing.
Concavity: The second derivative $f''(x)$ $f^{''} (x)$ tells us about concavity.
- $f''(x) > 0$ : Concave Up (looks like a cup U).
- $f''(x) < 0$ : Concave Down (looks like a frown).
Point of Inflection: A point where the concavity changes (e.g., from concave up to concave down). This occurs where $f''(x) = 0$ or is undefined, and the sign of $f''(x)$ actually changes across the point.

L'Hopital's Rule

Used to evaluate limits of indeterminate forms

0/0

\infty/\infty

. It states that the limit of the ratio of functions is the limit of the ratio of their derivatives.

L'Hopital's Rule

Limit of a ratio of functions.

\lim_{x \to c} \frac{f(x)}{g(x)} = \lim_{x \to c} \frac{f'(x)}{g'(x)}

Variables

Symbol	Description	Unit
$f(x), g(x)$	Differentiable functions producing indeterminate forms	-
$c$	The limit point	-

Civil Engineering Optimization: Pipeline and Canal Routing

In infrastructure design, civil engineers utilize optimization to find the most cost-effective path for utility pipelines, roads, or canals crossing multiple regions (such as dry land versus riverbeds) where excavation and construction costs differ.

Interactive Simulation

Interact with the simulation below to find the mathematically optimal path that minimizes total project cost based on cost-per-meter ratios.

Canal Optimization

Adjust the depth $y$ of the trapezoidal canal. The total area is held constant at 50 m². Notice how the wetted perimeter $P$ changes, reaching a minimum when the cross-section approaches a half-hexagon.

Depth

y

: 5.37 m

Cross-Section Properties:

Area A: 50.0 m² (Constant)

Depth y: 5.37 m

Bottom Width b: 6.21 m

Wetted Perimeter P: 18.61 m

Optimal Design (Minimum P)

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Key Takeaways

Tangent lines approximate curves locally. The angle of intersection between two curves uses the slopes of their tangent lines.
Velocity and acceleration are the first and second derivatives of position in rectilinear motion.
Marginal Analysis uses the derivative to find the incremental cost or revenue, maximizing profit where $R'(x) = C'(x)$ .
Related Rates problems require implicit differentiation with respect to time. Always substitute after differentiating.
Optimization uses first and second derivative tests to find global max/min values, crucial for design efficiency.
L'Hopital's Rule simplifies finding limits of indeterminate forms using derivatives.

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Learning Objectives

Tangent and Normal Lines

Tangent Line

Normal Line

Angle of Intersection Between Curves

How to Find the Angle of Intersection

Angle of Intersection Formula

Rates of Change and Rectilinear Motion

Rectilinear Motion

Kinematic Equations

Marginal Analysis in Economics

Cost Function C(x)C(x)C(x)

Marginal Cost C′(x)C'(x)C′(x)

Revenue Function R(x)R(x)R(x)

Marginal Revenue R′(x)R'(x)R′(x)

Profit Optimization

Related Rates

Common Strategy for Related Rates

Interactive Simulation

Related Rates: Sliding Ladder

Interactive Simulation

Hydraulic Related Rates: Conical Reservoir

Optimization: Maxima and Minima

Absolute vs. Relative Extrema

Finding Extrema

Interactive Simulation

Box Optimization Problem

Curve Sketching

First and Second Derivative Tests

L'Hopital's Rule

L'Hopital's Rule

Civil Engineering Optimization: Pipeline and Canal Routing

Interactive Simulation

Canal Optimization

Cost Function $C(x)$

Marginal Cost $C'(x)$

Revenue Function $R(x)$

Marginal Revenue $R'(x)$