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Tony's Intertwingled Memex β€’ Reference Manual

Closed Interval Method

Formulas & Definitions
Core Definition

The Closed Interval Method is an exact analytical algorithm used to locate the absolute maximum and absolute minimum values of a continuous function f(x)f(x)f(x) on a closed interval [a,b][a, b][a,b]. Because absolute extrema can occur only at interior critical numbers or at boundary endpoints, the method evaluates the original function f(x)f(x)f(x) across all candidate points and directly compares their heights (yyy-values).


Concept Explanation

1. The 5-Step Closed Interval Method Pipeline

When a function satisfies the preconditions of the Extreme Value Theorem, execute the following 5-step pipeline:

Step 1: Check Preconditions (Continuity on [a, b])
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Step 2: Differentiate (Compute f'(x))
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Step 3: Find & Filter Interior Critical Numbers (c in (a, b) where f'(c)=0 or DNE)
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Step 4: Evaluate Original Function f(x) at:
        - Surviving interior critical numbers: f(c_1), f(c_2), ...
        - Left boundary endpoint: f(a)
        - Right boundary endpoint: f(b)
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Step 5: Compare Heights:
        - Highest value  --> Absolute Maximum Value
        - Lowest value   --> Absolute Minimum Value
Closed_Interval_Method_Candidates.png

2. Common Pitfalls to Avoid

  • Pitfall 1: The Derivative Evaluation Trap: Never substitute candidate points back into the derivative fβ€²(x)f'(x)fβ€²(x). Substituting critical numbers into fβ€²(x)f'(x)fβ€²(x) yields 000 or undefined. Always evaluate the original function f(x)f(x)f(x) to find the physical heights (yyy-values).
  • Pitfall 2: Forgetting Endpoints: Absolute extrema frequently occur at the boundaries x=ax = ax=a or x=bx = bx=b, where fβ€²(x)β‰ 0f'(x) \neq 0fβ€²(x)ξ€ =0. Neglecting endpoint evaluations can cause you to miss the true global maximum or minimum.
  • Pitfall 3: Failing to Filter Candidates: Only critical numbers located strictly inside the open interval (a,b)(a, b)(a,b) are valid candidates. Any solutions to fβ€²(x)=0f'(x) = 0fβ€²(x)=0 outside (a,b)(a, b)(a,b) must be discarded.
  • Pitfall 4: Overlooking Singular Points (fβ€²(x)Β DNEf'(x) \text{ DNE}fβ€²(x)Β DNE): Always check whether the denominator of fβ€²(x)f'(x)fβ€²(x) can equal zero within (a,b)(a, b)(a,b) (e.g., fractional exponents such as x2/3x^{2/3}x2/3 or x1/3x^{1/3}x1/3).

Engineering Applications

  • Civil Structural Beam Bending Moments: Reinforced concrete bridge beams spanning x∈[0,L]x \in [0, L]x∈[0,L] experience internal bending moment distributions M(x)M(x)M(x). Civil engineers use the Closed Interval Method to compare moments at support piers (x=0,Lx = 0, Lx=0,L) against internal critical moment sections (Mβ€²(x)=0M'(x) = 0Mβ€²(x)=0), ensuring rebar steel reinforcement is placed at the absolute peak bending stress location.
  • Transistor Thermal Duty-Cycle Analysis: Power semiconductor devices (such as GaN MOSFETs) experience thermal junction heating T(t)T(t)T(t) over a periodic switching cycle [0,tcycle][0, t_{\text{cycle}}][0,tcycle​]. Electronic systems engineers apply the Closed Interval Method to verify that the absolute peak junction temperature does not breach the silicon thermal damage ceiling.
  • Subsea Pipeline Pressure Cycling: Marine petroleum pipelines spanning a seabed elevation profile z(s)z(s)z(s) over total pipeline length s∈[0,Lpipe]s \in [0, L_{\text{pipe}}]s∈[0,Lpipe​] must withstand hydrostatic burst pressure. Engineers evaluate pipeline wall stresses at intermediate high/low points and boundary manifolds using closed-interval optimization.

Example Problems

Example 1: Polynomial on a Closed Interval

Find the absolute maximum and minimum values of f(x)=x3βˆ’3x2+1f(x) = x^3 - 3x^2 + 1f(x)=x3βˆ’3x2+1 on the closed interval [βˆ’1,4][-1, 4][βˆ’1,4]:

Solution
  1. Check Continuity: f(x)f(x)f(x) is a polynomial, so it is continuous on [βˆ’1,4][-1, 4][βˆ’1,4]. The EVT applies.
  2. Differentiate:
    fβ€²(x)=3x2βˆ’6x=3x(xβˆ’2)f'(x) = 3x^2 - 6x = 3x(x - 2)fβ€²(x)=3x2βˆ’6x=3x(xβˆ’2)
  3. Locate and Filter Critical Numbers: Set fβ€²(x)=0f'(x) = 0fβ€²(x)=0:
    3x(xβˆ’2)=0β€…β€ŠβŸΉβ€…β€Šx=0andx=23x(x - 2) = 0 \implies x = 0 \quad \text{and} \quad x = 23x(xβˆ’2)=0⟹x=0andx=2
    Filter: Both x=0x = 0x=0 and x=2x = 2x=2 lie strictly inside the interior interval (βˆ’1,4)(-1, 4)(βˆ’1,4). Both are retained.
  4. Evaluate Original Function f(x)f(x)f(x) at All Candidates:
    • Left Endpoint (x=βˆ’1x = -1x=βˆ’1):
      f(βˆ’1)=(βˆ’1)3βˆ’3(βˆ’1)2+1=βˆ’1βˆ’3+1=βˆ’3f(-1) = (-1)^3 - 3(-1)^2 + 1 = -1 - 3 + 1 = -3f(βˆ’1)=(βˆ’1)3βˆ’3(βˆ’1)2+1=βˆ’1βˆ’3+1=βˆ’3
    • First Critical Number (x=0x = 0x=0):
      f(0)=(0)3βˆ’3(0)2+1=1f(0) = (0)^3 - 3(0)^2 + 1 = 1f(0)=(0)3βˆ’3(0)2+1=1
    • Second Critical Number (x=2x = 2x=2):
      f(2)=(2)3βˆ’3(2)2+1=8βˆ’12+1=βˆ’3f(2) = (2)^3 - 3(2)^2 + 1 = 8 - 12 + 1 = -3f(2)=(2)3βˆ’3(2)2+1=8βˆ’12+1=βˆ’3
    • Right Endpoint (x=4x = 4x=4):
      f(4)=(4)3βˆ’3(4)2+1=64βˆ’48+1=17f(4) = (4)^3 - 3(4)^2 + 1 = 64 - 48 + 1 = 17f(4)=(4)3βˆ’3(4)2+1=64βˆ’48+1=17
  5. Compare and Conclude:
    • Absolute Maximum Value: 171717 at location x=4x = 4x=4.
    • Absolute Minimum Value: βˆ’3-3βˆ’3 at locations x=βˆ’1x = -1x=βˆ’1 and x=2x = 2x=2.

Example 2: Function with a Cusp on a Closed Interval

Find the absolute extrema of g(x)=2xβˆ’3x2/3g(x) = 2x - 3x^{2/3}g(x)=2xβˆ’3x2/3 on [βˆ’1,8][-1, 8][βˆ’1,8]:

Solution
  1. Check Continuity: g(x)=2xβˆ’3(x3)2g(x) = 2x - 3(\sqrt[3]{x})^2g(x)=2xβˆ’3(3x​)2 is continuous everywhere, including on [βˆ’1,8][-1, 8][βˆ’1,8].
  2. Differentiate:
    gβ€²(x)=2βˆ’3(23xβˆ’1/3)=2βˆ’2x1/3=2x1/3βˆ’2x1/3g'(x) = 2 - 3\left(\frac{2}{3}x^{-1/3}\right) = 2 - \frac{2}{x^{1/3}} = \frac{2x^{1/3} - 2}{x^{1/3}}gβ€²(x)=2βˆ’3(32​xβˆ’1/3)=2βˆ’x1/32​=x1/32x1/3βˆ’2​
  3. Find Critical Numbers:
    • Stationary Points (gβ€²(x)=0g'(x) = 0gβ€²(x)=0): Numerator equals zero:
      2x1/3βˆ’2=0β€…β€ŠβŸΉβ€…β€Šx1/3=1β€…β€ŠβŸΉβ€…β€Šx=12x^{1/3} - 2 = 0 \implies x^{1/3} = 1 \implies x = 12x1/3βˆ’2=0⟹x1/3=1⟹x=1
    • Singular Points (gβ€²(x)Β DNEg'(x) \text{ DNE}gβ€²(x)Β DNE): Denominator equals zero:
      x1/3=0β€…β€ŠβŸΉβ€…β€Šx=0x^{1/3} = 0 \implies x = 0x1/3=0⟹x=0
    • Filter: Both x=0x = 0x=0 and x=1x = 1x=1 lie in (βˆ’1,8)(-1, 8)(βˆ’1,8).
  4. Evaluate Original Function g(x)g(x)g(x):
    • Left Endpoint (x=βˆ’1x = -1x=βˆ’1): g(βˆ’1)=2(βˆ’1)βˆ’3(βˆ’1)2/3=βˆ’2βˆ’3(1)=βˆ’5g(-1) = 2(-1) - 3(-1)^{2/3} = -2 - 3(1) = -5g(βˆ’1)=2(βˆ’1)βˆ’3(βˆ’1)2/3=βˆ’2βˆ’3(1)=βˆ’5
    • Singular Point (x=0x = 0x=0): g(0)=2(0)βˆ’3(0)2/3=0g(0) = 2(0) - 3(0)^{2/3} = 0g(0)=2(0)βˆ’3(0)2/3=0
    • Stationary Point (x=1x = 1x=1): g(1)=2(1)βˆ’3(1)2/3=2βˆ’3=βˆ’1g(1) = 2(1) - 3(1)^{2/3} = 2 - 3 = -1g(1)=2(1)βˆ’3(1)2/3=2βˆ’3=βˆ’1
    • Right Endpoint (x=8x = 8x=8): g(8)=2(8)βˆ’3(8)2/3=16βˆ’3(4)=16βˆ’12=4g(8) = 2(8) - 3(8)^{2/3} = 16 - 3(4) = 16 - 12 = 4g(8)=2(8)βˆ’3(8)2/3=16βˆ’3(4)=16βˆ’12=4
  5. Compare and Conclude:
    • Absolute Maximum Value: 444 at location x=8x = 8x=8.
    • Absolute Minimum Value: βˆ’5-5βˆ’5 at location x=βˆ’1x = -1x=βˆ’1.

Connections & References

  • Theoretical Basis:
    • Extreme Value Theorem
    • Critical Numbers and Critical Points
  • Alternative/Related Tests:
    • First Derivative Test
    • Absolute and Relative Extrema
  • Course Sessions:
    • Calc 1 Session 13 - Critical Points and Extrema
    • Calc 1 Session 14 - Optimizing Areas and Volumes
    • Calc 1 Session 15 - Optimizing Distance and Time