Part 6 - Chapter 21.

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Presentation transcript:

Part 6 - Chapter 21

Part 6 Numerical Differentiation and Integration Calculus is the mathematics of change. Because engineers must continuously deal with systems and processes that change, calculus is an essential tool of engineering. Standing in the heart of calculus are the mathematical concepts of differentiation and integration:

Figure PT6.1

Figure PT6.2

Noncomputer Methods for Differentiation and Integration The function to be differentiated or integrated will typically be in one of the following three forms: A simple continuous function such as polynomial, an exponential, or a trigonometric function. A complicated continuous function that is difficult or impossible to differentiate or integrate directly. A tabulated function where values of x and f(x) are given at a number of discrete points, as is often the case with experimental or field data.

Figure PT6.4

Figure PT6.7

Figure PT6.10

Newton-Cotes Integration Formulas Chapter 21 The Newton-Cotes formulas are the most common numerical integration schemes. They are based on the strategy of replacing a complicated function or tabulated data with an approximating function that is easy to integrate:

Figure 21.1

Figure 21.2

The Trapezoidal Rule The Trapezoidal rule is the first of the Newton-Cotes closed integration formulas, corresponding to the case where the polynomial is first order: The area under this first order polynomial is an estimate of the integral of f(x) between the limits of a and b: Trapezoidal rule

Figure 21.4

Error of the Trapezoidal Rule/ When we employ the integral under a straight line segment to approximate the integral under a curve, error may be substantial: where x lies somewhere in the interval from a to b.

Figure 21.6

The Multiple Application Trapezoidal Rule/ One way to improve the accuracy of the trapezoidal rule is to divide the integration interval from a to b into a number of segments and apply the method to each segment. The areas of individual segments can then be added to yield the integral for the entire interval. Substituting the trapezoidal rule for each integral yields:

Figure 21.8

An error for multiple-application trapezoidal rule can be obtained by summing the individual errors for each segment: Thus, if the number of segments is doubled, the truncation error will be quartered.

Simpson’s Rules More accurate estimate of an integral is obtained if a high-order polynomial is used to connect the points. The formulas that result from taking the integrals under such polynomials are called Simpson’s rules. Simpson’s 1/3 Rule/ Results when a second-order interpolating polynomial is used.

Figure 21.10

Simpson’s 1/3 rule is more accurate than trapezoidal rule. Single segment application of Simpson’s 1/3 rule has a truncation error of: Simpson’s 1/3 rule is more accurate than trapezoidal rule.

The Multiple-Application Simpson’s 1/3 Rule/ Just as the trapezoidal rule, Simpson’s rule can be improved by dividing the integration interval into a number of segments of equal width. Yields accurate results and considered superior to trapezoidal rule for most applications. However, it is limited to cases where values are equispaced. Further, it is limited to situations where there are an even number of segments and odd number of points.

Figure 21.11

Simpson’s 3/8 Rule/ An odd-segment-even-point formula used in conjunction with the 1/3 rule to permit evaluation of both even and odd numbers of segments. More accurate

Figure 21.12