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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 Numerical Differentiation and Integration Part 6 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:
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 212 Figure PT6.1
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 213 Figure PT6.2
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 214 Figure PT6.4
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 215 Figure PT6.7
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 216 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:
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 217 Figure 21.1
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 218 Figure 21.2
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 9 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
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2110 Figure 21.4
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2111 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 lies somewhere in the interval from a to b.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2112 Figure 21.6
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 13 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:
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2114 Figure 21.8
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2115 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.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2116 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.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2117 Figure 21.10
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 18 Simpson’s 1/3 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.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2119 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.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2120 Figure 21.11
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University 21 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
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2122 Figure 21.12
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2123 Integration of Equations Chapter 22 Functions to be integrated numerically are in two forms: –A table of values. We are limited by the number of points that are given. –A function. We can generate as many values of f(x) as needed to attain acceptable accuracy. Will focus on two techniques that are designed to analyze functions: –Romberg integration –Gauss quadrature
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2124 Romberg Integration Is based on successive application of the trapezoidal rule to attain efficient numerical integrals of functions. Richardson’s Extrapolation/ Uses two estimates of an integral to compute a third and more accurate approximation.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2125 Gauss Quadrature Gauss quadrature implements a strategy of positioning any two points on a curve to define a straight line that would balance the positive and negative errors. Hence the area evaluated under this straight line provides an improved estimate of the integral.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2126 Figure 22.5
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2127 Figure 22.6
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 28 Improper Integrals Improper integrals can be evaluated by making a change of variable that transforms the infinite range to one that is finite, where –A is chosen as a sufficiently large negative value so that the function has begun to approach zero asymptotically at least as fast as 1/x 2.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2129 Numerical Differentiation Chapter 23 Notion of numerical differentiation has been introduced in Chapter 4. In this chapter more accurate formulas that retain more terms will be developed.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 30 High Accuracy Differentiation Formulas High-accuracy divided-difference formulas can be generated by including additional terms from the Taylor series expansion.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2131 Inclusion of the 2 nd derivative term has improved the accuracy to O(h 2 ). Similar improved versions can be developed for the backward and centered formulas as well as for the approximations of the higher derivatives.
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Copyright © 2006 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. by Lale Yurttas, Texas A&M University Chapter 2132 Richardson Extrapolation There are two ways to improve derivative estimates when employing finite divided differences: –Decrease the step size, or –Use a higher-order formula that employs more points. A third approach, based on Richardson extrapolation, uses two derivative estimates t compute a third, more accurate approximation.
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