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LectureLecture

1100

Numerical Methods for EngineeringNumerical Methods for Engineering MECN 3500 MECN 3500

Professor: Dr. Omar E. Meza CastilloProfessor: Dr. Omar E. Meza Castilloomeza@bayamon.inter.edu

http://www.bc.inter.edu/facultad/omeza

Department of Mechanical EngineeringDepartment of Mechanical Engineering

Inter American University of Puerto RicoInter American University of Puerto Rico

Bayamon CampusBayamon Campus

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Tentative Lectures ScheduleTentative Lectures Schedule

TopicTopic LectureLecture

Mathematical Modeling and Engineering Problem SolvingMathematical Modeling and Engineering Problem Solving 11

Introduction to MatlabIntroduction to Matlab 22

Numerical ErrorNumerical Error 33

Root FindingRoot Finding 4-5-64-5-6

System of Linear EquationsSystem of Linear Equations 7-87-8

Least Square Curve FittingLeast Square Curve Fitting 99

Numerical IntegrationNumerical Integration 1010

Ordinary Differential Equations Ordinary Differential Equations

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Newton-Cotes Integration FormulasNewton-Cotes Integration Formulas

Numerical IntegrationNumerical Integration

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To solve numerical problems and To solve numerical problems and appreciate their applications for appreciate their applications for engineering problem solving.engineering problem solving.

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Course ObjectivesCourse Objectives

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badxxfb

a and between curve under the area )(

b

a

dxxf

dxxf

)( :nintegratio Definite •

)( :nintegratio Indefinite •

IntroductionIntroduction

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They are based on the strategy of replacing a complicated function or tabulated data with an approximating function that is easier to integrate:

b

a n

b

adxxfdxxfI )()(

where fn(x) is a polynomial of degree n.

f1(x)f2(x)

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Piecewise functions can be used also to approximate the integral.

3 piecewise linear functions to approximate f(x) between a and b.

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Two forms of the Newton-Cotes formulas:

Closed Forms: the data points at the beginning and end of the limits of integration are known.

Open Forms: integration limits extend beyond the range of the data.

Lecture 10Lecture 10MEC

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2

)()()(

)()( 1

bfafab

dxxfdxxfIb

a

b

a

The integral is approximated by a line:

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Statement: Use the trapezoidal rule to estimate

Example 21.1 Example 21.1

8.0

0

5432 400900675200252.0 dxxxxxx

%5.89

1728.02

232.02.08.0

2

)8.0()0()08.0(

2

)()()(

t

ff

bfafabI

Solution:

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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.

The Multiple-Application Trapezoidal RuleThe Multiple-Application Trapezoidal Rule

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n

n

x

x

x

x

x

x

dxxfdxxfdxxfI1

2

1

1

0

)()()(

2

)()(

2

)()(

2

)()( 12110 nn xfxfh

xfxfh

xfxfhI

n

xfxfxfabxfxfxf

hI

n

n

ii

n

n

ii 2

)()(2)()()()(2)(

2

1

101

10

The total integral is

Substituting the trapezoidal rule for each integral:

Grouping terms:

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Statement: Use the multiple-application trapezoidal rule for n = 2 to estimate

Example 21.1 Example 21.1

8.0

0

5432 400900675200252.0 dxxxxxx

%9.34

0688.14

232.0)456.2(22.08.0

4

)8.0()4.0(2)0()08.0(

)2(2

)()(2)()( 210

t

fff

xfxfxfabI

Solution:

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on Computer Algorithms for the Trapezoidal RuleComputer Algorithms for the Trapezoidal Rule

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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 RulesSimpson’s Rules

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This rule results when a second-order interpolating polynomial is used.

2

where)()(4)(3

)())((

))((

)())((

))(()(

))((

))((

,and Let

)()(

210

21202

10

12101

200

2010

21

20

2

2

0

abhxfxfxf

hI

dxxfxxxx

xxxx

xfxxxx

xxxxxf

xxxx

xxxxI

xbxa

dxxfdxxfI

x

x

b

a

b

a

•After integration,

Simpson’s 1/3 RuleSimpson’s 1/3 Rule

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Statement: Single Application of Simpson’s 1/3 Rule

5432 400900675200252.0)( xxxxxxf

From a=0 to b=0.8. recall that the exact integral is 1.640533

%6.16,2730667.0367467.1640533.1where

367467.16

232.0)456.2(42.08.0

ttE

I

Which is approximately 5 times more accurate than for a single application of the trapezoidal rule (Example 21.1)

Example 21.4 Example 21.4

Solution:

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This rule results when a third-order interpolating polynomial is used.

3

where)()(3)(3)(8

3

,yields This

)()(

3210

3

abhxfxfxfxf

hI

dxxfdxxfIb

a

b

a

Simpson’s 8/3 RuleSimpson’s 8/3 Rule

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Statement: Single Application of Simpson’s 3/8 rule to integrate

5432 400900675200252.0)( xxxxxxf

From a=0 to b=0.8.

Simpson’s rule 3/8 requires four equally spaced points:

232.0)8.0(,487177.3)5333.0(,432724.1)2667.0(,2.0)0( ffff

%4.7,1213630.0519170.1640533.1where

519170.18

232.0)487177.3432724.1(32.08.0

ttE

I

Example 21.6 Example 21.6

Solution:

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Statement: Estimate the cross section area of the stream.

Case StudiesCase Studies

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•Consider this example

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•Trapezoidal rule (h = 4):

•Trapezoidal rule (h = 2):

2

2

m 2.6320

0)8.24.36.3464428.1(20)020(

m 6.5310

0)4.3442(20)020(

I

I

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Integration with Matlab

•Use quad for functions.

SoftwareSoftware

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Homework8 Homework8 www.bc.inter.edu/facultad/omeza

Omar E. Meza Castillo Ph.D.Omar E. Meza Castillo Ph.D.

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