numerical methods formulas, Study Guides, Projects, Research of Numerical Methods in Engineering

problems and exercises :) used for numerical methods

Typology: Study Guides, Projects, Research

2018/2019

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Numerical Methods – Final work-sheet
Numerical derivatives
Forward finite difference
𝛿(𝑥)=𝑓(𝑥+∆𝑥)𝑓(𝑥)
∆𝑥
Backward finite difference
𝛿(𝑥)=𝑓(𝑥)𝑓(𝑥∆𝑥)
∆𝑥
Centered finite difference
𝛿(𝑥)=𝑓(𝑥+∆𝑥)𝑓(𝑥∆𝑥)
2∆𝑥
Numerical Integration
Left endpoint approximation
𝑓(𝑥)𝑑𝑥
𝑓(𝑥)∆𝑥


Right endpoint approximation
𝑓(𝑥)𝑑𝑥
𝑓(𝑥)∆𝑥


Midpoint approximation
𝑓(𝑥)𝑑𝑥
𝑓𝑥+𝑥
2∆𝑥


The Trapezoidal Rule
𝑓(𝑥)𝑑𝑥
=∆𝑥
2(𝑓(𝑥)+2𝑓(𝑥)

 +𝑓(𝑥))
Simpson 1/3 Rule
𝑓(𝑥)𝑑𝑥
=∆𝑥
3(𝑓(𝑥)+4𝑓(𝑥)


  +2 𝑓(𝑥)


  +𝑓(𝑥))
Simpson 3/8 Rule
𝑓(𝑥)𝑑𝑥
=3∆𝑥
8(𝑓(𝑥)+3𝑓(𝑥)


  +2𝑓(𝑥)


 +𝑓(𝑥))
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Numerical Methods – Final work-sheet

Numerical derivatives

Forward finite difference

Backward finite difference

ି

Centered finite difference

Numerical Integration

Left endpoint approximation

௡ିଵ

௜ୀ଴

Right endpoint approximation

௜ାଵ

௡ିଵ

௜ୀ଴

Midpoint approximation

௜ିଵ

௡ିଵ

௜ୀ଴

The Trapezoidal Rule

௡ିଵ

௜ୀଵ

Simpson 1/3 Rule

௡ିଵ

௜ୀଵ

௜ ௢ௗௗ

௡ିଵ

௜ୀଵ

௜ ௘௩௘௡

Simpson 3/8 Rule

௡ିଵ

௜ୀଵ

௜ ஷଷ௞

௡ିଵ

௜ୀଵ

௜ୀଷ௞

Two-Point Gauss-Legendre Formula

ିଵ

Change of variable: 𝑥 =

௕ା௔

௕ି௔

Differential Equations

Euler Method

௡ାଵ

Heun’ Method

௡ାଵ

௡ାଵ

௡ାଵ

௡ାଵ

Midpoint method

௡ା

௡ାଵ

௜ାଵ

௡ା

Second order Runge-Kutta Methods

௜ାଵ

) ∙ ∆t

ଵଵ

The coefficients satisfy the following relations:

ଵଵ

Fourth-Order Runge-Kutta Method

y y  k k k k h

i 1 i 1 2 3 4

 

k f t h y kh

k f t h y k h

k f t hy k h

k f t y

i i

i i

i i

i i

4 3

3 2

2 1

1