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Fatigue Under Wind Loading: Failure Model, Random Loading, and Varying Wind Speed, Slides of Environmental Law and Policy

Fatigue under wind loading, focusing on failure models based on sinusoidal test results, narrow band random loading, and the effect of varying wind speed. It includes information on stress amplitudes, probability density of peaks, and the weibull probability distribution.

Typology: Slides

2012/2013

Uploaded on 04/25/2013

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gurudev 🇮🇳

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Download Fatigue Under Wind Loading: Failure Model, Random Loading, and Varying Wind Speed and more Slides Environmental Law and Policy in PDF only on Docsity!

  • Occurs on slender chimneys, masts under vortex shedding - narrow

(frequency) band

  • Occurs on steel roofing under wide band loading
  • May occur in along-wind dynamic response - background - wide band
  • resonant - narrow band
  • Failure model - based on sinusoidal test results

Typical s-N graph

:

  • Failure model

Miner’s Rule :  1 

i

i

N

n

Assumes fractional damage at different stress amplitudes adds

linearly to give total damage

ni = number of stress cycles at given amplitude

Ni = number of stress cycles for failure at that amplitude

No restriction on order of

loading

‘High-cycle’ fatigue (stresses below yield

stress)

  • Narrow band random loading :

since N(s) = K/s

m

total number of cycles with amplitudes in the range s to s,

n(s) = o

T fp(s). s

fractional damage at stress level, s

K

υ Tf (s) s δs

N(s)

n(s)

m o p

  • Narrow band random loading :

By Miner’s Rule :

Probability distribution of peaks is

Rayleigh : (Lecture 3)

K

υ T f (s) s ds

N(s)

n(s) D

m o 0 p

0

 

    

2

2

p (^2) 2 σ

s exp σ

s f (s)

substituting, damage ds

2 σ

s s exp Kσ

υ T D 2

2 m 1 (^20)

o 

 

m ( 2 σ) Γ( K

υ (^) o T m  

(x) is the Gamma Function ( n! = (n+1) )

EXCEL gives loge (x) : GAMMALN()

  • Wide band loading :

More typical of wind loading

Fatigue damage under wide band loading : D wb =

D nb

 = empirical factor

Lower limit for  = 0.926 - 0.033m (m = exponent of s-N

curve)

  • Effect of varying wind speed :

Standard deviation of stress is a function of mean wind

speed :  = AU

n

Probability distribution of U :

(Weibull)

k

U c

U

F (U) 1 exp

Loxton 1984-2000 (all directions)

0 5 10 15 20 25 Wind speed (m/s)

data Weibull fit (k=1.36, c=3.40)

Probability of exceedence

  • Effect of varying wind speed :

Total damage for all mean wind speeds :

  1. U f (U) dU 2

m Γ( K

υ T( 2 A) D (^) U

mn

0

m o 

 

dU c

U

exp c

k

  1. U 2

m Γ( K

υ T( 2 A)

k

k

mn k 1

0

m o

   

k

mn k

  1. Γ( 2

m Γ( K

υ T( 2 A) c D

m mn o   

  • Fatigue life :

Lower limit (based on narrow band vibrations) :

) k

mn k

  1. Γ( 2

m υ ( 2 A) c Γ(

K T m mn o

lower  

 

) k

mn k

  1. Γ( 2

m λυ ( 2 A) c Γ(

K T m mn o

upper  

 

Upper limit (based on wide band vibrations) ( < 1) :

o

(cycling rate or ‘effective’ frequency)

Can be taken as natural frequency for lower limit;

0.5 x natural frequency for upper limit

Sensitivity :

Fatigue life is inversely proportional to

A

m

  • sensitive to stress concentrations

Fatigue life is inversely proportional to

c

mn

  • sensitive to wind climate