Reliability Aspects · 2013-05-27 · -theory of probability and statistics, fuzzy logic -...
Transcript of Reliability Aspects · 2013-05-27 · -theory of probability and statistics, fuzzy logic -...
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Reliability Aspects
Milan HolickýCTU in Prague
Leonardo da VinciAssessment of existing structuresProject number: CZ/08/LLP‐LdV/TOI/134005
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Uncertainties are always present•Uncertainties (aleatoric and epistemic) Decription
- randomness - natural variability- statistical uncertainties - lack of data- model uncertainties - simplified models - vagueness - imprecision in definitions- gross errors - human factors- ignorance - lack of knowledge
•Tools- theory of probability and statistics, fuzzy logic- reliability theory and risk engineeringSome uncertainties are difficult to quantify
Density Plot (Shifted Lognormal) - [A1_792]
210 220 230 240 250 260 270 280 290 300 310 320 330 340 350 360 370 380 390 400 410 4200.000
0.005
0.010
0.015
0.020
Relative frequency
Yield strength [MPa]
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Reliability - ability of a structure to fulfil all required
functions during a specified period of time under given conditions
Failure probability Pf
- most important measure of structural reliability
Eurocode EN 1990:
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Limit State Approach• Limit states - states beyond which
the structure no longer fulfils the relevant design criteria
• Ultimate limit states– loss of equilibrium of a structure as a rigid body– rupture, collapse, failure – fatigue failure
• Serviceability limit states– functional ability of a structure or its part– users comfort– appearance
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Reliability Methods
pf 10−1 10−2 10−3 10−4 10−5 10−6 10−7
β 1,3 2,3 3,1 3,7 4,2 4,7 5,2
Reliability measures: failure probability pf and reliability index β
Historical methodsEmpirical methods
FORMLevel II
ProbabilisticLevel III
Level I
Partial Factor Method
Calibration
Calibration
Calibration
Probabilistic methodsDeterministic methods
Historical methodsEmpirical methods
FORMLevel II
ProbabilisticLevel III
Design point methodLevel I
Partial Factor MethodLevel I
Calibration
Calibration
Calibration
Probabilistic methodsDeterministic methods
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Fundamental case for normal distribution E ≤ R
Prubab. Failure
0
Reliability
βσG μG
( )ϕG x
μ μ μ σ σ σG R E G R E= − = +, 2 2 2
Reliability index : 2/1220 )( ER
ER
G
Guσσμμ
σμβ
+−
==−=
G = R - ETransformation of G to standardized variable U=(G – μG)/σG
For G = 0 the standardized variable u0 =(0 – μG)/σG
pf= Φ(−β)
Failure probability
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Fundamental case E < R
probab.
e0
Reliability
βσG μG
Failure
( )G xφ
Reliability index for normal dist.: RR eu σμβ /)( 00 −=−=
Load E=e0 known, resistance R random: μR, σR, (αR)Limit state function: g(X) = G = R – E = 0
Transformation of R to standardized variable U=(R – μR)/σR
For R = e0 the standardized variable u0 =(e0 – μR)/σR
pf= Φ(−β)
pf = ΦR(e0)For normal distribution
Failure probability
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E
R
An example of the fundamental caseZ = R - E
μZ = μR - μE = 100 – 50 = 50
β = μZ /σZ = 3.54
Pf = P(Z < 0) = ΦZ(0) = 0.0002
22E
2R
2Z 14σσσ =+=
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β = μZ /σZ = 3.54 Pf = P(Z < 0) = ΦZ(0) = 0.0002,
β Is the distance of the mean of reliability margin from the origin
Relaibility margin and index β
Prubab. Failure
0
Reliability
βσG μG
( )ϕG x
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Z = R - E
∫∫<
ϕϕ=<=0)X(Z
ERf derd)e()r()0Z(PP
E
R
Probabilistic approach
Techniques:
Numerical integration (NI)
Monte Carlo (MC)
First order Second moment method (FOSM)
Third moment method (accounting forskewness)
First Order Reliability Methods (FORM)
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E
R
distribution mean sd R resistance Lognormal 100 10 E load effect Gumbel 50 5
Probabilistic models
40 60 80 100 120 140 0 .00
0 .02
0 .04
0 .06
P rob ab ility d ensity ϕ E (x ), ϕ R (x )
R an d o m v ariab le X
L oad effec t E , G um b el d is trib u tion , μ E = 50 , σ E = 5 R esis tan ce R
lo g-n o rm al d is trib u tion , μ R = 1 0 0 , σ R = 1 0
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Eurocode concepts of partial factors
Reliability index β
Action reliability indexβE = αE β
Resistance reliability indexβR = αR β
Main actionβE = - 0,7 β
AccompanyingβE = - 0,28 β
ResistanceβR = 0,8 β
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Partial factor
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E
R
distribution mean sd R resistance Lognormal 100 10 E load effect Gumbel 50 5
Partial factor approach
40 60 80 100 120 140 0 .00
0 .02
0 .04
0 .06
P rob ab ility d ensity ϕ E (x ), ϕ R (x )
R an d o m v ariab le X
L oad effec t E , G um b el d is trib u tion , μ E = 50 , σ E = 5 R esis tan ce R
lo g-n o rm al d is trib u tion , μ R = 1 0 0 , σ R = 1 0
E k R k
Rk/γm > Ek γQ
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Indicative target reliabilities in ISO 13822
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Updating distributions
fX(x), fX(x|I)
X
prior distribution fX(x)
updated distribution fX(x|I)
updated xdprior xd
P(x|I) = P(x) P(I | x) / P(I)
fX (x|I) = C fX(x) P( I | x)
updated prior likelihood
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q)xL( q)fC)x|(qf QQ |ˆ|(ˆ ''' =
dq)x|(qfqxfxf QXUX ∫
∞
∞−
= ˆ)()( ''
Formal Updating formulas
Ask the expert !
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Concluding remarks on reliability aspects
Uncertainties are always present
Probability Theory may be helpful
Reliability targets depends on consequences of failure
Reliability targets depend on costs of improving
Existing structures may have a lower target reliability
Reliability may be updated using inspection results
There is a relation partial factor – reliability index
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Fatigue steel structures
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no cracks found, but? measured 1 mm, but?
Find
P(a(t+Δt) > d | a(t) = .. of a(t)<..)
0.0
0.2
0.4
0.6
0.8
1.0
0 5 10 15 20 25Scheurafmeting [mm]
POD
alpha = 1 ; beta = 3 alpha = 3 ; beta = 10
d crack a
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Example: Resistance with unknown mean mR and known stand. Dev. sR =17,5
Assume we have 3 observations with mean mm = 350Then mR has sm = 17,5/√3 = 10.If the load is to 304 then:
mZ= 350‐304=46sZ =√(17,52 +102) = 20,2β=2,27Pf=0,0116
Now we have one extra observation equal to 350.In that case the estimate of the mean mm does not change. The standard deviation of the mean changes to 17,5/√(4) = 8,8
mZ= 350‐304=46,sZ =√(17,52 +8,82) = 19,6,β=2,35Pf=0,0095
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Reliabilty level Beta (one year periods)given a crack found at t=10 a
0
2
4
6
8
0 5 10 15 20 25
relia
bilit
y in
dex
time [year]
without inspection
after inspection
fully correlated
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Existing Structures (NEN 8700)
Reliability index in case of assessment
Minimum β < βnew – 1.0
Human safety: β > 3.6 – 0.8 log T
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limit
Condition⇑
Time ⇒
Inspection en monitoring
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E
R
EXAMPLE
Resistance: R = π d2 fy / 4Load effect: E = Vρ
Failure if E>R or: Vρ > π d2 fy / 4Limit state: Vρ = π d2 fy / 4
Limit state function: Z = R-E = π d2 fy / 4 - Vρ
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Reliability index
Probability of Failure = Φ(‐β) ≈ 10 ‐ β
β 1.3 2.3 3.1 3.7 4.2 4.7
P(F)=Φ(-β) 10-1 10-2 10-3 10-4 10-5 10-6
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Relation Partial factors and beta‐level:
α = 0.7‐0.8β = 3.3 ‐ 3.8 ‐ 4,3 (life time, Annex B)k = 1.64 (resistance)k = 0.0 (loads)V = coefficient of variation
γ = exp{α β V – kV} ≈ 1 + α β V
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Extensions
• load fluctuations• systems • degradation• inspection• risk analysis• target reliabilities
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JCSS TARGET RELIABILITIES βfor a one year reference period
Consequences of failure ⇒
Minor Moderate Large
Large β=3.1 (pF≈10‐3) β=3.3 (pF≈ 5 10‐4) β=3.7 (pF≈ 10‐4)
Normal β=3.7 (pF≈10‐4) β=4.2 (pF ≈ 10‐5) β=4.4 (pF ≈ 5 10‐6)
Small β=4.2 (pF≈10‐5) β=4.4 (pF≈ 5 10‐5) β=4.7 (pF≈ 10‐6)
Cost toincrease safety ⇓
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Human life safety• Include value for human life in D• Still reasons for IR and SR• Example: p < 10‐4 / year
optimal annual failure probability
0
0,05
0,1
0,15
0,2
0,25
0 10 20 30 40 50 60
design working time [year]
times
0,0
01
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Consequence class
Minimum reference period
for existing building
β-NEW β-EXISTING
wn wd wn wd 0 1 year 3.3 2,3 1.8 0.8 1 15 years 3.3 2,3 1.8a 1.1a 2 15 years 3.8 2.8 2.5a 2.5a 3 15 years 4.3 3.3 3.3a 3.3a
Class 0: As class 1, but no human safety involved wn = wind not dominant wd = wind dominant (a) = in this case is the minimum limit for personal safety normative
Example NEN 8700 (Netherlands)
Minimum values for the reliability index β with a minimum reference period
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Updating
1) Updating distributions (eg concrete strength)
x x
2) Updating failure probability P{F | I }Example: I = {crack = 0.6 mm}
see JCSS document on Existing Structures en ISO13822
Observations
Information ( I )Rk at design
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)()()(
IP IF PIFP ∩
=
)P(B)BP(AB)P(A =∩ Two types of information I:
equality type: h(x) = 0
inequality type: h(x) < 0; h(x) > 0
x = vector of basic variables
)I)P(IP(F I)P(F =∩
)0)(()0)(0)(()(
1
12
>>∩<
=thP
t h tZPIFP
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Reliability index β Reliability classes
Consequences for loss of human life, economical, social and environmental
consequences
βa for Ta= 1 yr
βd for Td= 50 yr
Examples of buildings andcivil engineering works
RC3 – high High 5,2 4,3 Important bridges, public buildings
RC2 – normal Medium 4,7 3,8 Residential and office buildings
RC1 – low Low 4,2 3,3 Agricultural buildings, greenhouses
Target Reliabilities in EN 1990, Annex B
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q)xL( q)fC)x|(qf QQ |ˆ|(ˆ ''' =
dq)x|(qfqxfxf QXUX ∫
∞
∞−
= ˆ)()( ''
Formal Updating formulas
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Cost optimisation / design versus assessment
PF = 10 ‐β