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The Code Optimisation Module - PROCODE
Rolf Skjong & Knut RonoldDet Norske Veritas
JCSS Workshop on Code Calibration, March 21-22 2002
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PROCODE
PROCODE was developed in the early nineties in the Reliability of Marine Structures Project
.. first use published at OMAE 1992 …code optimisation .. has been used extensively in many code calibration
studies on ship rules .. has been used on a project basis on other calibration
studies (e.g. Danish Wind Mill design code) .. is linked to PROBAN .. use PROBAN for all reliability calculations
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PROCODE
Objective– Optimisation of partial safety factors– Control Variables: Partial Safety Factors– Minimum Scatter around a target reliability by
minimising the penalty function
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PROCODE
SCOPE of code is specified by design cases External and Internal Conditions are specified
separately External:
– External could be environmental conditions (Hs,Tz)
– Conditions are associated with a Name-Set– PROCODE take care of the Name-Set and Names
that points to the PROBAN variables during execution
HS TZCOND1 VAR3 VAR5COND2 VAR7 VAR12
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PROCODE
Internal:– Relates to structural conditions– Internal could be such as material properties,
slenderness measures– Conditions are associated with a Name-Set– PROCODE take care of the Name-Set and Names
that points to the PROBAN variables during execution
LD RDS1 VAR2 VAR6DS2 VAR8 VAR11
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PROCODE
The scope is defined by the design cases defined by combining external and internal conditions
(COND1, DS1) (COND1, DS2)(COND2, DS1) (COND2, DS2)
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PROCODE
Variables– X, stochastic– E, environment– D, design situation , design parameters that may be chosen by the
designer
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PROCODE
Limit State Function: G(X,E,D,)>0 Code Check Function: h(x,e,d,,)>= 0 M failure modes k=1-M Nk code check functions n=1- Nk
Code check requirements: hnk(x,ei,di, ij, ) >= 0
Limit State functions: Gk(X,Ei,Di,ij) >= 0
i,j defining the scope matrix
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PROCODE
)),,,((min ,1
,mode,
kTijjik
M
kk pw
ij
DEX
},...1,,...1,0),,,,( ,, kjijink NnMkh dexSubjected to:
With one of the inequalities turning into equality
One design Case:
This is generalised to Multiple design cases in PROCODE
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PROCODE
Programmable functions– Limit States– Code Checks– Penalty functions
Defined by Data (additional to PROBAN)– Scope (Internal, Internal)– Safety Factor – Design Parameter
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PROCODE RESULTS
Code Evaluation (before optimisation starts) Optimised partial safety factors Resulting reliabilities Resulting design parameters (input to cost analysis)
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PROCODE Examples
Jack-up, spudcan/punching & tubular members/buckling
Tension Piles/Pull out Wind turbine rotor blades/fatigue Ship Structures/Long Series of studies
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PROCODE Examples
Wind turbine rotor blades/fatigue Ronold/C.Christensen “Optimisation of design code for
wind-turbine rotor blades in fatigue”. Eng.str. 23(2001)– Previous work on probabilistic design– Wish to develop code valid for variation of designs,
locations and materials– Fatigue in rotor blade root - SN approach– Material is fibre-reinforced polyester laminate
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PROCODE Examples
Wind turbine rotor blades/fatigue Scope Parameters
– Rotor radius– chord length– section modulus (blade root)– rotor frequency– hub height– material
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PROCODE Examples
T a b l e 1 R e s u l t s o f C o d e O p t i m i z a t i o n f o r W i n d - T u r b i n e R o t o r B l a d e s
P a r t i a l s a f e t y f a c t o r O p t i m i z e d s a f e t y f a c t o r
f
250.010
956.0
0590.00.1n
R
m
444.1437.0998.0 eD e s i g n c a s e A c h i e v e d r e l i a b i l i t y i n d e x S c a t t e r ( d e v i a t i o n f r o m t a r -
g e t )1 1 0 4 . 2 8 1 4 . 3 2 0 0 . 0 1 6 0 . 0 5 52 1 1 4 . 3 6 7 4 . 4 2 7 0 . 1 0 2 0 . 1 6 23 1 2 4 . 2 5 5 4 . 2 7 7 0 . 0 1 0 0 . 0 1 24 1 3 4 . 2 4 8 4 . 1 8 8 0 . 0 1 7 0 . 0 7 75 1 4 4 . 1 9 2 4 . 1 2 4 0 . 0 7 3 0 . 1 4 16 1 5 4 . 3 6 7 4 . 3 5 0 0 . 1 0 2 0 . 0 8 57 1 6 4 . 2 2 3 4 . 2 2 0 0 . 0 4 2 0 . 0 4 58 1 7 4 . 2 0 5 4 . 2 1 8 0 . 0 6 0 0 . 0 4 79 1 8 4 . 2 5 7 4 . 2 9 2 0 . 0 0 8 0 . 0 2 7
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PROCODE Examples
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PROCODE Examples
Table 1: Cross section area and weight of ship decks per meter length and per stiffer before and after rulecalibration, flat bar profiles.
BeforeCalibration
Calibrated:T=2.5 Calibrated:T=3.09 Calibrated:T=3.5 Calibrated:T=3.72
Ex.Area
( 2mm)
Weight(t)
Area
( 2mm)
Weight(t)
=3.09( 2mm)
Weight(t)
Area
( 2mm)
Weight(t)
Area
( 2mm)
Weight(t)
MeanValue
23301 0.1829 25875 0.2031 28546 0.2241 30230 0.2373 31086 0.2440
Table 2: Cross section area and weight of ship decks per meter length and per stiffer before and after rulecalibration, L-profiles.
Before Calibration Calibrated:T=2.5 Calibrated:T=3.09 Calibrated:T=3.5 Calibrated:T=3.72
Ex.Area
( 2mm)
Weight(t)
Area
( 2mm)
Weight(t)
=3.09( 2mm)
Weight
(t)Area
( 2mm)
Weight(t)
Area
( 2mm)
Weight(t)
MeanValue
23355 0.1833 21281 0.1671 22143 0.1738 24481 0.1922 26399 0.2072
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PROCODE Examples
Table 1: Total weight and cost for the average ship deck before and after Calibration, Flat bar and L- stiffenerprofiles.
Stiffener profile BeforeCalibration
After=2.50
After.=3.09
After=3.50
After=3.72
Flatbar Weight (T) 1,829 2,031 2,241 2,373 2,440
FlatbarCost (US$) 3,658,000 4,062,000 4,482,000 4,746,000 4,880,000L-profileWeight (T) 1,833 1,671 1,738 1,922 2,072L-profileCost (US$) 3,666,000 3,342,000 3,476,000 3,844,000 4,144,000
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PROCODE Examples
Table 1:Increase of the ship deck cost for different target beta,
Flat bar stiffener profiles.Cost increase relativeto
=2.50 =3.09 =3.50 =3.72
=2.50 - 10.3% 16.8% 20.1%
Past practice* =2.40
11.0% 22.5% 29.7% 33.4%
* before calibration
Table 2: Increase of the ship deck cost for different target beta,
L-stiffener profiles.Cost increase relative to =2.50 =3.09 =3.50 =3.72
=2.50 - 4.0% 15.0% 24.0%
Past practice* =3.40
-8.5% -5.5% 4.9% 13.0%
* before calibration
22
PROCODE Examples
Table 1: GCAF/NCAF in US$ million for increases ofthe reliability index
Flat Bar L-Profile
2.53.09 0.402/-2.80 0.128/-3.073.093.50 1.76/-1.74 2.46/-0.7433.503.72 4.44/1.24 9.93/6.73