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The Code Optimisation Module - PROCODE

Rolf Skjong & Knut RonoldDet Norske Veritas

Rolf.Skjong@dnv.com

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

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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