Structural Integrity of Offshore

Wind Foundations

Feargal Brennan

September 2013

Photo: DONG Energy

Presentation

Overview

• Risk based design optimisation;

• Tools to ensure Structural Integrity;

• Inspection Reliability;

• NDT/NDE or SHM?

• Summary & Conclusions.

Fixed Foundations

Risk & Reliability –

learning from Offshore

Oil & Gas

Risk = Probability x

Consequence

Cost with respect to

PoF

US contractor Fluor

has lost the major

arbitration case

against the owners

of the Greater

Gabbard offshore

wind farm SSE and

RWE and will take

a pre-tax hit of

$400m

Structural integrity

Assessment &

Management

Crack

Crack

tip ¼ node

Fla

w S

ize

(mm

)

No of Cycles

Actual

Behaviour

Most Likely Life Prediction not

taking POS into account

Extreme Life

Prediction

a

critical

Structural Analysis

Inspection & Monitoring

Inspection Reliability Damage Model

Repair/Remaining life

Assessment

Reliability Based Life-

Cycle Design,

Reassessment & life

Extension

8

Relia

bili

ty index

Time

Target Reliability

Inspection Strategies

Def

ect

Siz

e

Life

Deterministic Approach

Reliability (or Probabilistic)

inspection intervals

Reliability Based

Design

• Stochastic Modelling of Variables

• Design for Reliability

• Target Reliability set from standards for

existing configurations (DNV-OS-J101) or

generic standards (DNV, ISO)

• Basis for structural optimization and

reliability based inspection

Reliability Based

Design

DNV Classification Note 30-6

Reliability

Assessment

• To quantitatively assess reliability

based on detailed

characterisation of the asset

through inspections, monitoring

and damage modelling.

Offshore Design

Standards

Offshore Structures

Design Guidance

• DNV-OS-J101 Design of Offshore Wind Turbine Structures, October 2007.

• HSE Offshore Technology Report 2001/015 – Steel.

• Recommended Practice for Planning, Designing and Constructing Fixed

Offshore Platforms – Working Stress Design, API RP 2A-WSD, Dec 2002.

• Structural Welding Code – Steel, AWS D1.1/D1.1M2002, American Welding

Society/ANSI.

• Eurocode 3: Design of Steel Structures, BS EN 1993-1-1:2005.

• DNV-RP-C203 Fatigue Design of Offshore Steel Structures, Apr 2008.

• DNV-OS-C201 Structural Design of Offshore units (WSD Method), Oct

2008.

• HSE Offshore Technology Report 92 390 - Background to New Fatigue

Guidance for Steel Joints and Connections in Offshore Structures, 1999.

xxx

xxx

The fictitious Hot-

Spot Stress

21

DNV and BS 7608 Class C curves with and without thickness correction for 87 mm.

22

Damage reduction by misalignment on the C1 S-N curve in air.

Barriers to optimisation

of offshore structures

• The Hot-Spot Stress;

• 30 year old S-N curves;

• S-N Curves that were never

intended for large diameter

circumferential welds;

• API RP 2A etc., i.e. load or stress

based design.

Structural Integrity:

Session 5a

24

Surface Improvement

and good fabrication

practice

Structural Integrity:

Session 5a

25

Peening

Distance into Material Surface

Str

ess

Surface Residual Stress with Applied Bending Stress

Surface Residual Stress

Cold Working

Structural Integrity:

Session 5a

27

Cold Worked & Laser

Peened crack

Stoppers

0

5

10

15

20

25

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

Cycles x 1000

Cra

ck D

ep

th,

(mm

)

Reference -Crack 1

Reference -Crack 2

Test 1

Test 2

Newman and Raju

Offshore Inspection

POD

Flaw Size

% P

OD

Ideal POD

Behaviour

Likely Behaviour

Spurious / False Calls

POD Trials

Blind inspection trials are carried out on a

series of groups of representative

defective specimens

POD = No of successful inspections

No of attempts

P = S

N

POD Confidence

Confidence that the measured POD is

representative of the population is

dependent on sample size

Using a Binomial Distribution:

)!(!

!

,

)1()( )(

SNS

NC

Where

ppCSP

NS

SNS

NS

POD Confidence

)(1 NPC

The confidence that the point

estimate of P is representative

of the population

Probability of obtaining

N successes in N trials

=> for 90/95% POD the minimum

sample size is:

0.95 = 1 - 0.9N

=> N=28.4 i.e. 29 samples

RBI using POD and POS

Actual Behaviour

Fla

w S

ize

(mm

)

No of Cycles

a critical

Initial defect

distribution

POS of

detected

defect

POS of 90/95%

POD defect

Life prediction from initial

defect distribution

Life prediction from POS of

detected defect

Life prediction from

POS of 90/95% defect

POD Trials

NDT, NDE or SHM?

Emerging

Technologies to

support RBI

• The key to a quantitative risk assessment is

good quality information;

• The more information from different sources

leads to greater confidence in RBI input values;

• Structural Integrity Monitoring (SIM) of critical

components coupled with advanced damage

and failure models is becoming a rapidly

developing activity, however, the performance

reliability of SIM needs to be better understood.

How Inspections and

SIM work together

• Crack growth can be monitored and

assessed;

• Repairs and untested design details can be

assessed;

• SIM can point to areas that have been most

highly stressed helping to optimize

inspections and increase POD by simply

looking in the right place;

• SIM can monitor inaccessible areas allowing

relaxation of inaccessibility imposed design

penalties.

Summary &

Conclusions

Summary &

Conclusions

• The offshore and marine renewables industry

can not afford the “over design” luxury that Oil

& Gas has enjoyed;

• Materials, structural analysis techniques and

inspection/monitoring technology and

knowhow is unrecognizable compared to 30

years ago when Oil & Gas platforms were

designed;

Summary &

conclusions (ctd.)

• A combination of risk based design and

maintenance coupled with modern high

strength weldable steels and weld toe

improvement methods promise to deliver cost

effective advanced steel offshore foundations

for wind & marine renewables.