This document provides an overview of safety management for offshore structures. It discusses accident experiences that revealed hazards and risks. Risk can be controlled through adequate design, inspection, repair, maintenance, and quality assurance of engineering processes. Structural robustness is important and can be ensured using accidental collapse limit state criteria for fires, explosions, and other accidental loads. Reliability methodology is useful for obtaining quantitative safety measures regarding ultimate failure and fatigue failure under inspection and repair strategies. Overall, the document emphasizes a risk-based, probabilistic approach to safety management of offshore structures.

1. CORE Report No. 2005-04
SAFETY OF OFFSHORE
STRUCTURES
by
TORGEIR MOAN
Professor
Norwegian University of Science and Technology
and
Keppel Professor
National University of Singapore
Centre for Offshore Research & Engineering
National University of Singapore

2. Keppel Offshore and Marine Lecture
November 26. 2004
Safety of Offshore Structures
By
Professor Torgeir Moan
Director, Centre for Ships and Ocean Structures,
Norwegian University of Science and Technology
Keppel Professor, National University of Singapore

3. Foreword
The Second Keppel Offshore & Marine Lecture was delivered by Professor Torgeir
Moan at the National University of Singapore (NUS) on 26 November 2004. This report
is the written version of the lecture. The Lecture was supported by many professional
societies, including American Society of Mechanical Engineers (Singapore Section), The
Institution of Engineers Singapore, The Institute of Structural Engineers, The Joint
Branch of Royal Institution of Naval Architects and Institute of Marine Engineering
Science & Technology, Society of Naval Architects and Marine Engineers Singapore,
Singapore Shipping Association and Singapore Structural Steel Society.
The Keppel Professorship in Ocean, Offshore and Marine Technology in NUS was
launched officially by His Excellency, President S.R. Nathan of Singapore and
Chancellor of NUS on 19 September 2002. The Professorship has been established
under the Department of Civil Engineering, and is part of the bigger umbrella of the
Centre for Offshore Research & Engineering (CORE) in NUS. CORE has received seed
funding from Keppel Offshore & Marine Ltd and Economic Development Board
(Singapore). The Centre aims to be a focal point for industry participation and activities
in Singapore, and promotes multi-disciplinary research by drawing on the expertise of
various universities, research institutes, and centres for integrated R&D.
Professor Moan, the first Keppel Professor, is an academic of international stature
through his 30 years of close involvement in the international offshore oil and gas and
marine fraternity. He brings a global perspective to promote R&D in Singapore, with a
particular emphasis on the technological interests of Keppel Offshore & Marine. He will
serve as the beacon of guidance and inspiration for academics as well as industry.
CORE acknowledges the significant support of everyone in Keppel Offshore & Marine,
especially Mr Choo Chiau Beng, Mr Tong Chong Heong and Mr Charles Foo, for their
immense contributions. CORE is working closely in partnership with Keppel on R&D,
Education and Training to draw young talents into the offshore and marine industry.

4. Safety of Offshore Structures
Torgeir Moan
Centre for Ships and Ocean Structures
Norwegian University of Science and Technology
Summary
An overview of important developments regarding safety management of offshore
structures is given. Based on relevant experiences with accidents, the hazards and the
means to control the associated risk are categorized from a technical-physical as well
as human and organizational point of view. This includes considerations of the risk
associated with fatigue, corrosion and other degrading phenomena. The risk can be
controlled by use of adequate design criteria, inspection, repair and maintenance of
the structures as well as quality assurance and control of the engineering processes.
Such measures are briefly outlined, while the emphasis is placed upon a quantitative
design approach for dealing with structural robustness. In this connection the inherent
differences in the robustness of various structural concepts are pointed out. The appli-
cation of reliability methodology to obtain quantitative measures of structural safety
relating to ultimate failure as well as handle the combined effect of design, inspec-
tion and repair strategy on fatigue failure is highlighted. The application of risk
analysis to establish robustness criteria corresponding to a certain risk acceptance
level is briefly mentioned. The challenges of Quality Assurance and Control to new
structures are briefly outlined, with particular reference to recent examples of new
loading phenomena such as ringing and springing of platforms.
i

5. 1. Introduction
Oil and gas are the dominant sources of energy in our society. Twenty percent of
these hydrocarbons are recovered from reservoirs beneath the seabed. Various kinds
of platforms are used to support exploratory drilling equipment, and the chemical
(production) plants required to process the hydrocarbons. Large production platforms,
such as some of those in the North Sea, represent investment of billions of U.S. dol-
lars and significant operational costs. Pipelines or tankers are used to transport the
hydrocarbons to shore. This paper is limited to deal with offshore structures, see Fig.
1.
a) Offshore oil and gas b) Platform for exploratory c) Platform for oil and gas
exploitation drilling operation production (chemical processing)
Fig. 1 Subsea oil and gas exploitation
The continuous innovations to deal with new serviceability requirements and demand-
ing environments as well the inherent potential of risk of fires and explosions have
lead to an industry which has been in the forefront of development of design and
analysis methodology. Fig. 2 shows phases in the life cycle of offshore structures. The
life cycle of marine systems is similar to that of other systems. In view of the ecologi-
cal issue removal or clean-up need to be considered. In this aspect the recycling of the
material is an important issue. In the life cycle phases of structures the design phase is
particularly important. Offshore structures need to fulfil serviceability and safety re-
quirements. Serviceability requirements depend upon the function of the structure,
which is to provide a platform and support of equipment for drilling or for the produc-
tion of hydrocarbons. Drilling units need to be mobile while production platforms are
generally permanent. Production platforms are commonly designed to carry large
chemical factories together with large hydrocarbon inventories (Fig. 1c). Safety re-
1

6. quirements are introduced to limit fatalities as well as environmental and property
damages.
The focus here is on the structural safety during the life cycle of the platforms. A ra-
tional safety approach should be based on:
- Goal-setting; not prescriptive
- Probabilistic; not deterministic
- First principles; not purely experimental
- Integrated total; not separately
- Balance of safety elements; not hardware
Design Data, methods,
for criteria
- serviceability &
- producability
- safety Layout/
Scantlings
Fabrication
- Fabrication plan -
Fabrication &
- Inspection/repair
Operation
data
Operation
- Operation plan
Inspection/
monitoring/
repair /
maintenance
Reassessment
Removal and reuse
Fig. 2: Life cycle phases of offshore structures
The safety management of structures is different for different industries depending on
the organisation as well as regulatory contents. For instance the safety management of
offshore structures differs from that for trading ships. One reason for this difference is
the fact that safety management of trading vessels emerged for centuries through em-
piricism while off-shore structures have primarily come about in the last 50 years
when first principles of engineering science had been adequately developed to serve
as basis for design. Similarly the regulatory regime differs between ships and offshore
structures in that offshore operation take place on continental shelves under the juris-
diction of the local government. Typically authorities in the continental shelf states
have to issue regulations. Examples of these are MMS/API in USA, HSE in UK and
NPD in Norway. However the provisions for stability and other maritime issues are
based on those of IMO and their corresponding national organizations. Classification
societies primarily provide rules for drilling units and services for production facili-
ties, which primarily are handled by national authorities. Since early 1990s ISO has
been developing a harmonized set of codes for offshore structures with contribution
from all countries with major offshore operations.
Over the time safety management of offshore structures has been developed, in paral-
lel with the evolvement of the technology and the competence to deal with it. Initially
civil engineering was the driving force for structural safety management. Later the
2

7. aeronautical and nuclear industries also played an important role. However in the last
20-30 years the developments in the offshore industry has had a significant impact on
the development of safety approaches. This is partly because the offshore industry
plays a key role in the “world’s economy”. Moreover the oil and gas represent energy
with large potential accident consequences. Companies involved in structures and/or
facilities that experience accidents may suffer loss of reputation and this may damage
the public’s trust on the companies.
The rationalisation of safety management of offshore structures began in early 70’s.
Among the milestones is the introduction of Risk Analysis in 1981 and Accidental
Collapse Design criterion in 1984 by the Norwegian Petroleum Directorate and the
HSE Safety case approach in 1992, when the ALARP principle - as large as reasona-
bly practicable – was introduced for determining the target safety level.
To limit the likelihood of fatalities and environmental and property damages, offshore
structures should be designed, fabricated and operated in such a manner that the prob-
ability of the following failure modes is adequately small:
- overall, rigid body instability (capsizing) under permanent, variable and envi-
ronmental loads
- failure of (parts of) the structure foundation or mooring systems, considering
permanent, variable, and environmental as well as accidental loads
Stability requirements for floating platforms affect the layout and the internal struc-
ture – subdivision in compartments. Criteria to prevent progressive structural failure
after fatigue failure or accidental damage would have implications on overall layout
of all types of platforms. Otherwise a structural strength criterion affects the scant-
lings of the stiffened, flat, and cylindrical panels that typically constitute floating off-
shore structures.
If the location is far off shore then evacuation and rescue will be difficult. On the
other hand, this implies that accidents on offshore facilities affect the general public to
a lesser extent than accidents on similar facilities on land.
In the following sections accident experiences on offshore structures will be briefly
explained. Then, an outline of various measures to manage the safety or ensure that
the risk is within acceptable limits, is given. This includes: Design and inspection
criteria as well as reliability methodology to calibrate the partial safety factors to cor-
respond to a defined acceptable safety level. In particular it is explained how fatigue
failures can be avoided by design as well as inspections and regular monitoring of the
structure. Emphasis is placed on how structural robustness can be ensured by using
so-called Accidental Collapse Limit State (ALS) criteria. Such criteria are exempli-
fied in relation to fires, explosions and other accidental loads. Finally, Quality Assur-
ance and/or Quality Control of the engineering process will be described with particu-
lar reference to dealing with unknown wave loading and response phenomena.
2. Accident Experiences
2.1 Accident experiences at large
Safety may be regarded as the absence of accidents or failures. Hence the insight
about safety features can be gained from detailed information about accidents and
failures. To learn about the intrinsic nature of accidents, it is mandatory to study the
detailed accounts provided from investigations of catastrophic accidents since the
3

8. necessary resources are then spent to investigate such accidents. Such studies include
those of the platforms Alexander Kielland in 1980 (ALK, 1981, Moan and Holand,
1981b), Ocean Ranger in 1982 (OR, 1984), Piper Alpha in 1988 (PA, 1990), and P-36
in 2001 (P-36, 2003). See also Bea (2000a, 2000b). In addition, the statistics about
offshore accidents, such as ones given in WOAD (1996), provide an overview.
Global failure modes of concern are
- capsizing/sinking
- structural failure
- positioning system failure
the former two modes represent catastrophic events while the latter one is only critical
for Tension-leg platforms. Global failures normally develop in a sequence of technical
and physical events. However, to fully understand accidents it is necessary to interpret
them in the view of human and organizational factors (HOF). This includes possible
deficiencies in relevant codes, possible unknown phenomena that have materialized as
well as possible errors and omissions made in engineering processes, fabrication
processes or in the operation itself.
b) Model of Ocean c) Piper Alpha fire d) P - 36 accident in 2001
Ranger, which capsized in and explosion in 1988
a) Alexander L. Kielland
1982, during survival
before and after capsizing
testing
in 1980
Fig. 3: Examples of accidents which resulted in a total loss.
Let us consider an example: The platform shown in Figure 4a in the Gulf of Mexico.
This is one of many platforms that were damaged during the passage of the hurricane
Lilli. Physically there is no doubt that this accident was due to extreme wave forces.
To explain from a human and organizational point of view why the platform was not
strong enough to resist the wave forces, we have to look at the decisions that were
made during the design phase regarding loads, load effects, resistance and safety fac-
tors. The explanation might be that design was based on an inadequate wave condi-
tions or load calculation. The damage could also be due to the occurrence of a particu-
lar a wave phenomenon, such as an abnormal wave crest (see Fig. 4b) or another “un-
known” wave phenomenon. In the case of the exceptional wave in Fig. 4b, the ques-
tion is whether the extreme crest height of 18.5 m should be considered as the so-
called “freak” wave or simply a rare wave. Alternatively, the reason could be inade-
quate air-gap provided in the design. Yet another explanation might be that an im-
proper strength formulation was used (as was the case in design of early generation
platforms). Finally, the safety factors might not have been sufficient to cover the in-
herent uncertainties. For each of these possible causes, two explanations need to be
4

9. considered, namely 1) The state of art in offshore engineering was inadequate at the
time of design ; 2) Errors and omission were made during design or fabrication! Ob-
viously, these two explanations have different implications on the risk reducing ac-
tions.
In this connection it is noted that several types of environmental load phenomena,
such as green water on deck and slamming (Fig. 4 c-d) are subjected to large uncer-
tainties. In general, if the phenomenon is known but subject to significant uncertain-
ties, the design approach taken is normally conservative.
18
5
b) Wave record from a platform site in the
North Sea on January 1. 1995.
a)Severe damage caused on a jacket
platform in the Gulf of Mexico by
Hurricane Lilli
c) Green water and deck slamming d) Deck slamming on semi-
on FPSO submersible platform
Fig. 4 Structural damage due to environmental loads
The technical-physical sequence of events for the Alexander Kielland platform was:
fatigue failure of one brace, overload failure of 5 other braces, loss of column, flood-
ing into deck, and capsizing. For Ocean Ranger the accident sequence was: flooding
through broken window in ballast control room, closed electrical circuit, disabled bal-
last pumps, erroneous ballast operation, flooding through chain lockers and capsizing.
Piper Alpha suffered total loss after: a sequence of accidental release of hydrocarbons,
as well as escalating explosion and fire events. P-36 was lost after: an accidental re-
lease of explosive gas, burst of emergency tank, accidental explosion in a column,
progressive flooding, capsizing and sinking after 6 days.
Table 1 shows accident rates for mobile (drilling) and fixed (production) platforms
according to the initiating event of the accident WOAD (1996). Table 1 is primarily
based upon technical-physical causes. Severe weather conditions would normally af-
fect capsizing/ foundering as well as structural damage. In most cases there existed
human errors or omissions by designers, fabricators or operators of the given installa-
tion was a major contributor to the accident. The most notable in this connection is,
of course accidents caused by loads such as ship impacts, fires and explosions which
should not occur but do so because of errors and omissions during operation.
In general, accidents take place in sequences. For floating platforms, the loss of buoy-
ancy and stability is commonly an important aspect of total loss scenarios. Structural
damage can cause progressive structural failure or flooding. Progressive flooding at-
5

10. tributes to a greater probability of total loss of floating structures than progressive
structural failure.
Degradation due to corrosion and fatigue crack growth are gradual phenomena. How-
ever, if the fatigue life is insufficient to make Inspection, Monitoring, Maintenance
and Repair (IMMR) effective or if there is lack of robustness, fatigue can cause catas-
trophic accidents, see Fig. 5. Both cases shown in Fig.5 occurred for statically deter-
minate platforms. In other situations through-the-thickness cracks were detected by
inspections before they caused catastrophic failures (Moan, 2004). Corrosion is not
known to have caused accidents with floating offshore structures of significance. On
the other hand, maintenance related events for floating structures is limited. We need
to be aware of this problem, especially for structures with a low fatigue life.
Table 1: Number of accidents per 1000 platform-years. Adapted after WOAD
(1996).
World wide Gulf of Mexico North Sea
Type of
Mobile Fixed Fixed Fixed
accident
1970-79 /80-95 1970-79 /80-95 1970-79 /80-95 1970-79 /80-95
Blowout 18.8/ 11.4 2.5/0.9 2.2/1.0 2.6/1.6
Capsizing/ 24.0/ 19.5 0.5/0.8 0.3/1.1 2.6/0.5
foundering
Collision / contact 24.6/ 14.6 1.6/1.0 1.3/0.7 5.1/6.3
Dropped object 4.2/ 6.1 0.5/0.8 0.1/0.4 10.3/10.6
Explosion 7.4/3.3 0.7/1.6 0.3/0.4 2.6/8.3
Fire 12.3/ 2.0/7.5 1.0/7.8 18.0/42.5
11.9
Grounding 6.1/3.3 - - -
Spill/release 4.9/5.9 1.8/8.7 1.0/5.8 23.1/98.3
Structural damage 25.6/ 18.4 0.5/0.6 0.4/0.5 10.3/6.0
Column D
”Missing braces”
– that cause no
redundancy
Ranger I, 1979 Alexander Kielland, 1980
Fig. 5: The total losses of Ranger I in 1979 and Alexander Kielland in 1981 were
initiated by fatigue failure
6

11. An overall picture of the accident rate in an industry may be displayed by the so-
called Frequency-Consequence diagram as shown in Figure 6. The horizontal axis is
plotted the consequence, in this case in terms of fatalities, N. The vertical axis is
shown the frequency of N or more fatalities per accident. We see that the accident rate
for mobile drilling units is much higher than for fixed production platforms. Fixed
platforms are mainly used as production facilities. Moan and Holand (1981b) ex-
plained the main reasons for the differences in safety levels between mobile and fixed
platforms. Floating production platforms are not included because of the limited ex-
perience with such platforms. The risk is similar that that of passenger vessels and
tankers.
100
Marginally acceptable
Acceptable
Annual frquency of an event
10-1
with N or more fatalities
Oil platforms
Mobile
10-2 Fixed
10-3
Passenger
ferries
10-4
(not ro-ro)
Tankers
10-5
Merchant
vessels
1 10 100 1000 10000
Number of lives lost, N
Fig. 6: Comparison of experienced overall accident rates with respect to fatalities
in the offshore and shipping industries
2.2 Human and organizational factors
Basically, structural failure occurs when the resistance, R is less than the load effect,
S as indicated in Fig. 7. From a Human and Organizational Factor (HOF) point of
view this can be due to too small safety factors to account for the normal uncertainty
and variability in R and S relating to design criteria. But the main causes of actual
structural failures are the abnormal resistance and accidental loads due to human er-
rors and omissions.
Design errors materialise as a deficient (or excessive) resistance, which cannot be
derived from the parameters affecting the “normal” variability of resistance. Fabrica-
tion imperfections (such as cracks, plate misalignment, etc.), which also affect the
resistance, are influenced by human actions. The “normal” variability of welders per-
formance, environmental conditions, and soon lead to a “normal” variability in the
imperfection size. This is characterised by a smooth variation of the relevant imper-
fection parameter. Occasionally a deviation from “normal practice” does occur, for
instance as an abnormality caused by using a wet electrode, or another gross fabrica-
tion error. The Alexander L. accident in 1980 was caused by a fatigue failure of a
brace and design checks had not been carried out. The implied fatigue life was further
reduced – to 3.5 years - by a fabrication error (70 mm weld defect) as well as inade-
quate inspections (ALK, 1981). Although the fatigue failures that had been experi-
enced in semi-submersibles in the period 1965-70 resulted in fatigue standards, these
7

12. standards were not properly implemented even for platforms built in the 1970’s.
Many platforms built in the 1970’s had joints with design fatigue lives as low as 2-5
years. This fact was evidenced in the extraordinary surveys undertaken after Alexan-
der Kielland accident. The same happened to the first purpose built FPSO and shuttle
tankers put into service in the mid-1980’s. However, ships are obviously more robust
or damage-tolerant than mobile semi-submersible platforms.
Man-made live loads also have a “normal” and an “abnormal” component. While
some loads, notably fires and explosions, ship collisions, etc. do not have a normal
counterpart, they are simply caused by operational errors or technical faults. The mo-
bile platform Ocean Ranger capsized in the offshore of Newfoundland in 1982. The
accident was initiated by control room window breaking due to wave slamming. The
water entering the control room lead to the short circuit of the ballast valve system,
thereby leading to a spurious operation of ballast valves. The resulting accidental bal-
last condition could not be controlled partly because of lack of crew training and
partly because of inadequate ballast pumps, and open chain lockers (OR, 1984).
The catastrophic explosion and fire on the Piper Alpha platform in 1988 was initiated
by a gas leak from a blind flange of a condensation pump that was under maintenance
but not adequately shut down (PA, 1990). The main issue that caused the initiation of
this accident was the lack of communication between the maintenance team and the
control room operators. The gas ignited and the initial explosion lead to damage of an
oil pipe and subsequent oil fires and explosions.
In 2001 the platform P-36 in Brazil experienced a collapse of the emergency drainage
tank, accidental explosion and subsequent flooding capsizing and sinking. A series of
operational errors were identified as the main cause of the first event and also the
sinking (P-36, 2001).
It is a well known fact that the gross errors dominate as the cause of accidents, and
therefore appropriate control measures should be implemented. It is found that the
gross errors cause 80-90% of the failure of buildings and bridges and other civil engi-
neering structures (Matousek and Schneider, 1976). The same applies to offshore
structures.
R&D
Risk
reduction
Do the job Unknown material or Do the job
properly in load phenomenon properly in
the first place
the first place Causes
QA/QC Design QA/QC of
Abnormally Design error design
of design error
low Failure - oversight of load
QA/QC of
QA/QC Fabrication resistance R<S …
operation
error Operational error
of the as- Event
- accidental load
fabricated control
structure ULS: RC/γR > γS1SC1 + γS2SC2 (leak, etc)
FLS: D=Σni/Ni ≤ Dallowable ALS
Inadequate safety factors for design
normal variability of R and S check
Apply adequate safety factors
in ULS/FLS design check
Fig. 7 Interpretation of causes of structural failure and risk reduction measures.
8

13. It has been observed that errors and omissions occur especially in dealing with novel
materials and concepts as well as during periods with economic and time pressures.
In some cases, accidents have been caused by inadequate engineering practice such as
the lack of knowledge regarding new phenomena. Recently new phenomena such as
ringing and spinning of TLPs, degradation failure mechanism of flexible risers, have
been discovered. Nevertheless they were observed in time before any catastrophic
accident could occur.
3. Safety Management
3.1 General
Offshore drilling, production or transport facilities are systems consisting of struc-
tures, equipments and other hardware’s, as well as specified operational procedures
and operational personnel. Ideally these systems should be designed and operated to
comply with a certain acceptable risk levels as specified for example by the probabil-
ity of undesirable consequences and their implications. The safety management needs
to be synchronised with the life cycle of the structure. Structural failures are mainly
attributed to errors and omissions in design, fabrication and, especially, during opera-
tion. Therefore, Quality Assurance and Control (QA/QC) of procedures and the struc-
ture during fabrication and use (operation) is crucial.
To do a truly risk based design, by carrying out the design iteration on the basis of a
risk acceptance criterion, and to achieve a design that satisfies the acceptable safety
level, is not feasible. In reality, different subsystems, like:
- loads-carrying structure & mooring system
- process equipment
- evacuation and escape system
are designed according to criteria given for that particular subsystems. For instance, to
achieve a certain target level, which implies a certain residual risk level, safety criteria
for structural design are given in terms of Ultimate Limit State (ULS) and Fatigue
Limit State (FLS) criteria. Using appropriate probabilistic definitions of loads and
resistance together with safety factors, the desired safety level is achieved. The im-
plicit risk associated with these common structural design criteria is generally small!
The philosophy behind the Accidental Collapse Limit (ALS) criteria is discussed be-
low.
The nature of human errors differs from that of natural phenomena and “normal”
man-made variability and uncertainty. Different safety measures are required to con-
trol error-induced risks. A number of people maintain that gross errors are “Acts of
God” and cannot be dealt with.
However,
- weld defects and fatigue failures due to gross errors had occurred before the Kiel-
land accident
- ballast errors had occurred before the Ocean Ranger accident
- fires and explosions had occurred before the Piper Alpha accident
and so on
9

14. The occurrence of gross errors have been avoided by adequate competence, skills,
attitude and self-checking of those who do the design, fabrication or operation in the
first place; and by exercising “self-checking” in their work.
In addition, quality assurance and control should be implemented in all stages of de-
sign, fabrication and operation. While the QA/QC in the design phase is concerned
with scrutinizing the analysis, design checks and the final scantlings arrived at, the
QA/QC during fabrication and operation phases refers to inspection of the structure
itself.
As mentioned above, operational errors typically result in fires or explosions or other
accidental loads. Such events may be controlled by appropriate measures such as de-
tecting the gas/oil leakage and activating shut down valve; extinguishing of a fire by
an automatically-activated deluge system. These actions are often denoted as “Event
Control”.
Finally, Accidental Collapse Limit State criteria are implemented to achieve robust
offshore structures, that is to prevent that the “structural damage” occurring as fabri-
cation defects or due to accidental loads, escalate into total losses (Moan 1994).
Table 2 summarises the causes of structural failure from a risk management point of
view, and how the associated risk may be ameliorated.
Adequate evacuation and escape systems and associated procedures are crucial for
controlling failure consequences in terms of fatalities.
Table 2: Causes of structural failures and risk reduction measures
Cause Risk Reduction Measure
• Less than adequate safety margin to - Increased safety factor or margin in ULS, FLS;
cover “normal” inherent uncertain- - Improve inspection of the structure(FLS)
ties.
• Gross error or omission - Improve skills, competence, self- checking (for
during d, f, o)
- design (d) - QA/QC of engineering process (for d)
- fabrication (f) - Direct design for damage tolerance (ALS) – and
- operation (o) provide adequate damage condition (for f, o)
- Inspection/repair of the structure (for f, o)
• Unknown phenomena - Research & Development
3.2 Design and inspection criteria
Adequate performance of offshore structures is ensured by designing them to comply
with serviceability and safety requirements for a service life of 20 years or more, as
well as carrying out load or response monitoring, or inspection and taking the neces-
sary actions to reduce loads directly or indirectly, by, e.g., removal of marine growth,
or to repair, when necessary.
Serviceability criteria are introduced to make the structure comply with the functions
required. These criteria are commonly specified by the owner. Production platforms
are usually made to be site- specific, while drilling units are commonly intended for
operation in specific regions or world wide.
10

15. Safety requirements are imposed to avoid ultimate consequences such as fatalities and
environmental or property damages. Depending upon the regulatory regime, separate
acceptance criteria for these consequences are established. Property damage is meas-
ured in economic terms. Fatalities and pollution obviously also have economic impli-
cations. In particular, the increasing concern about environmental well-being can
cause small damages to have severe economic implications. While fatalities caused by
structural failures would be related to global failure, i.e. capsizing or total failure of
deck support, smaller structural damages may result in pollution; or property damage
which is costly to repair such as the damages of an underwater structure.
The current practice which is implemented in new offshore codes, issued e.g. by API
(1993/97), ISO 19900 (1994-) and NORSOK (1998a, 1998b, 1999, 2002) as well as
by many classification societies, and the most advanced codes are characterized by
- design criteria formulated in terms of limit states (ISO 19900, 1994)
– see Table 3
- semi-probabilistic methods for ultimate strength design which have been cali-
brated by reliability or risk analysis methodology
- fatigue design checks depending upon consequences of failure (damage-
tolerance) and access for inspection
- explicit accidental collapse design criteria to achieve damage-tolerance for the
system
- considerations of loads that include payload; wave, current and wind loads, ice
(for arctic structures), earthquake loads (for bottom supported structures), as
well as accidental loads such as e.g. fires, explosions and ship impacts
- global and local structural analysis by finite element methods for ultimate
strength and fatigue design checks
- nonlinear analyses to demonstrate damage tolerance in view of inspection plan-
ning and progressive failure due to accidental damage
Fatigue crack growth is primarily a local phenomenon. It requires stresses to be calcu-
lated with due account of the long-term wave conditions, global behaviour as well as
the geometric stress concentrations at all potential hot spot locations, and suitable
fatigue criteria (e.g. Miner’s rule). Fatigue strength is commonly described by SN-
curves, which have been obtained by laboratory experiments. Fracture mechanics
analysis of fatigue strength have been adopted to assess more accurately the different
stages of crack growth including calculation of residual fatigue life beyond through-
thickness crack, which is normally defined as fatigue failure. Detailed information
about crack propagation is also required to plan inspections and repair.
11

16. Table 3 Limit State Criteria for safety – with focus on structural integrity
L im it s ta te s P h y s ic a l a p p e a r a n c e R e m a rk s
o f fa ilu r e m o d e
U ltim a te (U L S ) D if f e r e n t f o r b o t t o m –
- O v e r a l l “ r ig i d b o d y ” s u p p o rte d , o r b u o y a n t
s t a b i lit y C o lla p s e d s tru c tu re s .
- U lt im a t e s t r e n g t h o f c y lin d e r C o m p o n e n t d e s ig n c h e c k
s t r u c t u r e , m o o r in g o r
p o s s ib le f o u n d a t io n
F a tig u e (F L S ) C o m p o n e n t d e s ig n c h e c k
- F a ilu r e o f w e ld e d jo in t s F a t ig u e - d e p e n d in g o n r e s i d u a l
d u e t o r e p e t it iv e lo a d s fra c tu re s y s te m s tre n g th a n d
a c c e s s f o r in s p e c t io n
A c c id e n ta l c o lla p s e ( A L S ) S y s t e m d e s ig n c h e c k
- U lt im a t e c a p a c it y 1 ) o f
J a c k -u p
d a m a g e d s t r u c t u r e w it h c o lla p s e d
“ c r e d i b le ” d a m a g e
An adequate safety against fatigue failure is ensured by design as well as by inspec-
tions and repairs. Fatigue design requirements depends upon inspect ability and fail-
ure consequences. Current requirements for fatigue design check in NORSOK are
shown in Table 4. These values were established by the NPD code committee in 1984
by judgement.
Table 4 Fatigue design factor, FDF to multiply with the planned service life to
obtain the required design fatigue life (NORSOK N-001, 2002).
Access for inspection and repair
Accessible (inspection according to generic scheme
No access or is carried out)
in the splash zone Above splash zone
Below splash zone
or internal
Substantial
10 3 2
consequences
Without substantial
3 2 1
consequences
1)
The consequences are substantial if the Accidental Collapse Limit State (ALS) criterion is
not satisfied in case of a failure of the relevant welded joint considered in the fatigue check.
Traditionally we design for dead-loads, payloads as well as environmental loads. But,
loads can also be induced by human errors or omissions during operation – and
cause accidental loads. They commonly develop though a complex chain of events.
For instance hydrocarbon fires and explosions result as a consequence of an acciden-
tal leak, spreading, ignition and combustion process. Accidental Collapse Limit State
(ALS) requirements are motivated by the design philosophy that “small damages,
which inevitably occur, e.g. due to ship impacts, explosions and other accidental
loads, should not cause disproportionate consequences”.
12

17. The first explicit requirements were established in Britain following the Ronan Point
apartment building progressive failure in 1968. In 1984 such criteria were extended
by NPD, to include such robustness criteria for the structure and mooring system.
While robustness requirements to the mooring are generally applied today, explicit
ALS criteria are not yet widespread. The World Trade Centre and other recent catas-
trophes have lead to further developments of robustness criteria for civil engineering
structures. See Figure 8.
ALS checks should apply to all relevant failure modes as shown in Figure 9. It is in-
teresting in this connection to note that ALS-type criteria were introduced for sinking/
instability of ships long before such criteria were established for structural integrity as
such. Thus, ALS were introduced in the first mobile platform rules (as described e.g.
by Beckwith and Skillman, 1976). The damage stability check has typically been
specified with damage limited to be one or two compartments flooded. According to
NPD this damage should be estimated by risk analysis, as discussed subsequently.
The criterion was formally introduced for all failure modes of offshore structures in
Norway in 1984 (NPD, 1984).
Applied
• Ronan point since
Motivation: early
appartment building codes
”small damages, Flooded
accident, 1968 which inevitably occur, volume
• Flixborough explosion, should not cause a) Capsizing/sinking due to (progressive) flooding
1974 disproportionate
• ECCS model codes, consequences!” Gaining
Explosion damage acceptance
1978
• Alexander L. Kielland
accident, 1980
• NPD Regulations for
Risk analysis, 1981 b) Structural failure e.g. due to impact damage,....
• NPD’s ALS criterion,
1984
• HSE Safety Case, 1992
Failure of Dynamic One One Generally
• WTC, September 11., 2001 Positioning System tether mooring applied
is handled in a similar failed line failed
manner
c) Failure of mooring system due to "premature" failure
Fig. 8: Historical development of ALS Fig. 9: Accidental Collapse Limit State
assessment of structures (ALS) requirements
The assessment of structures during operation is necessary in connection with a
planned change of platform function, extension of service life, occurrence of overload
damage due to hurricanes (Dunlap and Ibbs, 1994), subsidence of North Sea jackets
(Broughton, 1997), explosions, fires and ship impact, updating of inspection plans etc
(ISO 19900). Basically, the reassessment involves the same analyses and design
checks as carried out during initial design. However, depending upon the inherent
damage tolerance ensured by the initial design, the measures that have to be imple-
mented to improve the strength of an existing structure may be much more expensive
than ones for a new structure. This fact commonly justifies more advanced analyses of
loads, responses, resistances as well as use of reliability analysis and risk-based ap-
proaches than in the initial design (Moan, 2000a).
13

18. 3.3 Inspection, Monitoring, Maintenance and Repair
Inspection, Monitoring, Maintenance and Repair (IMMR) are important measures for
maintaining safety, especially with respect to fatigue, corrosion and other deteriora-
tion phenomena. To ensure structural integrity within the offshore sector in the North
Sea, the regulatory body defines the general framework while the audit of the oil
companies or rig owners defines: inspection and maintenance needs, reports planned
activity, findings and evaluates conditions annually and every fourth or fifth year.
Hence, the inspection history of a given structure is actively incorporated in the plan-
ning of future activities. The inspection and repair history is important for a rational
condition assessment procedure of the relevant structure and other, especially for “sis-
ter” structures.
The objective of inspections is to detect cracks, buckling, corrosion and other dam-
ages. Overload phenomena are often associated with a warning for which the inspec-
tion can be targeted, while degradation needs continuous surveillance. However, nor-
mally ample time for repair will be available in the latter cases.
An inspection plan involves:
- prioritizing which locations are to be inspected
- selecting inspection method (visual inspection, Magnet Particle Inspection, Eddy
Current) depending upon the damage of concern
- scheduling inspections
- establishing a repair strategy (size of damage to be repaired, repair method and
time aspects of repair)
Whether the inspection should be chosen to aim at detecting cracks by non-destructive
examination (NDE), close visual inspection, detect through-thickness cracks e.g. by
leak detection, or member failures would depend on how much resources are spent to
make the structure damage tolerant. The choice again would have implication on the
inspection method. The main inspection methods being the NDE methods consist of
detection of through-thickness crack by e.g. leak detection, and visual inspection by
failed members. The quality of visual inspection of NDE methods depends very much
upon the conditions during inspection. A large volume offshore structure is normally
accessible from the inside, while members with a small diameter such as TLP tethers
and joints in jacket braces, are not.
Permanent repairs are made by cutting out the old component and butt welding a new
component, re-welding, adding or removing scantlings, brackets, stiffeners, lugs or
collar plates.
Typically major inspections of offshore structures (special surveys, renewal surveys)
are carried every 4 - 5th year, while intermediate and annual inspections are normally
less extensive. Further refinement of the inspection planning has been made by intro-
ducing probabilistic methods as described below.
Inspection, monitoring and repair measures can contribute to the safety only when
there is a certain damage tolerance. This implies that there is an interrelation between
design criteria (fatigue life, damage tolerance) and the inspection and the repair crite-
ria. Fatigue design criteria, hence, depend upon inspection and failure consequences
as shown e.g. by Table 4.
However, during the operation, the situation is different. The strengthening of the
structure by increased scantlings is very expensive. The most relevant measure to in-
fluence safety relating to fatigue and other degradation phenomena is by using an im-
14

19. proved inspection method or increased frequency of inspections. The following sec-
tion briefly describes how fatigue design and inspection plans (based on an assumed
inspection method) can be established by reliability analysis to ensure an acceptable
safety level.
3.4 Quantitative Measures of Safety
Ideally the structural safety should be measured in a quantitative manner. Structural
reliability methods are applied to determine the failure probability, Pf which is asso-
ciated with normal uncertainties and variability in loads and resistance. Quantitative
risk assessment can be used to deal with the probability of undesirable events and
their consequences in general terms. This includes events induced by errors and omis-
sions, see Fig. 10.
Structural reliability analysis
Deck
Column
Prob. density function
Load effect
fS(s)
R,S Wave
pressure
Resistance fR(r)
PF=P[R≤S]
Uncertainty in R and S can be
r,s modelled by probability density
Quantitative risk analysis
End
events
Critical
event
Fault
tree Event
tree
Consequences
Fig. 10: Methods for quantifying the risk or safety level
The quantitative safety approach is based on estimating the implied failure probability
and comparing it with an acceptance level. This target safety level should depend
upon the following factors (e.g. Moan, 1998):
- type of initiating events (hazards) such as environmental loads, various accidental
loads, .. which may lead to different consequences
- type of SRA method or structural risk analysis, especially which uncertainties are
included
- failure cause and mode
- the possible consequences of failure in terms of risk to life, injury, economic losses
and the level of social inconvenience.
- the expense and effort required to reduce the risk.
In principle a target level which reflects all hazards (e.g. loads) and failure modes
(collapse, fatigue, ... ) as well as the different phases (in-place operation and tempo-
rary phases associated with fabrication, installation and repair) is defined with respect
to each of the three categories of ultimate consequences. The most severe of them
governs the decisions to be made. If all consequences are measured in economic
terms, then a single target safety level could be established. However, in practice it is
convenient to treat different hazards, failure modes, and phases separately, with sepa-
rate target levels. This may be reasonable because it is rare that all hazard scenarios
15

20. and failure modes contribute equally to the total failure probability. The principle of
establishing target levels for each hazard separately was adopted by NPD for acciden-
tal loads; see e.g. Moan et al. (1993b). It was also advocated by Cornell (1995). In
general it is recommended to calibrate the target level to correspond to that inherent in
structures which are considered to have an acceptable safety.
3.5 Structural reliability analysis
General
Structural reliability methods for calculating the failure probability are readily avail-
able. If the uncertainty in the resistance R and load effect S are described by probabil-
ity density functions. The failure probability can be calculated as P (R<S). It is impor-
tant to recognize that there are different types of uncertainties used to determine the
resultant uncertainties associated with loads and resistances. One type of uncertainty
(Type 1) is natural or inherent; this type of uncertainty is ‘information insensitive’ and
random. A second type of uncertainty (Type 2) is associated with modelling, paramet-
ric, and state uncertainties; this type of uncertainty is ‘information sensitive’ and sys-
tematic. Type 2 model uncertainties may be defined as the ratio of the actual or true
value of the variable to the predicted or nominal (design) value of the variable. A va-
riety of methods can be used to characterize the model uncertainty, including field test
data, laboratory test data, numerical data, and ‘expert’ judgment. Often it is not possi-
ble to develop explicit separations of Type 1 and Type 2 uncertainties and it is impor-
tant not to include them twice.
SRA is applied to determine the failure probability considering fundamental
variability, as well as uncertainties due to the lack of knowledge in loads, load effects
and resistance. The state of the art methods for calculating the failure probability are
the numerical First Order and Second Order Reliability as well as Monte Carlo
simulation methods (e.g. Melchers, 1999). However, analytical solutions exists for a
few cases, for instance, when failure is expressed by g( ) =R – S ≤ 0 and both the
resistance R and the load effect S are lognormal random variables.
The failure probability is expressed by:
Pf = P( g () ≤ 0) = Φ ( −β) or β = −Φ −1 ( Pf ) (1)
where Φ(-β) is the standard cumulative normal distribution, with numerical values as
shown in Table 5, and the reliability index, β = βLN can be exactly written as follows,
see e.g. Melchers (1999):
⎡µ 1+V 2 ⎤
ln ⎢ R S⎥
⎢ µS 1+V 2 ⎥
⎣ R⎦ ln ( µR /µS )
β LN = ≈ = β' LN (2)
2 )(1 + 2 )]
ln[(1 + V R VS V 2 +V 2
R S
This simple expression has turned out to be useful and was applied in the API reliabil-
ity based code calibration (Moses, 1987). The analytical formulation can also conven-
iently be used to express the relationship between Pf and safety factors.
16

21. Table 5 Relation between β and Pf.
β 1.0 1.4 1.8 2.2 2.6 3.0 3.4 3.8 4.2 4.6
-2 -2 -3 -4 -4
Pf 0.16 0.081 0.036 0.014 0.47 10 0.14 10 0.34 10 0.72 10 0.13 10 0.21 10—5
Reliability estimates are found to be sensitive to the distributions used for R and S.
The failure probability should refer to a time interval, e.g. a year or the service life. This
can be achieved by considering a load effect S that refers to an annual or service life
time maximum value. We note that the results of code calibration depend upon the
choice of reference period.
Reliability based code calibration
Reliability methods are increasingly used to make optimal decisions regarding safety
and the life cycle costs of offshore structures (see e.g. ISSC, 1988-1994; Moan, 1994).
In particular the efforts by Fjeld (1977); Lloyd and Karsan (1988), Moan (1988), Jor-
dan and Maes (1991) to calibrate their codes to a certain reliability. An evaluation of
previous efforts on calibration of offshore codes was provided by Moan (1995) in
conjunction with the ISO effort to harmonize the safety level in codes for offshore
structures across the variety of structural types (ISO, 1994). However, safety factors
on loads are not properly varied to reflect the differences in uncertainty in load predic-
tions for different types of structures.
To illustrate the relationship between partial safety factors, the uncertainty in resis-
tance and loads as well as Pf , consider the simplest design format, often used in code
calibration,
R c /γ R ≥ γ SSc (3)
where Rc and Sc are characteristic resistance and load effect, respectively. Let the (true)
random load effect, S and resistance, R be defined by their mean value (µ) and the
coefficient of variation (V):
µS = BSSC ,BS ≥ 1; VS = 0.15 − 0.30
µR = BR R C ,BR ≥ 1; VR = 0.1
The BS reflects the ratio of the mean load (which refers to an annual maximum if the
annual failure probability is to be calculated,) and the characteristic load effect (typi-
cally the 100 year value) as well as a possible bias in predicting wave load effects,
e.g. due to model uncertainty.
By inserting the design equation Eq.(3) into the approximate expression of Eq.(2)
ln ( µR /µS ) ln(BR γR γS /BS )
β LN ′ ≈ = or γR γS = (BR /BS ) exp(β' L N VR2 +VS2 ) (4)
VR2 + VS2 VR2 + VS2
With γR γS = 1.5; a typical BS = 0.8 for wave-induced load effects; BR = 1.1 and VR =
0.1, it is found that β’LN is about 3.2 for a VS of 0.20. This reliability index corre-
sponds to a Pf of 6 10-4. By decreasing BR/BS by 10 % reduces β’LN by 15%. It is
noted that the Similarly, by increasing Vs by 10 % reduces β’LN by 8%. At the same
time it is noted that the uncertainty in R has minimal influence on the safety level. Yet
it is important to estimate the mean bias of the resistance, BR accurately. It is also pos-
sible to approximately express R and S by (BR, VR) and (BS, VS), respectively, and
17

22. hence to express partial factors by the relevant uncertainties. (e.g. Melchers, 1999).
It is important to recognize that variables used in designing offshore structures are
often ‘conservative.’ Thus, there exists sources of ‘bias’ that must be recognized
quantitatively by the Bi's.
WSD: Goal: Implied Pf ≅ Pft
RC/γ > DC + LC + EC
Target R — resistance
Pf or β D, L, E — load effects due to
LRFD: • permanent
• live load
RC/γR > γDDC + γLLC + γEEC
• environmental effects
Load ratio, Ec/(Lc+Ec)
Fig. 11: Schematic illustration on how the implied safety level in a design code
for ultimate strength can be calibrated to be close to a given target level.
Fatigue Reliability Analysis
Structural reliability methods can also be used to calculate the probability of fatigue
failure. In Figure 12 the solid line with diamond symbol shows the fatigue failure
probability in the service life as a function of the design criterion – the fatigue design
factor, FDF. It is shown that the cumulative failure probability in the service life var-
ies from 10-1 to 10-4 when FDF varies from 1 to 10.
1.0E+00
Cumulative f ailure probability
1.0E-01 Cumulative, stdv (lnA )=0.15
Cumulative, stdv (lnA )=0.3
A nnual f ailure probability
A nnual, stdv (lnA )=0.15
1.0E-02 A nnual, stdv (lnA )=0.3
Failure probability
1.0E-03
1.0E-04
1.0E-05
1.0E-06
1 2 3 4 5 6 7 8 9 10
Fatigue de s ign factor
Fig. 12: Fatigue failure probabilities in the 20 year service period, as a function of the
fatigue design factor and the uncertainty level. A is an equivalent constant stress
range that represents the long term stress level (Moan, 2004).
A consistent fatigue safety level can be achieved, by varying the FDF versus the ef-
fect of an inspection program as well as the consequences of failure.
18

23. Reliability estimates by account of inspection
The effect of the inspection on the reliability level can be illustrated by representing
the crack depth using a random variable, A(t) which is a function of time t. The qual-
ity of the inspection in terms of the detectable crack size is also represented by a ran-
dom variable, Ad. The distribution of Ad corresponds to the Probability of Detection
(POD) curve for the inspection method in question.
The failure probability at the time, t (N-cycles) can be formulated
Pf ( t ) = P(a f - a N ≤ 0 ) = P [ F ( 0, t )] (5)
where af and aN are the crack size at failure and after N cycles, respectively.
The outcomes of inspections are assumed to be no crack detection (ND) or crack de-
tection (D) at time t after N cycles, which are described by:
I ND ( t ) : a N -a d ≤ 0 (6a)
I D ( t ):a N -a d ≥ 0 (6b)
In general, it is difficult to determine the distribution of the crack size (A) explicitly
when taking into account all uncertainties that affect the distribution as well as the
effect of inspections. Based on the Paris’ crack propagation law, Eqs. (5-6) can be
recasted into a convenient form for analysis as shown e.g. by Madsen and Sørensen
(1990).
The effect of inspection may be viewed in two different ways depending upon
whether it is assessed before inspections are done, e. g. during the design phase, or
afterwards during operation. If the effect of inspections is estimated before they are
carried out, two outcomes: D and ND are possible. The exact outcome is not known
but the probability of the outcomes can be estimated based on the reliability method.
At the design stage, the outcomes (e.g., crack detection or no detection) are not
known. When a single inspection is assumed to be made at time tI and possible cracks
detected are repaired, the failure probability in the period t ≥ tI can be determined by:
Pf (t) = P [ F(0, t I )] + P [S(0, t I ) and F(t I , t) | ID (t I )] ⋅ P [ ID (t I )] + P [S(0, t I )and F(t1 , t) | I ND (t I )]⋅ P [ I ND (t I )] (7)
where F(t1,t2) and S(t1,t2) are, respectively, mean failure and survival in time period
(t1,t2). Equation (7) can be generalised to cover cases with several inspections with
two alternative outcomes. Moan et al. (1993a) showed, based on reliability analysis,
how the allowable cumulative damage (D) at the design stage can be relaxed when
inspections are carried out. Such analyses served as basis for Table 4.
On the other hand if no failure has occurred before time tI and it is known that no
crack is detected at time tI, then the failure probability in the period t ≥ tI is
Pf (t) = P [ F(t I , t) | I ND (t I )] (8)
The knowledge of survival up to time tI and no crack detection at time tI reduces the
uncertainty and makes the failure probability drop. The reliability index β increases at
the time of inspection as illustrated by the example shown in Fig. 13.
19

24. 7
Event tree analysis
Basic case, No inspection
6 Upd, full inspection history
Upd, ONLY last inspection
5
Inspection
during
Reliability Index
operation with
4 No crack detection
3
No inspection 10-3
3×10-3
2
Effect of Inspection 3.5×10-2
predicted at design stage
1 Pf
0 5 10 15 20
Time (years)
Fig. 13: Reliability index as a function of time and inspection strategy. Inspection
Event Tree analysis is based on predictions at the design stage. The other
curves are based on inspections with known outcome during the service
life (Ayala-Uraga and Moan, 2002)
The updating methodology is useful in connection with extension of service life for
structures with joints governed by the fatigue criterion (Vårdal et al, 2000). In such
cases, the design fatigue life is in principle exhausted at the end of the planned service
life. Nevertheless, if no cracks have been detected during inspections, then a remain-
ing fatigue life can be demonstrated. However, it is not possible to bring the structure
back to its initial condition by inspection only. This is because the mean detectable
crack depth by NDE methods typically is 1.0 – 2.0 mm, while the initial crack depth
is 0.1 – 0.4 mm.
The calculation of the system failure probability after inspection may be approxi-
mated by independent system failure modes (Moan et al., 1999, 2002, 2004)
n
PFSYS|up = P [ FSYS | I]≈P [ FSYS(U)] + ∑ P ⎡ Fj | I ⎤ ⋅ P ⎡ FSYS(U) | Fj ⎤ +....
⎣ ⎦ ⎣
j=1
⎦ (9)
.
This formulation is based on modeling the ultimate failure of the system by a single
mode. Moreover, the formulation is limited to failure modes initiated by a single fa-
tigue failure and followed by ultimate global failure. The failure probability in Eq. (9)
is applicable when the inspection event I aims at detecting cracks before the failure of
individual members, (i.e. before they have caused rupture of the member). Another
inspection strategy would be to apply visual inspection to detect members failure and
repair failed members after the winter season in which those particular members
failed. In this case the Eq. (9) will have to be modified as follows: the individual fa-
tigue failures of components (Fj ) does not depend on the inspection event, and, rather
such an inspection and repair strategy will have implication on the time period, for
which the failure probability P[FSYS(U)|Fj] should be calculated.
A further simplification is to update the failure probability of each joint based on the
inspection result for that joint. This is conservative if no cracks are detected, but non-
conservative if cracks are detected.
Inspections may be prioritized by using Eq. (9) for each joint separately by allowing a
20

25. certain target probability level, PfSYS(T) to each term in the sum of Eq. (9). The target
fatigue failure probability for joint i, PFfT(i) is then obtained from
PfSYS(i) = P[FSYS | Fi ] ⋅ PFfT(i) ≤ PfSYS(T) (10)
where the system failure probability, PfSYS(i) is associated with a fatigue failure of
member (i) followed by an ultimate system failure. PfSYS(T) is obtained by generalizing
the acceptance criteria implied by Table 4. This approach has been implemented for
template-space frame structures (Moan et al., 1999).
Given the target level for a given joint, inspections and repairs by grinding or other
modifications are scheduled to maintain the reliability level at the target level as
shown in Fig. 14. Reliability level, β
No Inspection at time t=8
inspection with no crack detection
Target level
for a given joint
0 4 8 12 16 20 Time (years)
1st inspection 2nd inspection
Fig. 14: Scheduling of inspections to achieve a target safety level of PFfT(i).
This methodology is used to calibrate fatigue design requirements. It is then found
that the criteria in Table 4 are slightly “non-conservative”.
3.6 Safety implications of Ultimate and Fatigue Limit State criteria and Inspection,
Monitoring, Maintenace and Repair
The failure probability estimated by structural reliability analysis (SRA) normally
does not represent the experienced Pf for structures. This is because the safety factors
or margins normally applied to ensure safety are so large that Pf calculated by SRA
becomes much smaller than that related to other causes. For instance when proper
fatigue design checks and inspections have not been carried out, the likelihood of fa-
tigue failures (through-thickness cracks) for platforms (e.g. in the North Sea), is large
and cracks have occurred. However, with the exception of the Ranger I (1979) and
Alexander Kielland failure (1980) such cracks have been detected before they caused
total losses. As discussed above, errors and omissions in design, fabrication and op-
eration represent the main causes of the accidents experienced.
On the other hand, frequent occurrences of cracks provide a basis for correlating ac-
tual crack occurrences with state of art predictions for various offshore structures.
Hence, the current predictions for jackets are found to be conservative (Vårdal and
Moan, 1997), while for semi-submersibles and ships, the predictions seem to be rea-
sonable, as summarized by Moan (2004). This agreement is achieved when the SN
approach (or a calibrated fracture mechanics approach) is applied to predict the occur-
rence of fatigue failure (e.g. through thickness crack). Yet, if ULS and FLS design
checks are properly carried out, Pf will be “negligible” within the current safety re-
gime. This reserve capacity, implied by ULS and FLS requirements, provides some
21

26. resistance against other hazards like fires, explosions etc. However providing safety
for the mentioned hazards in this indirect manner is not an optimal risk-based design.
If more efforts were directed towards risk reduction actions by implementing ALS
criteria, then current safety factors for ULS and FLS could be reduced without in-
creasing the failure rate noticeably.
As explained above, SRA does not provide a measure of the actual total risk level
associated with offshore facilities. Yet, it is useful in ensuring that the ultimate
strength and fatigue design criteria are consistent by calibrating safety factors. More-
over, SRA provides a measure of the influence of various parameters on the reliability
and, hence, the effect of reducing the uncertainty on the failure probability.
Finally, it is noted that the random uncertainties in the ultimate strength commonly
have limited effect on the reliability compared to that inherent in load effects. On the
other hand, the systematic uncertainty (bias) in strength and load effects has the same
effect on the reliability measure.
3.7 Risk assessment
Risk assessment (Qualitative Risk assessment or Formal Safety Analysis etc.) is a tool
to support decision making regarding the safety of systems. The application of risk
assessment has evolved over 25 years in the offshore industry (Moan and Holand,
1981b, NPD (1981)). The Piper Alpha disaster (PA, 1990), was the direct reason for
introducing PRA, (or QRA), in the UK in 1992 (HSE, 1992). In the last 5 years such
methods have been applied in the maritime industry, albeit in different directions
(Moore et al. 2003). The offshore industry has focused on the application of risk as-
sessment to evaluate the safety of individual offshore facilities. The maritime industry
has primarily focused on the application of risk assessment to further enhance and
bring greater clarity to the process of making new ship rules or regulations.
The risk assessment methods is used because they provide a reliable direct determina-
tion of events probabilities e.g. probabilities as low as 10-4 per year. Up to now the
accumulated number of platform years world wide is about 120 000, 15 000 and 1 200
for fixed, mobile structures and FPSOs, respectively. However, to determine prob-
abilities as low as 10-4 per year requires about 23000 years of experiences to have a
90% chance of one occurrence. A further complexity is that the available data refer to
various types of platforms and, not least, different technologies over the years. Appli-
cation of a systems risk assessment is therefore attractive. The basis for this approach
is the facts that : a)almost every major accidental events have originated from a small
fault and gradually developed through long sequences or several parallel sequences
of increasingly more serious events, and culminates in the final event b) it is often
reasonably well known how a system responds to a certain event.
By combining the knowledge about system build-up with the knowledge about failure
rates for the elements of the system, it is possible to achieve an indication of the risks
in the system (Vinnem, 1999; Moan, 2000b).
The risk analysis process normally consists in the following steps (Fig 15):
- definition and description of the system
- identification of hazards
- analysis of possible causal event of hazards
- determination of the influence of the environmental conditions
- determination of the influence of active/passive safety systems (capacity; reliabil-
ity, accident action integrity, maintenance system …..)
22

27. - estimation of event probabilities/event magnitudes
- estimation of risk
Risk Analysis Planning
Risk Analysis Planning
System Definition
System Definition
Risk
Risk
Acceptance
Acceptance Risk
Criteria Hazard Identification Risk
Criteria Hazard Identification Reducing
Reducing
Measures
Measures
Frequency Consequence
Analysis Analysis
RISK ESTIMATION
RISK ESTIMATION
Risk Picture
Risk Picture
RISK ANALYSIS
RISK ANALYSIS
Risk Evaluation
Risk Evaluation Unacceptable
Tolerable
Acceptable
Acceptable
Fig. 15: General approach for risk based decision making
In most cases an Event-Fault Tree technique (Figure 16) is the most appropriate tool
for systematizing and documenting the analyses made. Although the Event-Fault tree
methodology is straightforward, there are many problems. An important challenge is
to determine the dominant of the (infinitely) many sequences. Events are not uniquely
defined in a single sequence but appear in many combinations. Moreover, human fac-
tors are difficult to account for in the risk assessment. However, operational errors
that result in accidental loads are implicitly dealt with by using data on experienced
releases of hydrocarbons, probability of ignition etc. Explicit prediction of design and
fabrication errors and omissions for a given structure is impossible. However, it is
possible to rate the likelihood of accidents as compared to gross errors (Bea, 2000a-b,
Lotsberg et al., to appear).
The risk analysis methodology currently applied in offshore engineering is reviewed
in detail by Vinnem (1999). In connection with accidental loads, the purpose of the
risk analysis is to determine the accidental events which annually are exceeded by a
probability of 10-4.
End
event
Critical
event
Fault tree Event tree
Consequences
Fig.16 Schematic sketch of the event – fault tree method.
23

28. 3.8 Failure probability implied by Accidental Collapse Limit State Criteria
The initial damage in the ALS criterion, (e.g. due to fires explosions, ship impacts, or,
fabrication defects causing abnormal fatigue crack growth), corresponds to a charac-
teristic event for each of the types of accidental loads which is exceeded by an annual
probability of 10-4, as identified by risk analyses. The (local) damage, or permanent
deformations or rupture of components need to be estimated by accounting for
nonlinear effects.
The structure is required to survive in the various damage conditions without global
failure when subjected to expected still-water and characteristic sea loads which are
exceeded by an annual probability of 10-2. In some cases compliance with this re-
quirement can be demonstrated by removing the damaged parts and then accomplish-
ing a conventional ULS design check based on a global linear analysis and component
design checks using truly ultimate strength formulations. However, such methods may
be very conservative and more accurate nonlinear analysis methods should be applied,
as described subsequently.
The conditional probability of failure in a year, for the damaged structure, can be es-
timated by Eqs. (1-2), assuming that the system failure can be modelled by one failure
mode and that the design criterion is fully utilized. The design checks in the ALS cri-
terion is based on a characteristic value of the resistance corresponding to a 95% or
5% fractile, implying a BR = 1.1. The characteristic load effect due to functional and
sea loads are 1.0-1.2 and 1.2-1.3 of the corresponding mean annual values, respec-
tively. The safety (load and resistance) factors are generally equal to 1.0 for both
checks. For environmental loads, this conditional failure probability will be of the
order of 0.1.
The intended probability of total loss implied by the ALS criterion for each category
of abnormal strength and accidental load would then be of the order of 10-5 (Moan,
1983). Obviously, such estimates are not possible to substantiate by experiences.
3.9 Design for damage tolerance
Introduction
The current regulations for offshore structures in Norway are based on the following
principles:
- Design the structure to withstand environmental and operational loading through-
out its lifecycle.
- Prevent accidents and protect against their effects
- Tolerate at least one failure or operational error without resulting in a major haz-
ard or damage to structure
- Provide measures to detect, control, and mitigate hazards at an early time acciden-
tal escalation.
Accidental Collapse Limit State criteria can be viewed as a means to reduce the con-
sequences of accidental events (Fig. 17). The NORSOK N-001 code specifies quanti-
tative ALS criteria based on an estimated damage condition and a survival check. The
robustness criteria in most other codes, however, do not refer to any specific hazard
but rather require that progressive failure of the structure with one element removed at
a time, is prevented. Hence, no performance objective for a “real threat” is created.
24

29. The weakness with such a criterion is that it does not distinguish between the differ-
ences in vulnerability
In a risk analysis perspective the ALS check of offshore structures is aimed at pre-
venting progressive failure and hence reduce the consequences due to accidental
loads, as indicated in Figure 17. Beside progressive structural failure, such events
may induce progressive flooding and hence the capsizing of floating structures.
P, F • Estimate the damage due to accidental loads (A)
Risk control of accidental events at an annual probability of 10 -4
A - apply risk analysis to establish
A design accidental loads
Reduce probability Reduce consequences
"unknown
"known events" Critical
events" event
Indirect design Fault Event tree
Reduce Direct ALS design - robustness tree
errors & - Abnormal resistance P, F End events:
Event - redundancy Accidental loads
omissions Control - Accidental loads - ductility • Survival check of the damaged structure as a whole,
considering P, F and
environmental loads ( E ) at a probability of 10 -2
Risk Analysis, or, Target annual probability of total loss:
Prescriptive code requirements 10 -5 for each type of hazard
E
Fig. 17: The role of ALS in risk control Fig. 18: Accidental Collapse Limit State
(NPD, 1984)
The relevant accidental loads and abnormal conditions of structural strength are
drawn from the risk analysis, see e.g. Vinnem (1999) and Moan (2000b), where the
relevant factors that affect the accidental loads are accounted for. In particular, the
risk reduction can be achieved by minimizing the probability of initiating events:
leakage and ignition (that can cause fire or explosion), ship impact, etc. or by mini-
mizing the consequences of hazards. The passive or active measures can be used to
control the magnitude of an accidental event and, thereby, its consequences. For in-
stance, fire loads are partly controlled by sprinkler/inert gas system or firewalls.
Fenders are commonly used to reduce the damage due to collisions.
ALS checks apply to all relevant failure modes as indicated in Table 6. An account of
accidental loads in conjunction with the design of the structure, equipment, and safety
systems is a crucial safety measure to prevent escalating accidents. Typical situations
where direct design may affect the layout and scantlings are indicated by Table 7 for
different subsystems:
- loads-carrying structure & mooring system
- process equipment
- evacuation and escape system
25

30. Table 6 Examples of accidental loads for relevant failure modes of platforms.
Structural Failure mode Relevant accidental load or condition
concept
Fixed platforms Structural failure All
Structural failure All
Floating Instability • Collision, dropped object, unintended
platforms
pressure…, unintended ballast that
initiate flooding
Mooring system strength • Collision on platform
• Abnormal strength
Tension-leg plat- Structural failure All
forms Mooring - slack • Accidental actions that initiate flooding
system - strength • Collision on platform
• Dropped object on tether
• (Abnormal strength)
Table 7 Design implications of accidental loads for hull structure
Passive protection
Load Structure Equipment
system
Columns /deck (if not pro- Exposed equipment (if not
Fire Fire barriers
tected) protected)
Exposed equipment (if not Blast / Fire
Explosion Topside (if not protected)
protected) barriers
Ship Waterline structure (subdivi- Possibly exposed risers, (if Possible fender
impact sion) (if not protected) not protected) systems
Equipment on deck, risers
Dropped Impact
Deck Buoyancy elements and subsea (if not pro-
object protection
tected)
Design accidental loads
The characteristic value of accidental loads is defined as the load which annually is
exceeded by a probability of 10-4 and should be determined by risk analysis. For each
physical phenomenon (fire, explosions, collisions, ..) there is normally a continuous
spectrum of accidental events. A finite number of events have to be selected by
judgement. These events represent different load intensity at different probabilities.
The characteristic accidental load on different components of a given installation can
be determined as follows (Moan, 2000b):
- establish exceedance diagram for the load on each component
- allocate a certain portion of the reference exceedance probability (10-4) to each
component
- determine the characteristic load for each component from the relevant load
exceedance diagram and reference probability.
If the accidental load is described by several parameters (e.g. heat flux and duration
for a fire; pressure peak and duration for an explosion) design values may be obtained
from the joint probability distribution by contour curves (NORSOK N-003, 1999).
26

31. However, in view of the uncertainties associated with the probabilistic analysis, a
more pragmatic approach is sufficient. Yet significant analysis efforts are involved in
identifying the relevant design scenarios for the different types of accidental loads.
For each design accident scenario, the damage imposed on the offshore installation
needs to be estimated followed by an analysis of the residual ultimate strength of the
damaged structure in order to demonstrate survival of the installation. To estimate
damage, (permanent deformation, rupture etc of parts of the structure), the nonlinear
material and the geometrical structural behaviour need to be accounted for. While in
general the nonlinear finite element methods are applied, simplified methods (e.g.
based on plastic mechanisms) are developed and calibrated using more refined meth-
ods, to limit the computational effort required.
The risk analysis of novel structures and systems, is found to be useful, in that they
provide insight which results in systems that have significant increase in safety at the
same expense. This applies in particular to the topside system. However, for mature
systems, the outcomes of risk analyses tend to confirm the results of previous analy-
ses. This fact together with the desire to simplify design practice suggests using spe-
cific, generic values for such cases. Examples of typical values for some accidental
loads are given in subsequent sections.
Analysis tools for estimating the initial damage and survival
Current ultimate strength code checks of marine structures are commonly based on
load effects (member and joint forces) that are obtained by a linear global analysis.
Experiments or theory which accounts for plasticity and large deflections are used to
obtain resistances of the members and joints. Hence, this methodology focuses on the
first failure of a structural component and not the overall collapse of the structure,
which is of main concern. The advent of computer technology and the finite element
method have made it possible to develop analysis tools that account for nonlinear
geometrical and material effects, and, therefore, make it possible to account for redis-
tribution of the forces and subsequent component failures until the system’s collapse.
By using such methods a more realistic measure of the overall strength of structures is
achieved. Recently, Skallerud and Amdahl (2002) prepared a state-of-the-art review
of methods for nonlinear analysis of space frame offshore structures. Paik and Tha-
yamballi (2003) gave an overview of methods for ultimate strength analysis of steel-
plated structures.
Simplified methods for calculating the hull girder strength are based on considerations
of the intact longitudinal elements and beam theory, essentially based on Smith’s
work (1977), and reviewed by e.g. Yao et al. (2000). Such an approach has also been
extended to estimate the ultimate capacity of the damaged hull girder (Smith, 1977).
However, it is necessary to further investigate the implication of an initial damage that
involves rupture and, hence, represent an initial crack type damage which could cause
rupture before reaching the ultimate capacity obtained by calculation models based
upon ductile material behaviour.
Fires and explosions effects
The dominant fire and explosion events are associated with hydrocarbon leak from
flanges, valves, equipment seals, nozzles etc. As indicated in Fig. 19 fire and explo-
sion events are strongly correlated. Commonly the effect of 40 – 60 scenarios needs to
be analyzed. This means that the location and magnitude of relevant hydrocarbon
27