Failure assessment diagram (FAD).
(All images courtesy INTECSEA and Heerema Marine Contractors UK Ltd.)
0 0.2 0.4 0.6 0.8 1 1. 2
Lr (plastic failure)
FAD approach simplifcation.
CRA pipe Simplified model in FAD approach
C-Mn pipe C-Mn pipe
point location depends on the applied loadings, flaw size, and flaw
location. If the assessment point is within the failure assessment
curve, the flaw size is acceptable; if the assessment point is on the
curve, the critical case is obtained. Otherwise, the flaw size is not
acceptable. It should be noted that the increase in flaw size (or increase in applied loads) will lead to the movement of the assessment
point toward the failure assessment curve. The critical value (of flaw
size or applied loading) is obtained when the assessment point lies
on the failure assessment curve; this is potentially the optimum solution.
The key advantages of the FAD approach are:
• Computationally inexpensive
• Well documented in standards
• Verified and widely accepted in the industry
• Implemented in ready-to-use tools, such as Crack Wise.
These major advantages make the FAD approach easily executable and widely used throughout many subsea pipeline projects. Importantly, the very short execution time (minutes for a case) allows
a large number of sensitivity studies as well as optimization of the
tolerable flaw sizes.
The FAD approach, nevertheless, has some
inherent limitations as its essential equations
are derived for homogeneous material under
uni-directional loadings. This implies two conditions: (i) the multi-material domain must be
able to be simplified as a single-material domain, and (ii) the applied loadings should be
In a conventional pipeline project without
CRA layers, the above two conditions are eas-
ily achieved. Firstly, the C-Mn steel has been
used as pipe material for long time, and the
weld metal is highly likely to overmatch the
parent metal. As such, the bi-material domain
comprising of parent pipe and weld metal can
be conservatively simplified as a single-mate-
rial domain with the weld metal replaced by
the parent pipe metal. Secondly, the maximum
tensile strain is obtained during installation
condition, therefore only uni-directional load-
ing is applied.
For a CRA pipeline project in a HP/HT
field, the above two conditions are not always
achieved. Firstly, the selected anti-corrosion
weld metals may not overmatch the parent
pipe, especially at high temperature. Similarly,
the CRA layer may not overmatch the parent
pipe, especially at high temperature. Secondly,
the pipe in a HP/HT field is highly likely to experience lateral buckling. In that case, biaxial
loading, in longitudinal and hoop directions, is
Workarounds to enhance the FAD approach
have been carried out over the past few years.
Nevertheless, there is still a lack of consistency on the FAD approach that prevents it
from being widely applied to CRA pipes and/
or strain-based ECAs.
The CDF approach has been developed re-
cently for strain-based and CRA pipe ECAs as
an alternative to the FAD approach. The typi-
cal detailed model can be seen in the 3D finite
element fracture model image, which shows a half pipe with sym-
metric boundary conditions. Commonly, one end of the pipe is fixed
and displacements (either axial or rotational) are enforced at the
other end. If the ECA is carried out for a reeled pipe, a displacement
control model is utilized. If the ECA is carried out for the operating
condition, temperature and internal pressure are applied instead.
The key advantages offered by the FEA-based CDF approach are:
• Ability to model a multi-material domain
• Ability to model all types of material mismatching, including
undermatching and partial overmatching
• Ability to model biaxial loading condition, i.e. internal pressure
with axial tension.
A drawback of this approach is that a significant amount of time
is required for the whole process, including finite element model
generation, processing and post-processing. As a result, adopting
the CDF approach for ECA has a considerable impact on the project
duration. Thus, performing optimization studies and probabilistic
ECA using the CDF approach might be unsuitable to some projects,
or even impossible in some scenarios.