Minimizing the stress concentration factor (SCF) in pipe joint welding subjected to
fatigue is a major concern. Machining the pipe ends is one way to achieve this.
However, this adds cost, time, risk of potential crack starters, and loss of wall
thickness which is detrimental for strength and engineering critical assessment
(ECA) in particular. Pipe joint sorting (certain joints in sequence) and end matching
(rotating the joints for best fit) are other ways. However, this adds time, costly
logistics, risk of errors, and does not guarantee the minimum possible SCF is
achieved.


WHAT THE SOFTWARE DOES

Calculates the maximum, minimum, and average hi-lo, CL eccentricity, and SCF
(stress concentration factor) and identifies the corresponding joints

Selects a subset of any desired number of pipe joints that result in the best SCF
(Note: Selecting a subset with the best end measurements, whether ID, OD,
OOR, or thickness does not guarantee that the minimum possible SCF will be
achieved since the SCF is a function of all those measurements)

Calculates the maximum, minimum, and average hi-lo, CL eccentricity, and SCF  
of the selected subset and identifies the corresponding joints

Considers any random joint, any end (to be) welded to any random joint, any
end, based on either the OD or ID and any desired SCF formula

Renders extensive and exhaustive effort readily available, for example
Nnumber of iterations to determine the hi-lo, eccentricity, and SCF
100 joints: ~40,000
500 joints: ~1,000,000
Number of iterations to select half of the pipe joints with the best SCF
Selecting 50 of 100 joints: ~310,000
Selecting 250 of 500 joints: ~35,000,000

It is nearly impossible to perform this analysis using spreadsheets


EXAMPLE BENEFITS

Verifying early that the maximum possible SCF doesn't exceed the SCF
assumed in the design, i.e. before actual welding starts where the hi-lo is
measured and SCF is calculated

Determining the additional margin on fatigue life (if any as per the calculated
maximum possible SCF versus the SCF assumed in the design)

Determining whether machining of the pipe ends is required where eliminating
machining
Saves cost
Saves time
Prevents loss of wall thickness (detrimental for strength and ECA especially)
Eliminates the risk of potential crack starters

Determining whether pipe joint sorting (certain joints in sequence) or end
matching (rotating the joints for best fit) is required where eliminating sorting or
matching
Saves logistics cost and effort of marking and keeping track of joints especially
during transportation and stacking
Saves time on the firing line
Prevents likely errors

Selecting the best joints (groups) to put in the high fatigue zones such as the  
riser sagbend and hang off

Selecting the best joints to send offshore for installation while keeping the rest
onshore for spares (such as a spare riser)


ITERATION PROCESS

First End-To-First End

















Second End-To-Second End

















First End-To-Second End

















Second End-To-First End

















EXAMPLE

A project has more than 600 pipe joints and needs to select the best 100 joints
that produce the best SCF considering welding joints randomly, i.e. welding any
joint, any end to any joint, any end.

Note that selection based on joint end measurements alone whether best ID,
OD, OOR, or thickness does not guarantee the best SCF as the SCF is a
function of all those measurements.

The table and plot below show the huge difference in results of the selected
best 100 joints compared to the entire 600+ batch

End matching (rotating joints) can still be performed on the selected best 100
joints to improve further the hi-lo and SCF if desired; regardless, it is always best
practice to use the best pipe joints for the project or group the joints as per
criticality of use
ARTIFEX ENGINEERING INC.
SOFTWARE
PIPE JOINT MANAGEMENT SOFTWARE (PJMS)
Page Title
SOFTWARE
ARTIFEX ENGINEERING INC.
ARTIFEX ENGINEERING INC