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
Number 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)

Reducing the strong/weak effect of conjoining joints since joints producing the
lowest SCF typically have small wall thickness variation as can be seen in the example plots below


 EXAMPLE

A project has 620 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 plots below show the huge difference in results of the selected
best 100 joints compared to the entire 620 joint 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