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The mechanical properties of some operating pipelines are unknown or uncertain, yet pipe yield strength is a required input of design pressure calculations. ASME CRTD -Vol. 91 “Applications Guide for Determining the Yield Strength of In-Service Pipe by Hardness Evaluation: Final Report” [1] describes the means by which the lower bound yield strength of a pipeline segment can be determined based on nondestructive measurements of hardness in the field on randomly selected pipe joints. The procedure allows the lower bound limit of yield strength to be determined at a selected confidence level and with selected percentile limit of pipe that could have yield strengths lower than the calculated lower bound limit of yield strength. Key steps in the process include: • Preassessment to ensure that the pipeline segment includes pipe having consistent characteristics. • Development of a qualified hardness testing procedure that replicates laboratory hardness test results. • Qualification testing of the test technician. • Adjustment of the data from randomly selected pipe joints to estimate the lower bound hardness of the pipeline segment. • Determination of the lower bound yield strength for the pipeline segment based upon the calculated lower bound hardness. This paper describes the key requirements of ASME CRTD - Vol. 91, the capabilities and limitations of the procedure for estimating yield strength from hardness, and the field application of the procedure.

The use of cold field bends is not practical for some pipeline construction applications, particularly for large diameter pipelines built with restricted work space. For many reasons, the use of segmented induction bends and long-radius elbows becomes a necessary part of normal construction practice. This paper describes the results of the second phase of a recently-completed joint industry project pertaining to welding of field segmented induction bends and elbows for pipeline construction. In this phase, optimal methods for mapping, cutting, beveling, and transitioning induction bends and elbows were developed. Recommended practices for welding in the field and for a variety of related issues were also developed. The information was summarized and used to develop a generic specification for segmenting and welding of induction bends and elbows.

The application of requirements contained in many industry codes and standards requires some interpretation by the user and by the regulator who is called upon to enforce their use. There are often differences in the way requirements are interpreted because of ambiguous specification language, unclear rationale behind the requirements, or novel or non-traditional applications. Some industry codes and standards contain guidance in the form of commentary sections or companion documents to assist in matters of interpretation and application. Until recently, this was not the case for API Standard 1104 – Welding of Pipelines and Related Facilities,(1) where requests for interpretation have been frequent because of unclear requirements or an absence of information pertaining to rationale. This paper describes a project sponsored by Pipeline Research Council International (PRCI) and carried out by DNV GL that resulted in the development of a guidance document for API 1104.(2)

This work responds to a need to obtain statistically adequate quantities of input data for probabilistic assessments of girth welded pipelines. It is desirable to limit the data collection efforts to that warranted by overall reliability and confidence requirements. This is motivated by the challenge of limited and/or high-cost access to in-service pipelines for property measurement and flaw inspection. The goal of this work is to develop a methodology for specifying the minimum, cost-optimized sampling frequency for each of the model input parameters in a multiple girth weld fitness-for-service (FFS) assessment. The sampling frequency specifies the number of samples for each of the model variables to minimize the given cost function. The methodology is based on a user-specified confidence level for the computed reliability of a given pipeline segment (or segments), as well as the estimated per-sample cost of obtaining data for each parameter. The methodology is implemented as an add-on module in the GirthRel computer program. By expressing FFS in the language of risk-based inspection and maintenance, tools such as the one developed here will be invaluable to the development of a pipeline risk management system.