Reduced order models, commonly referred to as ROMs, have been used in many areas of engineering due to their reduced complexity and corresponding speed of computation and solution. In transient pipeline simulation, transfer function-based ROMs have experienced widespread adoption spanning multiple decades due to their efficiency compared with higher order computational fluid dynamics. Many examples can be traced back to the 1980s Králik et. al. paper that considers simplified transfer functions. The choice of order of the simplified transfer functions then becomes the primary parameter that other authors amend compared with Králik. However, changing the order of the simplified transfer functions can have profound effects on the response of the system. Incidentally, it is necessary to understand the difference between true pipeline behaviors versus effects from the modeler’s choice in further approximating the simplified transfer functions.
In this paper, we explore various simplified transfer function models and compare them with both a commercial grade modeling software and more importantly, with field data obtained from a large US based gas transmission pipeline. The field data validates certain model approximations and provides the modeling community a new set of high-resolution data that can be used for validating other models. We end the paper with an analysis and conclusion of how accurate the transfer function models were given the observed field data.
Pipelines are the most efficient method to transport energy over large distances. They produce the lowest amount of Greenhouse Gases over their life cycles when compared with Railway or Road based transportation [1] as well as being the safest method when comparing incident number and magnitude [2].
