Piping systems of energy industries in oil & gas play a critical role in meeting the increasing global energy demand. A great portion of these pipelines is located in high seismic-prone areas. Such systems have been found to be quite vulnerable to seismic events. Current seismic design approaches to piping systems are mainly based on the allowable stress method, even though more modern design methods are currently available for buildings or nuclear power plants; for example, the Performance-Based Earthquake Engineering (PBEE) framework has not been applied yet to piping systems and relevant structures. In this respect, both information about the quantification of limit states for pipes and adequate non-linear structural models for seismic analysis of piping systems and relevant structures are very limited.
One of the key ingredients of PBEE approach for the assessment of the seismic vulnerability of existing structures is the evaluation of fragility curves, namely the probability of exceeding a certain level of damage for a given seismic intensity measure (IM). However, the contributions in the literature on this delicate aspect are very limited.
This paper deals with such a problem by using a very popular method, namely the Cloud Analysis, originally developed as a method for probabilistic seismic demand analysis of civil structures. This method is here applied to a typical piping system for process plants. For this purpose, the structure is properly modelled, especially support structure and pipe, including pipe fittings like elbows and bolted flange joints. Using natural accelerograms selected from the PEER database and in accordance with given hazard conditions, the probabilistic seismic demand analysis is performed adopting different engineering demand parameters (EDP) consistent with the damage states expected in the pipes and fittings and in the support structure.
According to the results of experimental tests campaign performed in the past by some of the authors on flanged joints, and elbows, different damage states (leakage, yielding, rupture) have been identified and related to the corresponding EDP and the corresponding probability of exceeding has been determined by assuming a lognormal distribution of the response. The analysis intends to recognise the most probable damage condition in a refinery piping system subjected to a seismic input.
Improved seismic hazard model with application to probabilistic seismic demand analysis
