Abstract

A cold-worked carbon steel pulsation dampener in glycol service failed catastrophically necessitating investigation of the underlying causes. This paper describes the methodology followed to determine the most probable root causes of the failure. In addition to more traditional metallurgical investigation approaches, a new fractographic approach (referred to as statistical fractography) from which fracture mechanics parameters are extracted from the statistical analysis of the fracture roughness was used.

Statistical fractography provides the fracture properties of the failed material as well as the local mechanical conditions driving crack growth. It revealed here that failure had occurred in three stages: (1) an internal explosion or similar event resulting in shell buckling, overloading the deformed wall (2) initiation and slow crack propagation likely due to an environmentally assisted cracking mechanism and (3) ultimate failure through the rapid growth of a through-wall crack separating the dampener in two parts.

In addition to the fractographic investigations, an initial series of slow strain rate mechanical tests were conducted in glycol bearing environments to understand the susceptibility of the material constituting the dampener to environmentally assisted cracking and controlling parameters. Whilst not conclusive at this stage, a susceptibility to EAC has been evidenced from the failure strain coming to support the scenario inferred from the fractographic analysis of the failed dampener.

Introduction

A cold-worked carbon steel pulsation dampener located on a glycol circulation pump failed catastrophically in service. The two parts of the failed dampener were projected several tens of meters across the offshore facility. The failure was investigated initially using traditional metallurgical techniques, but this failed to reach a conclusive failure mechanism. Statistical fractography, the focus of this paper and newly developed technique of failure analysis that relies on the measurement from the statistical analysis of the fracture roughness of mechanical quantities like the material toughness and the local stress levels, was then employed. In this study, we show how this approach enables to identify and quantify the different steps that led to the failure of the part from which a most likely scenario of failure can be inferred.

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