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High Temperature Hydrogen Attack (HTHA): Life Assessment Methods for Carbon Steel and Carbon 0.50% Mo Materials

By Ralph E. King P.E. at Stress Engineering Services, Inc., and Brian Olson at Stress Engineering Services Inc.. This article appears in the November/December 2015 issue of Inspectioneering Journal

Introduction

Ammonia, refinery, and chemical plants operate various process systems and equipment that include reactors, heat exchangers, pressure vessels, and piping in critical operations. As a part of the process, many of these assets are exposed to hydrogen at elevated temperatures and degrade as a result of a process known as high temperature hydrogen attack (HTHA). To ensure the mechanical integrity and fitness-for-service (FFS) of the equipment, facility managers, reliability engineers, and inspection technicians must understand the HTHA damage mechanism and the probable level of HTHA damage their equipment has relative to available industry failure data. This relative damage probability can be used to inform owner/operators (within the framework of process safety management (PSM)) as to the risk of failure when risk ranking assets using the owner/user’s PSM risk matrix (probability and consequence).

Until recently, the use of API RP-941 Nelson Curves was thought to provide the margins and limits of process conditions relative to various alloy selections (carbon steel and C-0.5Mo steel included). Recent failures below the Nelson Curves and even below proposed revised curve off-sets have raised questions as to the reliability of the Nelson Curve approach to ensure FFS of equipment at levels required by PSM. Typically for large consequence events, the probability of failure upon demand must be substantially small to meet most owners’ PSM risk requirements. That would indicate that potentially HTHA damaged equipment must operate well outside (conservatively) of the reported HTHA failure population. To assist clients with understanding the PSM risk associated with operating certain aged equipment susceptible to HTHA, Stress Engineering Services (SES) has developed a new HTHA assessment methodology to evaluate equipment for damage relative to reported industry failures. The following discussion provides an outline of our approach.

HTHA Life Assessment Methodology

An HTHA life assessment should provide guidance for classifying the likelihood of an HTHA-related failure per the owner/user’s PSM risk matrix. Our approach is based on quantifying HTHA scenarios for use in the client’s risk management decision-making framework, so that informed decisions can be made regarding equipment inspection and replacement schedules. This particular assessment methodology:

  • Is based on published and API RP 941 failure data;
  • Uses theoretical damage rate equations that are empirically fit;
  • Has been validated against newly-reported failures;
  • Is capable of assessing the significance of non-steady state operating conditions;
  • Provides an improved technical basis for repair/replace decisions; and
  • Is capable of reproducing Nelson Curve plots for a given design life.

This new framework for assessing HTHA risk includes the following:

  1. HTHA Screening - The HTHA Screening Method uses the time in service, pressure, temperature, and hydrogen partial pressure to estimate the accumulated HTHA damage relative to the reported failures for a specific metallurgy. The model uses rate expressions that are similar to the commonly-used Pv and Pw models and void-growth models for creep. This empirical model is calibrated to API RP-941 failures and select literature data, and validated against recent failures not yet included in API RP-941. It can be used over a range of general materials of construction (carbon steels and low-alloy steels). This methane-based model provides credible correlation between laboratory and field-failure data. Finally, it uses a simplified approach to understand the relative damage in the asset and plots that asset’s service history versus the API RP-941 failure population for each alloy. An example is provided in Figure 1 below.

Figure 1. HTHA Screening Based on Failure Population.Figure 1. HTHA Screening Based on Failure Population.

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