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Practical Considerations For The Assessment Of HTHA Risk

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Becht is among multiple engineering groups which has developed a practical model to continue giving owner-operators higher confidence by extending HTHA assessment methodologies to be more quantitative using decades of development from the literature. This model has incorporated a well-established analytical damage model that can produce time-based Nelson Curves for carbon steel and C-0.5Mo materials, based on the temperature, hydrogen partial pressure and applied stresses.

The key to any quantitative model is managing the input parameters and validation of input data.

Product Number: 51323-19187-SG
Author: Jeremy Staats, Dave Dewees, Gerrit Buchheim, Frank Sapienza
Publication Date: 2023
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Recent developments in HTHA models now allow the quantitative assessment of HTHA likelihood and risk. This paper will discuss practical considerations and factors which are important in successfully completing a quantitative assessment such as data validation and the importance of sensitivity analysis. Factors such as outlier analysis, instrument validation, how to account for unknown conditions, and evaluation at different critical thresholds in the equipment will be elucidated. The key input parameters will be discussed. Understanding the limitations of available inputs is critical to understanding the usefulness of the analysis. This work builds on work previously presented at the API inspection summit in 2022.

Recent developments in HTHA models now allow the quantitative assessment of HTHA likelihood and risk. This paper will discuss practical considerations and factors which are important in successfully completing a quantitative assessment such as data validation and the importance of sensitivity analysis. Factors such as outlier analysis, instrument validation, how to account for unknown conditions, and evaluation at different critical thresholds in the equipment will be elucidated. The key input parameters will be discussed. Understanding the limitations of available inputs is critical to understanding the usefulness of the analysis. This work builds on work previously presented at the API inspection summit in 2022.

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