Enhancing early-stage hydrogen damage detection: Simulation studies on different total focusing method algorithms in ultrasonic evaluation

Abstract

Steel structures play a crucial role in various aspects of hydrogen applications, composed of containers, pipelines, and storage tanks for transporting and storing hydrogen. However, the complex interaction between hydrogen and steel, especially in some specific operational conditions such as high temperature and high pressure, introduces several challenges that can compromise the integrity and safety of these structures. High Temperature Hydrogen Attack (HTHA) is a well-known mechanism affecting carbon steel and low-alloy steel in the petrochemical and refining industries, which turns into a more severe problem for hydrogen applications. With the development and implementation of the Total Focusing Method (TFM) with Full Matrix Capture (FMC), the capabilities of the ultrasonic testing technique have been significantly improved, providing more precise imaging and characterization of defects. This thesis evaluates and compares the performance of four different TFM algorithms, through simulation, in detecting early-stage HTHA. All simulations are conducted with a steel block containing two separate regions of inclusions and voids. The results are reconstructed images using TFM algorithms which include Delay-and-Sum (DAS), Coherence Factor (CF), Sign Coherence Factor (SCF), and Phase Coherence Factor (PCF). The results reveal that a longitudinal wave at 7.5 MHz with DAS or PCF algorithm provides the clearest image of HTHA voids. 5 MHz longitudinal wave generally yields a higher maximum amplitude. However, this makes it more difficult to detect stage 2 damage due to the damage’s low amplitude and noise from inclusions. For shear wave signals post-processed with the same algorithm, the reconstructed images tend to provide more information about smaller voids compared to those using longitudinal waves. In contrast, shear wave mode suffers significantly from inclusion noise, leading to challenges in the distinction between inclusion signals and actual damage signals. This comparative analysis of TFM algorithms demonstrates their potential in detecting early-stage HTHA, each with its strengths and limitations. The choice of algorithm should be selected depending on the specific demands of the inspection task, balancing factors such as resolution, and signal-to-noise ratio.