Determining the Endurance Limit of Oil and Gas Steels Based on Software-assisted Indentation Testing Results
نویسندگان
1 Department of Oil and Gas Transportation and Storage, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russia
2 Department of Oil and Gas Transportation and Storage, Empress Catherine II Saint Petersburg Mining University, Saint Petersburg, Russia
doi
10.5829/ije.2026.39.03c.09چکیده
This study presents a new approach to determine the endurance limit of steels used in oil and gas pipelines through software-assisted indentation testing. The method involves analyzing the results of static indentation into the surface of the pipe wall or a metallic sample. A relationship has been established for calculating the endurance limit based on the true strength characteristics of the material, which is further simplified to express the endurance limit as a linear function of the tensile strength and relative reduction in area. Regression equations have been obtained for pipeline steels in general and specifically for steel grade 09G2S. The established linear relationship, based on data analysis for a wide range of structural steels, demonstrated a high degree of correlation (correlation coefficient r2=0.92−0.96), allowing for the recommendation of a two-parameter model for assessing the ultimate strength in engineering calculations. This model significantly simplifies the process of determining the cyclic durability of structural elements without the need for labor-intensive fatigue testing. A new method for assessing the ultimate strength of pipe steels, based on software-assisted indentation testing, has also been justified, showing high efficiency and accuracy (relative error compared to the standard method is less than 5 %). The results of the study are significant for enhancing the reliability and safety of equipment operation in the oil and gas industry. Future work is expected to expand the applicability of the proposed model and integrate machine learning methods to improve the accuracy of predicting the mechanical properties of materials.