Evaluation of Burst Pressure on API X52 Pipes: Validation of Predictive Models via Full-Scale Experimental Data

Authors

  • Teddy Setiawan Sultan Ageng Tirtayasa University
  • Dedy Triawan Suprayogi Universitas Sultan Ageng Tirtayasa
  • Hadi Wahyudi Universitas Sultan Ageng Tirtayasa

DOI:

https://doi.org/10.32497/jrm.v21i1.7209

Keywords:

API X52, Burst Pressure, full-scale experiment, pipeline integrity, theoretical prediction

Abstract

Ensuring the operational safety of steel pipelines depends heavily on understanding their failure points, or burst pressure. While various mathematical models are widely used in engineering practice, their accuracy for specific grades like API X52 often lacks robust field validation, as these models are essentially simplifications of complex real-world conditions. This study bridges this gap by evaluating the predictive accuracy of five major models-barlow, Von Mises, Zhu-Leis, API RP 1111 and DNV-OS-F101 against data obtained from a full-scale hydrostatic burst test. Using a pipe specimen with a 12 inch diameter and 11.13 mm wall thickness, the experimental result identified the actual burst pressure at 5,400 psi. comparative analysis revealed that the Barlow equation provided the highest accuracy with a relative error of only 4.12%, followed by the semi-empirical Zhu-Leis solution with a 6.97% deviation. Conversely, API RP 1111 method was found to be highly conservative by showing 17.24% deviation, which underscores its role as a safe design limit rather than a predictor of actual failure. These findings offer practitioners confidence that for thin-walled API X52 pipes with a diameter to thickness ratio of approximately 29, the Barlow model remains a practical and reliable reference for assessing pipeline integrity and estimating safe by operating limits.

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Published

2026-05-01

How to Cite

Setiawan, T., Suprayogi, D. T., & Wahyudi, H. (2026). Evaluation of Burst Pressure on API X52 Pipes: Validation of Predictive Models via Full-Scale Experimental Data. Jurnal Rekayasa Mesin, 21(1), 17–22. https://doi.org/10.32497/jrm.v21i1.7209