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Structural Engineering and Mechanics Volume 81, Number 5, March10 2022 , pages 565-574 DOI: https://doi.org/10.12989/sem.2022.81.5.565 |
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Prediction of stress intensity factor range for API 5L grade X65 steel by using GPR and MPMR |
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A. Ramachandra Murthy, S. Vishnuvardhan, M. Saravanana and P. Gandhi
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| Abstract | ||
| The infrastructures such as offshore, bridges, power plant, oil and gas piping and aircraft operate in a harsh environment during their service life. Structural integrity of engineering components used in these industries is paramount for the reliability and economics of operation. Two regression models based on the concept of Gaussian process regression (GPR) and Minimax probability machine regression (MPMR) were developed to predict stress intensity factor range (K). Both GPR and MPMR are in the frame work of probability distribution. Models were developed by using the fatigue crack growth data in MATLAB by appropriately modifying the tools. Fatigue crack growth experiments were carried out on Eccentrically-loaded Single Edge notch Tension (ESE(T)) specimens made of API 5L X65 Grade steel in inert and corrosive environments (2.0% and 3.5% NaCl). The experiments were carried out under constant amplitude cyclic loading with a stress ratio of 0.1 and 5.0 Hz frequency (inert environment), 0.5 Hz frequency (corrosive environment). Crack growth rate (da/dN) and stress intensity factor range (K) values were evaluated at incremental values of loading cycle and crack length. About 70 to 75% of the data has been used for training and the remaining for validation of the models. It is observed that the predicted SIF range is in good agreement with the corresponding experimental observations. Further, the performance of the models was assessed with several statistical parameters, namely, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Coefficient of Efficiency (E), Root Mean Square Error to Observation's Standard Deviation Ratio (RSR), Normalized Mean Bias Error (NMBE), Performance Index (p) and Variance Account Factor (VAF). | ||
| Key Words | ||
| API 5L grade X65 steel; corrosion fatigue; Gaussian process regression; minimax probability machine regression; statistical analysis; stress intensity factor range | ||
| Address | ||
| A. Ramachandra Murthy, S. Vishnuvardhan, M. Saravanana and P. Gandhi: Fatigue & Fracture Laboratory, CSIR-Structural Engineering Research Centre, Chennai, 600 113, India | ||