Application of a Statistical Regression Technique for Dynamic Analysis of Submarine Pipelines

Abstract

This study employs a statistical regression technique to investigate the maximum displacement, stress, and natural vibration frequencies of a submarine pipeline subjected to hydrodynamic wave forces. Eighteen pipeline models are designed, varying in wall thickness from 10 mm to 30 mm and diameter from 500 mm to 1000 mm. The hydrodynamic drag and inertia forces are performed by using the Morison equation. Computer-aided Finite Element Analysis is employed to simulate the complex interactions between the fluid and structure in 18 pipelines. Multiple Regression technique is used to evaluate the reliability metrics, considering uncertainties in geometrical properties affecting pipeline performance. Full Quadratic models are developed for expressing more effective and concise mathematical equations. Analysis of Variance (ANOVA) is performed to determine the adequacy of the model in representing the observed data. The Coefficient of Determination (R2), Mean Square Error (MSE), and Mean Absolute Error (MAE) are calculated to assess the equation’s predictive accuracy and reliability. The results confirm the suitability of the suggested regression technique for analyzing the relationships between predictor variables and the response variable.