Numerical Investigation of Lateral Buckling in Fluid-Conveying Pipes

2026-05-19T13:55:28+00:00

Subsea pipes for offshore oil and gas operations face the risk of flow-induced lateral buckling failures. This study implements a one-way coupled computational fluid dynamics (CFD) and finite element analysis (FEA) approach to evaluate the fluid-structure interaction effects on pipe buckling behavior. The model consists of a 6m long, 0.5m diameter steel pipe subjected to varied internal flow velocities, axial loads, pipe thicknesses, operating pressures and temperatures. The findings demonstrate that internal pressure has the most significant impact, with critical buckling pressure doubling from 3.1 bar to 6.8 bar for a pipe thickness increase from 5mm to 20mm. Axial loads of 0 to 40 MPa reduced the critical velocity by 2.5 m/s. Gradual effects were seen for diameter and temperatures changes. The post-buckling response reveals single wavelength sinusoidal deformation shapes, with displacements amplifying exponentially beyond critical velocities. At 3 m/s over the threshold, pipe deflections reached 0.35m. The model effectively quantifies stability limits to guide subsea pipe design.

Optimisation Studies of Naphthalene Adsorption on Bentonite Clay Impregnated on Chitosan and Surfactant using RSM–CCD, ANN–BP and ANN–PSO Techniques

2026-05-26T12:37:52+00:00

The effects of process variables on naphthalene adsorption on bentonite clay–cetyltrimethylammonium bromide (CTAB)–chitosan matrix were investigated in this study. The independent variables are initial concentration ( ), adsorbent dosage ( ), contact time ( ), temperature ( ) and pH ( ) while the response variable is the % removal of naphthalene. The adsorption process was modelled and optimised using the response surface methodology (RSM)–central composite design (CCD), artificial neural network (ANN)–back propagation (BP) and ANN–particle swarm optimization (PSO) algorithms. The interactive terms of and , and , and , and and give a synergistic effect on the adsorption process. On account of –value, temperature and adsorbent dosage are the most influential single terms. Among the square terms, adsorbent dosage was found to be the most controlling factor while adsorbent dosage and contact time were the most significant interactive factors for the adsorption process. The RSM–CCD, ANN–BP and ANN–PSO aptly modelled and optimised the process variables. However, the ANN-PSO algorithm excelled over the RSM–PSO and ANN–BP owing to its highest value of 0.9803, least value of the error functions considered and percentage error of validation. Hence, ANN-PSO is projected for the optimisation studies of naphthalene adsorption on the synthesised bentonite clay–cetyltrimethylammonium bromide (CTAB)–chitosan matrix. These approaches enable scalable and data-driven solutions, which minimise costly trial-and-error experiments for treating industrial wastewater contaminated with persistent pollutants of PAHs.

Journal of Engineering Research

Numerical Investigation of Lateral Buckling in Fluid-Conveying Pipes

Optimisation Studies of Naphthalene Adsorption on Bentonite Clay Impregnated on Chitosan and Surfactant using RSM–CCD, ANN–BP and ANN–PSO Techniques