In industrial piping systems, turbomachinery, heat exchangers etc., pipe bends are essential components. Computational fluid dynamics (CFD), which is frequently used to analyse the flow behaviour in such systems, provides extremely precise estimates but is computationally expensive. As a result, a computationally efficient method is developed in this paper by leveraging machine learning for such computationally expensive CFD problems. Random forest regression (RFR) is used as the machine learning algorithm in this work. Four different fluid flow characteristics (i.e., axial velocity, x-velocity, y-velocity and z-velocity) are studied in this work. The accuracy of the RFR models is assessed by using a number of statistical metrics such as mean-absolute error (MAE), mean-squared-error (MSE), root-mean-squared-error (RMSE), maximum error (Max.Error) and median error (Med.Error) etc. It is observed that the RFR models can produce considerable cost reductions in computing by surrogating the CFD model. Minor loss in estimation accuracy as compared to the CFD models is observed. While the magnitude of intricate flow characteristics such as the additional vortices are correctly predicted, some error in their location is observed.

The present paper makes an effort to find the flow separation characteristics under high Reynolds number in pipe bends. Single phase turbulent flow through pipe bends is investigated using k-ε turbulence model. After the validation of present model against existing experimental results, a detailed study has been performed to study the influence of Reynolds number on flow separation and reattachment. The separation region and the velocity field of the primary and the secondary flows in different sections have been illustrated. Numerical results show that flow separation can be clearly visualized for bend with low curvature ratio. Distributions of the velocity vector show the secondary motion clearly induced by the movement of fluid from inner to outer wall of the bend leading to flow separation. This paper provides numerical results to understand the flow characteristics of fluid flow in 90° bend pipe

This paper deals with the modeling of turbulent flow through a 90 deg pipe bend using an unsteady Reynolds-averaged Navier–Stokes (U-RANS) approach where k–ε model is used for turbulence closure. While limitations in solving complex flows of the k–ε model have been reported in the literature, this study demonstrates that for pipe flows with curvature, the k–ε model performs reasonably well. Investigations have been carried out to find out the influence of Reynolds number (Re) and bend curvature ratio (Rc/D) on turbulent flow parameters, namely, instantaneous axial velocity, turbulent kinetic energy, turbulent intensity, and wall shear stress. Bend curvature is found to strongly influence the turbulent flow characteristics, while no such high Reynolds number dependency is observed in this study range. In general, this paper presents a computationally cost-effective numerical study on the time averaged turbulent flow field in a 90 deg pipe bend, which may be used for the design and development of 90 deg pipe bends at a high Reynolds number regime.

The race of taking more cargo on a ship has increased the size of ships as well as other aspects, such as their capacity and structural complexity, which affect the stability of ships. For naval architects and academics, accurately predicting seakeeping performances is difficult. In order to address this, the seakeeping performance of a container ship hall built by Korea Research Institute for Ships and Ocean Engineering (KRISO), i.e., KRISO container ship hall (KCS) is described in this research utilizing a numerical method. Maxsurf software based on strip theory was used to determine the results, where the containership hull was considered and input motions were applied with appropriate boundary conditions. Later, the ship's heading and speed were changed to see the effect of the seakeeping performance of the container ship. The current study is concentrated on systematic comparative research on the investigation of the ship's pitch, heave, and roll movements in irregular waves. It has been found that rolling motion was the highest at 22 kn at the 60° heading angle, potentially affecting ship stability. The significant amplitude analysis indicates that the roll motion is the largest at 60° of wave direction. The pitch motion response and the heave motion are near for each heading angle when the wave frequency exceeds 0.5 and 1 rad/s, respectively. The calculation findings show that seakeeping performance is directly related to ship direction and speed. Furthermore, threatening heading angles during sailing are classified, which could also help in enhancing ship stability.