CFD and ANN approach to predict the flow pattern around the square and rectangular bluff body for high Reynolds number. (2021)

• Record Type: Journal Article
• Authors: Talele, Virendra; V.K., Mathew; Sonawane, Niranjan; Sanap, Sudarshan; Chandak, Archana; Nema, Anurag
• Is Part Of: Materials today. Volume 47:Part 11(2021)
• Page Start: 3177
• Page End: 3185
• Publication Date: 2021
• Subjects: CFD -- Flow separation -- Artificial neural network -- Reynolds number -- Square block -- Rectangular block; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2021.06.285
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: The present numerical investigation consists of a detailed evaluation of flow over the bluff body to determine its behavior of boundary layer flow separation around the surfaces. In the present study, square and rectangle shape bluff body is investigated for higher Reynolds number ranging from 63, 651 to 636, 505 with three different cases of the angle of inclination 0°, 10°, and 20°. Optimize k– ∊ standard turbulent model with fine mesh grid is used to perform numerical investigation, and the results are validated from the literature in capturing flow separation from the surfaces. It is found that the flow separation regime behind the square and rectangular bluff body changes with Reynolds number and angle of inclination. It is also observed that the flow separation increases from the top side of the bluff body with an increase in the angle of inclination. The size and frequency of vortex generation increase with an increase in Reynolds number. A correlation is proposed for the vortex generation as a function of Reynolds number and angle of inclination. The prediction of vortices generation behind the square and rectangular bluff body is determined using the artificial neural network driven by CFD Data. A verification study is proposed in ANN approach based on neuron independent study to validate output field parameter of CFD.