Numerical-Experimental Geometric Optimization of the Ahmed Body and Analyzing Boundary Layer Profiles
Mohamad Abdolmaleki,
Ali Mashhadian,
Sorosh Amiri,
Vahid Esfahanian and
Hossein Afshin ()
Additional contact information
Mohamad Abdolmaleki: Sharif University of Technology
Ali Mashhadian: Sharif University of Technology
Sorosh Amiri: Sharif University of Technology
Vahid Esfahanian: Tehran University
Hossein Afshin: Sharif University of Technology
Journal of Optimization Theory and Applications, 2022, vol. 192, issue 1, No 1, 35 pages
Abstract:
Abstract The trade-off between the fuel consumption and drag coefficient makes the investigations of drag reduction of utmost importance. In this paper, the rear-end shape optimization of Ahmed body is performed. Before changing the geometry, to identify the suitable simulation method and validate it, the standard Ahmed body is simulated using k − ω shear stress transport (SST) and k-epsilon turbulence models. The slant angle, rear box angle, and rear box length as variables were optimized simultaneously. Optimizations conducted by genetic algorithm (GA) and particle swarm optimization (PSO) methods indicate a 26.3% decrease in the drag coefficient. To ensure the validity of the results, a numerical-experimental study is conducted on the optimized model. Thereafter, the velocity profiles and flow structure in the boundary layers of the original geometry were compared to those of the optimized geometry at different sections. The results indicate that there are points where the velocity profile in the boundary layer can exceed the free stream velocity and return to it again, an overlooked observation in the previous studies. In addition to the streamlines, to better understand the formation of three-dimensional vortexes, the Q-criterion factor is computed and illustrated.
Keywords: Drag coefficient; Optimization; Ahmed body; PSO; GA; Velocity profile (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s10957-021-01932-w Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:192:y:2022:i:1:d:10.1007_s10957-021-01932-w
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1007/s10957-021-01932-w
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().