Volume 18, Issue 69 (fall 2014)                   jwss 2014, 18(69): 89-100 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Goleij H, Ahadiyan J, Ghomeshi M, Arjmandi H. The Functional Comparison of the Turbulent Model to the RNG Model at Predicting the Plunge Point Depth. jwss 2014; 18 (69) :89-100
URL: http://jstnar.iut.ac.ir/article-1-2865-en.html
Dept. Water Struc. of Shahid Chamran Univ. of Ahwaz, Iran , Hassan_goleij37@yahoo.com
Abstract:   (11759 Views)

While the mass density current penetrates the stagnant fluid, a plunge point occurs. In this regard, the boundary of the dense fluid with ambient fluid is determined at the plunge point height. In this research, the hydraulic parameters of the dense flow and the bed slope of the stagnant fluid which have a significant effect on the plunge point have been investigated under the two turbulence models: the k- and the RNG at the Flow-3D model. To achieve the purpose of this research, a physical model was set up at the hydraulics laboratory of Shahid Chamran University (SCU), Ahwaz, Iran. Then, using the Flow-3D model with both the k- and the RNG turbulence model, the height of the plunge point was simulated according to the same experimental condition. Findings showed that the predicted depth under the RNG model is closer to the results of the physical model. For example, the k- and RNG model for the 12% slope can estimate the plunge point depth by 30% and 12.28% respectively more than the experimental data. However, for all the slopes, the k-e model can on average overestimate by 27% and RNG model 10.5% more than the results of experimental data. The statistical analysis showed that the RNG model predicts the plunge point depths with a satisfactory precision.

Full-Text [PDF 2988 kb]   (4036 Downloads)    
Type of Study: Research | Subject: Ggeneral
Received: 2015/01/11 | Accepted: 2015/01/11 | Published: 2015/01/11

Add your comments about this article : Your username or Email:
CAPTCHA

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | JWSS - Isfahan University of Technology

Designed & Developed by : Yektaweb