CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
Numerical examination on two-equations turbulence models for flow across NACA 0012 airfoil with different angle of attack
Authors
Gerald Pacaba Arada
M. W. Muhieldeen
+3 more
Yu Han Ng
Lit Ken Tan
Wah Yen Tey
Publication date
1 January 2020
Publisher
Animo Repository
Abstract
Selection of an appropriate and efficient turbulence models is important for fast and accurate computation in fluid dynamics. In order to investigate the computational efficiency of turbulence models, numerical examination based on two-equations turbulence models for flow across NACA 0012 airfoil was carried out by using ANSYS Fluent at various angle of attack (-12o to 20o) and at a Reynold number of 3 × 106. The case study is chosen as its transition from viscid to inviscid flow region which would put a strain on computational performance of turbulence models. The two-equation models being investigated are Standard k-ε model, RNG k-ε model, k-ε Realizable model, Standard k-ω model, k-ω BSL model and k-ω SST model. The drag, lift and pressure coefficient between simulation and experimental results are compared. The convergence rate of these turbulence models is collated as well. The contours of static pressure and velocity magnitude was simulated, and boundary layer separation was noticed from 10° angle of attack. In general, the predicted data have good agreement with experimental data. Amongst the investigated models, k-ω SST model showed the best agreement with experimental result meanwhile RNG k-ε model showed the slowest convergence rate among all the turbulence models. © 2020, Penerbit Akademia Baru. All rights reserved
Similar works
Full text
Available Versions
Animo Repository - De La Salle University Research
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:animorepository.dlsu.edu.p...
Last time updated on 03/12/2021