Assessment of ability of RANS based turbulence models to predict the mould filling process and oxide film formation in aluminum casting
by A. Mehdizadeh; S. Jana; A. Sadiki
Progress in Computational Fluid Dynamics, An International Journal (PCFD), Vol. 13, No. 1, 2013

Abstract: Mould filling operations involve usually turbulent flow processes. Up to now a reliable evaluation of the effects of turbulence on the mould filling process along with the oxide film formation and disintegration does not exist. This paper aims to assess the ability of RANS based turbulence models in mould filling process in Rectangular Runner (RR runner) configuration in aluminum casting. For this purpose, three types of turbulence models have been considered for their specific capability throughout the literature. Different numerical simulations have been performed using various boundary conditions and pouring rates. It has been established that the k-ε-v² model is able to predict better the flow dynamics during the filling process. Based on the stability concept of the interface, a modified expression for the total amount of oxide films formed during this process has been introduced. This expression has been used to find an optimal pouring rate which led to 0.5m/s for RR runner under the investigated conditions.

Online publication date: Thu, 31-Oct-2013

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the Progress in Computational Fluid Dynamics, An International Journal (PCFD):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com