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-   -   About Some Concepts:Laminar flow, turbulent flow, steady flow and time-dependent flow (https://www.cfd-online.com/Forums/main/113983-about-some-concepts-laminar-flow-turbulent-flow-steady-flow-time-dependent-flow.html)

Jing March 2, 2013 13:24

About Some Concepts:Laminar flow, turbulent flow, steady flow and time-dependent flow
 
Hi everyone,

I have some confusion between these basic concepts-Laminar flow, turbulent flow, steady flow and time-dependent flow.

I thought laminar flow was steady flow, while turbulent flow was connected with time-dependent flow before, but I just found it should be wrong.

Can I understand those concepts in the following way now:
Laminar flow and turbulent flow are distinguished in the scale of space, while steady flow and time-dependent flow are distinguished in the aspect of time; both laminar and turbulent flow could be either steady or time-dependent?

And another question is: For turbulent flow,"time-averaged" properties are used in RANS equations, what is the scale of that time?

Any discussions are appreciated.

Regards,
Jing

michujo March 2, 2013 13:44

Hi Jing.

Just to clarify: you're right in that laminar flow can be either steady or unsteady. However, turbulent flow is always unsteady. Turbulence is an inherently unsteady process since it involves rapid variations of the thermo-fluid properties. Turbulent flows can, nevertheless, be statistically steady, in the sense that the mean flow features do not vary over time.

In RANS you are modelling all the turbulent scales so I think the time scale of the averaging procedure should be the characteristic time associated with the slowest eddy.
Maybe some expert around here can tell you more about this stuff.

Cheers,
Michujo.

Aeronautics El. K. March 2, 2013 13:54

Laminar is a flow in which the fluid flows in parallel layers while turbulence is a stochastic phenomenon. Steady is a flow where the properties reach a steady state after some time and they do not vary any more while in unsteady flow the properties vary in time although there might be a periodicity in the variation.
Solving a turbulent flow using RANS models means that you're solving a steady flow.

Jing March 2, 2013 14:11

Quote:

Originally Posted by michujo (Post 411076)
Hi Jing.

Just to clarify: you're right in that laminar flow can be either steady or unsteady. However, turbulent flow is always unsteady. Turbulence is an inherently unsteady process since it involves rapid variations of the thermo-fluid properties. Turbulent flows can, nevertheless, be statistically steady, in the sense that the mean flow features do not vary over time.

In RANS you are modelling all the turbulent scales so I think the time scale of the averaging procedure should be the characteristic time associated with the slowest eddy.
Maybe some expert around here can tell you more about this stuff.

Cheers,
Michujo.

Hi Michujo, thank you for your clear explanation for the concepts, and I think I get what you mean of "Turbulence is always unsteady, but can be statistically steady".

Cheers,
Jing

Jing March 2, 2013 14:18

Quote:

Originally Posted by Aeronautics El. K. (Post 411077)
Laminar is a flow in which the fluid flows in parallel layers while turbulence is a stochastic phenomenon. Steady is a flow where the properties reach a steady state after some time and they do not vary any more while in unsteady flow the properties vary in time although there might be a periodicity in the variation.
Solving a turbulent flow using RANS models means that you're solving a steady flow.

Hi, why you say "Solving a turbulent flow using RANS models means that you're solving a steady flow",I didn't get it and couldn't agree with this point.

Cheers,
Jing

FMDenaro March 2, 2013 15:02

Quote:

Originally Posted by Jing (Post 411079)
Hi, why you say "Solving a turbulent flow using RANS models means that you're solving a steady flow",I didn't get it and couldn't agree with this point.

Cheers,
Jing


RANS average is intrinsically steady when defined by

<f>(x) = lim (1/T) Int [0, T] f(x,t) dt
T-> inf


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