iteration questions in discrete phase
 

hello, fellows.

I'm a beginner in fluent and try to do a coal gasification simulation..

I think i've set well other options and settings(maybe)

The divergence occur if i do directly start calculation. so i firstly simulated without coal injection and add coal injection, then the calculation was completed.

and i'm doing my job like that..

But, anyway, one of my reference paper says like this,

''For the finite rate model, where the Eulerian-Largrangian approach is used, the iterations are conducted by alternating between the continuous and the discrete phases. Initially, one iteration in the continuous phase is conducted followed by one iteration in the discrete phase to avoid having the flame die out. The iteration number in the continuous phase gradually increases as the flame becomes more stable. Once the flame is stably established, fifteen iterations are performed in the continuous phase followed by one iteration in the discrete phase. The drag, particle surface reaction, and mass transfer between the discrete and the continuous phases are calculated. Based on the discrete phase calculation results, the continuous phase is updated in the next iteration, and the process is repeated."

Water-gas shift modeling in coal gasification in an entrained-flow gasifier - Part 2: Gasifiaction application, X. Lu, T. Wang/ Fuel 108 (2013)


my question is this. So the authors are saying their computation was performed like this

15 (continuous phase iterations) - 1 (discrete phase iteration) - 15 (continuous phase iterations) - 1 (discrete phase iteration) - 15 - 1...

but is that possible in FLUENT? do they mean they did manually performed 15 iteration(continuous phase) and 1(discrete phase) and 15 and 1 bla bla..?

no matter how i try, i couldn't find automatically do like that in fluent


P.S. one more question..

if that kind of residual pattern(i attached image) occurs, can i trust the result?
i conducted over 6000 iterations.

I think the paper is saying about the number of continuous phase iteration per DPM iteration. I attached an image.
but i'm not sure.. somebody else will know well about it.


and residual graph itself looks cool if you are using transient solver.
but the solution should be validated in many perspectives as you know.

turbulence viscosity limitation is being warned, but the number of cells is decreasing. so I would keep calculating or control the residual criterion if I were you.

Thx sang woo.

Ah.. however.. sadly.. this is steady-state simulation

then.. can I say that

1. the residual patterns means the calculation what i'm doing is soooooo unstable
2. so.. needs other solution, such as more iterations..?

but more iterations didn't make the residual patterns stable :(
as i mentioned above, i did more than 6000 iterations but still dizzy residual graphs were shown.

anyway i'll try as you have attached, lol

thank you soooooooo much.

DPM problem
 

Hi all, iam working on a boiler problem and I am using group injection. My combusting material is coal mv, I am using combusting at material type and the devolatilizing species are mv_vol. The vaporization Temperature of the combusting material is 400K. When I use at injection initial Temperature T=400K, it's all ok, but when I use initial Temperature T=300K I have many problems, such as "Temperature limited to 1 or to 5000K. Is it wrong to have initial Temperature less than Vaporization Temperature?

Thanks in advance,
apo

Some time the limited temperature may vanish as your simulation progresses. But if it does not then you must take a close look at your mesh and simulation setup.

There are number of reasons why you have the limited temperature warning. I think first you must check your mesh (not just quality but fineness also) and make sure you have good mesh. Then you can check the solution methods and make sure that you use higher order discretization schemes. Also use lower relaxation factors.

Also you can go to solution controls and then click limits. Here you can have upper and lower limits for temperature.

Further you can check the problem area with Iso-value adaption.