Bow Shock In Capsule and Canopy

tllarosetllarose Member

Hello,

I am using the fluent solver to trying and resolve a simplified case of a deployed parachute at Mach 1.85. Main issue is that the bow shock and wakes are not resolving properly, picture attached. I am using a pressure inlet where the gauge pressure is the dynamic pressure of the system and the operating pressure is the air pressure at my desired altitude. I could use some help on this setup. Also wondering where there is some good literature about the implications of playing with the turbulent viscosity ratios/numbers beyond the users manual.

Would it also be good to set my fluid density to ideal gas, and the solver to density based? This is my current set-up. Also using SA turbulence model and energy equation is on.

Mesh is about 9Mil elements, probably could be resolved better around geometry edges but when I use sphere of influence it blows up the element number, any suggestions there? Also thinking of making a model of just the capsule and trying to create the bow shock there at a far lower element count. So suggestions for how to fully properly resolve a 3D mesh for supersonic flow would be great.

Again my main issue right now is that the pressure profile is not correct at all, also getting these messages in the fluent console each iteration and my residuals blow up to e+12. Also confused why the first message references a time step but I am just solving 1000 iterations frozen in time. Assuming it is something about the solver giving the problem some sort of time domain/parameter so that it can resolve the simulation?

 time step reduced in 131 cells due to excessive temperature change

 absolute pressure limited to 1.000000e+00 in 84 cells on zone 4 

 absolute pressure limited to 5.000000e+10 in 364 cells on zone 4 

 temperature limited to 1.000000e+00 in 85 cells on zone 4 

 temperature limited to 5.000000e+03 in 2358 cells on zone 4 

 

Thanks for reading,

Tim LaRose

 

Comments

  • Kalyan GoparajuKalyan Goparaju Forum Coordinator
    edited May 19

    Hello Tim, 

    Since you know the velocity, why not use the velocity-inlet instead of pressure-inlet? Your operating pressure can still be the atmospheric pressure at the given altitude.

    In compressible flows, the fluid density is indeed determined according to idea gas law. So, yes, please set density to ideal gas law. As for the solver, the pressure-based scheme should be adept enough for simulating this case. As for the turbulence model, I would recommend starting with the default k-omega SST model. A 9 million mesh is a reasonable start. I would recommend making the above changes first instead of changing the mesh. 

    Thanks, 

    Kalyan

     

  • tllarosetllarose Member
    edited May 21

    Hi there Kalyan,

    Firstly, I meant to say pressure-far-field for the input. Many places online say this is the way to go for compressible flow, in addition to a density based solver. They also suggest that velocity inlets are only for in compressible flow. Could you please shed some light on why these other settings you're suggesting still allow for an accurate representation of flow.

    Also, great that I can set op pressure to atmospheric at that altitude, but then where will the solver incorporate the dynamic pressure of the system? Does this just get solved for when you used pressure based solver and velocity input?

    Do you have any knowledge of if I should set dynamic pressure or another pressure value as gauge pressure if I use a pressure-far-field inlet BC?

    Still looking to give your approach a spin.

    Thanks again,

    Tim LaRose

  • Kalyan GoparajuKalyan Goparaju Forum Coordinator
    edited May 20

    Hello Tim, 

    For Compressible Flows, Pressure far-field as initial condition should suffice. Please continue using it. As for dynamic pressure, it is calculated based on velocity and density, you don't have to specify this value. 

    Please look at this section of the User Manual for some tips on how to model compressible flows

    https://ansyshelp.ansys.com/account/secured?returnurl=/Views/Secured/corp/v201/en/flu_ug/flu_ug_sec_compressible.html

    Thanks, 

    Kalyan

  • tllarosetllarose Member
    edited May 21
    Hi there Kalyan,

    Running the sim now with gauge pressure at 0 for the BCs, operating pressure is still atmospheric. This does make the most sense, ran with a non-zero gauge before because the solver gave me a warning that I shouldn’t have a zero gauge.

    Could you please speak to why the solver doesn’t like a zero gauge? What is happening with these BCs in relation to the problem as a whole?

    Also, why use SST? What is simple about it’s deployment/use in the solver? Using SA right now as it is considered to be a good low equation option for my supersonic conditions according to the parachute modeling literature.

    Thanks again,
    Tim
  • Kalyan GoparajuKalyan Goparaju Forum Coordinator
    edited May 21

    Hello Tim, 

    I am guessing that when you ran the earlier case, you had both operating pressure and gauge pressure set to 0 (by mistake perhaps) and hence Fluent displayed the error message. 

    SA model is actually quite good for aerospace applications and has been observed to perform well for wall-bounded flows and in adverse pressure gradients. However, It is known to yield poor results for free shear layer flows. For your case though, I think it should be fine. Here is a link that has the general description of the different turbulence models including their pros and cons. Hope this helps. 

    https://ansyshelp.ansys.com/account/secured?returnurl=/Views/Secured/corp/v201/en/flu_ug/flu_ug_sec_turb_rans.html%23flu_ug_sec_turb_rans_trans

    Thanks, 

    Kalyan

  • tllarosetllarose Member
    edited May 21
    Kalyan,

    For the pressure, I had operatingn pressure set to atmospheric and gauge pressure on inlet and outlet BCs set to 0. The solver gave a pre-calculation warning. Could you please speak to why this is.

    Thanks,
    Tim
  • Kalyan GoparajuKalyan Goparaju Forum Coordinator
    edited May 21

    Hi Tim, 

    Can  you please post an image of the warning you see? Also, try setting operating pressure to 0 and then set the gauge pressures to absolute total pressure at the inlet, and absolute atmospheric pressure at the outlet. 

    Thanks, 

    Kalyan

  • rahkumarrahkumar Member
    edited May 21

    Hello Tim, 

    Another suggestion... You can also try simulating using Density based method with Explicit formulation and AUSM scheme. 

  • tllarosetllarose Member
    edited May 25

    Hi Y'all,

    Image of my error is attached. Had some success setting OP pressure to my atmospheric value and gauge pressures to zero. I have updated the geometry and am about to run the solver again with these settings. Kalyan I am a little confused because I thought we were saying beforehand that velocity at the inlet will create a dynamic pressure in the model so if I wanted to switch it up wouldn't I just set op pressure to zero and the inlet and outlet gauge pressure to atmospheric?

    Rahul I appreciate the suggestion, what makes you say those approaches may be valid here?

    Will post pictures of my new geometry once I run this solver again.

    Thanks,

    Tim

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

  • tllarosetllarose Member
    edited May 25

     ... also running my new sim with the explict formulation and AUSM scheme selected

  • Kalyan GoparajuKalyan Goparaju Forum Coordinator
    edited May 25

    Hello Tim, 

    That was just a suggestion in case setting setting operating pressure to my atmospheric value and gauge pressures to zero didn't work.

    Thanks, 

    Kalyan

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