Posts for the month of December 2014

new 3-clump runs

I implemented a rotation angle, so that we could view the emission maps from another angle. I also fixed the initial ionization fraction of the clumps, so they don't start off bright in H-alpha as they did before.

The emission maps below are both rotated 90 deg about the y-axis, so we are now looking along the x-axis. And they are also tilted, or inclined, 45 deg toward the observer.

The first one is the usual set up where all 3 clumps are in the same plane. The second one has the slower moving clump offset, so from this viewing angle you see this clump on the right.

planar clumps emission

offset clump emission

Below is a slice of the planar set up showing density. This is just to get an idea of physically what is being simulated. The offset set up is the same except the slower moving clump on the left is rotated 45 deg about the stationary clump in a direction that moves it to the "background".

planar clumps density slice

For the offset set up, you can't see all clumps via a slice, so 3D is required. I have to play around with 3D rendering a bit more, but hopefully this at least gives you a visual for the set up.

offset clump density 3D

Movies

obliqueview1.gif

Binary separation = 7 AU

obliqueview2.gif

Binary separtion = 20 AU

E vs. t line plots for the colliding flows runs

Check them out: E vs. t line plots

Notes from last week's meeting on colliding flows

Download them here. Updated the page to include them as well see here.

Updated CollidingFlowsFigures page

CollidingFlowsFigures

Added:

-Tables

-Spectra

-Currently working on E/t plots to post today

-Figures for the Shear15 case

Tracking Max Speeds update

EigenMaxSpeed looks good now. RiemannMaxSpeed still gets weird. Need to look into this more.

movie

Planetary Atmospheres

Updated boundary conditions to go from rho = 1e-9 to tau = 1e4

Inner boundary: (tau=1e4)

  • r=7.815240e+09
  • rho= 4.972392e-03
  • T= 2.306330e+03
  • M_enclosed=2.173174e+30
  • P=4.145923e+08

Point particle

  • M_point=2.1632e30 = M_enclosed - V(r)*rho

Outer Boundary (rho < 1e-9)

  • r=8.181350e+09
  • rho=9.488437e-10
  • T=1.115419e+03
  • P=3.826197e+01

Also, calculated the effective aspect ratio for simulation region: 'w' = 75.672

which gives Ncells = Nr3w2 = 5726 Nr3 = (18 Nr)3

So if we want 100 zones in radius, we would be effectively simulating an 18003 sim.

Here are the previous values I used

Inner boundary: (tau=10)

  • r=7.9568e9
  • rho=3.8901e-5
  • T=1.4682e3
  • M_enclosed=2.1733e30
  • P=2.0648e6 (2.0648 atm)

Point particle

  • M_point=2.1732e30 = M_enclosed - V(r)*rho

Outer Boundary (rho < 1e-9)

  • r=8.1814e9 (3% of inner boundary)
  • rho=9.4884e-10
  • T=1.1154e+03
  • P=38.2620

PLoit showing mesh

Plot showing density (click for movie)

Plot showing temperature (click for movie)

Binary star

oblique.gif

Separation: 7AU

Temperature: 2000K

Primary mass = 0.8 SM

Secondary mass = 0.5 SM

Globus gridftp for transferring big data

I was using this very convenient tools when transferring ~2TB data from Gordon at SDSC to CIRC machines: as simple as drag the files from A to B and without worrying disconnect. Here's some basic steps:

  1. Sign up an account on globus.org


  1. Sign in


  1. Transfer Files with Endpoints: click "Transfer Files" on the right top Set up the path and endpoints as shown below and pick up files and use the arrows (blue triangles) to start transfer.

1) Endpoints for CIRC machines

For CIRC machines, the endpoint is "univofrochester#circ" and you need to login with your username and password on Bluehive/BlueStreak. The default path is your home directory on Bluehive. But you can access to your bh scratch or bgq scratch. For example for me— /scratch/bliu17 as bh scratch and /gpfs/fs2/bgqscratch/bliu17 as bgq scratch.

2) Endpoints for XSEDE machines:

xsede#gordon for Gordon at SDSC ( path example: /oasis/scratch/bliu/ for my scratch ) xsede#stampede for Stampede at TACC ( path example:/scratch/01688/bliu for my scratch ) More information can be found here:https://www.xsede.org/data-transfers

3) Endpoint for your own machine:

You can setup an endpoint for your own laptop also. Click "Manage Endpints" on the right top then "add Globus Connect Personal" and follow the instructions


  1. You will receive emails once the transferring is done/get problems.

Convective Stability

Worked on calculating convective instability and opacities. Found description of stellar convection here

Plot showing as well as

Plot showing optical depth from star

Image showing density in log space as well as optical depths of 1 and 2 in black, and the region of stability is outline in pink

And here are the density, temperature and pressure profiles.

pnStudy: M2-9

Results from Bruce:

Meeting - 12/15/14

  • Presentation - presented some plots on magnetic fields in cluster forming simulations at journal club last week. Think it helps to answer the question of the role of B in star formation. Am attaching this presentation to this blog post.
  • Fabian's Code - learned some basic IDL and took a look into Fabian's code for analyzing filaments.

Meeting Update 12/15/2014 - Eddie

As a reminder, here are the parameters I used for my 3-D, 3-clump set up:

Ambient/Wind Clumps
density (1/cc) 1e3 5e5
velocity (km/s) 27.2644 0, 5, 10
temperature (K) 5e3 10

So the density contrast is 500, the clumps are initially in pressure equilibrium with the ambient, and the fastest clump leads to a Mach number of approximately 5. Total simulation time ~ 50 years.

  • Fixing the ionized sulfur species in the wind boundary condition solved the issues I was having with my emission maps. Here are some maps at different viewing angles:
  • I ran a 1-D radiative shock model with parameters from my 3-clump set up and found a cooling length of approximately 4.999e13 cm = 3.342 AU. As we have done in the past, this is defined as the distance for the gas to cool down to 1000 K. This means that my cooling length resolution for the most recent runs is 13.37 cells/Lcool.
    • This cooling length calculation is for the strongest possible shock (plane-parallel shock, velocity of fast-moving clump). Most of the shock structure on the grid will have cooling lengths longer than this due to oblique angles and slower moving or stationary clumps.
    • At this resolution, the run took almost 3 days (69.38 hrs) on 120 cores on bluehive. This equals approx 8326 SUs. You might recall from last week, that this same run took 77.3 hrs on 96 cores (7420 SUs), so slightly slower but less expensive which is expected.


  • I have updates on MaxSpeed tracking that I will share tomorrow, and then it will be time to focus my development efforts on the new Outflow object module.

Testing new spectra params

Attaching 2 spectra here to see differences between:

-Cube spectral region, constant interpolation

-Rectangle spectral region, constant interpolation

-Cube spectral region, spectral interpolation

Gravitational Energy Spectra:

Kinetic Energy Spectra:

As can be seen from plots, no difference between choosing a cubic or rectangular region in the box over which to perform the spectral decomposition (curves lie on top of each other). There is a difference between the interpolation, though.. Spectral prolongation seems to somewhat smooth out the curves.. I will go ahead and make code for rectangle boxes and spectral prolongation for next week plots meeting.

Colliding Flows Paper Figures

Here is the first round of figures. Essentially this is the reason for lack of blogposts the past few weeks:

CollidingFlowsFigures

Please check them out! Keep in mind this is the first round, so some of the text on the figures might be weird (dates and such).

Critical Mass-Flux contours

2.5D self gravity

  • Upper right panel is 2.5D with 20482 effective
  • Lower right panel is 2.5 D with 2562 effective
  • left half is slice from 3D with 1282 effective

Meeting Update 12/08/2014 - Eddie

  • Got more file space on bluehive which will make post-processing emission maps much easier and quicker.
  • Finished implementing MaxSpeed tracking. Need to analyze the results, will share at tomorrow's code meeting.
  • Mach stem HEDLA paper revisions submitted.
  • Discovered and fixed (hopefully) and error in my Mach stem module:

  • A 3-D 3-clump run at 40 cells/rclump took ~77.3 hrs on 96 cores on bluehive. This is about 7420 SUs. Not bad at all, so we could reach higher resolutions if we need to. I'll figure out the cooling length as soon as I get a chance. The 3-clump sim that I had is re-running with the fix to the wind BC.

Meeting Update

Fourier Spectra

Link to last week's post on this here

Paper figures progress

Here is where we are with paper figures:

I. Dynamics & Morphology

Col density X
Energy Spectra - B, KE, gravitational X
B v. n PDFs X
Beta maps X

II. Identifying Filaments & Characterizing their Dynamics

3D plot of filaments (at end of sim, across different runs), with and without streamlines
Pick out 3 or 4 best filaments then plot along filament angle between mean field and filament direction
Radial characteristics
Morphology identification, hub n spokes? Filaments and fibers?
Flow along vs. onto filaments
Projected streamlines plot X

III. Put in terms of Observer

Velocity spectra and/or velocity dispersion X
Density spectra X
Polarization maps
Characterizing projection effects?

IV. Amira Code

Identify filaments by hand and their characteristics
Code that into Amira X
Make easy filament set and test with Amira
Then harder test case
Use to count different filaments in time

2.5D spherically symmetrical outflow

I ran the isotropic wind simulation in 2.5D for lambda = 5.3, 2*Jupiter-mass planet and t = 250 days.

*The density profile agrees well with the curves given in S&P for the symmetric case.

  • At r = 4R, S&P shows that the density drops to ~0.01 of the initial value. The simulation gives 0.03

*At r~2R, S&P shows ~0.1 of initial rho. The simulation gives 0.10

*The velocity profile shows a transition from subsonic to supersonic flow at higher distances. The only difference is that my simulation gives a sonic surface much closer to the planet as compared to S&P result. They see one at r = 2R. I got one at approximately r = 1.2.

Movie here. http://www.pas.rochester.edu/~mehr/wikistuff/2.gif

My term paper

This term paper relate to our research. So I would like to present it in group meeting.

Spectra for No-Shear Production Run

Both spectra are taken within a 40 pc cube at the center of the simulation domain, coinciding with the collision region. This is for the No Shear case, taken at t=0 (above) and t=10 Myr (below). Fields are given in the legend, from top to bottom: Total Energy (Field 105), Gravitational Energy, Kinetic Energy, Magnetic Energy, rho2, v2, v_div2.


Initial conditions:

Nothing too interesting here. We see all energies are largest on largest size scales (smallest wave numbers on x-axis) and drop off to 0 on the smallest size scales. I guess this size scale would correspond to the smallest cell size. There are no features on the largest scales, meaning that the power on those scales is pretty uniform over that range. As we move to smaller scales, the power falls off. This makes sense — smaller volume elements contain less energy than the bulk. However, at a certain scale we begin to see wiggles. This indicates we are getting an enhancement of energy on those scales. I guess this has to do with the rippled interface of the collision region.

The different forms of energy all look the same at t = 0, they all are composed of doublet-peaks. This seems to make sense, that they would be functionally similar at t=0. One thing that is different about them is the height of their peaks in the various spectra. The magnetic, gravitational, and density curves seem to share the same peak heights, but on different absolute scales. The Kinetic and Total energy curves also share the same peak heights, but now they lie on top of each other, and the same goes for v2 and v_div2.


t=10 Myr


Here is a page on this plot with the details on how I generated them:

https://astrobear.pas.rochester.edu/trac/wiki/u/erica/CF_Spectra

Solution to streamlines issues.

Turns out we are calling the wrong position in the array. The expressions should be:

By_downx = array_decompose(projections,0)

Bz_downx = array_decompose(projections,1)

Bz_downy = array_decompose(projections,0)

Bx_downy = array_decompose(projections,1)

Byz_downx = {<By_downx>, <Bz_downx>}

Bzx_downy = {<Bz_downy>, <Bx_downy>}

This yields the following:

down the barrel

Which makes much more sense.

Potential problems with projected streamlines?

So I am attempting to plot the streamlines for our colliding flows problem. Here is an example of the shear-0 case at 10.1 Myr (or frame 101) (also I did these under Erica' account on BH2 - hence the username haha).

The first image is down the barrel of the two flows (otherwise projecting the mass down the x-axis) thus the vertical axis is z and the horizontal is y.

The second image is a projection down the y-axis. Thus the vertical axis is x and the horizontal is z. This makes sense given that we've defined GxBounds = 0d0,0d0,0d0,62.5d0,75d0,75d0. The two flows are colliding along x, so in the second image, they are coming in from top and bottom.

In both images I've plotted the column density maps for min = 60 and max = 1000. I did similarly for the min/max of the streamlines which are plotted on top of the column density maps. I also checked that they are scaled by magnitude. Now after talking with Erica we are not sure if these streamlines make any physical sense if we have defined a magnetic field along the flow axis (i.e. x). Ignore the visit axis labels as they are generic and don't define the dimensions of our problem.

down the barrel

down y

In our problem.f90 we have defined the projections for streamlines like so:

    !For 'projected' streamlines plot of the data down x:                                                                                                           
    CALL CreateProjection(projection)
    Projection%dim=1
    Projection%Field(1)%iD=By_field
    Projection%Field(1)%component=BOTHCOMP
    Projection%field(1)%name='By'
    Projection%Field(2)%iD=Bz_field
    Projection%Field(2)%component=BOTHCOMP
    Projection%field(2)%name='Bz'

    !For 'projected' streamlines plot of the data down y:                                                                                                           
    CALL CreateProjection(projection)
    Projection%dim=2
    Projection%Field(1)%iD=Bz_field
    Projection%Field(1)%component=BOTHCOMP
    Projection%field(1)%name='Bz'
    Projection%Field(2)%iD=Bx_field
    Projection%Field(2)%component=BOTHCOMP
    Projection%field(2)%name='Bx'

So in Visit I defined a few expressions to be able to plot the streamlines. For down the x-axis (which correspond to the mass1 CDMs):

By_downx = array_decompose(projections, 1)

Bz_downx = array_decompose(projections, 2)

which you can create the expression for the vector Byz_downx = {<By_downx, Bz_downx>} to plot the streamlines like I have above. The first component corresponds should correspond to the right axis if the horizontal component is truly y. Thus the second component will correspond to z if the vertical is truly z. So I think I have these lined up correctly? For projections down the y-axis (corresponding to mass2 CDMs):

Bz_downy = array_decompose(projections, 1)

Bx_downy = array_decompose(projections, 2)

you can create Bzx_downy = {<Bz_downy>, <Bx_downy>}. Clearly from the size of the box we know the horizonal component is z, and thus the first parameter in our vector should be Bz. Similarly for the second being x. However the streamlines don't seem right? Not sure what is going on.

interesting things

Click the picture to see enlarged picture. This is a simple incompressible or steady state flow, mass conserved disk-jet model. They are stream lines.

Meeting update

Have a spectra code for mass, velocity, and energy spectra. Am working now on limiting the region in the grid where the spectra is being computed. First am doing this for the no shear case, as this should be the most straight-forward.