Initiate passive tracers and read their information
Passive tracers are useful to track the evolutions of the temperature, pressure and their spatial positions of moving materials during the simulation. Passive tracers can be initiated when you start a new model, and they are the Lagrangian points that move with the materials. The initiation and extraction of information from passive tracers can be easily done using the following methods.
Initiate passive tracers in the model
Let's use a simple model of a "falling sphere" as the example. We initiate the passive tracers by turning on the flag: Passive_Tracer=1
and assign a spatial range to populate tracers in the entire simulation box PassiveTracer_Box=[-1,1,-1,1,-1,1])
. The default tracer density is 100 x 1 x 100 along x, y, z axes.
using LaMEM, GeophysicalModelGenerator, Plots
model = Model(Grid(nel=(16,16,16), x=[-1,1], y=[-1,1], z=[-1,1]), PassiveTracers(Passive_Tracer=1, PassiveTracer_Box=[-1,1,-1,1,-1,1]))
matrix = Phase(ID=0,Name="matrix",eta=1e20,rho=3000)
sphere = Phase(ID=1,Name="sphere",eta=1e23,rho=3200)
add_phase!(model, sphere, matrix)
add_sphere!(model,cen=(0.0,0.0,0.0), radius=(0.5,))
run_lamem(model,1)
The model output files should include a file called output_passive_tracers.pvd
which you can visualize using ParaView. The image below shows the initial state (t=0) of all tracers. Different colors represent different phases of the tracers: Phase 0 is blue, Phase 1 is red.
Read passive tracers information back to Julia
We can check the overall passive tracers information at timestep = 0 using:
data,time = read_LaMEM_timestep(model, 0, passive_tracers=true)
It returns:
(CartData
size : (10000,)
x ϵ [ -0.99 : 0.99]
y ϵ [ 0.0 : 0.0]
z ϵ [ -0.99 : 0.99]
fields : (:Phase, :Temperature, :Pressure, :ID)
, [0.0])
The data.x
, data.y
, and data.z
are structures that contain spatial information of tracers while parameters such like data.fields.Phase
contain the phase, temperature, pressure and index (ID) of tracers.
Sometimes we want to select tracers in a smaller region for further investigation. For example, to track the P-T-t evolution of a subducting slab, we can specify a region of interest (e.g., the upper crust portion of the slab) therefore select tracers within that region only.
In the "falling sphere" example, let's find all the "sphere phase" tracers in the 1st quadrant (x>0, and z>0) of the sphere.
ID = findall(data.x.val .> 0 .&& data.z.val .> 0 .&& data.fields.Phase .== 1)
The ID
parameter records the indices of these tracers. Note we need to do data.x.val
to get the numerical value of the x-coordinate because data.x
is a GeoUnit
structure also containing unit
, and isdimensional
information. The dot in front of >
and &&
implies that it is applied to every point the array data.
Once we select the tracers of interest (we now know the ID of these tracers), we can read their information.
passive_tracers = passivetracer_time(ID,model)
Let's take a look at the passive_tracers
, and see what information it contains:
# Retrieve the keys from the passive_tracers
keys_list = keys(passive_tracers)
# Iterate over each key and print the size of the associated data
for key in keys_list
data_size = size(passive_tracers[key])
println("Key: $key, Size: $data_size")
end
It returns:
Key: x, Size: (489, 4)
Key: y, Size: (489, 4)
Key: z, Size: (489, 4)
Key: Phase, Size: (489, 4)
Key: Temperature, Size: (489, 4)
Key: Pressure, Size: (489, 4)
Key: Time_Myrs, Size: (4,)
The passive_tracers
contains spatial coordinates and P, T, Phase properties and also the associated temporal information for all 4 time steps in matrixes. Now let's plot the position of selected tracer at t=0.
using Plots
scatter(passive_tracers.x[:,1], passive_tracers.z[:,1], title="Scatter Plot of Selected Passive Tracers", legend=false, aspect_ratio=:equal)
We can plot a temporal evolution of P-T of a specific tracer. In the following line, we only select one tracer whose ID==1 among the 489 tracers we selected.
plot( passive_tracers.Temperature[1,:], passive_tracers.Pressure[1,:])
Since the example "falling sphere" code does not contain much dynamics and it only runs for a few timesteps, the resulted P-T path contain little information.
It is also doable to plot the the average P, T properties of a small group of tracers of our selection.