mirror of
https://gitlab.rlp.net/mobitar/ReCo.jl.git
synced 2024-09-19 19:01:17 +00:00
97 lines
No EOL
2.1 KiB
Julia
97 lines
No EOL
2.1 KiB
Julia
using Distributions: Uniform
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using Dates: now
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using JSON3: JSON3
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using ReCo: Bundle, Particle
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function initial_particle_grid_pos(i, j; grid_box_width, l)
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term = -0.5 * grid_box_width - l
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return [k * grid_box_width + term for k in (i, j)]
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end
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function generate_particles(grid_n::Int64, grid_box_width::Float64, l::Float64)
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particles = Vector{Particle}(undef, grid_n^2)
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id = 1
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for i in 1:grid_n
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for j in 1:grid_n
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particles[id] = Particle(;
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id=id,
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c=initial_particle_grid_pos(i, j; grid_box_width=grid_box_width, l=l),
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φ=rand(Uniform(-π, π)),
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)
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id += 1
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end
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end
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return particles
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end
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function generate_particles(bundle::Bundle, N::Int64)
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particles = Vector{Particle}(undef, N)
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for id in 1:N
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particles[id] = Particle(; id=id, c=bundle.c[id, end], φ=bundle.φ[id, end])
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end
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return particles
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end
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function init_sim(;
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N::Int64, v::Float64, δt::Float64=1e-5, packing_ratio::Float64=0.5, comment::String=""
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)
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@assert N > 0
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@assert v >= 0
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@assert δt in 1e-7:1e-7:1e-4
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@assert packing_ratio > 0
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μ = 1.0
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D₀ = 1.0
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particle_diameter = 1.0
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Dᵣ = 3 * D₀ / (particle_diameter^2)
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σ = 1.0
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ϵ = 100.0
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interaction_r = 2^(1 / 6) * σ
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grid_n = round(Int64, ceil(sqrt(N)))
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N = grid_n^2
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l = sqrt(N * π / packing_ratio) * σ / 4
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grid_box_width = 2 * l / grid_n
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sim_consts = (;
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# Input
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N,
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v,
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δt,
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packing_ratio,
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# Calculated
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μ,
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D₀,
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particle_diameter,
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Dᵣ,
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σ,
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ϵ,
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interaction_r,
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grid_n,
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l,
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grid_box_width,
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)
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particles = generate_particles(grid_n, grid_box_width, l)
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bundle = Bundle(N, 1)
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save_snapshot!(bundle, 1, 0.0, particles)
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dir = "exports/$(now())_N=$(N)_v=$(v)_#$(rand(1000:9999))$comment"
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mkpath(dir)
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open("$dir/sim_consts.json", "w") do f
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JSON3.pretty(f, sim_consts)
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end
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save_bundle(dir, bundle, 1, 0.0)
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return dir
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end |