Creating PDEs from ODEs

Modeling the Brusselator PDE:

\[\begin{split} \begin{align} \frac{\partial u}{\partial t} &= 1 + u^2v - 4.4u + \alpha (\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2}) + f(x, y, t) \\ \frac{\partial v}{\partial t} &= 3.4u - u^2 v + \alpha (\frac{\partial^2 u}{\partial x^2} + \frac{\partial^2 u}{\partial y^2}) \end{align} \end{split}\]

import ComponentArrays as CA
using SimpleUnPack
using OrdinaryDiffEq
using LinearSolve
using Plots

function build_brussilator(; N::Int=32, x_min=0, y_min=0, t_min=0, x_max=1, y_max=1, t_max=11.5, α = 10.0)
    @assert (x_min < x_max) && (y_min < y_max) && (t_min < t_max) && (N > 1)
    u0 = CA.ComponentArray(u = zeros(N, N), v = zeros(N, N))
    xx = range(x_min, x_max, length=N)
    yy = range(y_min, y_max, length=N)
    dx = step(xx)
    dy = step(yy)
    ps = CA.ComponentArray(; α, xx, yy, N, dx, dy)

    for i in 1:N, j in 1:N
        x = xx[j]
        y = yy[i]
        u0.u[i, j] = 22 * (y * (1 - y))
        u0.v[i, j] = 27 * (x * (1 - x))
    end

    odef = (ds, s, p, t) -> begin
        @unpack α, xx, yy, dx, dy = p
        @unpack u, v = s
        brusselator_f(x, y, t) = (((x - 0.3)^2 + (y - 0.6)^2) <= 0.1^2) * (t >= 1.1) * 5
        for (i, y) in enumerate(yy), (j, x) in enumerate(xx)
            uterm = 1.0 + v[i, j] * u[i, j]^2 - 4.4 * u[i, j] + brusselator_f(x, y, t)
            vterm = 3.4 * u[i, j] - v[i, j] * u[i, j]^2
            # No flux boundary conditions
            i_prev = clamp(i - 1, 1, N)
            i_next = clamp(i + 1, 1, N)
            j_prev = clamp(j - 1, 1, N)
            j_next = clamp(j + 1, 1, N)
            unabla = (u[i, j_prev] - 2u[i, j] + u[i, j_next]) / dx^2 + (u[i_prev, j] - 2u[i, j] + u[i_next, j]) / dy^2
            vnabla = (v[i, j_prev] - 2v[i, j] + v[i, j_next]) / dx^2 + (v[i_prev, j] - 2v[i, j] + v[i_next, j]) / dy^2
            ds.u[i, j] = α * unabla + uterm
            ds.v[i, j] = α * vnabla + vterm
        end
    end
    return (; u0, odef, ps)
end

build_brussilator (generic function with 1 method)

@unpack u0, odef, ps = build_brussilator()
tspan = (0.0, 11.5)
prob = ODEProblem(odef, u0, tspan, ps)
@time sol = solve(prob, KenCarp47(linsolve = KrylovJL_GMRES()), saveat=0.1)

 34.763881 seconds (1.25 G allocations: 33.734 GiB, 9.79% gc time, 10.76% compilation time)

retcode: Success
Interpolation: 1st order linear
t: 116-element Vector{Float64}:
  0.0
  0.1
  0.2
  0.3
  0.4
  0.5
  0.6
  0.7
  0.8
  0.9
  ⋮
 10.7
 10.8
 10.9
 11.0
 11.1
 11.2
 11.3
 11.4
 11.5
u: 116-element Vector{ComponentArrays.ComponentVector{Float64, Vector{Float64}, Tuple{ComponentArrays.Axis{(u = ViewAxis(1:1024, ShapedAxis((32, 32))), v = ViewAxis(1025:2048, ShapedAxis((32, 32))))}}}}:
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 ComponentVector{Float64}(u = [6.773290649233472 6.773290725936031 … 6.773290725936014 6.773290649233484; 6.77328532685449 6.773285414416952 … 6.773285414416986 6.773285326854452; … ; 6.773285326854472 6.773285414416982 … 6.773285414416978 6.773285326854461; 6.773290649233485 6.7732907259360235 … 6.773290725936022 6.773290649233483], v = [0.6709604463847637 0.6709539992600472 … 0.6709539992600495 0.6709604463847645; 0.6709605815409581 0.6709541235532056 … 0.6709541235532068 0.670960581540964; … ; 0.6709605815409634 0.6709541235531926 … 0.6709541235531861 0.670960581540975; 0.6709604463847623 0.6709539992600636 … 0.6709539992600494 0.670960446384754])
 ComponentVector{Float64}(u = [6.356141376219994 6.35614137371218 … 6.3561413737121795 6.3561413762199885; 6.356141371068119 6.356141368581267 … 6.356141368581257 6.35614137106812; … ; 6.3561413710681185 6.356141368581258 … 6.3561413685812695 6.356141371068112; 6.3561413762199885 6.356141373712178 … 6.35614137371218 6.356141376219993], v = [0.5264757088675984 0.526475702969669 … 0.5264757029696688 0.5264757088675975; 0.5264757071909414 0.5264757012721475 … 0.5264757012721479 0.5264757071909418; … ; 0.5264757071909406 0.5264757012721485 … 0.5264757012721483 0.5264757071909414; 0.5264757088675993 0.5264757029696683 … 0.5264757029696681 0.5264757088675988])
 ComponentVector{Float64}(u = [5.8039450312330025 5.803945032670937 … 5.803945032670955 5.8039450312330105; 5.803945008829085 5.803945010331297 … 5.803945010331298 5.803945008829071; … ; 5.803945008829085 5.803945010331292 … 5.803945010331283 5.803945008829103; 5.803945031233014 5.803945032670929 … 5.803945032670947 5.80394503123299], v = [0.5710329001041721 0.5710328713798584 … 0.5710328713798626 0.5710329001041705; 0.5710329002710766 0.5710328714823919 … 0.5710328714823888 0.5710329002710778; … ; 0.5710329002710796 0.5710328714823935 … 0.5710328714823905 0.571032900271078; 0.5710329001041679 0.5710328713798644 … 0.5710328713798642 0.571032900104169])
 ComponentVector{Float64}(u = [5.297578205206687 5.297578209392803 … 5.297578209392773 5.297578205206653; 5.297578175531061 5.297578179783483 … 5.297578179783501 5.297578175531086; … ; 5.297578175531074 5.297578179783508 … 5.297578179783506 5.29757817553104; 5.29757820520665 5.297578209392824 … 5.297578209392806 5.2975782052067], v = [0.6226807503070436 0.6226807123779619 … 0.6226807123779533 0.622680750307051; 0.6226807524560014 0.6226807144605842 … 0.6226807144605878 0.6226807524559981; … ; 0.6226807524559957 0.6226807144605788 … 0.6226807144605859 0.6226807524559975; 0.622680750307053 0.6226807123779476 … 0.62268071237795 0.6226807503070518])
 ComponentVector{Float64}(u = [4.835550075851494 4.835550077670883 … 4.835550077670894 4.835550075851434; 4.835550062182636 4.835550064035003 … 4.835550064035016 4.835550062182632; … ; 4.835550062182667 4.83555006403501 … 4.835550064034994 4.8355500621826435; 4.835550075851446 4.835550077670894 … 4.835550077670941 4.835550075851473], v = [0.6783892452223519 0.6783892276259822 … 0.6783892276259791 0.67838924522236; 0.6783892460201488 0.6783892283908307 … 0.6783892283908279 0.6783892460201475; … ; 0.6783892460201474 0.678389228390825 … 0.6783892283908277 0.6783892460201472; 0.6783892452223589 0.678389227625972 … 0.6783892276259778 0.6783892452223582])
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 ComponentVector{Float64}(u = [4.0252218880435775 4.025222368295847 … 4.025369779908983 4.025370567726263; 4.025220010016473 4.025220482358175 … 4.02536931517563 4.025370110494713; … ; 4.025048196758811 4.025048231437623 … 4.025307294522808 4.025308693447834; 4.025049871923686 4.0250499735892875 … 4.025307216918114 4.025308609598616], v = [0.8033001849117587 0.8033001538675842 … 0.8032947885203122 0.8032947689722305; 0.803300221364924 0.8033001903211177 … 0.8032948044737356 0.803294784820357; … ; 0.8033047604989224 0.8033047266120706 … 0.80329729537036 0.8032972643655582; 0.8033047585844018 0.8033047244358746 … 0.8032973029851302 0.8032972720128221])
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 ⋮
 ComponentVector{Float64}(u = [0.4168802797269945 0.4168741647838941 … 0.4150735538034345 0.4150639740405664; 0.4169015964043824 0.4168955656681689 … 0.41507907083134615 0.4150694069099402; … ; 0.41891794665429755 0.41891642859239336 … 0.415848254909682 0.4158317324390199; 0.4189003028908161 0.4188980638980493 … 0.4158495479781351 0.415833093326587], v = [4.146044990330784 4.146044992898402 … 4.146045615883768 4.146045618971389; 4.146044982735447 4.146044985307038 … 4.146045614175036 4.146045617291338; … ; 4.146044092179732 4.146044096180869 … 4.146045381686316 4.1460453880296; 4.146044094218854 4.146044098298231 … 4.146045381305585 4.146045387641745])
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This notebook was generated using Literate.jl.