Case1-I2VIS.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "663010e1",
   "metadata": {},
   "source": [
    "## Importing Packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cd7734f1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "plots (generic function with 1 method)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Import necessary packages\n",
    "using SparseArrays\n",
    "using LinearAlgebra\n",
    "using IterativeSolvers\n",
    "using WriteVTK\n",
    "using Printf\n",
    "using Statistics \n",
    "include(\"Grid.jl\")\n",
    "include(\"GridOperations.jl\")\n",
    "include(\"Markers.jl\")\n",
    "include(\"Stokes.jl\")\n",
    "include(\"Temperature.jl\")\n",
    "\n",
    "# note that we import pyplot last to avoid a name conflict with grid.\n",
    "using PyPlot\n",
    "include(\"Visualization.jl\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2da15853",
   "metadata": {},
   "source": [
    "## Topography Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "7f6869af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "initial_medium_mantle_depth (generic function with 1 method)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The initial topography setup follows the following:\n",
    "# y = A*cos[k(x-b)]+c \n",
    "# |A| is the amplitude \n",
    "# k is the wave number (k=2π/wavelength)\n",
    "# The period is 2π/k \n",
    "# The horizontal shift is b \n",
    "# The vertical shift is c (midline)\n",
    "function initial_surface_depth(x::Float64)\n",
    "    w = 2.8e6\n",
    "    A = 7.0e3\n",
    "    k = (2*pi)/w\n",
    "    b = 1.4e6\n",
    "    c = 1.7e4\n",
    "    return (A) * (cos(k*(x-b))) + (c)\n",
    "end\n",
    "\n",
    "function initial_medium_mantle_depth(x::Float64)\n",
    "     return 1.07e5\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dabeac75",
   "metadata": {},
   "source": [
    "## Material Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "37800217",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "initial_conditions! (generic function with 1 method)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "struct Materials\n",
    "    # 1 - mantle\n",
    "    # 2 - medium \n",
    "    # 3 - sticky air\n",
    "    alpha::Vector{Float64} # Thermal expansion (1/K)\n",
    "    rho0::Vector{Float64} # Density (kg/m^3)\n",
    "    Hr::Vector{Float64} # Radiogenic heat production (W/m^3)\n",
    "    Cp::Vector{Float64} # Heat capacity (J/kg*K)\n",
    "    kThermal::Vector{Float64} # Thermal conductivity (W/m*K)\n",
    "    eta::Vector{Float64} # Viscosity (Pa*s)\n",
    "    function Materials()\n",
    "        new([3e-5,2e-5,0.0],[3300.0,3300.0,1.0],[2e-8,3e-8,0.0],[1000.0,1000.0,3.3e6],[3.0,2.0,300.0],[1e21,1e23,1e18])\n",
    "    end    \n",
    "end\n",
    "\n",
    "function update_marker_prop!(markers::Markers,materials::Materials)\n",
    "    eta = markers.scalarFields[\"eta\"]\n",
    "    rho = markers.scalarFields[\"rho\"]\n",
    "    T = markers.scalarFields[\"T\"]\n",
    "    mmat = markers.integers[markers.integerFields[\"material\"],:]\n",
    "    for i in 1:markers.nmark\n",
    "        markers.scalars[rho,i] = materials.rho0[mmat[i]]\n",
    "    end\n",
    "end\n",
    "\n",
    "function initial_conditions!(markers::Markers,materials::Materials)\n",
    "    material = markers.integerFields[\"material\"]\n",
    "    T = markers.scalarFields[\"T\"]\n",
    "    eta = markers.scalarFields[\"eta\"]\n",
    "    alpha = markers.scalarFields[\"alpha\"]\n",
    "    Cp = markers.scalarFields[\"Cp\"]\n",
    "    Hr = markers.scalarFields[\"Hr\"]\n",
    "    \n",
    "    for i in 1:markers.nmark\n",
    "        mx = markers.x[1,i]\n",
    "        my = markers.x[2,i]\n",
    "        hmed = initial_medium_mantle_depth(mx)\n",
    "        hsurf = initial_surface_depth(mx)\n",
    "        if my > hmed\n",
    "            # mantle\n",
    "            markers.integers[material,i] = 1\n",
    "            markers.scalars[T,i] = 1500.0\n",
    "            markers.scalars[eta,i] = materials.eta[1]\n",
    "            markers.scalars[alpha,i] = materials.alpha[1]        \n",
    "            markers.scalars[Cp,i] = materials.Cp[1]\n",
    "            markers.scalars[Hr,i] = materials.Hr[1]  \n",
    "        elseif my > hsurf\n",
    "            # medium\n",
    "            markers.integers[material,i] = 2\n",
    "            markers.scalars[T,i] = 1800.0\n",
    "            markers.scalars[eta,i] = materials.eta[2]\n",
    "            markers.scalars[alpha,i] = materials.alpha[2]\n",
    "            markers.scalars[Cp,i] = materials.Cp[2]\n",
    "            markers.scalars[Hr,i] = materials.Hr[2]  \n",
    "        else\n",
    "            # sticky air\n",
    "            markers.integers[material,i] = 3\n",
    "            markers.scalars[T,i] = 273.0            \n",
    "            markers.scalars[eta,i] = materials.eta[3]\n",
    "            markers.scalars[alpha,i] = materials.alpha[3]  \n",
    "            markers.scalars[Cp,i] = materials.Cp[3]\n",
    "            markers.scalars[Hr,i] = materials.Hr[3] \n",
    "        end\n",
    "    end \n",
    "    # end loop over markers\n",
    "    update_marker_prop!(markers,materials)\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "734a64eb",
   "metadata": {},
   "source": [
    "## Model Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "0e10d064",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Creating Markers...\n",
      "  0.064101 seconds (19 allocations: 97.205 MiB, 55.64% gc time)\n",
      "Initial condition...\n",
      "  0.163358 seconds (3.11 M allocations: 49.772 MiB)\n",
      "Finished Step 1 time=0.007938358741048895 Myr\n",
      "  2.876300 seconds (6.24 M allocations: 1.083 GiB, 3.82% gc time, 1.03% compilation time)\n"
     ]
    }
   ],
   "source": [
    "function run(nstep::Int64)\n",
    "    nx = 208\n",
    "    ny = 140\n",
    "    W = 2.8e6\n",
    "    H = 7.17e5\n",
    "    gx = 0.0\n",
    "    gy = 10.0\n",
    "\n",
    "    Tbctype = [-1,-1,1,1] #left, right, top, bottom\n",
    "    Tbcval = [0.0,0.0,273.0,1500.0]\n",
    "    \n",
    "    bc = BoundaryConditions(0,0,0,0) # currently does nothing but is required argument to stokes solver.\n",
    "    materials = Materials()\n",
    "    \n",
    "    markx = 6\n",
    "    marky = 6\n",
    "    seconds_in_year = 3.15e7\n",
    "    plot_interval = 1e6*seconds_in_year # plot interval in seconds\n",
    "    end_time = 3e7*seconds_in_year\n",
    "    dtmax = plot_interval\n",
    "    grid = CartesianGrid(W,H,nx,ny)\n",
    "    println(\"Creating Markers...\")\n",
    "    @time markers = Markers(grid,[\"alpha\",\"T\",\"rho\",\"eta\",\"Cp\",\"Hr\"],[\"material\"] ; nmx=markx,nmy=marky,random=true)\n",
    "    println(\"Initial condition...\")\n",
    "    @time initial_conditions!(markers, materials)\n",
    "    \n",
    "    air_medium_interface = zeros(Float64,grid.nx+1)\n",
    "    mantle_medium_interface = zeros(Float64,grid.nx+1)\n",
    "\n",
    "    # define arrays for k, rho, cp, H at the basic nodes. Fill them with constant values for now.\n",
    "    kThermal = 3.0 .*ones(grid.ny,grid.nx);\n",
    "\n",
    "    time = 0.0\n",
    "    iout=0\n",
    "    last_plot = 0.0\n",
    "    rho_c = nothing\n",
    "    dt = 1e10\n",
    "\n",
    "      local rho_c\n",
    "      local rho_vx\n",
    "      local rho_vy\n",
    "      local alpha\n",
    "      local Hr\n",
    "      local Cp_c\n",
    "      local eta_s\n",
    "      local eta_n\n",
    "      local vxc\n",
    "      local vyc\n",
    "      local T\n",
    "      local dt\n",
    "      local dTmax\n",
    "      local dTemp\n",
    "      local Tnew\n",
    "      local Tlast\n",
    "\n",
    "    output_dir = \"test\"\n",
    "    for itime in 1:nstep\n",
    "        # 1. Transfer properties markers -> nodes\n",
    "        update_marker_prop!(markers,materials)\n",
    "        # 1a. Basic Nodes\n",
    "        eta_s_new, = marker_to_stag(markers,grid,[\"eta\",],\"basic\");\n",
    "        # 1b. Cell Centers\n",
    "        rho_c_new,Cp_c_new,alpha_new,eta_n_new,Tlast_new,Hr_new = marker_to_stag(markers,grid,[\"rho\",\"Cp\",\"alpha\",\"eta\",\"T\",\"Hr\"],\"center\")\n",
    "        # 1c. Vx and Vy nodes:\n",
    "        rho_vx_new, = marker_to_stag(markers,grid,[\"rho\",],\"vx\")\n",
    "        rho_vy_new, = marker_to_stag(markers,grid,[\"rho\",],\"vy\")\n",
    "\n",
    "        # deal with any NaN values from interpolation:\n",
    "        if itime > 1\n",
    "            if any(isnan.(eta_s_new))\n",
    "                println(\"found nan values\")\n",
    "            end\n",
    "            replace_nan!(eta_s,eta_s_new)\n",
    "            replace_nan!(rho_c,rho_c_new)\n",
    "            replace_nan!(Hr,Hr_new)\n",
    "            replace_nan!(Cp_c,Cp_c_new)\n",
    "            replace_nan!(alpha,alpha_new)\n",
    "            replace_nan!(eta_n,eta_n_new)\n",
    "            replace_nan!(Tlast,Tlast_new)\n",
    "            replace_nan!(rho_vx,rho_vx_new)\n",
    "            replace_nan!(rho_vy,rho_vy_new)\n",
    "        end\n",
    "        # Copy field data \n",
    "        rho_vx = copy(rho_vx_new)\n",
    "        rho_vy = copy(rho_vy_new)\n",
    "        rho_c = copy(rho_c_new)\n",
    "        Hr = copy(Hr_new)\n",
    "        Cp_c = copy(Cp_c_new)\n",
    "        alpha = copy(alpha_new)\n",
    "        eta_s = copy(eta_s_new)\n",
    "        eta_n = copy(eta_n_new)\n",
    "        Tlast = copy(Tlast_new)\n",
    "    \n",
    "        # 2. Assemble and solve the stokes equations\n",
    "        L,R = form_stokes(grid,eta_s,eta_n,rho_vx,rho_vy,bc,gx,gy;dt=dt)\n",
    "        stokes_solution = L\\R\n",
    "        vx,vy,P = unpack(stokes_solution,grid;ghost=true)\n",
    "    \n",
    "        # Get the velocity at the cell centers:\n",
    "        vxc,vyc = velocity_to_centers(grid,vx,vy)\n",
    "        adiabatic_heating = compute_adiabatic_heating(grid,rho_c,Tlast,alpha,gx,gy,vxc,vyc)\n",
    "        shear_heating = compute_shear_heating(grid,vx,vy,eta_n,eta_s)\n",
    "        H = (adiabatic_heating .+ shear_heating .+ Hr)\n",
    "    \n",
    "        # 3. Compute the advection timestep:\n",
    "        if itime > 1\n",
    "            this_dtmax = min(1.2*dt,dtmax)\n",
    "        else\n",
    "            this_dtmax = dtmax\n",
    "        end\n",
    "        dt = compute_timestep(grid,vxc,vyc ; dtmax=this_dtmax)\n",
    "        \n",
    "        dTmax = Inf\n",
    "        dTemp = nothing\n",
    "        Tnew = nothing\n",
    "        titer=1\n",
    "        for titer=1:2\n",
    "            # assemble and solve the energy equation\n",
    "#             println(\"Trying with timestep \",dt/3.15e7/1e6,\" Myr\")\n",
    "            L,R = assemble_energy_equation_center(grid,rho_c,Cp_c,kThermal,H,Tlast,dt,Tbctype,Tbcval)\n",
    "            Tnew = L\\R;\n",
    "            Tnew = reshape(Tnew,grid.ny,grid.nx);\n",
    "            Tnew = ghost_temperature_center(grid,Tnew,Tbctype,Tbcval);\n",
    "\n",
    "            T = copy(Tnew)\n",
    "\n",
    "            dTemp = Tnew-Tlast\n",
    "            # compute the maximum temperature change\n",
    "            dTmax = maximum(abs.(dTemp[2:end-1,2:end-1])) \n",
    "#             println(\"dTmax=\",dTmax,\" dt=\",dt/3.15e7/1e6)\n",
    "            dt = min(dt,dTmax < 10.0 ? dt : dt*10.0/dTmax)\n",
    "            if dTmax < 10.0\n",
    "                break\n",
    "            end\n",
    "        end\n",
    "\n",
    "        dT_subgrid_node = subgrid_temperature_relaxation_center!(markers,grid,Tlast,Cp_c[1,1],kThermal[1,1],dt)\n",
    "        dT_remaining = dTemp - dT_subgrid_node\n",
    "\n",
    "        cell_center_change_to_markers!(markers,grid,dT_remaining,\"T\")\n",
    "        \n",
    "        mat, = marker_to_stag(markers,grid,markers.integers[[markers.integerFields[\"material\"]],:],\"center\")\n",
    "        function get_interface(grid::CartesianGrid,mat,contour_value)\n",
    "            interface_position = zeros(Float64,grid.nx+1);\n",
    "            for j in 1:grid.nx+1\n",
    "                i = 1\n",
    "                while i <= grid.ny\n",
    "                    if mat[i,j] == contour_value\n",
    "                        interface_position[j] = grid.yc[i]\n",
    "                        break\n",
    "                elseif mat[i+1,j] < contour_value\n",
    "                        # interface is located within this cell.\n",
    "                        interface_position[j] = grid.yc[i] + (grid.yc[i+1]-grid.yc[i])/(mat[i+1,j]-mat[i,j])*(contour_value-mat[i,j])\n",
    "                        break\n",
    "                    end\n",
    "                    i = i+1\n",
    "                end\n",
    "            end\n",
    "            return interface_position\n",
    "        end\n",
    "        air_medium_interface = get_interface(grid,mat,2.5)\n",
    "        mantle_medium_interface = get_interface(grid,mat,1.5)\n",
    "\n",
    "#         if time == 0.0 || time - last_plot >= plot_interval\n",
    "#             last_plot = time \n",
    "#             name = @sprintf(\"%s/viz.%04d.vtr\",output_dir,iout)\n",
    "#             println(\"Writing visualization fle \",name)\n",
    "#             vn = velocity_to_basic_nodes(grid,vxc,vyc)\n",
    "\n",
    "#         visualization(grid,rho_c,eta_s,vn,P,Tnew[2:end-1,2:end-1],time/seconds_in_year;filename=name)\n",
    "#             name = @sprintf(\"%s/markers.%04d.vtp\",output_dir,iout)\n",
    "#             visualization(markers,time/seconds_in_year;filename=name)\n",
    "#             iout += 1\n",
    "#         end\n",
    "        \n",
    "#         println(\"Min/Max velocity: \",minimum(vyc),\" \",maximum(vyc))\n",
    "        move_markers_rk4!(markers,grid,vx,vy,dt,continuity_weight=1/3)\n",
    "        time += dt\n",
    "        println(\"Finished Step \",itime,\" time=\",time/seconds_in_year/1e6,\" Myr\")\n",
    "    end\n",
    "    return grid,markers,vxc,vyc,rho_c,eta_n,Tnew,time,air_medium_interface,mantle_medium_interface\n",
    "end\n",
    "@time grid,markers,vxc,vyc,rho_c,eta_n,Tnew,time,air_medium_interface,mantle_medium_interface = run(1);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3e835b7",
   "metadata": {},
   "source": [
    "## Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "d2d4ec8a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 2 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mat, = marker_to_stag(markers,grid,markers.integers[[markers.integerFields[\"material\"]],:],\"center\")\n",
    "x_time = @sprintf(\"%.3g\",time/3.15e7/1e6)\n",
    "\n",
    "# Model Schematic\n",
    "# figure(figsize=(12,2))\n",
    "figure()\n",
    "pcolor(grid.xc/1000,grid.yc/1000,mat)\n",
    "colorbar()\n",
    "plot(grid.xc/1000,air_medium_interface/1000,\"r\",label=\"air/medium interface\")\n",
    "plot(grid.xc/1000,mantle_medium_interface/1000,\"m\",label=\"mantle/medium interface\")\n",
    "title(L\"Model\\,\\,Schematic\\,\\,at\\,\\,%$x_time\\,Myr\")\n",
    "gca().invert_yaxis()\n",
    "gca().set_ylabel(L\"Depth\\,(km)\")\n",
    "gca().set_xlabel(L\"Width\\,(km)\") \n",
    "# gca().set_aspect(\"equal\")\n",
    "# legend(loc=\"upper right\",bbox_to_anchor=[1.6,1.0])\n",
    "legend(loc=\"upper right\",bbox_to_anchor=[1.9,1.0])\n",
    "show()\n",
    "\n",
    "# Temperature Profile \n",
    "# figure(figsize=(12,3))\n",
    "figure()\n",
    "scatter(markers.x[1,:]/1000,markers.x[2,:]/1000,c=markers.scalars[markers.scalarFields[\"T\"],:],s=0.1)\n",
    "plot(grid.xc/1000,air_medium_interface/1000,\"r\",label=\"air/crust interface\")\n",
    "plot(grid.xc/1000,mantle_medium_interface/1000,\"m\",label=\"mantle/medium interface\")\n",
    "title(L\"Temperature\\,\\,Profile\\,\\,at\\,\\,%$x_time\\,Myr\")\n",
    "colorbar(label=L\"K\")\n",
    "gca().invert_yaxis()\n",
    "gca().set_ylabel(L\"Height\\,(km)\")\n",
    "gca().set_xlabel(L\"Width\\,(km)\")\n",
    "# gca().set_aspect(\"equal\")\n",
    "# legend(loc=\"upper right\",bbox_to_anchor=[1.5,1.0])\n",
    "legend(loc=\"upper right\",bbox_to_anchor=[1.9,1.0])\n",
    "show()\n",
    "\n",
    "# Viscosity Profile \n",
    "# figure(figsize=(12,3))\n",
    "figure()\n",
    "scatter(markers.x[1,:]/1000,markers.x[2,:]/1000,c=log10.(markers.scalars[markers.scalarFields[\"eta\"],:]),s=0.1)\n",
    "plot(grid.xc/1000,air_medium_interface/1000,\"r\",label=\"air/crust interface\")\n",
    "plot(grid.xc/1000,mantle_medium_interface/1000,\"m\",label=\"mantle/medium interface\")\n",
    "title(L\"Viscosity\\,\\,Profile\\,\\,at\\,\\,%$x_time\\,Myr\")\n",
    "colorbar(label=L\"Pa\\cdot{s}\")\n",
    "gca().invert_yaxis()\n",
    "gca().set_ylabel(L\"Height\\,(km)\")\n",
    "gca().set_xlabel(L\"Width\\,(km)\")\n",
    "# gca().set_aspect(\"equal\")\n",
    "# legend(loc=\"upper right\",bbox_to_anchor=[1.5,1.0])\n",
    "legend(loc=\"upper right\",bbox_to_anchor=[1.9,1.0])\n",
    "show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "3e8ca377",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "Figure(PyObject <Figure size 640x480 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "PyObject <matplotlib.collections.PathCollection object at 0x11a3c43a0>"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C = ((3/16*pi^3) * ((2.8e6)^3/(air_medium_interface).^3) * (1e17/1e21)) / 1000 \n",
    "b = log.(C)\n",
    "scatter(air_medium_interface/1000,b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3e145aa0",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.8.2",
   "language": "julia",
   "name": "julia-1.8"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.8.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}