{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Meandering river" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "\n", "import timflow.transient as tft" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "ml = tft.Model3D(\n", " kaq=[2, 1, 5, 10, 4],\n", " z=[10, 8, 6, 4, 2, 0],\n", " Saq=[0.1, 0.0001, 0.0002, 0.0002, 0.0001],\n", " topboundary=\"phreatic\",\n", " kzoverkh=0.1,\n", " tmin=1,\n", " tmax=10,\n", ")\n", "w = tft.Well(ml, -25, 0, rw=0.3, tsandQ=[(0, 100)], layers=[2, 3])\n", "\n", "dxdy = 30 * np.pi / 100 * np.cos(np.pi)\n", "x1 = np.arange(-150, -100, 10)\n", "y1 = (x1 + 100) * dxdy\n", "x2 = np.linspace(-100, 100, 20)\n", "y2 = 30 * np.sin(x2 * np.pi / 100)\n", "yls = np.hstack((y1, y2))\n", "xls = np.hstack((x1, x2))\n", "xy = np.array([xls, yls]).T\n", "\n", "ls1 = tft.RiverString(ml, xy=xy, tsandh=\"fixed\", layers=[0, 1])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "ml.solve()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "ml.plots.contour(win=[-150, 150, -50, 50], ngr=40, t=1, layers=1, labels=False);" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "ml.plots.contour(win=[-150, 150, -50, 50], ngr=40, t=1, layers=2, labels=False);" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.13.5" } }, "nbformat": 4, "nbformat_minor": 4 }