diff --git a/.gitignore b/.gitignore index 97fbbddb2..840e5ab71 100644 --- a/.gitignore +++ b/.gitignore @@ -3,6 +3,7 @@ __pycache__/ .cache *.ipynb +*.ipynb_checkpoints *.pyc *.egg-info dist diff --git a/docs/_config.yml b/docs/_config.yml index b879a2e98..1a10db78d 100644 --- a/docs/_config.yml +++ b/docs/_config.yml @@ -23,7 +23,7 @@ bibtex_bibfiles: # Information about where the book exists on the web repository: - url: https://github.com/nrel/floris + url: https://github.com/NREL/floris path_to_book: docs branch: main diff --git a/docs/_toc.yml b/docs/_toc.yml index 360f2b422..927d8d04f 100644 --- a/docs/_toc.yml +++ b/docs/_toc.yml @@ -18,7 +18,8 @@ parts: - caption: Theory and Background chapters: - - file: reference + - file: wake_models + - file: bibliography - caption: Developer Reference chapters: diff --git a/docs/bibliography.md b/docs/bibliography.md new file mode 100644 index 000000000..dab6bd897 --- /dev/null +++ b/docs/bibliography.md @@ -0,0 +1,6 @@ + +# Bibliography + +```{bibliography} +:style: unsrt +``` diff --git a/docs/wake_models.ipynb b/docs/wake_models.ipynb new file mode 100644 index 000000000..1851343bd --- /dev/null +++ b/docs/wake_models.ipynb @@ -0,0 +1,589 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Wake Models\n", + "\n", + "A wake model in FLORIS is made up of four components that together constitute a wake.\n", + "At minimum, the velocity deficit profile behind a wind turbine is required. For most models,\n", + "an additional wake deflection model is included to model the effect of yaw misalignment.\n", + "Turbulence models are also available to couple with the deficit and deflection components.\n", + "Finally, methods for combining wakes with the rest of the flow field are available.\n", + "\n", + "Computationally, the solver algorithm and grid-type supported by each wake model can also\n", + "be considered as part of the model itself. As shown in the diagram below, the mathematical\n", + "formulations can be considered as the main components of the model. These are typically\n", + "associated directly to each other and in some cases they are bundled together into\n", + "a single mathematical formulation. The solver algorithm and grid type are associated\n", + "to the math formulation, but they are typically more generic.\n", + "\n", + "```{mermaid}\n", + "flowchart LR\n", + " A[\"Deficit\"]\n", + " B[\"Deflection\"]\n", + " C[\"Turbulence\"]\n", + " D[\"Velocity\"]\n", + " E[\"Solver\"]\n", + " F[\"Grid\"]\n", + "\n", + " subgraph H[FLORIS Wake Model]\n", + " direction LR\n", + " subgraph G[Math Model]\n", + " direction LR\n", + " A---B\n", + " B---C\n", + " C---D\n", + " end\n", + " G---E\n", + " E---F\n", + " end\n", + "```" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "from floris.tools import FlorisInterface\n", + "import floris.tools.visualization as wakeviz" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Velocity deficit\n", + "\n", + "The velocity deficit models describe the velocity profile behind a wind turbine as a function of\n", + "distance from the turbine plus additional model-specific parameters." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Jensen\n", + "The Jensen model computes the wake velocity deficit based on the classic Jensen/Park model\n", + "{cite:t}`jensen1983note`. It is often refered to as a \"top-hat\" model because the spanwise\n", + "velocity profile is constant across the wake and abruptly jumps to freestream outside of the\n", + "wake boundary line. The plot below shows the profile of the wake deficit. The grid is\n", + "intentionally coarse to highlight the streamwise linearity of this model. The slope of\n", + "the wake boundary line, or wake expansion, is a user parameter." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 1, figsize=(10, 10))\n", + "fi = FlorisInterface(\"../examples/inputs/jensen.yaml\")\n", + "fi.reinitialize(layout_x=np.array([0.0]), layout_y=np.array([0.0]))\n", + "horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_resolution=40,\n", + ")\n", + "wakeviz.visualize_cut_plane(horizontal_plane, ax=axes)\n", + "wakeviz.plot_turbines_with_fi(fi, ax=axes)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Gauss and GCH\n", + "The Gaussian velocity model is implemented based on {cite:t}`bastankhah2016experimental` and\n", + "{cite:t}`niayifar2016analytical`. This model represents the velocity deficity as a gaussian\n", + "distribution in the spanwise direction, and the gaussian profile is controlled by user parameters.\n", + "There is a near wake zone and a far wake zone. Both maintain the gaussian profile in the spanwise\n", + "direction, but they have different models for wake recovery. " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 1, figsize=(10, 10))\n", + "fi = FlorisInterface(\"../examples/inputs/gch.yaml\")\n", + "fi.reinitialize(layout_x=np.array([0.0]), layout_y=np.array([0.0]))\n", + "horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_resolution=200,\n", + ")\n", + "wakeviz.visualize_cut_plane(horizontal_plane, ax=axes)\n", + "wakeviz.plot_turbines_with_fi(fi, ax=axes)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Cumulative Curl\n", + "The cumulative curl model is an implementation of the model described in {cite:t}`bay_2022`,\n", + "which itself is based on the cumulative model of {cite:t}`bastankhah_2021`" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 1, figsize=(10, 10))\n", + "fi = FlorisInterface(\"../examples/inputs/cc.yaml\")\n", + "fi.reinitialize(layout_x=np.array([0.0]), layout_y=np.array([0.0]))\n", + "horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_resolution=200,\n", + ")\n", + "wakeviz.visualize_cut_plane(horizontal_plane, ax=axes)\n", + "wakeviz.plot_turbines_with_fi(fi, ax=axes)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### TurbOPark\n", + "Model based on the TurbOPark model. For model details see the following references:\n", + "\n", + "- https://github.com/OrstedRD/TurbOPark\n", + "- https://github.com/OrstedRD/TurbOPark/blob/main/TurbOPark%20description.pdf\n", + "- Nygaard, Nicolai Gayle, et al. \"Modelling cluster wakes and wind farm blockage.\" 2020" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Wake deflection\n", + "\n", + "The deflection models capture the effects of rotor misalignment to the incoming wind by\n", + "computing a shift away from the wake centerline. This class of models are a function of\n", + "the distance from the turbine causing the wake and that turbine's yaw angle in addition\n", + "to other model-specific parameters." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Jimenez\n", + "Jiménez wake deflection model, derived from {cite:t}`jimenez2010application`." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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I1fprmJ48CNSIk629rp5sMDt3a4DeXnnp5WPs2DZMJUnIsozR8fNvZhjeohZHkaXq1aXGe4AD7v4CgJl9HrgPUPBaB6K4n4Hhu8nSnDAOyNKQ5thxomiALHOCrNXrKsoGc/rUCU6dPE671QQgqVTZum07w1tHelyzje2ll49xze6ds6//ev+zDPY3MDNOnx3jzW+4p4e1E1mfehW8rgIOzXl9GHh9j+oiy2RBBOQkSYdm6PQNXE8w2Wbi7LNEUZ1q3+5eV1E2gAPPPs3k+DS79+ymUq0B0GpOc/TIS5w+dYJX3XhLj2u4cZkZ3/ruID901yhhGFJJEl73mpsB+OZ3/lOPayeyPq3Z4STM7AEze9zMHh8l63V15CLS9ijOKYIgo9MexfOUSv0a0nSS0VP6YpaVO3P6JLm/nm3bdzEwuIWBwS2M7NjFrbe/jjOnT/a6ehtaGAaMTxb9OU+cPkO1ov6cIivVqxavI8DVc17vKctmuftDwEMA+6yqAXvWqNb0EfI8xT2jOfkynU5xx2O1nhGElV5XTzaAIAiZnDwD9J9XPj42Shjqxuwr6eYb9vJvvvw01WSSIAi489ZXz87buU39OUWWo1ffWt8G9pnZXorA9W7gZ3pUF1mBvsFbqFTbTIw+R2NwH+1WTNqJqDf0cyKyOm66+Ta+8vAzPP5Yk2q1CkC71SKMIm68+TU9rt3GNtjf4LU3v557bj9FHJ9/urjhWt30ILIcPQle7p6a2QeArwIh8Bl31wBQ61Bz8iCV6i4ag/t6XRXZoBr9A+y76W9yy22TdNrFjRtJpUKSqEW1Wy4MXSKyfD371+TuXwG+0qvPl5XLsyZBWO91NWSTSJIKlYrCloisb/ozRpZteuJpBoZfA+TkWZuxM0+QtiOyLKTdbLFl2+t6XUUREZE1Zc3e1ShrX1zpkKYvkmdtgjABApLaLpLKbtL2OK3p472uooiIyJqi4CUr4LSnTxKECXnewSwo73JskqXTTE0c7HUFRURE1hRdapRlS6rbOHP828DVZNkJGoM7STsnqTVuoNM6CWgUEBERkbnU4iXLVuvbQ7VvF532OLXG9QAEYXG7/+DW23tZNRERkTVJwUuWrTl1jMHhO3AyJkefptU8Sa1v7+z8an1XD2snIiKy9uhSoyybmRFGNRqDdxDFKUmlQ7sVk+fF/Epte28rKCIissaoxUuWrVLb0esqiIiIrCtq8ZIVabfOMD1xGAumieOULKtjwXag1uuqiYiIrDkKXrJso6dewn2aKL6KuLKVJElpTmdMTx5lcgz6Bq7vdRVFRETWFAUvWbbW9BiD2+4iS0OiOCVKOiQeE4S7aDe/2evqiYiIrDnq4yUrEJB2xuaVpp1xzMIe1EdERGRtU4uXLFu9/0amJ58j6zxPnETESUqrmZNnCcM7XtXr6omIiKw5Cl6ybGHUoH/LHXTaGUEwRVLpEFf7yLM6UTzd6+qJiIisOQpesmJBkBDFAVHcIc9j8qzXNRIREVmb1MdLREREpEsUvERERES6RJcaZUHjDDLh/YwyjHlGP6NE8S2MnuwHcwwjxwkwcnfMIE5SMCOMO+S5YVaUi4iISEHBS+YZ4Aw5AS0qZERMU+eH7a287kSD0ROPMEWDcQZoUWOaOikV2iSkQEhKSJOcaao0qTDN/ttuIYxzqn0pUez0DbQJQqd/qNXrTRUREekqBS+ZJ7SMrRwHg90cuuTymYekRJz1rYwzyBAnOc5udnOQl9gHd97B2RN1toxMcfZEnb7BFqMnavgW1CImIiKbioKXrFhoGSEZfYxz1K+lRZWDfhOvcBWHfS+Hnx1kajzm7CsVmtMRp1+u0m6GvHK4TpxkxJWMOMmJ4oy4mhOFThjn1PqNMIIwdIJQIU1ERNY/BS9ZNQ0b5zV8m5SIq3mBFlWuZz93P/ZnTHqDKQaYoJ8JBphggEn6adFHkwoBTkSHnJA646Qk7P+ht5HnRq0vJQyNWiOn2pdTqedsGUl7vbkiIiJLpuAlqyqylIiUqjWB0ctap+0Jz/idBJbxA7+RgJzTvo1XDDyDsVMRmHPicEQQOZ2WEcYQx3nxnDhxUkyHEQwMh0VLWQRBCIFBYyi/shsuIiJyGRS8pOcSa3O7PQbArTxOSkxKxLv+4nO0qNL0OlP0MekNpulnnAGmKFrQ2lTo4yyTbGEbL9OixsG/937ixAEYGslptYzGoOOuy5UiItJbCl6ypphBTIfYOtRY/GeHMg94nltJiTnuu5hggLbD2KkAd2d6wjj8bESnA098MyYMHIsgLlvJkroTJ06tD6LE2TpCMR1DvVG0mCUViJIubbyIiGx4Cl6yboWWcyNPAHDLnJasn/zzT5ER0fGYNlVaVJn2OlM0mPY6kzQ4xU4GOc0ow9QYJyblqZ/55wwMO80pY2DIiStGlsL2PU6cFJctwxBMww6LiMgyKXjJhhOYE5StZnWmFlzmiF9LhwpjvoXTjND2hOa0MfkDozUNL33fyHNoTQMUqS4IwCKoViGKoFKHSs1pDMDgUNEyVm9AX3/Z12yoaD0TERGZsaLgZWb/OfBPgZuBe9z98TnzHgTeB2TAL7r7V8vytwO/A4TAp9z9N1ZSB5HluMoOFhNzWsre+n99aXY682C21axFlTZVpr3GS+xjyE8wzhamqdPHKE/9wifJc8hSOPoDGNoOnRacqBbhK64UjyQpAlsQFg8REdl8Vtri9STwE8D/PrfQzG4B3g3cCuwGvm5mN5azPwG8BTgMfNvMHnb3p1dYD5FVFVpOSJvE2vQxOVs+7KdoUWPIT3OGbcWQGZ/+b5lgCy2v4gxxlAotajSpkRPghEBOvXyfhBY1m2T6p/4BjUGo1ouWsZFdkFQhTmDn1T3acBERuaJWFLzcfT+Azb9V7D7g8+7eAl40swPAPeW8A+7+Qrne58tlFbxkXRi0M8AZMLiaFxZddmZE/9QjnuUOaoyTe8ghbmALpzhy3T9gagKSGkyOwpEXodoHZ47DD7ZBpVIEsiyDHVdBp130MRMRkfXrSvXxugp4dM7rw2UZcN5v0BwGXn+F6iDSUzMj+lesxa3+OG2qpBYx6GdoUaPxm3+fSQaZpk7NG0zQzyR9pPRxlCodYiBggNO8AoTWYZsdZ+q/+TWqddi+u7gLdGAIdl/T660VEZHLccngZWZfB3YuMOvD7v7l1a/S7Oc+ADwAMKJ7AGSdS6xNQhuALXb6stZxh+e4jTYJkXc4yD5iOkRDcOwQTE0UHfpPfqvo0F+tQ61edPBPqlCrQaUGlWoxLIYNFC1oxc8waUwzEZFeuGSicfc3L+N9jwBze6nsKctYpPzCz30IeAhgn1V9GXUQWdfM4EaeIHcjtZhreJ62J7R//W/NDpHRpM7V5eCyUzRoUucMdVrUGeYVMiuG1BjhZfzD/xPtdtE6FieQduCGm6HR3+stFRHZPK5UU9LDwL81s9+m6Fy/D/hLinvI9pnZXorA9W7gZ65QHUQ2hMCchKLFrG6Tl14BeNmv4RQ7MJzTPsIoQwQpTE/BE48XLV/tFjz6SNEaFidF61itXrSeVWpFi1lfA/r7iv5mtXpxd2ZUDkKroTJERJZupcNJ/F3gfwVGgP/bzP7a3d/m7k+Z2RcoOs2nwPvdPSvX+QDwVYrhJD7j7k+taAtEZJ7d9hK7eal4YUVH/+y3vkhKTMsrtGfuvPQa0/TRpM601znLVoyzZGS8QoOKNdny2x+l0wILjB27HQyaU/Dq25yo/E1MERG5PCu9q/FLwJcuMu+jwEcXKP8K8JWVfK6ILM1MR/9LtZqd8a2cYicpEZPez0l2cuqEkXbg9Cnj2f0GOOOjxn/8EwgCJ4yKFrNGo2g9q1Sd/n4YHgqpVJyk6gxvLVrKoggGBl2tZSKyaelvVRGZNWSnGOJU8WKm8/1vfhF3yCmGx8iIaHm1HFi2QsurnGJHcQenT9GixlmG2fmpj5DlcOjFgDwrfhdzetKo9RnD2/zc0BgX9OCMg/m9/judK7bJIiJdpeAlIpdkBiFFqxm05rWaXe0vcortZESkPk5GzJkzAa2mMT5mvHwY0rQIUFOT536CKYqdvoZTrxf9xpIK7NqZE5d3Xw4N5dTqcPU1ue7CFJENQcFLRFasatNcxbmfYbqe78ODrz1vGXeKYFa2mrU94QwjjDFMn58lJ+QI11H71x8hioobAY6+HLB9Z0616rx8xKhWIakUfcuisAhnCmQisp4oeIlIV5hRxq4UgD6DAR9ljC1kFpESE/rznH3v+2lToel1RtnC01Rpk5CR0Jn9yrLyvzkRHUZ++b3EsVOrO7Va8VzvK6brNahUc6o1qM6Etrh4TtTXTES6TMFLRHomtOxcnzI470fLF+IOKfFsy1nHi3HKWv/Ln9LySnF3JnXOUoxx1qROh6SMezEZIVWm6LcxckJGfu0XGRnJGBrKAYgi51X7OvT3a+hAEbkyFLxEZN0wg5gOMWVv+yVeZmx7whN+D302TkTK1ld1OPhShOcQV5zxsYAnnogZGHDq9Yx6H0WrWbW4O7NazalWoZ4ExJETRUXLmS53isjlUvASkU0jsTZ38k2ysp9Zev/f5lqPaVGjTZWYKn1eY5I6J+mjRZUWNTrEGMY2O0qHCjs++k8IQrh+b5tOauBQrTm339bq9SaKyBqn4CUim0pgTrCMVrOn/S5yAgCu29vhuecSnn02IQyLcckOHY75i29ViWMnqTj1WnFHZq2W01fPqdWcRpyXrWZOHDtx2d8sjpwguEIbLCJrioKXiMhluMW+Ozud/+ybuXW231hE22MGqM62kLW8wjh1TtBHs2xNa5Mw8svvod0OyDPIOZf5gqAIYXGSE0dOpQKNvoyBgZxKJacRh1QTp78/o1IpLnHGUXHps5KoP5psLpPNNn3VpNfVWDYFLxGRJVpuqxm/89l5w2qkxLQ9KQeknRmUtsIL7GYnB3ECbvj0Rzh+Iqa/P2PrUIq7kWUwNR3ympunZoPY7KC0Iutcludcu310wXl/9YMjvPHVe7tco9Wj4CUi0kUXDqtRFM5f7oTvZJxBUhJqVWi3cw6/XOHgoQpZbuQ5nDwV8eePNnAgMAgjpxI7cZJTjZ1GtUWtmtNXz6jXcqqV4lGrOkkyf1BaLxvPwnRume4ckO575MkDbO3vI4kG2D7QwDbQHSwKXiIia9CIHWOEY8WLn7uPQWCwnHexVrOZHz+faTUb+N0PMTkdcvZYRKsV0OoY7U5AmhqeG2Hoxe9tBk4lcbZt7VCr5sWIaaGTxDl7r5nu1S6QTexHb72BY2cnOHjiDE8cPMr2wQa7hgYYGWj0umorpuAlIrLOXG6rGb/0d2fD2lyZB7OBrfiZp5DjXMUoIW0muPPzHwGMHxyucnY0otUyqpWiP1kUFf3QZobT2EANEbKGRGHInq2D7Nk6SDtNOXpmjAPHTvG9g0dJ0/TSb7CGKXiJiGwyoeWEtEloFwUGfT7BOFvICHnqpz9MRsS4D/Acjdm+Z8UwHCE5ETmG4QTlb3iGZNz+z/4LKklGJcmpVXKqlay8tJlRq+RlWDs/uIlcShJFXDsyzLUjw0y3Oxw7dbbXVVoRBS8RESGxNls5fn7hIq1Z81rNiGh/6DtMliGtXd4s0KJCh4QOFTIC8jK4gdNglC12mjv+5T8EII6cHVubXLdblzc3u4MnznDtyNC88loSc9324R7UaPUoeImIyJLNazWDy7670x0mGeA5fw0xLfrrKXGU0+4EfPOvtrL/+TaVJKNWLVrNZlrPapV8tsUsCp0KRhTqcudGtJE6019IwUtERLrKDBqMcTuPkhHx8nt/abblLPKEk3OH1qBKhwotKrO/tznTavbqf/LjAMUgtqEThjnVuLi8WU0yqkkZ2qoptSQnSXLiKCfGicOcKNTlzrXqmm1bel2FK0bBS0REemIlrWa5G9m/+NJ5d3d2PGaCCqeole9ao0NSXvos+qjttWe485MfIMsC2p2AZjvklr1n2TGsn3taa46PTvDK6DjNdtGZvppE7BjsZ6RR63HNVkbBS0RE1p15g9jCJUPbAb+VCQaZmIpn36PVNv7kL64iDPLZlrNKnFGtZFTijFolo5rk1Cop9bBJEufEoRctZ+UjCtVqttqeOnSM77wwwJtv76MWF1FlupNy8MQZjp8Z49ard/S4hsun4CUiIpvCq+wpADq/8jhQtJoFRGyfc4NASsSEVzhVXuJsz94skHDjgz9NmhtZFpBmNju4rFkR2KIgJ4y8uNyZFOGtlmTUoia1JKOSZERhGdhmwltYBD4534mxCa7ffje7hw7Plg0Bu4cGeOR7zwIKXiIiIuvKgq1mcPGWs489ct7LzMPzBrEtLndGnC7v5py5s/OWf/qzTLdD0jQgzQLS3MhzYyZuBcz0U8uJwpxqkjKypUktbM2GsyjKiQJn2+A0lThf7V2xYtPtDifGJhhu1GlUKyt+vzAIGJ+enFd+dnKaKFzfvyiv4CUiIrIMoRXjl8Gc/mELhbZff4z4gqLcrRwX7fxfIGh6zBG2c5CUt/xvPwEGWQ55J+DEZMKJ0So7h6dIoiKkxeHaudx5dmKao6fHaHVS+qoJN+zcxpa+5fXHuv3a3fzBnx/m/33qGNWk2HutTocwCLn92l2rWe2uU/ASERHpssVa27b4ac6ylW+9//fnhLKIptcYZWsZ2AKcoFihbDsLyQjIeO2vvIVKklGNM+qVlGqcUqum1OKMOC5b0OaEttW43FlLYm6/bjcAB4+f5uCJM/Naps5MTNFOM4YbdeJo8V90H6xXec01e/gbr6rQ7JSd6+OIShzhWbaiuvaagpeIiMgaUrVpdnJ4/owLWtNmWs1mLnNmhHSIaf2Lv2KMKq3zBrMtBrKdaWXLCcu45hiGkXP7B/4WYViMk1aJU2pJVoS2SqfooxZn5y59hjlJlBGFTuwdzBwzY7LZ5uT4JNftGD7vkmOaZRw6eZbjo+PUKgmVKOKGkS0MNeqL7otKGbY2ko21NSIiIpvEkvuoXWBeH7VPfLNsWYs5NW8ctersOGr9nGXYTpY/FBVxx6/9BJ4XH/riKy8RRXtotkeIgml2Dxf9tDpZjhn80Kv3Uq8kTLXaRPT+8mgvKHiJiIhsQgv2UYPLDm4z3vDq1wMwPt2k2TnIG2++gfHmJN99fidHz0wRhznT7XGeO3qSTpqwY6hRXOakTTvKiYLikmcYbI4gpuAlIiIiy/aNn/1XND3nOB0M+Kb9Ge4OxBwrW9QmPOAEKV/BgIhdDPH6f/ZTdLKQNAvoZAF5boxNJTQ70ey4amcnK2VftIw4zDfEz0OtKHiZ2W8BfwdoA88D73H3s+W8B4H3ARnwi+7+1bL87cDvACHwKXf/jZXUQURERHrrZdoEGLvK+zfNbHZkNIA+Ozfy1iFv4Rznlf/+N+e9T8f7aTJAWvZD+yNi8jljrIFx1wffDkAUlL/dGRahrHhk5dAbM33QzpUv3p2/e1ba4vU14EF3T83sY8CDwH9nZrcA7wZuBXYDXzezG8t1PgG8BTgMfNvMHnb3p1dYDxEREemRhIBhQipW3Mk45RmGUbOAzJ1wTlOVw2zvLnc/7wexGzZOg/FFP6v9sWIA3OkFxlGb+3pmeub1Hb/6ttn3MCgCW5QTzQa3c88zY6rF3p4tD1bpUuiKgpe7/+mcl48CP1lO3wd83t1bwItmdgC4p5x3wN1fADCzz5fLKniJiIisU3ssOe91DjTJqBEwSsaYZwwQkmCc9YxryuVtBdcOL9pH7SI6v/Xdc/VzY3KBcdQufH3nh95BJw3pZOF5twKE5lw3coZdWxYPiQtZzT5e7wX+sJy+iiKIzThclgEcuqD89atYBxEREemxhoU0yot7/QR0cM6Q0sG52hK2WG+7mF/0jtALnP3n31+wvOkBTwHP2NJ/ReCSW25mXwd2LjDrw+7+5XKZDwMp8Lkl1+Din/sA8ADAiO4BEBERWZdiC9hBwI554/evX+EyAteMSyYad3/zYvPN7OeBdwFv8uI2BoAjwNVzFttTlrFI+YWf+xDwEMA+q26Oe0xFRERkQ1vRL02Wdyj+KvBj7j41Z9bDwLvNrGJme4F9wF8C3wb2mdleM0soOuA/vJI6iIiIiKwXK72G9y+BCvC1soPco+7+X7n7U2b2BYpO8ynwfnfPAMzsA8BXKYaT+Iy7P7XCOoiIiIisC3bu6uDatc+q/vHo2l5XQ0REROSS3pU++x13v3uheSu61CgiIiIil0/BS0RERKRLFLxEREREukTBS0RERKRLFLxEREREukTBS0RERKRLFLxEREREukTBS0RERKRLFLxEREREukTBS0RERKRLFLxEREREukTBS0RERKRLFLxEREREukTBS0RERKRLzN17XYdLMrMTwMEufNQ24GQXPme90v5ZnPbP4rR/Fqf9szjtn8Vp/yyu2/vnWncfWWjGughe3WJmj7v73b2ux1ql/bM47Z/Faf8sTvtncdo/i9P+Wdxa2j+61CgiIiLSJQpeIiIiIl2i4HW+h3pdgTVO+2dx2j+L0/5ZnPbP4rR/Fqf9s7g1s3/Ux0tERESkS9TiJSIiItIlmzZ4mdlvmdkzZvY9M/uSmW2ZM+9BMztgZt83s7fNKX97WXbAzD7Yk4r3yGbedgAzu9rMHjGzp83sKTP7R2X5sJl9zcyeK5+HynIzs98t99f3zOyu3m5Bd5hZaGZ/ZWb/oXy918weK/fDH5pZUpZXytcHyvnX9bTiXWBmW8zsi+X3zn4z+5s6fs4xs18q/209aWZ/YGbVzXz8mNlnzOy4mT05p2zJx4uZ3V8u/5yZ3d+LbbkSLrJ/1sd53d035QN4KxCV0x8DPlZO3wL8J6AC7AWeB8Ly8TxwPZCUy9zS6+3o0r7atNs+Zx/sAu4qp/uBZ8tj5TeBD5blH5xzHL0T+BPAgHuBx3q9DV3aT78M/FvgP5SvvwC8u5z+JPBfl9P/EPhkOf1u4A97Xfcu7JvPAr9QTifAFh0/s/vmKuBFoDbnuPn5zXz8AD8M3AU8OadsSccLMAy8UD4PldNDvd62K7h/1sV5fdO2eLn7n7p7Wr58FNhTTt8HfN7dW+7+InAAuKd8HHD3F9y9DXy+XHYz2MzbDoC7H3X375bT48B+ipPFfRQnVMrnHy+n7wN+3wuPAlvMbFd3a91dZrYH+NvAp8rXBvxnwBfLRS7cPzP77YvAm8rlNyQzG6Q4UXwawN3b7n4WHT9zRUDNzCKgDhxlEx8/7v5nwOkLipd6vLwN+Jq7n3b3M8DXgLdf8cp3wUL7Z72c1zdt8LrAeyn+WoDiZHpozrzDZdnFyjeDzbzt85SXNe4EHgN2uPvRctYxYEc5vRn32ceBXwXy8vVW4OycL8K5+2B2/5TzR8vlN6q9wAngX5eXYj9lZn3o+AHA3Y8A/zPwEkXgGgW+g46fCy31eNlUx9EF1ux5fUMHLzP7etlf4MLHfXOW+TCQAp/rXU1lvTCzBvDvgH/s7mNz53nRpr0pbxM2s3cBx939O72uyxoVUVwW+T13vxOYpLhUNGuTHz9DFC0Ne4HdQB8bpGXmStnMx8ulrPXzetTrClxJ7v7mxeab2c8D7wLeVB7EAEeAq+cstqcsY5HyjW6xfbJpmFlMEbo+5+5/XBa/Yma73P1o2bR/vCzfbPvsDcCPmdk7gSowAPwOxSWPqGyVmLsPZvbP4fLS0iBwqvvV7prDwGF3f6x8/UWK4KXjp/Bm4EV3PwFgZn9McUzp+DnfUo+XI8CPXlD+/3Shnj2zHs7rG7rFazFm9naKyyI/5u5Tc2Y9DLy7vGtmL7AP+Evg28C+8i6bhKJD58PdrnePbOZtB2b7K30a2O/uvz1n1sPAzJ1C9wNfnlP+c+XdRvcCo3MuEWw47v6gu+9x9+sojo//6O4/CzwC/GS52IX7Z2a//WS5/Ib9693djwGHzOymsuhNwNPo+JnxEnCvmdXLf2sz+0fHz/mWerx8FXirmQ2VrYpvLcs2pHVzXr/SvffX6oOic90h4K/LxyfnzPswxZ0O3wfeMaf8nRR3sz0PfLjX29Dl/bVpt73c/jdSNOt/b84x806KfiXfAJ4Dvg4Ml8sb8Ilyfz0B3N3rbejivvpRzt3VeD3FF9wB4I+ASlleLV8fKOdf3+t6d2G/vBZ4vDyG/j3FXWY6fs7tn/8BeAZ4Evg/Ke5A27THD/AHFP3dOhQtpu9bzvFC0dfpQPl4T6+36wrvn3VxXtfI9SIiIiJdsmkvNYqIiIh0m4KXiIiISJcoeImIiIh0iYKXiIiISJcoeImIiIh0iYKXiIiISJcoeImIiIh0iYKXiIiISJf8/3cTnysM2o8/AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 1, figsize=(10, 10))\n", + "fi = FlorisInterface(\"../examples/inputs/jensen.yaml\")\n", + "fi.reinitialize(layout_x=np.array([0.0]), layout_y=np.array([0.0]))\n", + "yaw_angles = np.zeros((1, 1, 2))\n", + "yaw_angles[:,:,0] = 20.0\n", + "horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_resolution=40,\n", + " yaw_angles=yaw_angles\n", + ")\n", + "wakeviz.visualize_cut_plane(horizontal_plane, ax=axes)\n", + "wakeviz.plot_turbines_with_fi(fi, ax=axes)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Gauss and GCH\n", + "The Gauss deflection model is a blend of the models described in\n", + "{cite:t}`bastankhah2016experimental` and {cite:t}`King2019Controls` for calculating\n", + "the deflection field in turbine wakes." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig, axes = plt.subplots(1, 1, figsize=(10, 10))\n", + "fi = FlorisInterface(\"../examples/inputs/gch.yaml\")\n", + "fi.reinitialize(layout_x=np.array([0.0]), layout_y=np.array([0.0]))\n", + "yaw_angles = np.zeros((1, 1, 2))\n", + "yaw_angles[:,:,0] = 20.0\n", + "horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_resolution=40,\n", + " yaw_angles=yaw_angles\n", + ")\n", + "wakeviz.visualize_cut_plane(horizontal_plane, ax=axes)\n", + "wakeviz.plot_turbines_with_fi(fi, ax=axes)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Turbulence\n", + "\n", + "### Crespo-Hernandez\n", + "\n", + "CrespoHernandez is a wake-turbulence model that is used to compute additional variability introduced\n", + "to the flow field by operation of a wind turbine. Implementation of the model follows the original\n", + "formulation and limitations outlined in {cite:t}`crespo1996turbulence`." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Wake combination\n", + "\n", + "The wakes throughout the flow field need to be combined in a careful manner in order to\n", + "accurately capture their coupled effects. A simple model is to simple add them,\n", + "but this can result in negative velocities a few turbines into the farm. More careful\n", + "methods are available within FLORIS and shown here.\n", + "\n", + "Each model is described below and its effects are plotted with two turbines in a line.\n", + "These descriptions use the Jensen and Jimenez models since they highlight the differences\n", + "in the combination models themselves.\n", + "The upper plots show the turbine wakes individually to give a reference for the uncombined wake.\n", + "The lower plots show both turbines along with their wakes combined with the chosen model." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [], + "source": [ + "def combination_plot(method: str):\n", + " X_UPSTREAM = 0.0\n", + " X_DOWNSTREAM = 5 * 126.0\n", + " X0_BOUND = -200\n", + " X1_BOUND = 1500\n", + "\n", + " # Set the combination method\n", + " fi = FlorisInterface(\"../examples/inputs/jensen.yaml\")\n", + " settings = fi.floris.as_dict()\n", + " settings[\"wake\"][\"model_strings\"][\"combination_model\"] = method\n", + " fi = FlorisInterface(settings)\n", + "\n", + " # Plot two turbines individually\n", + " fig, axes = plt.subplots(1, 2, figsize=(10, 10))\n", + " fi.reinitialize(layout_x=np.array([X_UPSTREAM]), layout_y=np.zeros(1))\n", + " horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_bounds=(X0_BOUND, X1_BOUND),\n", + " yaw_angles=np.array([[[20.0]]])\n", + " )\n", + " wakeviz.visualize_cut_plane(horizontal_plane, ax=axes[0])\n", + " wakeviz.plot_turbines_with_fi(fi, ax=axes[0])\n", + " wakeviz.plot_turbines_with_fi(fi, ax=axes[1])\n", + "\n", + " fi.reinitialize(layout_x=np.array([X_DOWNSTREAM]), layout_y=np.zeros(1))\n", + " horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_bounds=(X0_BOUND, X1_BOUND),\n", + " yaw_angles=np.array([[[0.0]]])\n", + " )\n", + " wakeviz.visualize_cut_plane(horizontal_plane, ax=axes[1])\n", + " wakeviz.plot_turbines_with_fi(fi, ax=axes[0])\n", + " wakeviz.plot_turbines_with_fi(fi, ax=axes[1])\n", + "\n", + " # Plot the combination of turbines\n", + " fig, axes = plt.subplots(1, 1, figsize=(10, 10))\n", + " fi.reinitialize(layout_x=np.array([X_UPSTREAM, X_DOWNSTREAM]), layout_y=np.zeros(2))\n", + " horizontal_plane = fi.calculate_horizontal_plane(\n", + " height=90.0,\n", + " x_bounds=(X0_BOUND, X1_BOUND),\n", + " yaw_angles=np.array([[[20.0, 0.0]]])\n", + " )\n", + " wakeviz.visualize_cut_plane(horizontal_plane, ax=axes)\n", + " wakeviz.plot_turbines_with_fi(fi, ax=axes)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Freestream Linear Superposition (FLS)\n", + "\n", + "FLS uses freestream linear superposition to apply the wake velocity deficits to the freestream\n", + "flow field." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "tags": [ + "hide-input" + ] + }, + "outputs": [ + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "combination_plot(\"fls\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Max\n", + "\n", + "The MAX model incorporates the velocity deficits into the base flow field by selecting the\n", + "maximum of the two for each point. For more information, refer to {cite:t}`gunn2016limitations`." + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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xCIIi4+deoJifrHd4Zg2q19yb9wEHVfWwqhaAzwEP1ymWy/LJA3FiiRyo4rppmtvvJpXtY/TEP9Q7vHWvv7ebAwezFEt2CdHU1Jqov0x9BJQI/DlUfTQoEfh5Jsf2kp8bY3zk2XqHZ9agel367ANOVL0+CdxfvYKIPAo8CtBZpzADigTBLBr4zEwe4fzZo8QmBNfNU5gfq0tMZsHx02cpFJMA+L7PxamZhakyNKC9OVfnCOtvJl8gE1/bkz02oCvWX9AYdZipPUUJglnmZ05TmL9AKtuF62WYmzpLPNlb7/DMGtSwd7NR1cdVdY+q7mleZgLQWvDIIqJcvLCX2anj5GfPILikmzbSufEH6hKTWXD89FnisYWZ8p8/8BpHTp7h6KkzPHdg/Vya9le49vv80dM1jMRUa4Q6zNSWr4pPHnFcmjp24ft5Ji/sBZSSP4fvz9Q7RLMG1es07xTQX/V6Y1TWUErMARl6Bt+D40Gx0EJbz05cb4LZqaP1Dm/dk6qZ/V3XJZmI84Y7hhFVvvvsS3WMrLa+uf8g5yfnGews0JVL2WjSm29N1F+m9l7UcEin62TINm0l1zrM5IXn6Bp8M5NjLxAE138LNrN+1atF7Wlgm4hsFpE48AjwRJ1iuSzBRQQ0KFGYO0+uZRep7EZaOndRzE/VO7x1z3UdpmfCz2H0wjjJ+PqsBN+6fQstmSaOjY7ztb2HeOn4GUYn7cz9JloT9ZepvbskjRIQBLMUCxNMjIUDCIr5SUq+3XvVXJ+6tKipaklEPgx8mXB4+6dUdV89YllJjAR5Yojjks0OUZjvBqCYn6SlwwZ51dv2LZv4y787QKk0QzIOu3cOV5Z1d7TWMbLaSsXhB7cH5FL9FIoFzoxPcejceV48ml/xsqi5Pmul/jK154qQIEk+uh1fYW6URLqNU4e+CBTp2/JILWcNWvPy+QKF/ByOQDoRX7eThNeth6uqfgn4Ur32fzUCfIKgQH72LKXSONPjB/AmCiQzHi3tt9U7vHWvOZdl98772D50nlw6ahyO5ibbOtBX03nU6slxIJcK526Kex6Dna0MdrYyO5/n3MXpOkd3a1oL9ZepjyQOU9JKS8duXC+GF/cQ91780gSJVLtNeHsVZmeneP6Fl3GcefLz8zTlMpQKBVpbmhjetpXYOpviqGEHEzQCRXHdZpradpFt2gIakMr1k20aZG7mTL3DM5GYt75H1B0fHV+2PBWPsalz/bQsGlNvI1qkQB7VEo6zMNra9ZJ4sSyzU8frGN3aceTIAYaHb+dNP/BG7t2zm0w6zZveeD+tLS3sf2X9DBQrs0RtBW7U4Oi44VxqXryZptYd5Nq24bp2zzbTGFSF2fz6TlaNaRRKgOoMxfzEovJYoom5aTvBvxqKkk6lAWjK5ZieCfvcbujtqTxfTyxRW4GPjx91AJ2bPoUGJYr5CQrzExQLNpjANIae1nb2nuiqdxjGrHtdEsMnjkiWmanD5OdGK8tEnEUj1c3lbeyLcfrMYSYmJnjt9ddpyoVzYuo66c6ylJ2Gr8BDmSsFPPO1U8SSCYQEuGdI5yDwLVEzjWN8ZpKXj59lvhD2VUvGPLqa0nQ1ZescmTHrR1EDlDn8Up5Xn3s7qscROUEq104skUX9TpKZFpLpAHFcxBFaOwtsGArwPAFPcN1weh0vBvE4tHTU+Zeqg/vvv53jRw5z9NhxmrIZtg5tBsKJzXduH77C1qvL9332HTxKLpVgsKcDz6l9sm2J2gru5CIpDdg4eYjxyQ4OcoHSyI8wicvpplaOv9JLLOHT3lsknoQNQyXaemyU3Y24Y3hbvUNYc/afPMvZiSy7BtKkYuGZ51yhyPGxCUYnZ9jZZ61t69GQWPeMWjtMnm3M0aIn+eG5n2GWEqfIsnduOyUcetlDnCM4gAABwik2s592IGwtqp4F0cdlanAnsXi0TCTcTuHpr0IyA/1bIJaAcv96EXAFXA82DUNnT3TDFid8OE40zsoDt0FnNDp37hxbt24BQDRACO8243kezU1NNR0o5rouA71dnDo7wlMvv0pLNs22/g0kanjHF0vUVvCw28oAcbLyp0xoiXMUGZZPAvCtySTdk0McZxv7j76BAgkOfWOA13DIDw/jxYWegRJNHUpLR7Auz4qux3967FfDJ+u0ift6jE1Os73vTja0nq6Mem3NpOhtzvL3+w+HNzwy686jriXotVZA+Q/exujVDM8HM/ykk+cn+Q57dZY75FvX9H6qcPJYP1O0VMqcKKFThJNs5tDX76CAE5UsCHB4iX5KXD6hyL3jAZLJKDlUEAfy80J3r9I3CMM7wI0akJzozR0HYh70D4QtfjeDqqAaJp2NoCWXpTWb5sSZc7x69CQdLU30tNduoJYlaisYIM5BzYOGnfm2SbKybIs7SZ/sZ5j9PMgXgOhL5W/k1VfvZpYm9r28hzHSHKGFCxt2EUtAPAGZZqW1U0mkYdsuaGqFdBMk7ATYXAfXcZiau7SD7cTMHJ5rfWKMqaWiBsTEYV4DfGBeA9ywTeiaiUC/d4LFt5ZdsJ2XeXCFuZZVw4RtObNBhle+chfzpKu3QFAcAk6zmS9e5iyvRIzSO99HLMoBwxYvKs2ByZQytLVILBa+F9EiVfAcZdu2Ipu3FCsJooNTScpirs/ExGbamufIZhvnhH1sYpLTYxfYOdS/KEkrlkpMTs/QlEndtBkILFFbQVZc7pY0JVW8Jal9n1x6KhF+qU7Sz0kAfow/B8I/zpkzYV8hH5cDeg8n2cQ0LTz3V7dRwqNInOLu+4jFoX8r5JqhcwNs3g5xL0zwjFnOHQO9PPH0Kb65f4RULLz+MV8s4QrcOdBT5+iMWT96ibFP50jgkFdlqyR4Tecpogws8z/jZhMBl+W74+TcKe7lO9f93vknf4sCyWWXjQVdvM4uCktSDEEJcPhrtjBN05JloRIeufe8jb7eSfKFEfxiHkFxnTjZTBebBlrYunkekfCSqERXESQI8Fxl26ZZchk/LFPClkINWwKv1/jkNMdOn6OzpZkNne2Lls3M5Tl3YYK9h4/Tmssy3N9DMra6qZUlaldhaZJ2rUQg6y5MPPoAf3/JOnN+krPP9TNFEy889UbmyfIcvXyTZkDw3vQAmWyY9CUy0NMLg9sgmYR05obCM2tcczrFnQOD3DWYXDSYIF5uTbPLyMbURIfEaMEjT0BSHFwRWsRDVW+5e/AmnAIJCssuyzmTbObgdb1voMLzf5djFodWEsRwAaVIwDjzHKaPg3IXURtd1ZaKT4wxepdtRYwxz/2PvR0XRQNFogRWAc/xuWf7RXrb58PqUhVFEA2Yz+d5/fgZhjZkGNrYc0l9mkun2LG5H98POHDsJGMXp9i4ynfGsUStQaTceTbzOgB38mylXBVK6vHqd++o9FOYoINXuYtxSnz9bT+N64HnQd8gZKKkLdcKu+4JE7mW1hs7mzBrQyLmkfAWPmi120cZU3OeCB6LZ86/1ZK0m8kRxXPO8hYnvezyF4Mz3OXsv+z2l7vcOx60ce6/fHPZ9sU54nyRNlQWPjdBKWiBCS5SJMn9v/6v+M7zwaJ+gAQBqtCSnaezpcDYhMvYxDn2DLdd5W97dSxRa3AiEJMSdzgvLCp/F38NQPDt/8i8ppkJMuzlXuZJIShjdPBnDBLgETz4HtIZyGSVLcNKKiU4Ap09yrbbw0ursdoNYDHGGGMuyxGYVp+sLE54p9XHvULOe7nLvR3uGB2MXVMcB3UeB2Gjxgl+9+klwzVCinBBOzimaUaYJEuS5+XJa9rPlViitsY5oqRlhrQzww/xd8uuM/XV32KSVi5oJ69yFz4eoHyfbi7SjiK0/8TbaWkN/7hjcWXnHUVa28LXI+fsbNAYY0xtDJHgKAX8QIlHrZEFVVwRhqhdh+2tkiRQxXEEmGNeAxLIohbSWQ1wZRxPStxNjC6JWj1W8YKGJWrrQM6dIscUfRxnV9Vl1bJAhaOf38JFwk6SMzTxFDvJk0CAAkn2v/Qwnqt0d/t09/gIiucFDN9eoq017LiZ8CCVquVvZowx5laTEZedpCgSUIj6ocVFiNXhzg5OdVJGwCRKFzHyGnCKIgFKCochkqRvUnyWqBkcUYa8g1DV+fPNLG66LXzmP1MkzjHdyhidABSJ849sroz8KRKj99H3kUoFdHT6bB4s4BDgOsrQpjxtrT5CONWJzRphjDFmJTFxVpgFrvbaooEhvipHyXNRfbZIkna5uamUJWrmqsSdInGK7ODFy66jCuOPP06BJKfYzD/SC4CPx9d/4RcpFCRaT2lvLdKcDVAgnSixc3iGbKqEENDcFNDVXlymN4AxxhhTPyKCCwyTYpwSo5Q4FRTolzitNylhs0TNrBoRaHMvANDD6cUL//Rzlae+OpwKBpkjHKI6QxN/zVb86Nxpmibaf+ZhHCe8yN+cKzG4YQ4RxUHZOjDDxt4CaMDMrDXNGWOMqb1W8WjFYwYf5yY2LViiZmrOlYAB98iist38w6LXxb/4eGWEzbmgj7P0A+Gw639giBly0ZoORx57K9lUCYBEwmdT7yypeAlUyWZKbGifs+lJjDHG3BSZJaNTV5slaqYhxaRYed7vHqGfhcTu/iUTBs987PFKP7k50nyDgWhkK0zTTPcvvz+8PYkqiXhAb9scoDgS0NcxR2d7HoIATwLam+avOPzbGGOMqRVL1Myal3FmyBDe67KV82xYel+8/7FwL7zpIMcYHdErh71sqNzKpITHxg/9U2KuX1lfUHraZmnJ5QGIuz5DPZNkEmEiGfMCYjf3ZMoYY8w6ZomaWVeyzhRZpiqvBzi0aLn/P79IUDWruK8O59jIccJ7tRaI83/po0R4374iMe76pbfhOQu3FUl6RTb3TBD3AlClOVOgr2MGJ7rvHIT9+azhzhhjzJXcUKImIr8D/ChQAA4BH1TViWjZY8DPAz7wS6r65aj8IeAPABf4hKp+7EZiMGY1uRIsmtU6JjC4JJmDpyvPVGHmD7+w6JYlc2T5Fv2U8BCUKVro/Rc/Hq5czucUulqmcV2FANqycwx0TOI4AeqHKzWlC7Rm5m/Wr2qwOswY0/hutEXtSeAxVS2JyG8DjwG/KSI7gEeAncAG4Ksiclu0zR8BDwIngadF5AlVvfyNu4xpYCKQlelFZU1M0r101Osnv7ToZVFjnNdONErwTtDJ1+letM4sOYY+8DYcUVSVXCpPT+tMJdlTDejIzdHVPE0QWPvcdbI6zBjT0G4oUVPVr1S9fAr4yej5w8DnVDUPHBGRg8B90bKDqnoYQEQ+F61rlZxZV2JSpEcWkrleTi67nv+Zv6mMfp3QNl6P7h5R9n26GKeDNIf4nlzg3o88SDpRAML56gCak3PkUmEfO4KwLJsskPSKrHdWhxljGt1q9lH7OeAvo+d9hJVe2cmoDFjU0/skcP8qxmDMLcWVhYENHTJCByNL1jiw6NX0x57nwpJ74b1KE/OkF5XNkGPXr74TESXwlWyyQDoeJnhUErxZssnFCV4qVsKp6o93i7E6zBjTcK6YqInIV4GeZRZ9VFW/EK3zUaAEfHa1AhORR4FHATptzIMxV8WTEh6lRWXpaETsUqX//kLl+RnNUKhK8BRhmmbypColIAz/4jtxJKBy/TVQMokCzalwQuJyQpeOF2hJzVG5M3EgOKJIHa7QWh1mjFnLrlh7qOqPrLRcRH4WeC/wdi1fa4FTEM1QGtoYlbFC+dL9Pg48DrBNkrfsKbwxjSAtM5ckdK2cv2Q9/+P7KOribGucHK+RZWGkhDBLhtnKpMTRtrjc/+F7wj53Uf6WiJVoS8/gsNByGHdLNCVmb/h3KrM6zBizlt3oqM+HgN8AflBVq2vWJ4A/F5HfI+yIuw34PuGMBNtEZDNh5fYI8M9uJAZjTG05sjjnyDJJlskrbqcKFz7+MmE1EL5HnhQv01zphwdQIMEP/fqu1Qz5sqwOM8Y0uhttj/84kACelPCaxlOq+i9VdZ+I/BVhB9sS8CFV9QFE5MPAlwmHtn9KVffdYAzGmDVABJIsnm4kyTzNjF+y7rH/9kqtwrI6zBjT0GShpb9xbZOk/r43WO8wjDE19N7Sa8+q6p56x7EarA4zZn1ZzfrLblVtjDHGGNOgLFEzxhhjjGlQlqgZY4wxxjSoNdFHTURGgWN12n0HMFanfV+OxXR1LKar06gxZVS1s96BrIY61mGN+tlaTFfWiDFBY8bViDENq2ruyqtd2ZqYhbGelbWIPNNoHZotpqtjMV2dBo5pU73jWC31qsMa+LO1mK6gEWOCxoyrUWNarfeyS5/GGGOMMQ3KEjVjjDHGmAZlidqVPV7vAJZhMV0di+nqWEy3rkY8jhbT1WnEmKAx47qlY1oTgwmMMcYYY9Yja1EzxhhjjGlQlqhdhog8JCKvishBEflIDffbLyLfEJH9IrJPRH45Kv/3InJKRF6IHu+u2uaxKM5XReSdNymuoyLycrTvZ6KyNhF5UkRej362RuUiIn8YxfSSiOy+CfEMVx2LF0RkUkR+pR7HSUQ+JSIjIrK3quyaj42IfCBa/3UR+cBNiOl3ROSVaL9/KyItUfkmEZmrOmZ/UrXNG6LP/WAUtyyzuxuJ6Zo/r3p9N9caq8MuicvqsOXjsPrr+mOqTf2lqvZY8iC82fIhYAiIAy8CO2q0715gd/Q8B7wG7AD+PfBry6y/I4ovAWyO4nZvQlxHgY4lZf8V+Ej0/CPAb0fP3w38P0CAB4Dv1eDzOgsM1uM4AW8FdgN7r/fYAG3A4ehna/S8dZVjegfgRc9/uyqmTdXrLXmf70dxShT3u1Y5pmv6vOr53VxLD6vDlo3L6rDl92311/XHVJP6y1rUlncfcFBVD6tqAfgc8HAtdqyqZ1T1uej5FHAA6Fthk4eBz6lqXlWPAAcJ46+Fh4FPR88/DbyvqvwzGnoKaBGR3psYx9uBQ6q60oSiN+04qeq3gAvL7O9ajs07gSdV9YKqjgNPAg+tZkyq+hVVLUUvnwI2rvQeUVxNqvqUhrXPZ6p+j1WJaQWX+7zq9t1cY6wOuzrrvg6z+uv6Y1rBqtZflqgtrw84UfX6JCtXNDeFiGwC7gG+FxV9OGr2/VS5KZraxarAV0TkWRF5NCrrVtUz0fOzQHeNYyp7BPiLqtf1PE5l13psah3fzxGeYZZtFpHnReSbIvKWqlhP1iCma/m8GuK7uQY0xHGyOuyqNVodZvXX1bvp9Zclag1KRLLA54FfUdVJ4I+BLcDdwBngd2sc0ptVdTfwLuBDIvLW6oXRGUvNhxCLSBz4MeD/REX1Pk6XqNexuRwR+ShQAj4bFZ0BBlT1HuBXgT8XkaYahdNwn5dZHVaHXZ1Gr8Os/lpRTT4rS9SWdwror3q9MSqrCRGJEVZwn1XVvwFQ1XOq6qtqAPwvFpq8axKrqp6Kfo4Afxvt/1z5ckD0c6SWMUXeBTynquei+Op6nKpc67GpSXwi8rPAe4GfiSpgoub589HzZwn7UNwW7b/68sKqx3Qdn1ddv5triNVhS1gddk2s/roKtaq/LFFb3tPANhHZHJ3tPAI8UYsdR6NSPgkcUNXfqyqv7h/x40B55MkTwCMikhCRzcA2wg6UqxlTRkRy5eeEnTr3Rvsuj+75APCFqpjeH40QegC4WNWMvtp+mqpLBvU8Tktc67H5MvAOEWmNms/fEZWtGhF5CPgN4MdUdbaqvFNE3Oj5EOGxORzFNSkiD0R/l++v+j1WK6Zr/bzq9t1cY6wOWxyT1WHXxuqvq4upNvWX3sSRLGv5QTi65TXC7PyjNdzvmwmbmV8CXoge7wb+N/ByVP4E0Fu1zUejOF/lBka1rBDTEOHolBeBfeXjAbQDXwNeB74KtEXlAvxRFNPLwJ6bdKwywHmguaqs5seJsJI9AxQJ+xz8/PUcG8J+FwejxwdvQkwHCftHlP+u/iRa9yeiz/UF4DngR6veZw9h5XMI+DjRJNmrGNM1f171+m6utYfVYYtisjrs8jFY/XX9MdWk/rI7ExhjjDHGNCi79GmMMcYY06AsUTPGGGOMaVCWqBljjDHGNChL1IwxxhhjGpQlasYYY4wxDcoSNWOMMcaYBmWJmjHGGGNMg7JEzRhjjDGmQf1/ZfoFWLu2cG0AAAAASUVORK5CYII=", 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", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "combination_plot(\"max\")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Sum of Squares Freestream Superposition (SOSFS)\n", + "\n", + "This model combines the wakes via a sum of squares of the new wake to add and the existing\n", + "flow field." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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