{
"cells": [
{
"cell_type": "markdown",
"id": "f3e3d083",
"metadata": {},
"source": [
"# Dynamic Derivatives Using Sliding Interfaces\n",
"\n",
"This notebook demonstrates how to obtain **dynamic stability derivatives** by simulating unsteady flow over a NACA0012 wing that pitches back and forth within a **sliding interface**.\n",
"\n",
"### Geometry\n",
"The wing geometry has:\n",
"- **Chord** $c$ = 1 m\n",
"- **Span** $b$ = 2 m \n",
"- **Reference area** $A_{ref}$ = 2 m²\n",
"- **Moment length** = [$b$/2, $c$, $b$/2] = [1, 1, 1] m\n",
"- **Moment center** = [0, 0, 0] (at quarter-chord, midspan)\n",
"\n",
"\n",
"### Simulation Strategy\n",
"**Steady Initialization:**\n",
"- Ramp CFL from 1 to 100 over 1000 steps for robust convergence\n",
"- Fixed sliding interface (zero angular velocity) to establish baseline flow\n",
"- Maximum 10000 steps to ensure convergence\n",
"\n",
"**Unsteady Oscillation:**\n",
"- Sliding interface updated to oscillating motion\n",
"- Sinusoidal pitching with amplitude 2° and frequency 2.5 flowthru/rad\n",
"- 400 time steps (4 complete cycles)\n",
"\n",
"**Note:** The settings in this example are by no means a validation setup; they are crafted to showcase the capabilities of Flow360 and we have intentionally reduced node count and example FC cost. For rigorous validation, modify the settings as needed."
]
},
{
"cell_type": "markdown",
"id": "2975873a",
"metadata": {},
"source": [
"## 1. Download tutorial files"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "9e2d9175",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:17:20.316960Z",
"iopub.status.busy": "2026-07-14T10:17:20.316843Z",
"iopub.status.idle": "2026-07-14T10:17:20.739481Z",
"shell.execute_reply": "2026-07-14T10:17:20.739058Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:17:20] INFO: The file (geometry.csm) is being downloaded, please wait. \n"
]
}
],
"source": [
"import math\n",
"import flow360 as fl\n",
"from flow360.examples import TutorialDynamicDerivatives\n",
"\n",
"TutorialDynamicDerivatives.get_files()"
]
},
{
"cell_type": "markdown",
"id": "f6955b20",
"metadata": {},
"source": [
"The downloaded files include the geometry (CSM format) for the NACA0012 wing."
]
},
{
"cell_type": "markdown",
"id": "a8f48cc8",
"metadata": {},
"source": [
"## 2. Create project from geometry"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "94607f9b",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:17:20.741104Z",
"iopub.status.busy": "2026-07-14T10:17:20.741012Z",
"iopub.status.idle": "2026-07-14T10:18:16.349249Z",
"shell.execute_reply": "2026-07-14T10:18:16.348801Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:17:21] WARNING: DeprecationWarning: `length_unit` was not specified and \n",
" defaults to 'm'. Relying on this default is deprecated and will be \n",
" removed in a future release; specify the length unit of your \n",
" geometry/mesh explicitly to avoid silent unit/scale mistakes. \n"
]
},
{
"data": {
"text/html": [
"\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:17:37] INFO: Geometry successfully submitted: \n",
" type = Geometry \n",
" name = Dynamic Derivatives Using Sliding Interfaces \n",
" id = geo-e104cd6c-c836-4363-bd81-514b205aa45b \n",
" status = uploaded \n",
" project id = prj-daa8942a-c114-49de-8cfa-3501bb8d25c2 \n",
" \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
" INFO: Waiting for geometry to be processed. \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[?25l"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[?25h"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:18:16] INFO: Regrouping face entities under `faceName` tag (previous \n",
" `faceId`). \n"
]
}
],
"source": [
"project = fl.Project.from_geometry(\n",
" TutorialDynamicDerivatives.geometry,\n",
" name=\"Dynamic Derivatives Using Sliding Interfaces\",\n",
")\n",
"geometry = project.geometry\n",
"geometry.group_faces_by_tag(\"faceName\")"
]
},
{
"cell_type": "markdown",
"id": "9d3c384c",
"metadata": {},
"source": [
"The wing is enclosed in a cylindrical sliding interface as shown below:\n",
"\n",
"\n",
"\n",
"*Figure: Wing enclosed in cylindrical sliding interface. The interface rotates about the y-axis, causing the wing to pitch.*"
]
},
{
"cell_type": "markdown",
"id": "291b9eab",
"metadata": {},
"source": [
"## 3. Define sliding interface and meshing parameters\n",
"\n",
"The wing is enclosed in a cylindrical sliding interface:\n",
"- **Radius** = 1.0 m\n",
"- **Height** = 2.5 m\n",
"- **Rotation center** = [0, 0, 0]\n",
"- **Rotation axis** = y-axis [0, 1, 0]"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "fa7349a6",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:16.350947Z",
"iopub.status.busy": "2026-07-14T10:18:16.350855Z",
"iopub.status.idle": "2026-07-14T10:18:16.354895Z",
"shell.execute_reply": "2026-07-14T10:18:16.354619Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" INFO: using: SI unit system for unit inference. \n"
]
}
],
"source": [
"with fl.SI_unit_system:\n",
" cylinder = fl.Cylinder(\n",
" name=\"cylinder\",\n",
" axis=[0, 1, 0],\n",
" center=[0, 0, 0],\n",
" inner_radius=0,\n",
" outer_radius=1.0,\n",
" height=2.5,\n",
" )\n",
" sliding_interface = fl.RotationVolume(\n",
" spacing_axial=0.04,\n",
" spacing_radial=0.04,\n",
" spacing_circumferential=0.04,\n",
" entities=cylinder,\n",
" enclosed_entities=geometry[\"wing\"],\n",
" )\n",
" farfield = fl.AutomatedFarfield(name=\"farfield\")"
]
},
{
"cell_type": "markdown",
"id": "768ab93d",
"metadata": {},
"source": [
"Key meshing parameters:\n",
"- Automated meshing with sliding interface and farfield zones\n",
"- Refined leading and trailing edges for accuracy\n",
"- Boundary layer resolved with first layer thickness of 1e-6 m"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "da9fadb9",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:16.356068Z",
"iopub.status.busy": "2026-07-14T10:18:16.355986Z",
"iopub.status.idle": "2026-07-14T10:18:16.362727Z",
"shell.execute_reply": "2026-07-14T10:18:16.362439Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" INFO: using: SI unit system for unit inference. \n"
]
}
],
"source": [
"with fl.SI_unit_system:\n",
" meshing_params = fl.MeshingParams(\n",
" defaults=fl.MeshingDefaults(\n",
" surface_max_edge_length=0.03 * fl.u.m,\n",
" curvature_resolution_angle=8 * fl.u.deg,\n",
" surface_edge_growth_rate=1.15,\n",
" boundary_layer_first_layer_thickness=1e-6,\n",
" boundary_layer_growth_rate=1.15,\n",
" ),\n",
" refinement_factor=1.0,\n",
" volume_zones=[sliding_interface, farfield],\n",
" refinements=[\n",
" fl.SurfaceEdgeRefinement(\n",
" name=\"leadingEdge\",\n",
" method=fl.AngleBasedRefinement(value=1 * fl.u.degree),\n",
" edges=geometry[\"leadingEdge\"],\n",
" ),\n",
" fl.SurfaceEdgeRefinement(\n",
" name=\"trailingEdge\",\n",
" method=fl.HeightBasedRefinement(value=0.001),\n",
" edges=geometry[\"trailingEdge\"],\n",
" ),\n",
" ],\n",
" )"
]
},
{
"cell_type": "markdown",
"id": "10bec194",
"metadata": {},
"source": [
"## 4. Run steady case to initialize the flow field\n",
"\n",
"First, we run a steady case with a fixed sliding interface (zero angular velocity) to initialize the flow field. This provides a converged solution to start the unsteady simulation."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "b849b8e9",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:16.364026Z",
"iopub.status.busy": "2026-07-14T10:18:16.363943Z",
"iopub.status.idle": "2026-07-14T10:18:19.882085Z",
"shell.execute_reply": "2026-07-14T10:18:19.881463Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" INFO: using: SI unit system for unit inference. \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[?25l"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[?25h"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:18:19] INFO: Successfully submitted: \n",
" type = Case \n",
" name = Tutorial Dynamic Derivatives - Steady \n",
" Initialization \n",
" id = case-d266cafa-fc81-4f7b-9314-bc5c1216a737 \n",
" status = pending \n",
" project id = prj-daa8942a-c114-49de-8cfa-3501bb8d25c2 \n",
" \n"
]
}
],
"source": [
"with fl.SI_unit_system:\n",
" params = fl.SimulationParams(\n",
" meshing=meshing_params,\n",
" reference_geometry=fl.ReferenceGeometry(\n",
" moment_center=[0, 0, 0],\n",
" moment_length=[1, 1, 1],\n",
" area=2,\n",
" ),\n",
" operating_condition=fl.AerospaceCondition(\n",
" velocity_magnitude=50,\n",
" ),\n",
" time_stepping=fl.Steady(\n",
" max_steps=10000,\n",
" CFL=fl.RampCFL(initial=1, final=100, ramp_steps=1000),\n",
" ),\n",
" outputs=[\n",
" fl.VolumeOutput(name=\"VolumeOutput\", output_fields=[\"Mach\"]),\n",
" fl.SurfaceOutput(\n",
" name=\"SurfaceOutput\",\n",
" surfaces=geometry[\"*\"],\n",
" output_fields=[\"Cp\", \"CfVec\"],\n",
" ),\n",
" ],\n",
" models=[\n",
" fl.Rotation(\n",
" volumes=cylinder,\n",
" spec=fl.AngularVelocity(0 * fl.u.rad / fl.u.s),\n",
" ),\n",
" fl.Freestream(surfaces=farfield.farfield, name=\"Freestream\"),\n",
" fl.Wall(surfaces=geometry[\"wing\"], name=\"NoSlipWall\"),\n",
" fl.Fluid(\n",
" navier_stokes_solver=fl.NavierStokesSolver(\n",
" absolute_tolerance=1e-9,\n",
" linear_solver=fl.LinearSolver(max_iterations=35),\n",
" ),\n",
" turbulence_model_solver=fl.SpalartAllmaras(\n",
" absolute_tolerance=1e-8,\n",
" linear_solver=fl.LinearSolver(max_iterations=25),\n",
" ),\n",
" ),\n",
" ],\n",
" )\n",
"\n",
"project.run_case(params=params, name=\"Tutorial Dynamic Derivatives - Steady Initialization\")\n",
"\n",
"steady_case = fl.Case.from_cloud(project.case.id)"
]
},
{
"cell_type": "markdown",
"id": "cc628979",
"metadata": {},
"source": [
"## 5. Understanding the Oscillation Setup\n",
"\n",
"The sliding interface oscillates according to the angle expression:\n",
"\n",
"$$\\theta = A \\sin(\\omega_\\text{non-dim} \\cdot t_\\text{non-dim})$$\n",
"\n",
"Where:\n",
"- $A$ = 0.0349066 rad (equivalent to 2°) - amplitude of oscillation\n",
"- $\\omega_\\text{non-dim}$ = nondimensional angular frequency\n",
"- $t_\\text{non-dim}$ = nondimensional time\n",
"\n",
"**Calculating the nondimensional frequency:**\n",
"\n",
"We want the wing to complete one oscillation cycle over a specific number of flowthroughs. In this example, we use $n$ = 2.5 flowthru/rad, meaning when $\\omega \\cdot t$ changes by 1 radian, the air flows through 2.5 chord lengths.\n",
"\n",
"Given:\n",
"- Freestream velocity $U_\\infty$ = 50 m/s\n",
"- Chord $c$ = 1 m\n",
"- Speed of sound $C_\\infty$ = 340.294 m/s\n",
"- Grid unit $L_\\text{gridUnit}$ = 1 m\n",
"\n",
"Physical angular frequency:\n",
"$$\\omega_{physical} = \\frac{U_\\infty}{n \\cdot c} = \\frac{50}{2.5 \\times 1} = 20 \\text{ rad/s}$$\n",
"\n",
"Nondimensional angular frequency:\n",
"$$\\omega = \\frac{\\omega_{physical}}{C_\\infty / L_{gridUnit}} = \\frac{20}{340.294} \\approx 0.05877271$$\n",
"\n",
"**Time step size:**\n",
"\n",
"We split each oscillation period into 100 steps:\n",
"$$\\Delta t = 0.01 \\cdot \\frac{2\\pi}{\\omega} \\approx 0.01 \\cdot \\frac{2\\pi}{0.05877271}$$"
]
},
{
"cell_type": "markdown",
"id": "1d87d576",
"metadata": {},
"source": [
"## 6. Run unsteady case with oscillating interface\n",
"\n",
"Now we update the simulation parameters for the unsteady case and fork from the steady solution. Only the time stepping and rotation spec need to be modified."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "mns0hslu80b",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:19.884026Z",
"iopub.status.busy": "2026-07-14T10:18:19.883917Z",
"iopub.status.idle": "2026-07-14T10:18:22.925836Z",
"shell.execute_reply": "2026-07-14T10:18:22.925227Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" INFO: using: SI unit system for unit inference. \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[?25l"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[?25h"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:18:22] INFO: Successfully submitted: \n",
" type = Case \n",
" name = Tutorial Dynamic Derivatives - Unsteady \n",
" Oscillation \n",
" id = case-6f74399f-02cc-4dcc-aef9-b6cae60be38d \n",
" status = pending \n",
" project id = prj-daa8942a-c114-49de-8cfa-3501bb8d25c2 \n",
" \n"
]
}
],
"source": [
"# Update parameters for unsteady case\n",
"with fl.SI_unit_system:\n",
" params.time_stepping = fl.Unsteady(\n",
" max_pseudo_steps=80,\n",
" steps=400,\n",
" step_size=0.01 * 2.0 * math.pi / 20.0 * fl.u.s,\n",
" CFL=fl.RampCFL(initial=1, final=1e8, ramp_steps=20),\n",
" )\n",
" params.models[0].spec = fl.AngleExpression(\"0.0349066 * sin(0.05877271 * t)\")\n",
"\n",
"# Run unsteady case forked from steady solution\n",
"project.run_case(\n",
" params=params,\n",
" name=\"Tutorial Dynamic Derivatives - Unsteady Oscillation\",\n",
" fork_from=steady_case,\n",
")\n",
"unsteady_case = project.case"
]
},
{
"cell_type": "markdown",
"id": "654e33dd",
"metadata": {},
"source": [
"## 7. Postprocessing - Extract Dynamic Derivatives\n",
"\n",
"Once the simulation is complete, we download the results and calculate the dynamic derivatives. The key output is the `total_forces` data which contains force and moment coefficients at each time step."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "8a53583d",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:22.927837Z",
"iopub.status.busy": "2026-07-14T10:18:22.927734Z",
"iopub.status.idle": "2026-07-14T10:18:35.217942Z",
"shell.execute_reply": "2026-07-14T10:18:35.217378Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:18:23] INFO: Copy operation started for project \n",
" prj-b674e3dd-3515-4e2b-983b-15924d4ebf36. Waiting for completion... \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[?25l"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[?25h"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:18:30] INFO: Copy operation completed successfully. \n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\u001b[?25l"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[?25h"
]
},
{
"data": {
"text/html": [
"\n"
],
"text/plain": []
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"[12:18:35] INFO: Saved to total_forces.csv \n"
]
}
],
"source": [
"import flow360 as fl\n",
"import numpy as np\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"\n",
"cmap = plt.colormaps[\"tab10\"]\n",
"\n",
"# Load completed example case from the example library (flow360 25.8 or above).\n",
"# Use the exact example title: `by_name` fuzzy-matches, and a shorter query like\n",
"# \"Dynamic Derivatives\" can resolve to a different example (e.g. \"SDM Dynamic\n",
"# Pitch Damping Derivative\").\n",
"project = fl.Project.from_example(\n",
" by_name=\"Calculating Dynamic Derivatives using Sliding Interfaces\"\n",
")\n",
"case = project.get_case()\n",
"\n",
"# Note that in this example we're loading a pre-computed unsteady case from the example library,\n",
"# so the reader doesn't need to wait for the simulation to finish.\n",
"# For production usage, the user can use:\n",
"# case = unsteady_case\n",
"# or:\n",
"# case = fl.Case.from_cloud(\"your-case-id\")\n",
"\n",
"# Download and load results\n",
"case.results.total_forces.download(to_file=\"total_forces.csv\")\n",
"case.results.total_forces.load_from_local(\"total_forces.csv\")\n",
"total_forces = case.results.total_forces.as_dataframe()"
]
},
{
"cell_type": "markdown",
"id": "15ee4d05",
"metadata": {},
"source": [
"### Extract unique physical steps\n",
"\n",
"The `total_forces` data contains multiple rows per physical step (one per pseudo-step). We extract the final converged value at each physical step."
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "90417cd6",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:35.220042Z",
"iopub.status.busy": "2026-07-14T10:18:35.219835Z",
"iopub.status.idle": "2026-07-14T10:18:35.264037Z",
"shell.execute_reply": "2026-07-14T10:18:35.263639Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of physical steps: 400\n"
]
}
],
"source": [
"def extract_unique_physical_steps(input_df):\n",
" \"\"\"Extract the row at the last pseudo step at the end of each physical step.\"\"\"\n",
" physical_steps_raw = input_df[\"physical_step\"]\n",
" n_rows = len(physical_steps_raw)\n",
" selected_row_index = []\n",
" for i in range(n_rows - 1):\n",
" if physical_steps_raw.iloc[i + 1] > physical_steps_raw.iloc[i]:\n",
" selected_row_index.append(i)\n",
" selected_row_index.append(n_rows - 1)\n",
" output = pd.DataFrame()\n",
" for k, v in input_df.items():\n",
" output[k] = [v.iloc[j] for j in selected_row_index]\n",
" return output.reset_index(drop=True)\n",
"\n",
"\n",
"total_forces = extract_unique_physical_steps(total_forces)\n",
"print(f\"Number of physical steps: {len(total_forces)}\")"
]
},
{
"cell_type": "markdown",
"id": "a11af986",
"metadata": {},
"source": [
"### Calculate nondimensional time, angle of attack, and pitch rate\n",
"\n",
"We compute:\n",
"- Nondimensional time from physical steps\n",
"- Angle of attack $\\alpha = A \\sin(\\omega t)$\n",
"- Pitch rate $\\dot{\\alpha}$ using central differences, converted to rad/flowthru"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f70ff057",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:35.265480Z",
"iopub.status.busy": "2026-07-14T10:18:35.265391Z",
"iopub.status.idle": "2026-07-14T10:18:36.294513Z",
"shell.execute_reply": "2026-07-14T10:18:36.294050Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found 7 points where alpha = 0\n"
]
}
],
"source": [
"# Define simulation parameters\n",
"length_unit = case.params.private_attribute_asset_cache.project_length_unit # m\n",
"U_inf = case.params.operating_condition.velocity_magnitude # m/s\n",
"C_inf = 340.29400580821283 * fl.u.m / fl.u.s # speed of sound\n",
"n_chord_per_period = 2.5 # flowthru/rad\n",
"chord = 1 * fl.u.m\n",
"\n",
"omega_physical = U_inf / (n_chord_per_period * chord) # 1/s\n",
"omega_nondim = omega_physical / (C_inf / length_unit)\n",
"time_step_size_nondim = 0.01 * 2 * np.pi / omega_nondim # nondim\n",
"\n",
"amplitude_deg = 2 * fl.u.deg\n",
"amplitude_rad = amplitude_deg.to(fl.u.rad)\n",
"\n",
"\n",
"def compute_time_nondim(df):\n",
" \"\"\"Compute nondimensional time from physical step.\"\"\"\n",
" n_steps = len(df[\"physical_step\"])\n",
" df[\"time_nondim\"] = np.zeros(n_steps)\n",
" for i in range(n_steps):\n",
" df.loc[i, \"time_nondim\"] = time_step_size_nondim * (df.loc[i, \"physical_step\"] + 1)\n",
"\n",
"\n",
"def compute_alpha_dot(df):\n",
" \"\"\"Compute angle of attack and pitch rate.\"\"\"\n",
" n_steps = len(df[\"physical_step\"])\n",
" df[\"alpha\"] = np.zeros(n_steps)\n",
" df[\"alpha_dot\"] = np.zeros(n_steps)\n",
" alpha_eq_0_index = []\n",
"\n",
" # Compute alpha\n",
" for i in range(n_steps):\n",
" t = df.loc[i, \"time_nondim\"]\n",
" df.loc[i, \"alpha\"] = amplitude_rad * np.sin(omega_nondim * t)\n",
"\n",
" # Compute alpha_dot using central difference\n",
" for i in range(1, n_steps - 1):\n",
" df.loc[i, \"alpha_dot\"] = (\n",
" (df.loc[i + 1, \"alpha\"] - df.loc[i - 1, \"alpha\"])\n",
" / (2 * time_step_size_nondim)\n",
" * C_inf\n",
" / length_unit\n",
" * chord\n",
" / U_inf\n",
" )\n",
" if abs(df.loc[i, \"alpha\"]) < 1e-10:\n",
" alpha_eq_0_index.append(i)\n",
"\n",
" return alpha_eq_0_index\n",
"\n",
"\n",
"compute_time_nondim(total_forces)\n",
"alpha_eq_0_index = compute_alpha_dot(total_forces)\n",
"print(f\"Found {len(alpha_eq_0_index)} points where alpha = 0\")"
]
},
{
"cell_type": "markdown",
"id": "dd6feef9",
"metadata": {},
"source": [
"### Plot time history\n",
"\n",
"Plot the time history of the pitch moment coefficient $C_{My}$, angle of attack $\\alpha$, and pitch rate $\\dot{\\alpha}$. The blue and red dots mark the points where $\\alpha = 0$ (extrema of $\\dot{\\alpha}$)."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "1966b5c6",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:36.295779Z",
"iopub.status.busy": "2026-07-14T10:18:36.295690Z",
"iopub.status.idle": "2026-07-14T10:18:36.566139Z",
"shell.execute_reply": "2026-07-14T10:18:36.565684Z"
}
},
"outputs": [
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"def plot_time_history(df, alpha_eq_0_idx):\n",
" _, axs = plt.subplots(3, figsize=(10, 8))\n",
"\n",
" # Time history of CMy\n",
" axs[0].plot(df[\"physical_step\"], df[\"CMy\"], color=cmap.colors[0])\n",
" axs[0].set_yticks(np.linspace(-0.02, 0.02, 5))\n",
" axs[0].set_ylim([-0.02, 0.02])\n",
" axs[0].set_ylabel(\"CMy\")\n",
"\n",
" # Time history of alpha\n",
" axs[1].plot(df[\"physical_step\"], df[\"alpha\"], color=cmap.colors[1])\n",
" axs[1].set_ylabel(r\"$\\alpha$ (rad)\")\n",
"\n",
" # Time history of alpha_dot\n",
" axs[2].plot(df[\"physical_step\"][1:-2], df[\"alpha_dot\"][1:-2], color=cmap.colors[2])\n",
" axs[2].set_ylabel(r\"$\\dot{\\alpha}$ (rad/flowthru)\")\n",
" axs[2].set_xlabel(\"physical_step\")\n",
"\n",
" for ax in axs:\n",
" ax.label_outer()\n",
" ax.grid()\n",
"\n",
" # Mark alpha=0 points (blue for min alpha_dot, red for max alpha_dot)\n",
" for i in alpha_eq_0_idx:\n",
" color = \"b\" if df[\"alpha_dot\"][i] < 0 else \"r\"\n",
" axs[0].plot(df[\"physical_step\"][i], df[\"CMy\"][i], \"o\", color=color)\n",
" axs[1].plot(df[\"physical_step\"][i], df[\"alpha\"][i], \"o\", color=color)\n",
" axs[2].plot(df[\"physical_step\"][i], df[\"alpha_dot\"][i], \"o\", color=color)\n",
"\n",
" axs[0].set_title(\n",
" r\"Time History of CMy, $\\alpha$ and $\\dot{\\alpha}$\"\n",
" + \"\\n\"\n",
" + f\"flowthru/rad={n_chord_per_period:.1f}, amplitude={amplitude_deg:.1f}\"\n",
" )\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
"\n",
"plot_time_history(total_forces, alpha_eq_0_index)"
]
},
{
"cell_type": "markdown",
"id": "e915efb0",
"metadata": {},
"source": [
"### Extract dynamic derivative\n",
"\n",
"Plot $C_{My}$ vs $\\dot{\\alpha}$ for the last oscillation period and compute the dynamic derivative $\\frac{dC_{My}}{dq}$ from linear regression at $\\alpha = 0$."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "d451bb98",
"metadata": {
"execution": {
"iopub.execute_input": "2026-07-14T10:18:36.567876Z",
"iopub.status.busy": "2026-07-14T10:18:36.567672Z",
"iopub.status.idle": "2026-07-14T10:18:36.672265Z",
"shell.execute_reply": "2026-07-14T10:18:36.671894Z"
}
},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Dynamic derivative: dCMy/dq = -0.514\n"
]
}
],
"source": [
"def plot_CMy_vs_q(df, alpha_eq_0_idx):\n",
" plt.figure(figsize=(8, 6))\n",
"\n",
" # Plot CMy versus alpha_dot for the last period\n",
" n_steps = len(df[\"physical_step\"])\n",
" begin = n_steps - 201\n",
" end = n_steps - 1\n",
" alpha_dot = df.loc[begin:end, \"alpha_dot\"]\n",
" CMy = df.loc[begin:end, \"CMy\"]\n",
" plt.plot(alpha_dot, CMy, \".\")\n",
"\n",
" # Extract alpha=0 points in the last period\n",
" x = []\n",
" y = []\n",
" for i in alpha_eq_0_idx:\n",
" if i >= begin and i <= end:\n",
" x.append(df.loc[i, \"alpha_dot\"])\n",
" y.append(df.loc[i, \"CMy\"])\n",
"\n",
" # Mark the alpha=0 points\n",
" plt.plot(x[0], y[0], \"o\", color=\"r\", markersize=10)\n",
" plt.plot(x[1], y[1], \"o\", color=\"b\", markersize=10)\n",
"\n",
" # Linear regression through alpha=0 points\n",
" coef = np.polyfit(x, y, 1)\n",
" func = np.poly1d(coef)\n",
" x_line = np.linspace(-0.02, 0.02, 101)\n",
" plt.plot(x_line, func(x_line), \"--\", label=f\"slope = {coef[0]:.3f}\", color=\"k\")\n",
"\n",
" # Formatting\n",
" plt.xlabel(r\"$\\dot{\\alpha} = q$ (deg/flowthru)\")\n",
" plt.ylabel(\"CMy\")\n",
" plt.ylim([-0.02, 0.02])\n",
" plt.yticks(np.linspace(-0.02, 0.02, 5))\n",
" plt.grid()\n",
" plt.legend(loc=\"lower left\")\n",
" plt.title(\n",
" f\"Dynamic Derivative dCMy/dq\\nflowthru/rad={n_chord_per_period:.1f}, amplitude={amplitude_deg:.1f}\"\n",
" )\n",
"\n",
" # Set x-axis to deg/flowthru\n",
" tick_locations = np.linspace(-1, 1, 5) / 180 * np.pi\n",
" ax = plt.gca()\n",
" ax.set_xticks(tick_locations, [f\"{loc * 180 / np.pi:.1f}\" for loc in tick_locations])\n",
"\n",
" # Add text annotations\n",
" ax.text(\n",
" -0.016,\n",
" 0.01,\n",
" r\"$\\alpha = 0$\" + \"\\n\" + r\"min $\\dot{\\alpha}$\",\n",
" fontsize=14,\n",
" color=\"b\",\n",
" )\n",
" ax.text(\n",
" +0.012,\n",
" -0.014,\n",
" r\"$\\alpha = 0$\" + \"\\n\" + r\"max $\\dot{\\alpha}$\",\n",
" fontsize=14,\n",
" color=\"r\",\n",
" )\n",
"\n",
" plt.tight_layout()\n",
" plt.show()\n",
"\n",
" print(f\"\\nDynamic derivative: dCMy/dq = {coef[0]:.3f}\")\n",
"\n",
"\n",
"plot_CMy_vs_q(total_forces, alpha_eq_0_index)"
]
},
{
"cell_type": "markdown",
"id": "276324b9",
"metadata": {},
"source": [
"## Summary\n",
"\n",
"This notebook demonstrated the complete workflow for calculating dynamic derivatives using Flow360:\n",
"\n",
"1. **Download Tutorial Files**: Obtained the NACA0012 wing geometry (CSM format)\n",
"2. **Create Project**: Set up a Flow360 project from the geometry\n",
"3. **Define Sliding Interface and Meshing**: Configured the cylindrical sliding interface enclosing the wing, farfield zone, and mesh refinements\n",
"4. **Run Steady Case**: Initialized the flow field with a fixed sliding interface (zero angular velocity)\n",
"5. **Understanding Oscillation Setup**: Calculated nondimensional frequency and time step for sinusoidal pitching motion\n",
"6. **Run Unsteady Case**: Forked from steady solution and ran 400 time steps (4 complete cycles) with oscillating interface\n",
"7. **Postprocessing**: Extracted dynamic derivatives from force history\n",
" - Extracted unique physical steps from force history\n",
" - Computed angle of attack $\\alpha$ and pitch rate $\\dot{\\alpha}$\n",
" - Extracted dynamic derivative from linear fit at $\\alpha = 0$\n",
"\n",
"**Key Result**: The dynamic pitching moment derivative is approximately:\n",
"$$\\frac{dC_{My}}{d\\dot{\\alpha}} = \\frac{dC_{My}}{dq} \\approx -0.5$$\n",
"\n",
"This derivative is critical for:\n",
"- Flight dynamics modeling\n",
"- Stability and control analysis\n",
"- Control system design\n",
"- Aircraft certification"
]
}
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