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Commit 70e0f4ed authored by Hkorb's avatar Hkorb
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add example script with wifi

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Python/actuator_line_with_wifi/NREL5MW.cd 0 → 100644
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Python/actuator_line_with_wifi/NREL5MW.geo 0 → 100644
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2.8667 13.308 3.542 1
5.6 13.308 3.854 1
8.3333 13.308 4.167 1
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61.6333 0.106 1.419 0.18
63.00 0.000 0.878 0.18
Python/actuator_line_with_wifi/NREL5MW.json 0 → 100644
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{
"generator":
{
"rated_speed": 122.9,
"rated_torque": 43093.55,
"max_torque": 44748,
"max_torque_rate": 15000,
"efficiency": 0.944,
"slip": 0.1
},
"gearbox":
{
"ratio": 97
},
"blade":
{
"tip_radius": 63,
"inertia": 11776047,
"mass": 17740,
"file_format": "standard",
"standard_dict": {
"geometry_file": "NREL5MW.geo",
"cl_file": "NREL5MW.cl",
"cd_file": "NREL5MW.cd"
},
"openfast_dict": {
"input_file": "OpenFASTCoupled/NREL5MW.fst"
},
"max_pitch_rate": 8,
"root_radius": 1.5
},
"number_of_blades_per_turbine": 3
}
\ No newline at end of file
Python/actuator_line_with_wifi/SingleTurbine.json 0 → 100644
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{
"turbine_model": {
"name": "NREL5MW",
"file": "NREL5MW.json",
"file_type": "json"
},
"controller": {
"name": "NREL5MWController",
"type": "Greedy",
"file": "GreedyController.json",
"file_type": "json"
},
"hub_positions": [[0,0,0]]
}
\ No newline at end of file
Python/actuator_line_with_wifi/configActuatorLine.txt 0 → 100644
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##################################################
#information for Writing
##################################################
Path = ./output/
##################################################
#informationsfor reading
##################################################
GridPath = .
##################################################
Devices = 0
##################################################
tStartOut = 0
tOut = 300
tEnd = 600
##################################################
tStartAveraging = 0
tStartTmpAveraging = 300
tAveraging = 200
tStartOutProbe = 0
tOutProbe = 100
##################################################
Ma = 0.1
nodesPerDiameter = 32
velocity = 9
bodyForce = true
SGSconstant = 0.333333
TurbulenceModel = QR
QuadricLimiterP = 10000.0
QuadricLimiterD = 10000.0
QuadricLimiterM = 10000.0
##################################################
readPrecursor = false
nTimestepsReadPrecursor = 1
precursorFile = precursor/Precursor
##################################################
NumberOfNodesPerAL = 32
Python/actuator_line_with_wifi/controller.json 0 → 100644
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{
"filter_frequency": 0.25,
"regions":
[
{
"name": 1,
"min_speed": "-Inf",
"max_speed": 70,
"torque":
{
"mode": "zero"
}
},
{
"name": 1.5,
"min_speed": 70,
"max_speed": 91.3,
"torque":
{
"mode": "linear",
"kappa": 912.7,
"x_0": 70
}
},
{
"name": 2,
"min_speed": 91.3,
"max_speed": 120,
"torque":
{
"mode": "quadratic",
"kappa": 2.332287
}
},
{
"name": 2.5,
"min_speed": 120,
"max_speed": 122.9,
"min_pitch": "-Inf",
"max_pitch": 1,
"torque":
{
"mode": "linear",
"kappa": 4333,
"x_0": 111.3
}
},
{
"name": 3,
"min_speed": 0,
"max_speed": "Inf",
"min_pitch": 0,
"max_pitch": 90,
"pitch":
{
"mode": "PI",
"kappa_p": 0.01882681,
"kappa_i": 0.008068634,
"theta_k": 6.302336
},
"torque":
{
"mode": "inverse",
"kappa": 5296610
}
}
]
}
\ No newline at end of file
Python/actuator_line_with_wifi/read_output.py 0 → 100644
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#%%
from pandas import HDFStore
from matplotlib import pyplot as plt
import numpy as np
from pathlib import Path
from wiFI.turbine import create_turbine_from_farm_json
def get_blade_array(hdf5: HDFStore, key: str):
blade_df = hdf5.get(key)
_, n_turbines, n_blades, n_nodes = blade_df.columns[-1]
return blade_df.to_numpy().reshape(-1, 3, n_turbines+1, n_blades+1, n_nodes+1)
#%%
turbine_file = Path(__file__).parent/"SingleTurbine.json"
output_dir = Path(__file__).parents[2]/"output"
wifi_output = HDFStore(output_dir/"wifi.h5", mode="r")
turbine_model = create_turbine_from_farm_json(turbine_file, number_of_blade_nodes=32)
# %%
print(wifi_output.keys())
#%%
plt.plot(wifi_output["/Rotor_speed"])
# %%
blade_forces = get_blade_array(wifi_output, "Blade_forces")
plt.plot(blade_forces[-1, 0, 0, :, :].T)
# %%
blade_coordinates = get_blade_array(wifi_output, "Blade_coordinates")
plt.scatter(blade_coordinates[-1,1,0,:,:], blade_coordinates[-1,2,0,:,:])
# %%
blade_velocities = get_blade_array(wifi_output, "Blade_velocities")
plt.plot(blade_velocities[-1, 0, 0, :, :].T)
# %%
plt.plot(blade_velocities[-1, 1, 0,:,:].T)
# %%
Python/actuator_line_with_wifi/runscript.py 0 → 100644
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from pathlib import Path
from wiFI.turbine import create_turbine_from_farm_json
from wiFI.logging import LoggerConfig, LogEntry
from wiFI.interfaces.implementations.velocity_provider.VirtualFluids.VirtualFluids import create_standard_actuator_farm
from wiFI.controller.controller import ControllerTypes
from pyfluids import basics, gpu, logger, parallel
import numpy as np
#%%
sim_name = "ABL"
config_file = Path(__file__).parent/"configActuatorLine.txt"
turbine_file = Path(__file__).parent/"SingleTurbine.json"
controller_file = Path(__file__).parent/"controller.json"
def load_config_file(config_file: Path):
config = basics.ConfigurationFile()
config.load(str(config_file))
return config
def add_plane_probes(plane_locs: np.ndarray, para: gpu.Parameter, t_start_averaging: float, t_start_out_probe: float, t_out_probe: float, dt: float, dx: float, length: np.ndarray):
for n_probe, probe_pos in enumerate(plane_locs):
plane_probe = gpu.probes.PlaneProbe(f"planeProbe_{n_probe+1}", para.get_output_path(), int(t_start_averaging/dt), 10, int(t_start_out_probe/dt), int(t_out_probe/dt))
plane_probe.set_probe_plane(probe_pos, -length[1]/2, -length[2]/2, dx, length[1], length[2])
plane_probe.add_all_available_statistics()
para.add_probe(plane_probe)
def main(sim_name: str, config_file: Path, turbine_file: Path, controller_file: Path):
logger.Logger.initialize_logger()
config = load_config_file(config_file)
grid_builder = gpu.grid_generator.MultipleGridBuilder()
communicator = parallel.MPICommunicator.get_instance()
para = gpu.Parameter(communicator.get_number_of_processes(), communicator.get_process_id(), config)
bc_factory = gpu.BoundaryConditionFactory()
viscosity = config.get_float_value("viscosity", 1.56e-5)
velocity = config.get_float_value("velocity", 9.0)
mach = config.get_float_value("Ma", 0.1)
nodes_per_diameter = config.get_uint_value("nodesPerDiameter", 32)
density = config.get_float_value("Density", 1.225)
level = 0
n_blade_nodes = config.get_int_value("NumberOfNodesPerAL", 32)
read_precursor = config.get_bool_value("readPrecursor", False)
if read_precursor:
nTReadPrecursor = config.get_int_value("nTimestepsReadPrecursor")
use_distributions = config.get_bool_value("useDistributions", False)
precursor_directory = config.get_string_value("precursorDirectory")
# all in s
t_start_out = config.get_float_value("tStartOut")
t_out = config.get_float_value("tOut")
t_end = config.get_float_value("tEnd") # total time of simulation
t_start_averaging = config.get_float_value("tStartAveraging")
t_start_tmp_averaging = config.get_float_value("tStartTmpAveraging")
t_averaging = config.get_float_value("tAveraging")
t_start_out_probe = config.get_float_value("tStartOutProbe")
t_out_probe = config.get_float_value("tOutProbe")
turbine_model = create_turbine_from_farm_json(turbine_file,
n_blade_nodes,
load_data = True,
use_gpu = True)
diameter = turbine_model.blade_tip_radius*2
length = np.array([24,8,8])*diameter
dx = diameter/nodes_per_diameter
dt = dx * mach / (np.sqrt(3) * velocity)
velocity_ratio = dx/dt
velocity_LB = velocity / velocity_ratio # LB units
viscosity_LB = viscosity / (velocity_ratio * dx) # LB units
logger.vf_log_info(f"velocity [dx/dt] = {velocity_LB}")
logger.vf_log_info(f"dt = {dt}")
logger.vf_log_info(f"dx = {dx}")
logger.vf_log_info(f"viscosity [10^8 dx^2/dt] = {viscosity_LB*1e8}")
para.set_output_prefix(sim_name)
para.set_print_files(True)
output_path = Path(para.get_output_path())
output_path.mkdir(exist_ok=True)
para.set_forcing(0, 0, 0)
para.set_velocity_LB(velocity_LB)
para.set_viscosity_LB(viscosity_LB)
para.set_velocity_ratio(dx/dt)
para.set_viscosity_ratio(dx*dx/dt)
para.set_density_ratio(1.0)
para.configure_main_kernel(gpu.kernel.compressible.K17CompressibleNavierStokes)
para.set_timestep_start_out(int(t_start_out/dt))
para.set_timestep_out(int(t_out/dt))
para.set_timestep_end(int(t_end/dt))
para.set_is_body_force(True)
tm_factory = gpu.TurbulenceModelFactory(para)
tm_factory.read_config_file(config)
#%%
grid_scaling_factory = gpu.GridScalingFactory()
grid_scaling_factory.set_scaling_factory(gpu.GridScaling.ScaleCompressible)
grid_builder.add_coarse_grid(-3*diameter, -length[1]/2, -length[2]/2, length[0]-3*diameter, length[1]/2, length[2]/2, dx)
grid_builder.set_periodic_boundary_condition(False, True, True)
grid_builder.build_grids(False)
if read_precursor:
precursor = gpu.create_file_collection(precursor_directory + "/precursor", gpu.FileType.VTK)
grid_builder.set_precursor_boundary_condition(gpu.SideType.MX, precursor, nTReadPrecursor, 0, 0, 0)
else:
grid_builder.set_velocity_boundary_condition(gpu.SideType.MX, velocity_LB, 0, 0)
grid_builder.set_pressure_boundary_condition(gpu.SideType.PX, 0)
bc_factory.set_stress_boundary_condition(gpu.StressBC.StressPressureBounceBack)
bc_factory.set_slip_boundary_condition(gpu.SlipBC.SlipBounceBack)
bc_factory.set_pressure_boundary_condition(gpu.PressureBC.OutflowNonReflective)
if read_precursor:
bc_factory.set_precursor_boundary_condition(gpu.PrecursorBC.DistributionsPrecursor if use_distributions else gpu.PrecursorBC.VelocityPrecursor)
else:
bc_factory.set_velocity_boundary_condition(gpu.VelocityBC.VelocityAndPressureCompressible)
para.set_outflow_pressure_correction_factor(0.0)
para.set_initial_condition_uniform(velocity_LB, 0, 0)
logging_config = LoggerConfig("wifi", output_path, start_time=1000, log_period=100)
logging_dict = {"wind_farm": [LogEntry("rotor_speed", True, True),
LogEntry("azimuth", True, True)]}
tip_speed_ratio = 7.55*np.ones(turbine_model.n_turbines)
rotor_speeds = tip_speed_ratio * velocity / turbine_model.blade_tip_radius
smearing_width = 2*dx
farm = create_standard_actuator_farm(logging_config, logging_dict, turbine_model, density, smearing_width,
level, dt, dx, communicator.get_process_id(),
ControllerTypes.Greedy, controller_file, rotor_speeds)
# farm = gpu.ActuatorFarmStandalone(turbine_model.blade_tip_radius*2, turbine_model.n_nodes_per_blade, turbine_model.hub_positions.x, turbine_model.hub_positions.y, turbine_model.hub_positions.z, rotor_speeds, density, smearing_width, level, dt, dx)
farm.enable_output("ALM", 0, int(t_out_probe/dt))
para.add_actuator(farm)
plane_locs = np.array([-1,1,2,3,4])*diameter
add_plane_probes(plane_locs, para, t_start_averaging, t_start_out_probe, t_out_probe, dt, dx, length)
plane_probe = gpu.probes.PlaneProbe(f"streamwiseProbe", para.get_output_path(), int(t_start_averaging/dt), 10, int(t_start_out_probe/dt), int(t_out_probe/dt))
plane_probe.set_probe_plane(-diameter*3, 0, -length[2]/2, length[0], dx, length[2])
plane_probe.add_all_available_statistics()
para.add_probe(plane_probe)
cuda_memory_manager = gpu.CudaMemoryManager(para)
grid_generator = gpu.GridProvider.make_grid_generator(grid_builder, para, cuda_memory_manager, communicator)
sim = gpu.Simulation(para, cuda_memory_manager, communicator, grid_generator, bc_factory, tm_factory, grid_scaling_factory)
sim.run()
if __name__ == '__main__':
main(sim_name, config_file, turbine_file, controller_file)
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