def parse_flat_wall_probe(fname, yname):
"""Read a Nalu wall probe file."""
df = pd.read_csv(fname, delim_whitespace=True)
df.rename(
columns={
"Time": "time",
"coordinates[0]": "x",
"coordinates[1]": "y",
"tau_wall_probe[0]": "tau_wall",
"pressure_probe[0]": "pressure",
},
inplace=True,
)
# Keep only the last time step
time = np.unique(df["time"])
df = df.loc[df["time"] == time[-1]]
# Calculate coefficients
u0, rho0, mu = utilities.parse_ic(yname)
dynPres = rho0 * 0.5 * u0 * u0
df["cf"] = df["tau_wall"] / dynPres
df["cp"] = df["pressure"] / dynPres
return df.reset_index(drop=True)
def parse_surface_probe(fname, yname):
"""Read a Nalu exodus file to get surface data."""
wall_bdy = "bottomwall"
tauwall_field = "tau_wall"
pressure_field = "pressure"
# Indices of wall face in element
ss_node_ids = np.array([0, 1, 2, 3])
# Read in the Exodus II mesh
msh = Dataset(fname, "r")
ss_names = get_name_list(msh, "ss_names")
field_names = get_name_list(msh, "name_nod_var")
wall_idx = ss_names.index(wall_bdy)
tau_idx = field_names.index(tauwall_field)
pressure_idx = field_names.index(pressure_field)
# Get the coordinates and time
x = msh.variables["coordx"][:]
y = msh.variables["coordy"][:]
time = msh.variables["time_whole"][1:]
# Element mapping and wall node ids
nids = msh.variables["connect1"][:]
wall_elems = msh.variables["elem_ss%d" % (wall_idx + 1)][:] - 1
wall_nids_all = np.unique(nids[np.ix_(wall_elems,
ss_node_ids)].flatten()) - 1
# Get tau_wall and pressure on the wall
tau_wall_all = msh.variables["vals_nod_var%d" %
(tau_idx + 1)][:][1:, wall_nids_all]
pressure_all = msh.variables["vals_nod_var%d" %
(pressure_idx + 1)][:][1:, wall_nids_all]
# Keep only the last time step in a dataframe
df = pd.DataFrame()
df["tau_wall"] = tau_wall_all[-1, :]
df["pressure"] = pressure_all[-1, :]
df["time"] = time[-1]
df["x"] = x[wall_nids_all]
df["y"] = y[wall_nids_all]
print(x[wall_nids_all])
print(y[wall_nids_all])
# Calculate coefficients
u0, rho0, mu = utilities.parse_ic(yname)
dynPres = rho0 * 0.5 * u0 * u0
df["cf"] = df["tau_wall"] / dynPres
df["cp"] = df["pressure"] / dynPres
return df
def tauwall_hack(fname, yname):
"""
Hack to find all the wall quantities by looking at tau_wall > 0.
Identical to parse_surface_probe but without relying on sidesets.
"""
tauwall_field = "tau_wall"
pressure_field = "pressure"
# Read in the Exodus II mesh
msh = Dataset(fname, "r")
field_names = get_name_list(msh, "name_nod_var")
tau_idx = field_names.index(tauwall_field)
pressure_idx = field_names.index(pressure_field)
# Get the coordinates and time
x = msh.variables["coordx"][:]
y = msh.variables["coordy"][:]
time = msh.variables["time_whole"][1:]
# Get tau_wall and pressure everywhere
tau_wall_all = msh.variables["vals_nod_var%d" % (tau_idx + 1)][:]
pressure_all = msh.variables["vals_nod_var%d" % (pressure_idx + 1)][:]
# The wall is wherever tauwall is non-zero,
wall_idx = tau_wall_all[-1, :] > 1e-16
# Get the variables on the wall
tau_wall = tau_wall_all[1:, wall_idx]
pressure = pressure_all[1:, wall_idx]
x = x[wall_idx]
y = y[tau_wall_all[-1, :] > 1e-16]
# Keep only the last time step in a dataframe
df = pd.DataFrame()
df["tau_wall"] = tau_wall[-1, :]
df["pressure"] = pressure[-1, :]
df["time"] = time[-1]
df["x"] = x
df["y"] = y
# Calculate coefficients
u0, rho0, mu = utilities.parse_ic(yname)
dynPres = rho0 * 0.5 * u0 * u0
df["cf"] = df["tau_wall"] / dynPres
df["cp"] = df["pressure"] / dynPres
df.sort_values(by=["x"], inplace=True)
return df.groupby("x").mean().reset_index()
required=True,
)
args = parser.parse_args()
# Loop on folders
for i, folder in enumerate(args.folders):
# Setup
fdir = os.path.abspath(folder)
yname = os.path.join(fdir, "mcalister.yaml")
fname = "avg_slice.csv"
dim = defs.get_dimension(yname)
half_wing_length = defs.get_half_wing_length()
# simulation setup parameters
u0, v0, w0, umag0, rho0, mu = utilities.parse_ic(yname)
aoa = defs.get_aoa(fdir)
chord = 1
# experimental values
edir = os.path.abspath(os.path.join("exp_data", f"aoa-{aoa}"))
zslices = utilities.get_wing_slices(dim)
zslices["zslicen"] = zslices.zslice / half_wing_length
# data from other CFD simulations (SA model)
sadir = os.path.abspath(os.path.join("sitaraman_data", f"aoa-{aoa}"))
# Read in data
df = pd.read_csv(os.path.join(fdir, "wing_slices", fname),
delimiter=",")
renames = utilities.get_renames()
args = parser.parse_args()
# Constants
num_figs = 4
utau = 1
height = 1
# Loop on folders
for i, folder in enumerate(args.folders):
# Setup
fdir = os.path.abspath(folder)
yname = os.path.join(fdir, "channelflow.yaml")
# simulation setup parameters
u0, v0, w0, umag0, rho0, mu, flow_angle = utilities.parse_ic(yname)
nu = mu / rho0
Retau = utau * height / nu
# Read in data (all time steps)
prefix = "output"
suffix = ".csv"
# Get time steps
pattern = prefix + "*" + suffix
fnames = sorted(glob.glob(os.path.join(fdir, "lineouts", pattern)))
times = []
for fname in fnames:
times.append(int(re.findall(r"\d+", fname)[-1]))
times = np.unique(sorted(times))
help="Folder to post-process",
type=str,
required=True)
args = parser.parse_args()
# Setup
rdir = os.path.join(args.fdir, "results")
name = os.path.splitext(
os.path.basename(glob.glob(os.path.join(args.fdir, "*.yaml"))[0]))[0]
yname = os.path.join(args.fdir, name + ".yaml")
pname = os.path.join(rdir, "profiles.dat")
wname = os.path.join(rdir, "wall_vars.dat")
sname = os.path.join(rdir, "points.dat")
separation_exp = 0.665
reattachement_exp = 1.1
u0, rho0, mu = utilities.parse_ic(yname)
# Velocities
profiles = parse_probe(rdir, u0)
# Wall quantities
fname = os.path.join(rdir, name + ".e")
walldf = tauwall_hack(fname, yname)
# Separation and reattachement points
walldf["abs_cp_grad"] = np.fabs(np.gradient(walldf["cf"], walldf["x"]))
# Search for separation point near the experimental one
interval = 0.1
ubnd = (1 + interval) * separation_exp
lbnd = (1 - interval) * separation_exp