"""Estimation of vertical tail 3D lift coefficient."""
# This file is part of FAST-OAD_CS23 : A framework for rapid Overall Aircraft Design
# Copyright (C) 2022 ONERA & ISAE-SUPAERO
# FAST is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
import numpy as np
import scipy.interpolate as interp
import fastoad.api as oad
from ..figure_digitization import FigureDigitization
from ...constants import SUBMODEL_CL_ALPHA_VT
[docs]@oad.RegisterSubmodel(
SUBMODEL_CL_ALPHA_VT, "fastga.submodel.aerodynamics.vertical_tail.lift_curve_slope.legacy"
)
class ComputeClAlphaVerticalTail(FigureDigitization):
"""
Vertical tail lift coefficient estimation.
Based on : Roskam, Jan. Airplane Design: Part 6-Preliminary Calculation of Aerodynamic,
Thrust and Power Characteristics. DARcorporation, 1985. Equation (8.22) applied with the
geometric characteristics of the VTP and an effective aspect ratio different from the
geometric one obtained as described in section 10.2.4.1.
"""
[docs] def initialize(self):
self.options.declare("low_speed_aero", default=False, types=bool)
[docs] def setup(self):
if self.options["low_speed_aero"]:
self.add_input("data:aerodynamics:low_speed:mach", val=np.nan)
else:
self.add_input("data:aerodynamics:cruise:mach", val=np.nan)
self.add_input(
"data:aerodynamics:vertical_tail:airfoil:CL_alpha", val=np.nan, units="rad**-1"
)
self.add_input("data:geometry:has_T_tail", val=np.nan)
self.add_input("data:geometry:vertical_tail:aspect_ratio", val=np.nan)
self.add_input("data:geometry:vertical_tail:taper_ratio", val=np.nan)
self.add_input("data:geometry:vertical_tail:sweep_25", val=np.nan, units="deg")
self.add_input("data:geometry:vertical_tail:span", val=np.nan, units="m")
self.add_input("data:geometry:vertical_tail:area", val=np.nan, units="m**2")
self.add_input("data:geometry:horizontal_tail:area", val=np.nan, units="m**2")
self.add_input("data:geometry:fuselage:average_depth", val=np.nan, units="m")
if self.options["low_speed_aero"]:
self.add_output("data:aerodynamics:vertical_tail:low_speed:CL_alpha", units="rad**-1")
self.add_output("data:aerodynamics:vertical_tail:k_ar_effective")
else:
self.add_output("data:aerodynamics:vertical_tail:cruise:CL_alpha", units="rad**-1")
[docs] def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None):
if self.options["low_speed_aero"]:
mach = inputs["data:aerodynamics:low_speed:mach"]
beta = np.sqrt(1 - mach**2)
k = inputs["data:aerodynamics:vertical_tail:airfoil:CL_alpha"] / (2.0 * np.pi)
else:
mach = inputs["data:aerodynamics:cruise:mach"]
beta = np.sqrt(1 - mach**2)
k = inputs["data:aerodynamics:vertical_tail:airfoil:CL_alpha"] / (beta * 2.0 * np.pi)
tail_type = np.round(inputs["data:geometry:has_T_tail"])
sweep_25_vt = inputs["data:geometry:vertical_tail:sweep_25"]
span_vt = inputs["data:geometry:vertical_tail:span"]
area_vt = inputs["data:geometry:vertical_tail:area"]
taper_ratio_vt = inputs["data:geometry:vertical_tail:taper_ratio"]
area_ht = inputs["data:geometry:horizontal_tail:area"]
avg_fus_depth = inputs["data:geometry:fuselage:average_depth"]
# Compute the effect of fuselage and HTP as end plates which gives a different effective
# aspect ratio
k_ar_fuselage = self.k_ar_fuselage(taper_ratio_vt, span_vt, avg_fus_depth)
k_ar_fuselage_ht = 1.7 if tail_type == 1.0 else 1.2
k_vh = self.k_vh(float(area_ht / area_vt))
k_ar_effective = k_ar_fuselage * (1.0 + k_vh * (k_ar_fuselage_ht - 1.0))
lambda_vt = inputs["data:geometry:vertical_tail:aspect_ratio"] * k_ar_effective
if span_vt / avg_fus_depth < 2.0:
kv = 0.75
elif span_vt / avg_fus_depth < 3.5:
kv = interp.interp1d([2.0, 3.5], [0.75, 1.0])(float(span_vt / avg_fus_depth))
else:
kv = 1.0
cl_alpha_vt = (
kv
* 2
* np.pi
* lambda_vt
/ (
2
+ np.sqrt(
4
+ lambda_vt**2
* beta**2
/ k**2
* (1 + (np.tan(sweep_25_vt / 180.0 * np.pi)) ** 2 / beta**2)
)
)
)
if self.options["low_speed_aero"]:
outputs["data:aerodynamics:vertical_tail:low_speed:CL_alpha"] = cl_alpha_vt
outputs["data:aerodynamics:vertical_tail:k_ar_effective"] = k_ar_effective
else:
outputs["data:aerodynamics:vertical_tail:cruise:CL_alpha"] = cl_alpha_vt