本文整理汇总了Python中SUAVE.Structure.Data.damping_ratio方法的典型用法代码示例。如果您正苦于以下问题：Python Data.damping_ratio方法的具体用法？Python Data.damping_ratio怎么用？Python Data.damping_ratio使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类SUAVE.Structure.Data的用法示例。
在下文中一共展示了Data.damping_ratio方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: dutch_roll
# 需要导入模块: from SUAVE.Structure import Data [as 别名]
# 或者: from SUAVE.Structure.Data import damping_ratio [as 别名]
def dutch_roll(velocity, Cn_Beta, S_gross_w, density, span, I_z, Cn_r):
""" output = SUAVE.Methods.Flight_Dynamics.Dynamic_Stablity.Approximations.dutch_roll(velocity, Cn_Beta, S_gross_w, density, span, I_z, Cn_r)
Calculate the natural frequency and damping ratio for the approximate dutch roll characteristics
Inputs:
velocity - flight velocity at the condition being considered [meters/seconds]
Cn_Beta - coefficient for change in yawing moment due to sideslip [dimensionless]
S_gross_w - area of the wing [meters**2]
density - flight density at condition being considered [kg/meters**3]
span - wing span of the aircraft [meters]
I_z - moment of interia about the body z axis [kg * meters**2]
Cn_r - coefficient for change in yawing moment due to yawing velocity [dimensionless]
Outputs:
output - a data dictionary with fields:
dutch_w_n - natural frequency of the dutch roll mode [radian/second]
dutch_zeta - damping ratio of the dutch roll mode [dimensionless]
Assumptions:
Major effect of rudder deflection is the generation of the Dutch roll mode.
Dutch roll mode only consists of sideslip and yaw
Beta = -Psi
Phi and its derivatives are zero
consider only delta_r input and Theta = 0
Neglect Cy_r
X-Z axis is plane of symmetry
Constant mass of aircraft
Origin of axis system at c.g. of aircraft
Aircraft is a rigid body
Earth is inertial reference frame
Perturbations from equilibrium are small
Flow is Quasisteady
Source:
J.H. Blakelock, "Automatic Control of Aircraft and Missiles" Wiley & Sons, Inc. New York, 1991, p 132-134.
"""
#process
w_n = velocity * (Cn_Beta*S_gross_w*density*span/2./I_z)**0.5 # natural frequency
zeta = -Cn_r /8. * (2.*S_gross_w*density*span**3./I_z/Cn_Beta)**0.5 # damping ratio
output = Data()
output.natural_frequency = w_n
output.damping_ratio = zeta
return output示例2: short_period
# 需要导入模块: from SUAVE.Structure import Data [as 别名]
# 或者: from SUAVE.Structure.Data import damping_ratio [as 别名]
def short_period(velocity, density, S_gross_w, mac, Cm_q, Cz_alpha, mass, Cm_alpha, Iy, Cm_alpha_dot):
""" output = SUAVE.Methods.Flight_Dynamics.Dynamic_Stablity.Approximations.short_period(velocity, density, S_gross_w, mac, Cm_q, Cz_alpha, mass, Cm_alpha, Iy, Cm_alpha_dot)
Calculate the natural frequency and damping ratio for the approximate short period characteristics
Inputs:
velocity - flight velocity at the condition being considered [meters/seconds]
density - flight density at condition being considered [kg/meters**3]
S_gross_w - area of the wing [meters**2]
mac - mean aerodynamic chord of the wing [meters]
Cm_q - coefficient for the change in pitching moment due to pitch rate [dimensionless]
Cz_alpha - coefficient for the change in Z force due to the angle of attack [dimensionless]
mass - mass of the aircraft [kilograms]
Cm_alpha - coefficient for the change in pitching moment due to angle of attack [dimensionless]
Iy - moment of interia about the body y axis [kg * meters**2]
Cm_alpha_dot - coefficient for the change in pitching moment due to rate of change of angle of attack [dimensionless]
Outputs:
output - a data dictionary with fields:
w_n - natural frequency of the short period mode [radian/second]
zeta - damping ratio of the short period mode [dimensionless]
Assumptions:
X-Z axis is plane of symmetry
Constant mass of aircraft
Origin of axis system at c.g. of aircraft
Aircraft is a rigid body
Earth is inertial reference frame
Perturbations from equilibrium are small
Flow is Quasisteady
Constant forward airspeed
Neglect Cz_alpha_dot and Cz_q
Theta = 0
Source:
J.H. Blakelock, "Automatic Control of Aircraft and Missiles" Wiley & Sons, Inc. New York, 1991, p 46-50.
"""
#process
w_n = velocity * density * S_gross_w * mac / 2. * ((0.5*Cm_q*Cz_alpha - 2. * mass / density /S_gross_w /mac * Cm_alpha) / Iy /mass)**(0.5)
zeta = -0.25 * (Cm_q + Cm_alpha_dot + 2. * Iy * Cz_alpha / mass / (mac ** 2.)) * ( mass * mac ** 2. / Iy / (Cm_q * Cz_alpha * 0.5 - 2. * mass * Cm_alpha / density / S_gross_w / mac)) ** 0.5
output = Data()
output.natural_frequency = w_n
output.damping_ratio = zeta
return output示例3: phugoid
# 需要导入模块: from SUAVE.Structure import Data [as 别名]
# 或者: from SUAVE.Structure.Data import damping_ratio [as 别名]
def phugoid(g, velocity, CD, CL):
""" output = SUAVE.Methods.Flight_Dynamics.Dynamic_Stablity.Approximations.phugoid(g, velocity, CD, CL)
Calculate the natural frequency and damping ratio for the approximate phugoid characteristics
Inputs:
g - gravitational constant [meters/second**2]
velocity - flight velocity at the condition being considered [meters/seconds]
CD - coefficient of drag [dimensionless]
CL - coefficient of lift [dimensionless]
Outputs:
output - a data dictionary with fields:
phugoid_w_n - natural frequency of the phugoid mode [radian/second]
phugoid_zeta - damping ratio of the phugoid mode [dimensionless]
Assumptions:
constant angle of attack
theta changes very slowly
Inertial forces are neglected
Neglect Cz_q
Theta = 0
X-Z axis is plane of symmetry
Constant mass of aircraft
Origin of axis system at c.g. of aircraft
Aircraft is a rigid body
Earth is inertial reference frame
Perturbations from equilibrium are small
Flow is Quasisteady
Source:
J.H. Blakelock, "Automatic Control of Aircraft and Missiles" Wiley & Sons, Inc. New York, 1991, p 50-53.
"""
#process
w_n = g/velocity * (2.)**0.5
zeta = CD/(CL*(2.)**0.5)
output = Data()
output.natural_frequency = w_n
output.damping_ratio = zeta
return output