Python Data.roll_tau方法代码示例

# 需要导入模块: from SUAVE.Structure import Data [as 别名]
# 或者: from SUAVE.Structure.Data import roll_tau [as 别名]
def lateral_directional(velocity, Cn_Beta, S_gross_w, density, span, I_z, Cn_r, I_x, Cl_p, J_xz, Cl_r, Cl_Beta, Cn_p, Cy_phi, Cy_psi, Cy_Beta, mass):
    """ output = SUAVE.Methods.Flight_Dynamics.Dynamic_Stablity.Full_Linearized_Equations.lateral_directional(velocity, Cn_Beta, S_gross_w, density, span, I_z, Cn_r, I_x, Cl_p, J_xz, Cl_r, Cl_Beta, Cn_p, Cy_phi, Cy_psi, Cy_Beta)
        Calculate the natural frequency and damping ratio for the full linearized dutch roll mode along with the time constants for the roll and spiral modes        
        Inputs:
            velocity - flight velocity at the condition being considered [meters/seconds]
            Cn_Beta - coefficient for change in yawing moment due to sideslip [dimensionless] (no simple relation)
            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] ( - C_D(wing)/4 - 2 * Sv/S * (l_v/b)**2 * (dC_L/dalpha)(vert) * eta(vert))
            I_x - moment of interia about the body x axis [kg * meters**2]
            Cl_p - change in rolling moment due to the rolling velocity [dimensionless] (no simple relation for calculation)
            J_xz - products of inertia in the x-z direction [kg * meters**2] (if X and Z lie in a plane of symmetry then equal to zero)
            Cl_r - coefficient for change in rolling moment due to yawing velocity [dimensionless] (Usually equals C_L(wing)/4)
            Cl_Beta - coefficient for change in rolling moment due to sideslip [dimensionless] 
            Cn_p - coefficient for the change in yawing moment due to rolling velocity [dimensionless] (-C_L(wing)/8*(1 - depsilon/dalpha)) (depsilon/dalpha = 2/pi/e/AspectRatio dC_L(wing)/dalpha)
            Cy_phi  - coefficient for change in sideforce due to aircraft roll [dimensionless] (Usually equals C_L)
            Cy_psi - coefficient to account for gravity [dimensionless] (C_L * tan(Theta))
            Cy_Beta - coefficient for change in Y force due to sideslip [dimensionless] (no simple relation)
            mass - mass of the aircraft [kilograms]
        
        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]
                roll_tau - approximation of the time constant of the roll mode of an aircraft [seconds] (positive values are bad)
                spiral_tau - time constant for the spiral mode [seconds] (positive values are bad)
            
        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
            Zero initial conditions
            Neglect Cy_p and Cy_r
            
        Source:
            J.H. Blakelock, "Automatic Control of Aircraft and Missiles" Wiley & Sons, Inc. New York, 1991, p 118-124.
    """ 
    
    #process
    
    # constructing matrix of coefficients
    A = (0, -span * 0.5 / velocity * Cl_p, I_x/S_gross_w/(0.5*density*velocity**2)/span )  # L moment phi term
    B = (0, -span * 0.5 / velocity * Cl_r, -J_xz / S_gross_w / (0.5 * density * velocity ** 2.) / span) # L moment psi term
    C = (-Cl_Beta) # L moment Beta term
    D = (0, - span * 0.5 / velocity * Cn_p, -J_xz / S_gross_w / (0.5 * density * velocity ** 2.) / span ) # N moment phi term 
    E = (0, - span * 0.5 / velocity * Cn_r, I_z / S_gross_w / (0.5 * density * velocity ** 2.) / span ) # N moment psi term
    F = (-Cn_Beta) # N moment Beta term
    G = (-Cy_phi) # Y force phi term
    H = (-Cy_psi, mass * velocity / S_gross_w / (0.5 * density * velocity ** 2.))    
    I = (-Cy_Beta, mass * velocity / S_gross_w / (0.5 * density * velocity ** 2.))
    
    # Taking the determinant of the matrix ([A, B, C],[D, E, F],[G, H, I])
    EI = P.polymul(E,I)
    FH = P.polymul(F,H)
    part1 = P.polymul(A,P.polysub(EI,FH))
    DI = P.polymul(D,I)
    FG = P.polymul(F,G)
    part2 = P.polymul(B,P.polysub(FG,DI))    
    DH = P.polymul(D,H)
    GE = P.polymul(G,E)
    part3 = P.polymul(C,P.polysub(DH,GE))
    total = P.polyadd(part1,P.polyadd(part2,part3))
    poly = total / total[5]
    
    # Generate the time constant for the spiral and roll modes along with the damping and natural frequency for the dutch roll mode
    root = np.roots(poly)
    root = sorted(root,reverse=True)
    spiral_tau = 1 * root[0].real
    w_n = (root[1].imag**2 + root[1].real**2)**(-0.5)
    zeta = -2*root[1].real/w_n
    roll_tau = 1 * root [3].real
    
    output = Data()
    output.dutch_natural_frequency = w_n
    output.dutch_damping_ratio = zeta
    output.spiral_tau = spiral_tau
    output.roll_tau = roll_tau    
    
    return output

# 需要导入模块: from SUAVE.Structure import Data [as 别名]
# 或者: from SUAVE.Structure.Data import roll_tau [as 别名]
def main():

    # Taken from Blakelock
    
    #Lateral/Directional Inputs
    velocity = 440 * (Units['ft/sec']) # Flight Velocity
    Cn_Beta = 0.096 # Yawing moment coefficient due to sideslip
    S_gross_w = 2400 * (Units['ft**2']) # Wing reference area
    density = 0.002378 * (Units['slugs/ft**3']) # Sea level density
    span = 130 * Units.ft # Span of the aircraft
    mass = 5900 * Units.slugs # mass of the aircraft
    I_x = 1.995 * 10**6 * (Units['slugs*ft**2']) # Moment of Inertia in x-axis
    I_z = 4.2 * 10**6 * (Units['slugs*ft**2']) # Moment of Inertia in z-axis
    Cn_r = -0.107 # Yawing moment coefficient due to yawing velocity
    Cl_p = -0.38 #  Rolling moment coefficient due to the rolling velocity
    Cy_phi = 0.344 # Side force coefficient due to aircraft roll
    Cl_Beta = -0.057 # Rolling moment coefficient due to to sideslip
    Cl_r = 0.086 # Rolling moment coefficient due to the yawing velocity (usually evaluated analytically)
    J_xz = 0 # Assumed
    Cn_p = -0.0228
    Cy_psi = 0
    Cy_Beta = -0.6
    mass = 5900 * Units.slugs # mass of the aircraft
    
       
    dutch_roll=Approximations.dutch_roll(velocity, Cn_Beta, S_gross_w, density, span, I_z, Cn_r)
    roll_tau = Approximations.roll(I_x, S_gross_w, density, velocity, span, Cl_p)
    spiral_tau = Approximations.spiral(mass, velocity, density, S_gross_w, Cl_p, Cn_Beta, Cy_phi, Cl_Beta, Cn_r, Cl_r)
    lateral_directional = Full_Linearized_Equations.lateral_directional(velocity, Cn_Beta, S_gross_w, density, span, I_z, Cn_r, I_x, Cl_p, J_xz, Cl_r, Cl_Beta, Cn_p, Cy_phi, Cy_psi, Cy_Beta, mass)
        
    # Longitudinal Inputs
    mass= 5800 * Units.slugs # mass of the aircraft
    velocity = 600 * (Units['ft/sec']) # Flight Velocity
    mac = 20.2 * Units.ft # mean aerodynamic chord
    Cm_q = -11.4 # Change in pitching moment coefficient due to pitching velocity
    CL = 0.74 # Coefficient of Lift
    CD = 0.044 # Coefficient of Drag
    CL_alpha = 4.42 # Change in aircraft lift due to change in angle of attack
    Cz_alpha = -4.46
    SM = -0.14 # static margin
    Cm_alpha = SM * CL_alpha
    Cm_alpha_dot = -3.27
    Iy = 2.62 * 10**6 * (Units['slugs*ft**2']) # Moment of Inertia in y-axis
    density = 0.000585 * (Units['slugs/ft**3']) # 40,000 ft density
    g = 9.8 # gravitational constant
    Cz_u = -2*CL # change in Z force with respect to change in forward velocity
    Cm_alpha_dot = -3.27
    Cz_q = -3.94
    Cw = -CL 
    Theta = 0
    Cx_u = -2*CD
    Cx_alpha = 0.392
    Cz_alpha_dot = -1.13
    
    short_period = Approximations.short_period(velocity, density, S_gross_w, mac, Cm_q, Cz_alpha, mass, Cm_alpha, Iy, Cm_alpha_dot)
    phugoid = Approximations.phugoid(g, velocity, CD, CL)
    longitudinal = Full_Linearized_Equations.longitudinal(velocity, density, S_gross_w, mac, Cm_q, Cz_alpha, mass, Cm_alpha, Iy, Cm_alpha_dot, Cz_u, Cz_alpha_dot, Cz_q, Cw, Theta, Cx_u, Cx_alpha)
    
    # Expected Values
    Blakelock = Data()
    Blakelock.longitudinal_short_zeta = 0.352
    Blakelock.longitudinal_short_w_n = 1.145
    Blakelock.longitudinal_phugoid_zeta = 0.032
    Blakelock.longitudinal_phugoid_w_n = 0.073
    Blakelock.short_period_short_w_n = 1.15
    Blakelock.short_period_short_zeta = 0.35
    Blakelock.phugoid_phugoid_w_n = 0.0765
    Blakelock.phugoid_phugoid_zeta = 0.042
    Blakelock.lateral_directional_dutch_w_n = 1.345
    Blakelock.lateral_directional_dutch_zeta = 0.14
    Blakelock.lateral_directional_spiral_tau = 1/0.004
    Blakelock.lateral_directional_roll_tau = -1/2.09
    Blakelock.dutch_roll_dutch_w_n = 1.28
    Blakelock.dutch_roll_dutch_zeta = 0.114
    Blakelock.spiral_tau = 1./0.0042
    Blakelock.roll_tau = -0.493
    
    # Calculating error percentage
    error = Data()
    error.longitudinal_short_zeta = (Blakelock.longitudinal_short_zeta - longitudinal.short_damping_ratio) / Blakelock.longitudinal_short_zeta
    error.longitudinal_short_w_n = (Blakelock.longitudinal_short_w_n - longitudinal.short_natural_frequency) / Blakelock.longitudinal_short_w_n
    error.longitudinal_phugoid_zeta = (Blakelock.longitudinal_phugoid_zeta - longitudinal.phugoid_damping_ratio) / Blakelock.longitudinal_phugoid_zeta
    error.longitudinal_phugoid_w_n = (Blakelock.longitudinal_phugoid_w_n - longitudinal.phugoid_natural_frequency) / Blakelock.longitudinal_phugoid_w_n
    error.short_period_w_n = (Blakelock.short_period_short_w_n - short_period.natural_frequency) / Blakelock.short_period_short_w_n
    error.short_period_short_zeta = (Blakelock.short_period_short_zeta - short_period.damping_ratio) / Blakelock.short_period_short_zeta
    error.phugoid_phugoid_w_n = (Blakelock.phugoid_phugoid_w_n - phugoid.natural_frequency) / Blakelock.phugoid_phugoid_w_n
    error.phugoid_phugoid_zeta = (Blakelock.phugoid_phugoid_zeta - phugoid.damping_ratio) / Blakelock.phugoid_phugoid_zeta
    error.lateral_directional_dutch_w_n = (Blakelock.lateral_directional_dutch_w_n - lateral_directional.dutch_natural_frequency) / Blakelock.lateral_directional_dutch_w_n
    error.lateral_directional_dutch_zeta = (Blakelock.lateral_directional_dutch_zeta - lateral_directional.dutch_damping_ratio) / Blakelock.lateral_directional_dutch_zeta                              
    error.lateral_directional_spiral_tau = (Blakelock.lateral_directional_spiral_tau - lateral_directional.spiral_tau) / Blakelock.lateral_directional_spiral_tau
    error.lateral_directional_roll_tau = (Blakelock.lateral_directional_roll_tau - lateral_directional.roll_tau) / Blakelock.lateral_directional_roll_tau
    error.dutch_roll_dutch_w_n = (Blakelock.dutch_roll_dutch_w_n - dutch_roll.natural_frequency) / Blakelock.dutch_roll_dutch_w_n
    error.dutch_roll_dutch_zeta = (Blakelock.dutch_roll_dutch_zeta - dutch_roll.damping_ratio) / Blakelock.dutch_roll_dutch_zeta
    error.spiral_tau = (Blakelock.spiral_tau - spiral_tau) / Blakelock.spiral_tau                               
    error.roll_tau = (Blakelock.roll_tau - roll_tau) / Blakelock.roll_tau
    
    print  error
    
    for k,v in error.items():
        assert(np.abs(v)<0.08)
#.........这里部分代码省略.........