Example #1
0
def get_max_cl(Re, r):
    """
    Analyze airfoil at a fixed Re,
    changing aoa from 10 to 15 by 0.1
    and returns cl, cd, aoa that makes maximum cl
    """
    xf = XFoil()
    if r <= 0.175:
        xf.airfoil = naca6409
    else:
        xf.airfoil = naca2412
    xf.Re = Re
    xf.Re = Re
    xf.max_iter = 200
    xf.n_crit = 9.00
    xf.xtr = [1.00, 1.00]
    xf.M = 0
    a_seq, cl_seq, cd_seq, cm_seq, cp_seq = xf.aseq(10, 15, 0.1)
    # ignore nan by making it 0
    cl_seq = np.nan_to_num(cl_seq)
    # find the maximum cl
    cl_maxi = np.max(cl_seq)
    # index of the maximum cl
    idx = np.argmax(cl_seq)
    return round(cl_maxi, 2), round(a_seq[idx], 2), round(cd_seq[idx], 2)
def get_torque(angular_velocity):
    torque_sum_small = 0
    torque_sum_large = 0
    w = angular_velocity
    for key, value in dfdict.items():
        value["blade_velocity"] = value['r_position'] * w
        value["relative_velocity"] = round(
            math.sqrt(value["blade_velocity"]**2 + value["wind_velocity"]**2),
            2)
        value["arctan"] = math.degrees(
            math.atan2(value["wind_velocity"], value["blade_velocity"]))
        aoa = round(value["arctan"] - value["pitch_angle"], 2)
        value["angle_of_attack"] = aoa
        re_n = round(
            value["relative_velocity"] * value["chord_length"] / 0.00001511, 3)
        value["Reynolds_number"] = re_n
        xf = XFoil()
        if key < 13:
            xf.airfoil = naca6409
        else:
            xf.airfoil = naca2412
        xf.Re = re_n
        xf.max_iter = 100
        xf.n_crit = 9.00
        xf.xtr = [1.00, 1.00]
        xf.M = 0
        value["Cl"], value["Cd"], value["Cm"], value["Cp"] = xf.a(aoa)
        force_reference = 0.5 * density * value["relative_velocity"]**2
        if math.isnan(value["Cl"]):
            value["torque"] = 0
        else:
            lift = value["Cl"] * force_reference * 0.0125 * value[
                'chord_length']
            drag = value["Cd"] * force_reference * 0.0125 * value[
                'chord_length']
            value["torque"] = value["r_position"] * (
                lift * math.sin(math.radians(value["pitch_angle"])) -
                drag * math.cos(math.radians(value["pitch_angle"])))
        if key < 13:
            torque_sum_small += value["torque"]
        else:
            pass
        if key > 0:
            torque_sum_large += value["torque"]
        else:
            pass
    df2 = pd.DataFrame.from_dict(dfdict, orient="index")
    df_collection.append(df2)
    torque_sum_avg = 0.5 * (torque_sum_small + torque_sum_large)
    return torque_sum_avg
def total_dict(angular_velocity):
    torque_sum = 0
    w = angular_velocity
    for key, value in dfdict.items():
        value["blade_velocity"] = value['r_position'] * w
        value["relative_velocity"] = round(
            math.sqrt(value["blade_velocity"]**2 + value["wind_velocity"]**2),
            2)
        value["arctan"] = math.degrees(
            math.atan2(value["wind_velocity"], value["blade_velocity"]))
        aoa = round(value["arctan"] - value["pitch_angle"], 1)
        value["angle_of_attack"] = aoa
        re_n = round(value["relative_velocity"] * value["chord_length"] /
                     0.00001511)
        value["Reynolds_number"] = re_n
        xf = XFoil()
        if key < 13:
            xf.airfoil = naca6409
        else:
            xf.airfoil = naca2412
        xf.Re = round(re_n / 100) * 100
        xf.max_iter = 200
        xf.n_crit = 9.00
        xf.xtr = [1.00, 1.00]
        xf.M = 0
        c_l, c_d, c_m, c_p = xf.a(aoa)
        force_reference = 0.5 * density * value["relative_velocity"]**2
        if math.isnan(c_l):
            pass
        else:
            value["Cl"] = c_l
            value["Cd"] = c_d
            value["Cm"] = c_m
            value["Cp"] = c_p
            lift = c_l * force_reference * 0.0125 * value['chord_length']
            drag = c_d * force_reference * 0.0125 * value['chord_length']
            value["lift"] = lift
            value["drag"] = drag
            # value["torque"] = value["r_position"] * lift * math.sin(math.radians(value["pitch_angle"]))
            torque = value["r_position"] * (
                lift * math.sin(math.radians(value["pitch_angle"])) -
                drag * math.cos(math.radians(value["pitch_angle"])))
            value["torque"] = torque
            torque_sum += torque
        xf.reset_bls()
    # detailed_df = pd.DataFrame.from_dict(dfdict, orient="index")
    # print(detailed_df)
    print(torque_sum, angular_velocity)
    return dfdict, torque_sum
Example #4
0
    #TODO: CST airfoil for Xfoil
    cst_u = [ 0.135283,  0.088574,  0.177210,  0.080000,  0.231590,  0.189572,  0.192000]
    cst_l = [-0.101390, -0.007993, -0.240000, -0.129790, -0.147840, -0.000050,  0.221251]
    xx, yu, yl, t0, R0 = cst_foil(101, np.array(cst_u), np.array(cst_l), x=None, t=0.0954, tail=0.002)

    x = np.concatenate((np.flip(xx[1:]), xx[1:]), axis=0)
    y = np.concatenate((np.flip(yu[1:]), yl[1:]), axis=0)
    foil = Airfoil(x, y)

    #TODO: Xfoil
    xf = XFoil()
    xf.print = False
    xf.max_iter = 40
    xf.airfoil = foil
    xf.xtr = [0.0, 0.0]

    Minf = 0.2
    AoA  = 8.0
    Re   = 1e7
    fname = 'feature-xfoil.txt'

    xf.M = Minf
    xf.Re = Re

    cl, cd, cm, cp = xf.a(AoA)
    x, cp = xf.get_cp_distribution()

    with open(fname, 'w') as f:
        f.write('%10s   %15.6f \n'%('Minf', Minf))
        f.write('%10s   %15.6f \n'%('AoA', AoA))