def get_planar_dmc(vec_u_eff, variables, kite, architecture):
parent = architecture.parent_map[kite]
# get relevant variables for kite n
q = variables['xd']['q' + str(kite) + str(parent)]
# in kite body:
if parent > 0:
grandparent = architecture.parent_map[parent]
q_parent = variables['xd']['q' + str(parent) + str(grandparent)]
else:
q_parent = np.array([0., 0., 0.])
vec_t = q - q_parent # should be roughly "up-wards", ie, act like vec_w
vec_v = vect_op.cross(vec_t, vec_u_eff)
vec_w = vect_op.cross(vec_u_eff, vec_v)
uhat = vect_op.smooth_normalize(vec_u_eff)
vhat = vect_op.smooth_normalize(vec_v)
what = vect_op.smooth_normalize(vec_w)
planar_dcm = cas.horzcat(uhat, vhat, what)
return planar_dcm
def filament(seg_data, epsilon=1.e-2):
try:
point_obs = seg_data[:3]
point_1 = seg_data[3:6]
point_2 = seg_data[6:9]
Gamma = seg_data[9]
vec_1 = point_obs - point_1
vec_2 = point_obs - point_2
vec_0 = point_2 - point_1
r1 = vect_op.smooth_norm(vec_1)
r2 = vect_op.smooth_norm(vec_2)
r0 = vect_op.smooth_norm(vec_0)
factor = Gamma / (4. * np.pi)
num = (r1 + r2)
den_ori = (r1 * r2) * (r1 * r2 + cas.mtimes(vec_1.T, vec_2))
den_reg = (epsilon * r0)**2.
den = den_ori + den_reg
dir = vect_op.cross(vec_1, vec_2)
scale = factor * num / den
sol = dir * scale
except:
message = 'something went wrong while computing the filament biot-savart induction. proceed with zero induced velocity from this filament.'
awelogger.logger.error(message)
raise Exception(message)
return sol
def get_plane_fit_n_vec(parent, variables, parameters, architecture):
children = sorted(architecture.kites_map[parent])
kite0 = children[0]
kite1 = children[1]
kite2 = children[2]
# there is a potential failure here if the order of the kite nodes is not increaseing from kite0 -> kite1 -> kite2,
# where the direction of the cross-product flips, based on initialization where the lower number kites have a
# smaller azimuthal angle. presumably, this should be resulved by the sorting above, but, just in case!
if (kite0 > kite1) or (kite1 > kite2):
awelogger.logger.warning(
'based on assignment order of kites, normal vector (by cross product) may point in reverse.'
)
qkite0 = variables['xd']['q' + str(kite0) + str(parent)]
qkite1 = variables['xd']['q' + str(kite1) + str(parent)]
qkite2 = variables['xd']['q' + str(kite2) + str(parent)]
arm1 = qkite1 - qkite0
arm2 = qkite2 - qkite0
n_vec = vect_op.cross(arm1, arm2)
b_ref = parameters['theta0', 'geometry', 'b_ref']
varrho_temp = 8.
scale = b_ref**2. * varrho_temp**2.
n_vec = n_vec / scale
return n_vec
def get_total_drag(model_options, diam, q_upper, q_lower, dq_upper, dq_lower, atmos, wind, cd_tether_fun):
elem = model_options['tether']['aero_elements']
q_average = (q_upper + q_lower) / 2.
total_force = np.zeros((3, 1))
total_moment = np.zeros((3, 1))
for idx in range(elem):
loc_s_upper = float(idx + 1) / float(elem)
loc_s_lower = float(idx) / float(elem)
q_loc_upper = q_lower + loc_s_upper * (q_upper - q_lower)
q_loc_lower = q_lower + loc_s_lower * (q_upper - q_lower)
q_loc_average = (q_loc_lower + q_loc_upper)/2.
moment_arm = q_average - q_loc_average
dq_loc_upper = dq_lower + loc_s_upper * (dq_upper - dq_lower)
dq_loc_lower = dq_lower + loc_s_lower * (dq_upper - dq_lower)
loc_force = get_segment_force(diam, q_loc_upper, q_loc_lower, dq_loc_upper, dq_loc_lower, atmos, wind, cd_tether_fun)
loc_moment = vect_op.cross(moment_arm, loc_force)
total_force = total_force + loc_force
total_moment = total_moment + loc_moment
return [total_force, total_moment]
def approx_kite_tang_vector(variables, architecture, kite):
parent = architecture.parent_map[kite]
z_vec = tether_vector(variables, architecture, parent)
r_vec = approx_kite_radius_vector(variables, architecture, kite)
t_vec_dimensioned = vect_op.cross(z_vec, r_vec)
return t_vec_dimensioned
def approx_kite_normal_vector(variables, architecture, kite):
# z cross r = t
# r x t = n
r_vec = approx_kite_radius_vector(variables, architecture, kite)
t_vec = approx_kite_tang_vector(variables, architecture, kite)
n_vec = vect_op.cross(r_vec, t_vec)
return n_vec
def generate_rotational_dynamics(variables, f_nodes, parameters, outputs,
architecture):
kite_nodes = architecture.kite_nodes
parent_map = architecture.parent_map
j_inertia = parameters['theta0', 'geometry', 'j']
xd = variables['SI']['xd']
xddot = variables['SI']['xddot']
cstr_list = mdl_constraint.MdlConstraintList()
for kite in kite_nodes:
parent = parent_map[kite]
moment = f_nodes['m' + str(kite) + str(parent)]
rlocal = cas.reshape(xd['r' + str(kite) + str(parent)], (3, 3))
drlocal = cas.reshape(xddot['dr' + str(kite) + str(parent)], (3, 3))
omega = xd['omega' + str(kite) + str(parent)]
omega_skew = vect_op.skew(omega)
domega = xddot['domega' + str(kite) + str(parent)]
tether_moment = outputs['tether_moments']['n{}{}'.format(kite, parent)]
# moment = J dot(omega) + omega x (J omega) + [tether moment which is zero if holonomic constraints do not depend on omega]
J_dot_omega = cas.mtimes(j_inertia, domega)
omega_cross_J_omega = vect_op.cross(omega,
cas.mtimes(j_inertia, omega))
omega_derivative = moment - (J_dot_omega + omega_cross_J_omega +
tether_moment)
rotational_2nd_law = omega_derivative / vect_op.norm(
cas.diag(j_inertia))
rotation_dynamics_cstr = cstr_op.Constraint(expr=rotational_2nd_law,
name='rotation_dynamics' +
str(kite),
cstr_type='eq')
cstr_list.append(rotation_dynamics_cstr)
# Rdot = R omega_skew -> R ( kappa/2 (I - R.T R) + omega_skew )
baumgarte = parameters['theta0', 'kappa_r']
orthonormality = baumgarte / 2. * (cas.DM_eye(3) -
cas.mtimes(rlocal.T, rlocal))
ref_frame_deriv_matrix = drlocal - (cas.mtimes(
rlocal, orthonormality + omega_skew))
ref_frame_derivative = cas.reshape(ref_frame_deriv_matrix, (9, 1))
ortho_cstr = cstr_op.Constraint(expr=ref_frame_derivative,
name='ref_frame_deriv' + str(kite),
cstr_type='eq')
cstr_list.append(ortho_cstr)
return cstr_list, outputs
def get_binormal_n_vec(parent, variables, parameters, architecture):
children = architecture.kites_map[parent]
n_vec = np.zeros((3, 1))
for kite in children:
dqk = variables['xddot']['dq' + str(kite) + str(parent)]
ddqk = variables['xddot']['ddq' + str(kite) + str(parent)]
binormal_dim = vect_op.cross(dqk, ddqk)
n_vec = n_vec + binormal_dim
return n_vec
def get_actuator_moment(model_options, variables, outputs, parent,
architecture):
children = architecture.kites_map[parent]
total_moment_aero = np.zeros((3, 1))
for kite in children:
aero_force = outputs['aerodynamics']['f_aero_earth' + str(kite)]
kite_radius = actuator_geom.get_kite_radius_vector(
model_options, kite, variables, architecture)
aero_moment = vect_op.cross(kite_radius, aero_force)
total_moment_aero = total_moment_aero + aero_moment
return total_moment_aero
def get_binormal_nhat(parent, variables, parameters, architecture):
children = architecture.kites_map[parent]
nvec = np.zeros((3, 1))
for kite in children:
dqk = variables['xddot']['dq' + str(kite) + str(parent)]
ddqk = variables['xddot']['ddq' + str(kite) + str(parent)]
binormal_dim = vect_op.cross(dqk, ddqk)
nvec = nvec + binormal_dim
scale = 1.e-3
factor = scale * get_factor_var(parent, variables, parameters)
nhat = nvec * factor
return nhat
def get_element_drag_and_moment_fun(wind, atmos, cd_tether_fun):
info_sym = cas.SX.sym('info_sym', (16, 1))
q_upper = info_sym[:3]
q_lower = info_sym[3:6]
dq_upper = info_sym[6:9]
dq_lower = info_sym[9:12]
diam = info_sym[12]
q_seg_avg = info_sym[13:16]
q_average = (q_upper + q_lower) / 2.
zz = q_average[2]
ua = get_uapp(q_upper, q_lower, dq_upper, dq_lower, wind)
epsilon = 1.e-6
ua_norm = vect_op.smooth_norm(ua, epsilon)
ehat_ua = vect_op.smooth_normalize(ua, epsilon)
tether = q_upper - q_lower
length_sq = cas.mtimes(tether.T, tether)
length_parallel_to_wind = cas.mtimes(tether.T, ehat_ua)
length_perp_to_wind = vect_op.smooth_sqrt(
length_sq - length_parallel_to_wind**2., epsilon)
re_number = reynolds.get_reynolds_number(atmos, ua, diam, q_upper, q_lower)
cd = cd_tether_fun(re_number)
density = atmos.get_density(zz)
drag = cd * 0.5 * density * ua_norm * diam * length_perp_to_wind * ua
moment_arm = q_average - q_seg_avg
moment = vect_op.cross(moment_arm, drag)
element_drag_fun = cas.Function('element_drag_fun', [info_sym], [drag])
element_moment_fun = cas.Function('element_moment_fun', [info_sym],
[moment])
return element_drag_fun, element_moment_fun
def collect_kite_aerodynamics_outputs(options, architecture, atmos, wind,
variables, parameters,
base_aerodynamic_quantities, outputs):
if 'aerodynamics' not in list(outputs.keys()):
outputs['aerodynamics'] = {}
# unpack
kite = base_aerodynamic_quantities['kite']
air_velocity = base_aerodynamic_quantities['air_velocity']
aero_coefficients = base_aerodynamic_quantities['aero_coefficients']
f_aero_earth = base_aerodynamic_quantities['f_aero_earth']
f_aero_body = base_aerodynamic_quantities['f_aero_body']
f_aero_control = base_aerodynamic_quantities['f_aero_control']
f_aero_wind = base_aerodynamic_quantities['f_aero_wind']
f_lift_earth = base_aerodynamic_quantities['f_lift_earth']
f_drag_earth = base_aerodynamic_quantities['f_drag_earth']
f_side_earth = base_aerodynamic_quantities['f_side_earth']
m_aero_body = base_aerodynamic_quantities['m_aero_body']
kite_dcm = base_aerodynamic_quantities['kite_dcm']
q = base_aerodynamic_quantities['q']
f_lift_earth_overwrite = options['aero']['overwrite']['f_lift_earth']
if f_lift_earth_overwrite is not None:
f_lift_earth = f_lift_earth_overwrite
for name in set(base_aerodynamic_quantities['aero_coefficients'].keys()):
outputs['aerodynamics'][
name +
str(kite)] = base_aerodynamic_quantities['aero_coefficients'][name]
outputs['aerodynamics']['air_velocity' + str(kite)] = air_velocity
airspeed = vect_op.norm(air_velocity)
outputs['aerodynamics']['airspeed' + str(kite)] = airspeed
outputs['aerodynamics']['u_infty' + str(kite)] = wind.get_velocity(q[2])
rho = atmos.get_density(q[2])
outputs['aerodynamics']['air_density' + str(kite)] = rho
outputs['aerodynamics']['dyn_pressure' +
str(kite)] = 0.5 * rho * cas.mtimes(
air_velocity.T, air_velocity)
ehat_chord = kite_dcm[:, 0]
ehat_span = kite_dcm[:, 1]
ehat_up = kite_dcm[:, 2]
outputs['aerodynamics']['ehat_chord' + str(kite)] = ehat_chord
outputs['aerodynamics']['ehat_span' + str(kite)] = ehat_span
outputs['aerodynamics']['ehat_up' + str(kite)] = ehat_up
outputs['aerodynamics']['f_aero_body' + str(kite)] = f_aero_body
outputs['aerodynamics']['f_aero_control' + str(kite)] = f_aero_control
outputs['aerodynamics']['f_aero_earth' + str(kite)] = f_aero_earth
outputs['aerodynamics']['f_aero_wind' + str(kite)] = f_aero_wind
ortho = cas.reshape(cas.mtimes(kite_dcm.T, kite_dcm) - np.eye(3), (9, 1))
ortho_resi = cas.mtimes(ortho.T, ortho)
outputs['aerodynamics']['ortho_resi' + str(kite)] = ortho_resi
conversion_resis = []
conversion_targets = {
'control': f_aero_control,
'earth': f_aero_earth,
'wind': f_aero_wind
}
for f_aero_target in conversion_targets.values():
resi = 1. - vect_op.norm(f_aero_target) / vect_op.norm(f_aero_body)
conversion_resis = cas.vertcat(conversion_resis, resi)
resi = vect_op.norm(f_aero_earth - f_lift_earth - f_drag_earth -
f_side_earth) / vect_op.norm(f_aero_body)
conversion_resis = cas.vertcat(conversion_resis, resi)
outputs['aerodynamics']['check_conversion' + str(kite)] = conversion_resis
outputs['aerodynamics']['f_lift_earth' + str(kite)] = f_lift_earth
outputs['aerodynamics']['f_drag_earth' + str(kite)] = f_drag_earth
outputs['aerodynamics']['f_side_earth' + str(kite)] = f_side_earth
b_ref = parameters['theta0', 'geometry', 'b_ref']
c_ref = parameters['theta0', 'geometry', 'c_ref']
circulation_cross = vect_op.smooth_norm(
f_lift_earth) / b_ref / rho / vect_op.smooth_norm(
vect_op.cross(air_velocity, ehat_span))
circulation_cl = 0.5 * airspeed**2. * aero_coefficients[
'CL'] * c_ref / vect_op.smooth_norm(
vect_op.cross(air_velocity, ehat_span))
outputs['aerodynamics']['circulation_cross' +
str(kite)] = circulation_cross
outputs['aerodynamics']['circulation_cl' + str(kite)] = circulation_cl
outputs['aerodynamics']['circulation' + str(kite)] = circulation_cross
outputs['aerodynamics']['wingtip_ext' +
str(kite)] = q + ehat_span * b_ref / 2.
outputs['aerodynamics']['wingtip_int' +
str(kite)] = q - ehat_span * b_ref / 2.
outputs['aerodynamics']['fstar_aero' + str(kite)] = cas.mtimes(
air_velocity.T, ehat_chord) / c_ref
outputs['aerodynamics']['r' + str(kite)] = kite_dcm.reshape((9, 1))
if int(options['kite_dof']) == 6:
outputs['aerodynamics']['m_aero_body' + str(kite)] = m_aero_body
outputs['aerodynamics']['mach' + str(kite)] = get_mach(
options, atmos, air_velocity, q)
outputs['aerodynamics']['reynolds' + str(kite)] = get_reynolds(
options, atmos, air_velocity, q, parameters)
return outputs