def compute(self, inputs, outputs):
z_full = inputs["z_full"]
z_param = inputs["z_param"]
z_section = 0.5 * (z_full[:-1] + z_full[1:])
outputs["height_constraint"] = inputs["hub_height"] - z_param[-1]
outputs["rho_full"] = util.sectionalInterp(z_section, z_param, inputs["rho"])
outputs["outfitting_full"] = util.sectionalInterp(z_section, z_param, inputs["outfitting_factor"])
outputs["unit_cost_full"] = util.sectionalInterp(z_section, z_param, inputs["unit_cost"])
outputs["E_full"] = util.sectionalInterp(z_section, z_param, inputs["E"])
outputs["G_full"] = util.sectionalInterp(z_section, z_param, inputs["G"])
outputs["sigma_y_full"] = util.sectionalInterp(z_section, z_param, inputs["sigma_y"])
# Unpack for Elastodyn
z = 0.5 * (z_param[:-1] + z_param[1:])
rho = inputs["rho"]
E = inputs["E"]
G = inputs["G"]
Az = util.sectionalInterp(z, z_full, inputs["Az"])
Ixx = util.sectionalInterp(z, z_full, inputs["Ixx"])
Iyy = util.sectionalInterp(z, z_full, inputs["Iyy"])
Jz = util.sectionalInterp(z, z_full, inputs["Jz"])
outputs["sec_loc"] = (z - z[0]) / (z[-1] - z[0])
outputs["mass_den"] = rho * Az
outputs["foreaft_iner"] = rho * Ixx
outputs["sideside_iner"] = rho * Iyy
outputs["foreaft_stff"] = E * Ixx
outputs["sideside_stff"] = E * Iyy
outputs["tor_stff"] = G * Jz
outputs["axial_stff"] = E * Az
def compute(self, inputs, outputs):
# Check to make sure we have good values
if np.any(inputs["section_height"] <= 0.0):
raise ValueError(
"Section height values must be greater than zero, " +
str(inputs["section_height"]))
if np.any(inputs["wall_thickness"] <= 0.0):
raise ValueError(
"Wall thickness values must be greater than zero, " +
str(inputs["wall_thickness"]))
if np.any(inputs["diameter"] <= 0.0):
raise ValueError("Diameter values must be greater than zero, " +
str(inputs["diameter"]))
nRefine = int(np.round(self.options["nRefine"]))
z_param = float(inputs["foundation_height"]) + np.r_[
0.0, np.cumsum(inputs["section_height"].flatten())]
# Have to regine each element one at a time so that we preserve input nodes
z_full = np.array([])
for k in range(z_param.size - 1):
zref = np.linspace(z_param[k], z_param[k + 1], nRefine + 1)
z_full = np.append(z_full, zref)
z_full = np.unique(z_full)
outputs["z_full"] = z_full
outputs["d_full"] = np.interp(z_full, z_param, inputs["diameter"])
z_section = 0.5 * (z_full[:-1] + z_full[1:])
outputs["t_full"] = util.sectionalInterp(z_section, z_param,
inputs["wall_thickness"])
outputs["z_param"] = z_param
def testSectionalInterp(self):
x = np.arange(0.0, 2.1, 0.5)
y = np.array([-1.0, 1.0, -2.0, 2.0])
xi = np.array([-0.1, 0.25, 0.9, 1.4, 1.5, 1.6, 2.1])
yi = util.sectionalInterp(xi, x, y)
y_expect = np.array([-1.0, -1.0, 1.0, -2.0, 2.0, 2.0, 2.0])
npt.assert_array_equal(yi, y_expect)
def compute(self, inputs, outputs):
nRefine = int(np.round(self.options['nRefine']))
z_param = float(inputs['foundation_height']) + np.r_[
0.0, np.cumsum(inputs['section_height'].flatten())]
# Have to regine each element one at a time so that we preserve input nodes
z_full = np.array([])
for k in range(z_param.size - 1):
zref = np.linspace(z_param[k], z_param[k + 1], nRefine + 1)
z_full = np.append(z_full, zref)
z_full = np.unique(z_full)
outputs['z_full'] = z_full
outputs['d_full'] = np.interp(z_full, z_param, inputs['diameter'])
z_section = 0.5 * (z_full[:-1] + z_full[1:])
outputs['t_full'] = sectionalInterp(z_section, z_param,
inputs['wall_thickness'])
outputs['z_param'] = z_param
