def get_minpar(apar):
"""Function for returning parameter to be minimized."""
te_pair.I = apar[0]
te_pair.leg_area_ratio = apar[1]
te_pair.set_area()
te_pair.set_constants()
te_pair.solve_te_pair()
minpar = 1. / te_pair.P
return minpar
# Sherman.
te_pair = te_pair.TE_PAIRodule()
te_pair.I = current
te_pair.Ntype.material = 'MgSi'
te_pair.Ptype.material = 'HMS'
te_pair.T_h_goal = 500.
te_pair.T_c = 300.
te_pair.Ptype.node = 0
te_pair.Ntype.node = 0
te_pair.Ptype.area = area
te_pair.Ntype.area = te_pair.Ptype.area * area_ratio
te_pair.length = length
te_pair.area_void = 0.
te_pair.method = 'analytical'
te_pair.set_constants()
te_pair.solve_te_pair()
T_props = np.linspace(300,450.,100)
T_h_goal = np.linspace(300,600.,100)
A_opt = np.empty(np.size(T_props))
xi_opt = np.empty(np.size(T_props))
eta_max = np.empty(np.size(T_props))
abc = np.empty([np.size(T_props),3])
for i in range(np.size(T_props)):
te_pair.T_props = T_props[i]
te_pair.set_A_opt()
A_opt[i] = te_pair.A_opt
for i in range(np.size(T_h_goal)):
