Source code for openmdao.test_suite.scripts.sellar

import numpy as np

import openmdao.api as om
from openmdao.test_suite.components.sellar import SellarDis1, SellarDis2


[docs]class SellarMDAConnect(om.Group):
[docs] def setup(self): cycle = self.add_subsystem('cycle', om.Group(), promotes_inputs=['x', 'z']) cycle.add_subsystem('d1', SellarDis1(), promotes_inputs=['x', 'z']) cycle.add_subsystem('d2', SellarDis2(), promotes_inputs=['z']) cycle.connect('d1.y1', 'd2.y1') ###################################### # This is a "forgotten" connection!! ###################################### #cycle.connect('d2.y2', 'd1.y2') cycle.set_input_defaults('x', 1.0) cycle.set_input_defaults('z', np.array([5.0, 2.0])) # Nonlinear Block Gauss Seidel is a gradient free solver cycle.nonlinear_solver = om.NonlinearBlockGS() self.add_subsystem('obj_cmp', om.ExecComp('obj = x**2 + z[1] + y1 + exp(-y2)', z=np.array([0.0, 0.0]), x=0.0), promotes_inputs=['x', 'z']) self.add_subsystem('con_cmp1', om.ExecComp('con1 = 3.16 - y1')) self.add_subsystem('con_cmp2', om.ExecComp('con2 = y2 - 24.0')) self.connect('cycle.d1.y1', ['obj_cmp.y1', 'con_cmp1.y1']) self.connect('cycle.d2.y2', ['obj_cmp.y2', 'con_cmp2.y2'])
prob = om.Problem() prob.model = SellarMDAConnect() prob.driver = om.ScipyOptimizeDriver() prob.driver.options['optimizer'] = 'SLSQP' # prob.driver.options['maxiter'] = 100 prob.driver.options['tol'] = 1e-8 prob.set_solver_print(level=0) prob.model.add_design_var('x', lower=0, upper=10) prob.model.add_design_var('z', lower=0, upper=10) prob.model.add_objective('obj_cmp.obj') prob.model.add_constraint('con_cmp1.con1', upper=0) prob.model.add_constraint('con_cmp2.con2', upper=0) prob.setup() prob.set_val('x', 2.0) prob.set_val('z', [-1., -1.]) prob.run_driver() print('minimum found at') print(prob.get_val('x')[0]) print(prob.get_val('z')) print('minumum objective') print(prob.get_val('obj_cmp.obj')[0])