minimdo

Toolkit for formulating conceptual design equations, changing between declarative and input/output formulations and solve the resulting system of equations.

Minimal example

This is minimal code for running the Sellar problem (https://openmdao.org/newdocs/versions/latest/basic_user_guide/multidisciplinary_optimization/sellar_opt.html#)

z1,z2,x,y2 = Var('z1'), Var('z2'), Var('x'), Var('y2')

model = Model(solver=OPT)
m = model.root
a = adda(m, 'a', z2+x-0.2*y2)
y1 = adda(m, 'y1', z1**2+a)
adda(m, y2, y1**0.5+z1+z2)
addobj(m, x**2+z2+y1+exp(-y2)) 
addineq(m, 3.16-y1) 
addineq(m, y2-24) 
setsolvefor(m, [x,z1,z2], {x:[0,10], z1:[0,10], z2:[0,10]})
prob, mdao_in, groups = model.generate_mdao()

prob.run_driver() # optimal value about 3.183

organization

• ds: data structures |--- ds_symbolic |--- ds_units |--- ds_funcstruct |--- ds_tree |--- ds_notation
• cp: compute |--- cp_mdao |--- cp_operators
• al: algorithms |--- al_matching - Matching bipartite graph |--- al_tearing - Chosing tearing variables to optimize structure |--- al_inputopt - Chosing inputs to optimize structure |--- al_ma - Monotonicity Analysis
• vz: visualizations |--- vz_graphs |--- vz_dsm
• app: applications |--- app_allison |--- app_pump - Example from Allisons thesis |--- app_coffee |--- app_balloon |--- app_minisat - 5 eqs system spacecraft |--- app_miniac - 7 eqs aircraft |--- app_sat |--- app_pearl