1#@ s*: Label=FastTest
2#@ *: DakotaConfig=HAVE_NPSOL
3# DAKOTA Input File: dakota_rbdo_cantilever_trsb.in
4# Trust-region surrogate-based RBDO using the cantilever test function.
5
6environment,
7	method_pointer = 'SBLO'
8
9method,
10	id_method = 'SBLO'
11	surrogate_based_local
12	model_pointer = 'OPTIM_M'
13	  approx_method_pointer = 'OPTIM'
14#	  max_iterations = 50
15#	  soft_convergence_limit = 2
16	  trust_region
17	    initial_size = 0.2
18	    contraction_factor = 0.5
19	    expansion_factor   = 1.50
20	  output verbose
21
22###########################
23# begin opt specification #
24###########################
25method,
26	id_method = 'OPTIM'
27#	dot_sqp
28	npsol_sqp
29	  convergence_tolerance = 1.e-6
30
31model,
32	id_model = 'OPTIM_M'
33	surrogate local taylor_series
34	  variables_pointer = 'OPTIM_V'
35	  actual_model_pointer = 'OPTIM_TRUTH'
36	  responses_pointer = 'OPTIM_R'
37
38variables,
39	id_variables = 'OPTIM_V'
40	continuous_design = 2
41	  initial_point    2.5    2.5
42	  upper_bounds    10.0   10.0
43	  lower_bounds     1.0    1.0
44	  descriptors 'w' 't'
45
46responses,
47# minimize mean Weight
48# s.t.     p_S/D    <= .00135 Cases 0,1,2,3
49# s.t.     beta_S/D >= 3      Cases 4,5,6,7
50# s.t.     z_S/D    <= 0.     Cases 8,9,10,11,12,13,14,15
51#
52# NOTE: This specifies the TOTAL RESPONSE for the optimization,
53#       which is a combination of nested & interface responses.
54	id_responses = 'OPTIM_R'
55	objective_functions = 1
56	nonlinear_inequality_constraints = 2
57	nonlinear_inequality_upper_bounds = .00135 .00135 #s0,#s1
58#	nonlinear_inequality_lower_bounds = 3. 3.	  #s2,#s3
59#	nonlinear_inequality_upper_bounds = 1.e+50 1.e+50 #s2,#s3
60	analytic_gradients
61	no_hessians
62
63##########################
64# begin TS specification #
65##########################
66model,
67	id_model = 'OPTIM_TRUTH'
68	nested
69	  variables_pointer  = 'OPTIM_V'
70	  sub_method_pointer = 'UQ'
71	  primary_response_mapping   = 1. 0. 0. 0. 0. 0. 0. 0.
72	  secondary_response_mapping = 0. 0. 0. 0. 1. 0. 0. 0.
73				       0. 0. 0. 0. 0. 0. 0. 1.
74	  responses_pointer  = 'OPTIM_R'
75
76##########################
77# begin UQ specification #
78##########################
79method,
80	id_method = 'UQ'
81	model_pointer = 'UQ_M'
82	local_reliability nip
83	  mpp_search x_taylor_mpp		#s0,#s2,#s4,#s6
84#	  mpp_search no_approx			#s1,#s3,#s5,#s7
85	  num_response_levels = 0 1 1		#s0,#s1,#s2,#s3
86	  response_levels = 0.0 0.0		#s0,#s1,#s2,#s3
87#	  compute reliabilities			#s2,#s3
88#	  num_probability_levels = 0 1 1	#s4,#s5
89#	  probability_levels = .00135 .00135	#s4,#s5
90#	  num_reliability_levels = 0 1 1	#s6,#s7
91#	  reliability_levels = 3. 3.		#s6,#s7
92# g functions scaled using deterministic opt. conventions:
93# g<=0 is safe/feasible, g>0 is failed/violated.  Therefore,
94# we desire a complementary cumulative reliability index.
95	  complementary distribution
96
97model,
98	id_model = 'UQ_M'
99	single
100	  variables_pointer = 'UQ_V'
101	  interface_pointer = 'UQ_I'
102	  responses_pointer = 'UQ_R'
103
104variables,
105	id_variables = 'UQ_V'
106# continuous_design is not required (OUU will augment
107# automatically), but it is good form
108	continuous_design = 2
109	normal_uncertain = 4
110	  means             =  40000. 29.E+6 500. 1000.
111	  std_deviations    =  2000. 1.45E+6 100. 100.
112	  descriptors       =  'R' 'E' 'X' 'Y'
113
114interface,
115	id_interface = 'UQ_I'
116	direct
117	  analysis_driver = 'cantilever'
118#	  deactivate evaluation_cache restart_file
119
120responses,
121	id_responses = 'UQ_R'
122	response_functions = 3
123	analytic_gradients
124#	numerical_gradients
125#	  method_source dakota
126#	  interval_type central
127#	  fd_gradient_step_size = 1.e-4
128	no_hessians
129