1#@ TODO REVIEW: Do the reliability methods also need NPSOL?
2#@ *: DakotaConfig=HAVE_DOT
3#@ s8: TimeoutAbsolute=2100
4#@ s11: TimeoutAbsolute=2100
5
6# DAKOTA Input File: dakota_rbdo_short_column_analytic.in
7# Optimization under uncertainty using reliability methods within a
8# fully-analytic bi-level RBDO approach.  The RBDO problem is the
9# "short_column" problem from Kuschel and Rackwitz, 1997.  The
10# published soln is (b,h) = (8.668, 25.0) with f = 216.7
11
12environment,
13	  method_pointer = 'OPTIM'
14
15###########################
16# begin opt specification #
17###########################
18method,
19	id_method = 'OPTIM'
20	model_pointer = 'OPTIM_M'
21#	npsol_sqp
22	dot_sqp
23	  convergence_tolerance = 1.e-8
24	  output verbose
25
26model,
27	id_model = 'OPTIM_M'
28	nested
29	  variables_pointer  = 'OPTIM_V'
30	  sub_method_pointer = 'UQ'
31	  responses_pointer  = 'OPTIM_R'
32	  primary_response_mapping   = 1. 0. 0. 0. 0.
33	  secondary_response_mapping = 0. 0. 0. 0. 1.
34
35variables,
36	id_variables = 'OPTIM_V'
37	continuous_design = 2
38	  initial_point    10.    15.
39	  lower_bounds      5.    15.
40	  upper_bounds     15.    25.
41	  descriptors      'b'    'h'
42
43responses,
44# minimize b*h
45# s.t.     p    <= .00621  Cases 0,1
46# s.t.     beta >= 2.5     Cases 2,3
47# s.t.     z    >= 0.      Cases 4,5,6,7
48# NOTE: This specifies the TOTAL RESPONSE for the optimization,
49#       which is a combination of nested & interface responses.
50	id_responses = 'OPTIM_R'
51	objective_functions = 1
52	nonlinear_inequality_constraints = 1
53	nonlinear_inequality_upper_bounds = .00621 #s0,#s1,#s2
54#	nonlinear_inequality_lower_bounds = 2.5	   #s3,#s4,#s5
55#	nonlinear_inequality_lower_bounds = 0.     #s6,#s7,#s8,#s9,#s10,#s11
56#	nonlinear_inequality_upper_bounds = 1.e+50 #s3,#s4,#s5,#s6,#s7,#s8,#s9,#s10,#s11
57	analytic_gradients
58	no_hessians
59
60##########################
61# begin UQ specification #
62##########################
63method,
64	id_method = 'UQ'
65	model_pointer = 'UQ_M'
66	local_reliability #nip
67	  mpp_search x_taylor_mpp		#s0,#s3,#s6,#s9
68#	  mpp_search u_taylor_mpp		#s1,#s4,#s7,#s10
69#	  mpp_search no_approx			#s2,#s5,#s8,#s11
70	  num_response_levels = 0 1		#s0,#s1,#s2,#s3,#s4,#s5
71	  response_levels = 0.0			#s0,#s1,#s2,#s3,#s4,#s5
72#	  compute gen_reliabilities		#s3,#s4,#s5
73	  integration second_order
74#	  num_probability_levels = 0 1		#s6,#s7,#s8
75#	  probability_levels = .00621		#s6,#s7,#s8
76#	  num_gen_reliability_levels = 0 1	#s9,#s10,#s11
77#	  gen_reliability_levels = 2.5		#s9,#s10,#s11
78	  cumulative distribution
79
80model,
81	id_model = 'UQ_M'
82	single
83	  variables_pointer = 'UQ_V'
84	  interface_pointer = 'UQ_I'
85	  responses_pointer = 'UQ_R'
86
87variables,
88	id_variables = 'UQ_V'
89	continuous_design = 2
90	normal_uncertain = 2
91	  means              =  500.0   2000.0
92	  std_deviations     =  100.0    400.0
93	  descriptors        =   'P'      'M'
94	lognormal_uncertain = 1
95       	  means             =  5.0
96	  std_deviations    =  0.5
97	  descriptors       =  'Y'
98	uncertain_correlation_matrix =  1   0.5 0
99					0.5 1   0
100					0   0   1
101
102interface,
103	id_interface = 'UQ_I'
104	direct
105	  analysis_driver = 'short_column'
106
107responses,
108	id_responses = 'UQ_R'
109	response_functions = 2
110	analytic_gradients
111	analytic_hessians
112