1#@ s*: Label=FastTest
2#@ p*: Label=FastTest
3#@ p0: MPIProcs=2
4#@ s0: UserMan=cantilever_uq_sop_rel
5# DAKOTA Input File: dakota_uq_cantilever_sop_rel.in
6# Dakota Input File: cantilever_uq_sop_rel.in                           #s0
7# Second-order probability (SOP) for the cantilever test function using
8# reliability methods on the inner loop.
9
10# Combines EPISTEMIC UQ using sampling with ALEATORY UQ using
11# local_reliability.  Note that test 0 is the test where the outer loop is
12# treated as an interval variable, and test 1 is the case where the outer loop
13# is treated as uniform.  For test 0, the outer loop statistics are reported as
14# intervals on the inner loop statistics, where in test 1 they are treated as a
15# regular probability case in the outer loop.
16
17environment
18    top_method_pointer = 'EPISTEMIC'
19
20#################################
21# begin EPISTEMIC specification #
22#################################
23method
24  id_method = 'EPISTEMIC'
25  sampling
26    samples = 50 seed = 12347
27#	  response_levels = 9.52 3.0 3.0 #s1
28    model_pointer = 'EPIST_M'
29
30model
31  id_model = 'EPIST_M'
32  nested
33    sub_method_pointer = 'ALEATORY'
34    primary_variable_mapping   = 'X'    'Y'
35    secondary_variable_mapping = 'mean' 'mean'
36    primary_response_mapping   = 1. 0. 0. 0. 0. 0. 0. 0.
37                                 0. 0. 0. 0. 1. 0. 0. 0.
38                                 0. 0. 0. 0. 0. 0. 0. 1.
39  variables_pointer  = 'EPIST_V'
40  responses_pointer  = 'EPIST_R'
41
42variables
43  id_variables = 'EPIST_V'
44  continuous_interval_uncertain = 2       #s0,#p0
45    num_intervals = 1 1                   #s0,#p0
46    interval_probabilities =      1.0       1.0	  #s0,#p0
47    lower_bounds =      400.0     800.0	  #s0,#p0
48    upper_bounds =      600.0    1200.0	  #s0,#p0
49    descriptors      'X_mean'  'Y_mean'   #s0,#p0
50#  uniform_uncertain = 2			            #s1
51#    lower_bounds    400.   800.		      #s1
52#    upper_bounds    600.  1200.          #s1
53#    descriptors       'X_mean' 'Y_mean'	#s1
54
55responses
56# minimize mean Weight
57# s.t.     beta_S/D >= 3
58#
59# NOTE: This specifies the TOTAL RESPONSE for the optimization,
60#       which is a combination of nested & interface responses.
61  id_responses = 'EPIST_R'
62  response_functions = 3
63  descriptors = 'mean_wt' 'ccdf_beta_s' 'ccdf_beta_d'
64  no_gradients
65  no_hessians
66
67################################
68# begin ALEATORY specification #
69################################
70method
71  id_method = 'ALEATORY'
72  local_reliability
73    mpp_search no_approx
74    response_levels = 0.0 0.0
75      num_response_levels = 0 1 1
76    compute reliabilities
77    distribution complementary
78    model_pointer = 'ALEAT_M'
79
80model
81  id_model = 'ALEAT_M'
82  single
83    interface_pointer = 'ALEAT_I'
84  variables_pointer = 'ALEAT_V'
85  responses_pointer = 'ALEAT_R'
86
87variables
88  id_variables = 'ALEAT_V'
89  continuous_design = 2
90    initial_point    2.4522 3.8826
91    descriptors 'w' 't'
92  normal_uncertain = 4
93    means             =  40000. 29.E+6 500. 1000.
94    std_deviations    =  2000. 1.45E+6 100. 100.
95    descriptors       =  'R' 'E' 'X' 'Y'
96
97interface
98  id_interface = 'ALEAT_I'
99  analysis_drivers = 'cantilever'
100    direct
101  deactivate evaluation_cache restart_file
102
103responses
104  id_responses = 'ALEAT_R'
105  response_functions = 3
106  descriptors = 'weight' 'stress' 'displ'
107  analytic_gradients					#s0,#s1
108#  numerical_gradients					#p0
109#    method_source dakota				#p0
110#    interval_type central				#p0
111#    fd_gradient_step_size = 0.0001			#p0
112  no_hessians
113