1#@ On Windows: workdir issue?
2#@ *: DakotaConfig=UNIX
3# DAKOTA Input File: dakota_uq_timeseries_sop_optinterf.in
4# Mixed UQ with aleatory post-processing of optional interface simulation
5
6environment,
7	  method_pointer = 'EPISTEMIC'
8
9#################################
10# begin EPISTEMIC specification #
11#################################
12method,
13        id_method = 'EPISTEMIC'
14        model_pointer = 'EPIST_M'
15	polynomial_chaos
16	  sparse_grid_level = 1				#s0
17#	  expansion_order = 2				#s1
18#	  collocation_ratio = .5 seed = 12347		#s1
19
20model,
21        id_model = 'EPIST_M'
22        nested
23          variables_pointer  = 'EPIST_V'
24	  optional_interface_pointer  = 'OPTIONAL_I'
25	  optional_interface_responses_pointer = 'OPTIONAL_I_R'
26          sub_method_pointer = 'ALEATORY'
27          responses_pointer  = 'EPIST_R'
28          primary_variable_mapping   = 'E1'  'E2'  'E3'  'E4'
29	  			       'E5'  'E6'  'E7'  'E8'
30          primary_response_mapping   = 0. 0. 1.
31	hierarchical_tagging
32
33variables,
34        id_variables = 'EPIST_V'
35        uniform_uncertain = 8
36# coefficients for cubic polynomial trajectories with time:
37#                           const       linear      quad        cubic
38      	  lower_bounds    = 10.   0.1   10.   0.1  -0.2   5.   -0.03  0.05
39	  upper_bounds    = 20.   0.2   15.   0.3  -0.1   8.   -0.01  0.10
40	  descriptors     = 'E1'  'E2'  'E3'  'E4'  'E5'  'E6'  'E7'  'E8'
41
42responses,
43        id_responses = 'EPIST_R'
44        response_functions = 1
45        response_descriptors = 'PLOAS'
46        no_gradients
47        no_hessians
48
49##########################################
50# begin optional interface specification #
51##########################################
52interface,
53	id_interface = 'OPTIONAL_I'
54# make this part synchronous
55	fork
56	  analysis_driver = 'trajectory'
57	  work_directory named 'epistemic_simulation'
58# Note: file tagging affects the directory tag that's employed
59	  directory_tag directory_save   #file_tag file_save
60	  parameters_file = 'epist_params.in'
61	  results_file    = 'epist_results.out'
62
63responses,
64	id_responses = 'OPTIONAL_I_R'
65	response_functions = 0 # No response contribution; just a sim driver
66	no_gradients
67	no_hessians
68
69################################
70# begin ALEATORY specification #
71################################
72method,
73        id_method = 'ALEATORY'
74        model_pointer = 'ALEAT_M'
75	polynomial_chaos
76	  askey non_nested
77	  sparse_grid_level = 3
78          response_levels = 0.0
79          compute probabilities
80	  samples_on_emulator = 10000 seed = 12347 fixed_seed
81          cumulative distribution
82
83model,
84        id_model = 'ALEAT_M'
85        single
86          variables_pointer = 'ALEAT_V'
87          interface_pointer = 'ALEAT_I'
88          responses_pointer = 'ALEAT_R'
89# files not named, so reliant on content inside parameters files
90
91variables,
92        id_variables = 'ALEAT_V'
93# inactive variables passed from outer epistemic loop
94        continuous_state = 8
95	  descriptors     = 'E1'  'E2'  'E3'  'E4'  'E5'  'E6'  'E7'  'E8'
96# active variables on inner aleatory loop
97	normal_uncertain = 2
98	  means          =   80.0   300.0
99	  std_deviations =   20.0    75.0
100	  descriptors    = 'FailThresh1' 'FailThresh2'
101
102interface,
103	id_interface = 'ALEAT_I'
104# this part may execute asynchronously
105	fork asynchronous evaluation_concurrency = 6
106	  analysis_driver = 'trajectory_post'
107	  work_directory named 'aleatory_processing'
108# Note: file tagging affects the directory tag that's employed
109	  directory_tag directory_save file_save
110	  parameters_file = 'aleat_params.in'
111	  results_file    = 'aleat_results.out'
112	deactivate evaluation_cache
113
114responses,
115        id_responses = 'ALEAT_R'
116        response_functions = 1
117        response_descriptors = 'DeltaTime'
118        no_gradients
119        no_hessians
120
121