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