1#@ s*: Label=FastTest 2#@ TODO REVIEW: Do the reliability methods also need NPSOL? 3#@ *: DakotaConfig=HAVE_DOT 4# DAKOTA Input File: dakota_rbdo_short_column_trsb.in 5# Optimization under uncertainty using reliability methods within a 6# trust-region surrogate-based RBDO approach. The RBDO problem is the 7# "short_column" problem from Kuschel and Rackwitz, 1997. The 8# published soln is (b,h) = (8.668, 25.0) with f = 216.7 9 10environment, 11 method_pointer = 'SBLO' 12 13method, 14 id_method = 'SBLO' 15 surrogate_based_local 16 model_pointer = 'OPTIM_M' 17 approx_method_pointer = 'OPTIM' 18# max_iterations = 50 19# soft_convergence_limit = 2 20 trust_region 21 initial_size = 0.2 22 contraction_factor = 0.5 23 expansion_factor = 1.50 24 25########################### 26# begin opt specification # 27########################### 28method, 29 id_method = 'OPTIM' 30 dot_sqp 31# npsol_sqp 32 convergence_tolerance = 1.e-8 33 34model, 35 id_model = 'OPTIM_M' 36 surrogate local taylor_series 37 variables_pointer = 'OPTIM_V' 38 responses_pointer = 'OPTIM_R' 39 actual_model_pointer = 'OPTIM_TRUTH' 40 41variables, 42 id_variables = 'OPTIM_V' 43 continuous_design = 2 44 initial_point 10. 15. 45 lower_bounds 5. 15. 46 upper_bounds 15. 25. 47 descriptors 'b' 'h' 48 49responses, 50# minimize b*h 51# s.t. p <= .00621 Cases 0,1 52# s.t. beta >= 2.5 Cases 2,3 53# s.t. z >= 0. Cases 4,5,6,7 54# NOTE: This specifies the TOTAL RESPONSE for the optimization, 55# which is a combination of nested & interface responses. 56 id_responses = 'OPTIM_R' 57 objective_functions = 1 58 nonlinear_inequality_constraints = 1 59 nonlinear_inequality_upper_bounds = .00621 #s0,#s1,#s2 60# nonlinear_inequality_lower_bounds = 2.5 #s3,#s4,#s5 61# nonlinear_inequality_lower_bounds = 0. #s6,#s7,#s8,#s9,#s10,#s11 62# nonlinear_inequality_upper_bounds = 1.e+50 #s3,#s4,#s5,#s6,#s7,#s8,#s9,#s10,#s11 63 analytic_gradients 64 no_hessians 65 66########################## 67# begin TS specification # 68########################## 69 70model, 71 id_model = 'OPTIM_TRUTH' 72 nested 73 variables_pointer = 'OPTIM_V' 74 sub_method_pointer = 'UQ' 75 responses_pointer = 'OPTIM_R' 76 primary_response_mapping = 1. 0. 0. 0. 0. 77 secondary_response_mapping = 0. 0. 0. 0. 1. 78 79########################## 80# begin UQ specification # 81########################## 82method, 83 id_method = 'UQ' 84 model_pointer = 'UQ_M' 85 local_reliability #nip 86 mpp_search x_taylor_mpp #s0,#s3,#s6,#s9 87# mpp_search u_taylor_mpp #s1,#s4,#s7,#s10 88# mpp_search no_approx #s2,#s5,#s8,#s11 89 num_response_levels = 0 1 #s0,#s1,#s2,#s3,#s4,#s5 90 response_levels = 0.0 #s0,#s1,#s2,#s3,#s4,#s5 91# compute reliabilities #s3,#s4,#s5 92# num_probability_levels = 0 1 #s6,#s7,#s8 93# probability_levels = .00621 #s6,#s7,#s8 94# num_reliability_levels = 0 1 #s9,#s10,#s11 95# reliability_levels = 2.5 #s9,#s10,#s11 96 cumulative distribution 97 98model, 99 id_model = 'UQ_M' 100 single 101 variables_pointer = 'UQ_V' 102 interface_pointer = 'UQ_I' 103 responses_pointer = 'UQ_R' 104 105variables, 106 id_variables = 'UQ_V' 107 continuous_design = 2 108 normal_uncertain = 2 109 means = 500.0 2000.0 110 std_deviations = 100.0 400.0 111 descriptors = 'P' 'M' 112 lognormal_uncertain = 1 113 means = 5.0 114 std_deviations = 0.5 115 descriptors = 'Y' 116 uncertain_correlation_matrix = 1 0.5 0 117 0.5 1 0 118 0 0 1 119 120interface, 121 id_interface = 'UQ_I' 122 direct 123 analysis_driver = 'short_column' 124 125responses, 126 id_responses = 'UQ_R' 127 response_functions = 2 128 analytic_gradients 129 no_hessians 130