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