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_analytic.in 5# Optimization under uncertainty using reliability methods within a 6# fully-analytic bi-level 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 = 'OPTIM' 12 13########################### 14# begin opt specification # 15########################### 16method, 17 id_method = 'OPTIM' 18 model_pointer = 'OPTIM_M' 19# npsol_sqp 20 dot_sqp 21 convergence_tolerance = 1.e-8 22 23model, 24 id_model = 'OPTIM_M' 25 nested 26 variables_pointer = 'OPTIM_V' 27 sub_method_pointer = 'UQ' 28 responses_pointer = 'OPTIM_R' 29 primary_response_mapping = 1. 0. 0. 0. 0. 30 secondary_response_mapping = 0. 0. 0. 0. 1. 31 32variables, 33 id_variables = 'OPTIM_V' 34 continuous_design = 2 35 initial_point 10. 15. 36 lower_bounds 5. 15. 37 upper_bounds 15. 25. 38 descriptors 'b' 'h' 39 40responses, 41# minimize b*h 42# s.t. p <= .00621 Cases 0,1 43# s.t. beta >= 2.5 Cases 2,3 44# s.t. z >= 0. Cases 4,5,6,7 45# NOTE: This specifies the TOTAL RESPONSE for the optimization, 46# which is a combination of nested & interface responses. 47 id_responses = 'OPTIM_R' 48 objective_functions = 1 49 nonlinear_inequality_constraints = 1 50 nonlinear_inequality_upper_bounds = .00621 #s0,#s1,#s2 51# nonlinear_inequality_lower_bounds = 2.5 #s3,#s4,#s5 52# nonlinear_inequality_lower_bounds = 0. #s6,#s7,#s8,#s9,#s10,#s11 53# nonlinear_inequality_upper_bounds = 1.e+50 #s3,#s4,#s5,#s6,#s7,#s8,#s9,#s10,#s11 54 analytic_gradients 55 no_hessians 56 57########################## 58# begin UQ specification # 59########################## 60method, 61 id_method = 'UQ' 62 model_pointer = 'UQ_M' 63 local_reliability #nip 64 mpp_search x_taylor_mpp #s0,#s3,#s6,#s9 65# mpp_search u_taylor_mpp #s1,#s4,#s7,#s10 66# mpp_search no_approx #s2,#s5,#s8,#s11 67 num_response_levels = 0 1 #s0,#s1,#s2,#s3,#s4,#s5 68 response_levels = 0.0 #s0,#s1,#s2,#s3,#s4,#s5 69# compute reliabilities #s3,#s4,#s5 70# num_probability_levels = 0 1 #s6,#s7,#s8 71# probability_levels = .00621 #s6,#s7,#s8 72# num_reliability_levels = 0 1 #s9,#s10,#s11 73# reliability_levels = 2.5 #s9,#s10,#s11 74 cumulative distribution 75 76model, 77 id_model = 'UQ_M' 78 single 79 variables_pointer = 'UQ_V' 80 interface_pointer = 'UQ_I' 81 responses_pointer = 'UQ_R' 82 83variables, 84 id_variables = 'UQ_V' 85 continuous_design = 2 86 normal_uncertain = 2 87 means = 500.0 2000.0 88 std_deviations = 100.0 400.0 89 descriptors = 'P' 'M' 90 lognormal_uncertain = 1 91 means = 5.0 92 std_deviations = 0.5 93 descriptors = 'Y' 94 uncertain_correlation_matrix = 1 0.5 0 95 0.5 1 0 96 0 0 1 97 98interface, 99 id_interface = 'UQ_I' 100 direct 101 analysis_driver = 'short_column' 102 103responses, 104 id_responses = 'UQ_R' 105 response_functions = 2 106 analytic_gradients 107 no_hessians 108