Hi @damarginal

Here are the scripts. It says new users cannot upload, so I will copy paste them here:

## The UQLink Script:

fclose all;

clearvars;

clc;

Restart = 0;

%%= 0 is not restart, = 1 is restart

Analysis_Type = 1; % = 1 is model eval, = 2 is SOBOL analysis

Sample_Size = 1000;

%%

%% NAME DIRECTORIES AND VARIABLES, AND DELETE OLD FILES

Current_Folder=pwd;

%%find current dir

files = ls(‘AUTO_EAE_UQLab*.inp’); % (list of files with AUTO_EAE_UQLab*.inp)

for n = 1: size(files, 1)

delete(strtrim(files(n,:)));

end

if isunix

%% Unix

copyfile(strcat(Current_Folder,’/UQInput_Template/AUTO_EAE_UQLab.inp’), Current_Folder, ‘f’)

elseif ispc % Windows

copyfile(strcat(Current_Folder,’\UQInput_Template\AUTO_EAE_UQLab.inp’), Current_Folder, ‘f’)

end

if Restart == 0

%% = 0 is not restart so delete old folders

delete(‘AUTO_EAE_UQLab.zip’)

end

if ispc

Exe_File = ‘AAPU_EAE_UQ_Function_ELM2’;

%%this is the external .exe program

elseif isunix

Exe_File = ‘run_AAPU_EAE_UQ_Function_ELM2_Linux.sh’;

%% this is the external .sh program

end

%/global/software/matlab/R2017a/

Input_File = ‘AUTO_EAE_UQLab.inp’;

Output_File = ‘AUTO_EAE_UQLab.out’;

timer = tic;

%% INITIALIZE UQLAB

if isunix

%%Unix

cd /global/home/hpc4077/UQLab/core

uqlab

cd(Current_Folder);

elseif ispc % Windows

uqlab

end

%%

%%Model type:

Mopts.Type = ‘UQLink’ ;

Mopts.Name = ‘AUTO_EAE_UQLab’;

%%

%%Mandatory options:)

%%Provide the command line, i.e. a sample of the command line that will be)

%%run on the shell

if ispc

%%Windows

Command = strcat([Exe_File, ’ ‘, Input_File]);

elseif isunix

%%Unix

Deliminator = ‘"’;

Executable = [Deliminator fullfile(Current_Folder,Exe_File) Deliminator];

Command = sprintf(’%%s %%s %%s’, Executable, Input_File);

end

Mopts.Command = Command ; % load the file then run the matlab script

%%

%%Provide the template file, i.e. a copy of the original input files)

%%where the inputs of interest are replaced by markers:)

Mopts.Template = strcat(Input_File, ‘.tpl’);

%%

%%Provide the MATLAB file that is used to retrieve the quantity of interest)

%%from the code output file:)

Mopts.Output.FileName = Output_File ;

if isunix

%%Unix

Mopts.Output.Parser = ‘uq_readOutput’ ;

elseif ispc % Windows

Mopts.Output.Parser = ‘uq_readOutput’ ;

end

%%

% Format of the variables written in the Abaqus input file

Mopts.Format = {’%6.5f’};

%%

% Set the display to quiet

ModelOpts.Display = ‘quiet’ ;

%%

% Create the UQLink wrapper:

AUTO_EAE_Model = uq_createModel(Mopts) ;

%% 3 - DEFINE THE PROBABILISTIC MODEL

inputopts.Marginals(1).Name = ‘Pellet_Dia’;

inputopts.Marginals(1).Type = ‘Lognormal’ ; % Lognormal 0.96073 vs Gaussian 0.96070

inputopts.Marginals(1).Moments = [12.210092 0.00328781] ;

inputopts.Marginals(2).Name = ‘Sheath_ID’;

inputopts.Marginals(2).Type = ‘Lognormal’ ; % Lognormal 0.976272368 vs Gaussian 0.976253242

inputopts.Marginals(2).Moments = [12.299666 0.003665] ;

inputopts.Marginals(3).Name = ‘Dish_Dpth’;

inputopts.Marginals(3).Type = ‘Lognormal’ ; % Lognormal 0.913672446 vs Gaussian 0.895779768

inputopts.Marginals(3).Moments = [0.2098888889 0.0146364505] ;

inputopts.Marginals(4).Name = ‘Land_Width’;

inputopts.Marginals(4).Type = ‘Lognormal’ ; % Lognormal 0.967042334 vs Gaussian 0.959241921

inputopts.Marginals(4).Moments = [0.8235563 0.0324305] ;

inputopts.Marginals(5).Name = ‘Pelt_Density’;

inputopts.Marginals(5).Type = ‘Gaussian’ ; % Lognormal 0.992068054 vs Gaussian 0.992175757

inputopts.Marginals(5).Moments = [10.6256873 0.0198114] ;

inputopts.Marginals(6).Name = ‘Stac_Lengt’;

inputopts.Marginals(6).Type = ‘Gaussian’ ; % BASED ON ASSUMPTION OF GAUSSIAN, MEAN CENTERED BETWEEN MANUFACTURER MAX AND MIN TOLERANCE

inputopts.Marginals(6).Moments = [481.42500 0.261666667] ;

inputopts.Marginals(7).Name = ‘Sheat_Lengt’;

inputopts.Marginals(7).Type = ‘Gaussian’ ; % BASED ON ASSUMPTION OF GAUSSIAN, MEAN CENTERED BETWEEN MANUFACTURER MAX AND MIN TOLERANCE

inputopts.Marginals(7).Moments = [486.1300 0.016666667] ;

inputopts.Marginals(8).Name = ‘Weld_Disp_A’;

inputopts.Marginals(8).Type = ‘Gaussian’ ; % Lognormal 0.965769662 vs Gaussian 0.9706230 vs Weibull 0.977885841

inputopts.Marginals(8).Moments = [0.035528 0.000677] ;

inputopts.Marginals(9).Name = ‘Weld_Disp_B’;

inputopts.Marginals(9).Type = ‘Gaussian’ ; % Lognormal 0.965769662 vs Gaussian 0.9706230 vs Weibull 0.977885841

inputopts.Marginals(9).Moments = [0.035528 0.000677] ;

inputopts.Marginals(10).Name = ‘Sheat_Thick’;

inputopts.Marginals(10).Type = ‘Lognormal’ ; % Lognormal 0.973156331 vs Gaussian 0.972522273

inputopts.Marginals(10).Moments = [0.4008627 0.0018982] ;

inputopts.Marginals(11).Name = ‘He_Fract’;

inputopts.Marginals(11).Type = ‘Lognormal’ ; % Lognormal 0.976818174 vs Gaussian 0.973329443

inputopts.Marginals(11).Moments = [0.852541 0.024087] ;

inputopts.Marginals(12).Name = ‘Sheat_Rough’;

inputopts.Marginals(12).Type = ‘Gaussian’ ; % BASED ON ASSUMPTION OF GAUSSIAN, MEAN CENTERED BETWEEN PATENT LITERATURE CONTROL LIMIT OF 0.5 AND 0.3 AND 3 STDEV BETWEEN LIMITS AND MEAN

inputopts.Marginals(12).Moments = [0.4 0.0333] ;

inputopts.Marginals(13).Name = ‘Pell_Rough’;

inputopts.Marginals(13).Type = ‘Gaussian’ ; % BASED ON ASSUMPTION OF GAUSSIAN, MEAN AND STDEV DERIVED FROM LITERATURE

inputopts.Marginals(13).Moments = [0.776666667 0.130000000] ;

inputopts.Marginals(14).Name = ‘Pelt_Grain_Sz’;

inputopts.Marginals(14).Type = ‘Lognormal’ ; % Lognormal 0.968824216 vs Gaussian 0.952122186

inputopts.Marginals(14).Moments = [8.2256354 1.2219068] ;

inputopts.Marginals(15).Name = ‘Chamf_Dept’;

%% radial chamfer

inputopts.Marginals(15).Type = ‘Gaussian’ ;

%% BASED ON ASSUMPTION OF GAUSSIAN, and mean and std

inputopts.Marginals(15).Moments = [0.825 0.1] ;

inputopts.Marginals(15).Bounds = [0, 1.00];

%%Arbitary Limit decided by me)

inputopts.Marginals(16).Name = ‘Chamf_Leng’; % axial chamfer

inputopts.Marginals(16).Type = ‘Gaussian’ ;

%%BASED ON ASSUMPTION OF GAUSSIAN, and mean and std

inputopts.Marginals(16).Moments = [0.183 0.1] ;

inputopts.Marginals(16).Bounds = [0, 0.36]; % if greater than 0.36 the ELESTRES runs keep failing

inputopts.Marginals(17).Name = ‘Shth_Yld_Strss’;

inputopts.Marginals(17).Type = ‘Gaussian’ ; % Lognormal 0.996343578 vs Gaussian 0.99757754

inputopts.Marginals(17).Moments = [485.2622625 25.48472693] ;

inputopts.Marginals(18).Name = ‘Zone’;

inputopts.Marginals(18).Type = ‘Gaussian’ ; % Gaussian 0.95317

inputopts.Marginals(18).Moments = [5.1619 2.7480] ;

inputopts.Marginals(18).Bounds = [1, 12];

inputopts.Marginals(19).Name = ‘Bundle_Start_Spot’;

inputopts.Marginals(19).Type = ‘Uniform’ ;

inputopts.Marginals(19).Moments = [((8+1)/2) ((8-1)/(2*sqrt(3)))] ; % for Zone 6 … RSQ = 0.87

inputopts.Marginals(19).Bounds = [1, 8];

% Create the INPUT object

myInput = uq_createInput(inputopts);

uq_print(myInput)

%% 4 - VARIOUS APPLICATIONS

if Analysis_Type == 1; % = 1 is model eval,

%% 4.1 Estimation of the response PDF using Monte Carlo simulation

% Compute an experimental design (ED) of size 250 using Latin Hypercube Sampling:

X = uq_getSample(Sample_Size,‘LHS’) ;

%%

% Evaluate the Abaqus model (truss tip deflection) on the ED:

Y = uq_evalModel(AUTO_EAE_Model, X);

save(strcat(‘run_sample_size_’,num2str(Sample_Size)));

elseif Analysis_Type == 2; % = 2 is SOBOL analysis

SobolOpts.Type = ‘Sensitivity’;

SobolOpts.Method = ‘Sobol’;

SobolOpts.Sobol.Order = 1;

SobolOpts.Sobol.SampleSize = Sample_Size;

SobolAnalysis = uq_createAnalysis(SobolOpts);

uq_print(SobolAnalysis)

SobolResults = SobolAnalysis.Results;

save(strcat(‘SOBOL_sample_size_’,num2str(Sample_Size)));

elseif Analysis_Type == 3; % = 2 is PCE Sobol analysis

PCEOpts.Type = ‘Metamodel’;

PCEOpts.MetaType = ‘PCE’;

PCEOpts.FullModel = AUTO_EAE_Model;

PCEOpts.Degree = 7;

PCEOpts.ExpDesign.NSamples = 20000;

myPCE = uq_createModel(PCEOpts);

SobolOpts.Type = ‘Sensitivity’;

SobolOpts.Method = ‘Sobol’;

SobolOpts.Sobol.Order = 1;

SobolOpts.Sobol.SampleSize = 100000;

mySobolAnalysisPCE = uq_createAnalysis(SobolOpts);

uq_print(mySobolAnalysisPCE)

mySobolResultsPCE = mySobolAnalysisPCE.Results;

save(strcat(‘PCE_SOBOL_sample_size_’,num2str(SobolOpts.Sobol.SampleSize)));

end

time = toc(timer)

The Parser Script is simple:

function Y = uq_readOutput(outputfile)

%%Read t h e s i n g l e l i n e o f t h e f i l e , wh ich c o r r e s p o n d s t o t h e)

%%s o u g h t m idspan beam d e f l e c t i o n)

Y = dlmread(outputfile) ;

end

FYI, wherever there is a % sign, I put %% instead, because it was inadvertently triggering some math symbolism.

Thanks!