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Planar TrussExamplefor ComrelAdd-onRCPConsult, 2022-2025Page 1The Planar Truss Example for Comrel-TI as Gaussbased Add-onHere, a Strurel Add-On (*.sao) is described with the state function programmed inGaussfor Comrel-TIbased on the more sophisticated example %u201cPlanar Truss%u201d from the paper Response surface augmented moment method for efficient reliability analysis. The collection of several files (input, Gaussscript and description) stored into a single file GaussPlanarTruss.saousing the STRUREL Add-onCreator 2is briefly described.This example requires already sufficientfamiliarity with the theory underlying Comrel. It is therefore recommended that the user not familiar with the concepts and methods consultsInteractive Useand at least one Introductoryexample first. Additionally, a certain experience to program in Gaussis required.Attention %u2013to operate with data from GaussPlanarTruss.saoyour Comrel-TIdistribution must contain the standard GaussInterface as the file StrurelToGauss.sao.The Mechanical and Stochastic ModelThe definition of a problem to be analyzed by Comrel-TIis given by the state function and the input of the necessary data on one binary file (*.bti). Output from Comrel-TIwill be on several files explained below.First the state function definition is described. Then the definition and input preparation of the stochastic model as well as the further program control data by means of the Windows based interactive pre-and post-processor Comrelwill be explained.Next, run time and short output information to screen of this example are explained. Finally, the results of the postprocessing part of Comrelare discussed.Figure: Planar Truss geometry and loading.We consider a planar truss that consists of 23 rods as depicted in Figure above. Horizontal and diagonal rods have cross-sections A1, A2 and Young%u2019s moduli E1, E2, respectively. The truss sustains 6 vertical point loads P1 -P6. The variables X = [A1; A2; E1; E2; P1; . . . ; P6] are modelled by independent random variables with marginal distributions given in the table below.