Thanks Regis! This is perfect. I am currently travelling in Poland, I will test this later this week.
On Sat, Aug 12, 2017 at 11:20 PM regis lebrun < regis_anne.lebrun_dut...@yahoo.fr> wrote: > Hi Douglas, > > First of all, thanks for using OT. I checked the reference, and the method > used is NOT the FORM approximation, but the FOSM method. Ie a linearization > at the mean point of the input distribution and not at the most probable > point. So you must use the TaylorExpansionMoments class instead of the FORM > class. > I also checked your code, and you made two mistakes in the probabilistic > modeling: > + the marginal distributions are not given in the correct order wrt the > input varaibles of the model > + the standard deviation of L is 0.1 and not 0.0001 > > If you use correctly the TaylorExpansionMoments class (ie its > getMeanFirstOrder() and getCovariance() methods) you get for the > reliability index: > Beta=2.48039658511 > And the probability (use DistFunc.pNormal() for Phi): > P=0.00656181631695 > > I have a very limited access to the internet for the next two weeks (and > an old blackberry to write messages...) so I cannot send you the full > script before the 26th of August. > > Best regards > > Regis > > -------------------------------------------- > En date de : Ven 4.8.17, Douglas Long <douglaslon...@gmail.com> a écrit : > > Objet: Re: [ot-users] Open Turns FORM > À: "Users" <users@openturns.org> > Cc: "regis lebrun" <regis_anne.lebrun_dut...@yahoo.fr>, "Philip > Fernandes" <phil...@gmail.com> > Date: Vendredi 4 août 2017, 19h48 > > my > apologies. there was a type in the distributions > list.import > openturns as ot > > > myFunction = > ot.NumericalMathFunction(['P', > 'L', > 'W', > 'T'], > ['d'], > ['W*T - > P*L/4']) > > distributions_list = [ > ot.Normal(0.0001, 0.00002), > ot.Normal(600000, 100000), > ot.Normal(10, 2), > ot.Normal(8, 0.0001) > ] > copula = > ot.IndependentCopula(4) > compose_distribution = > ot.ComposedDistribution(distributions_list, copula) > > > vect = > ot.RandomVector(compose_distribution) > output > = ot.RandomVector(myFunction, vect) > myEvent > = ot.Event(output, ot.Less(), 0) > > myCobyla = ot.Cobyla() > myAlgo = > ot.FORM(myCobyla, myEvent, [0.0001,600000,10,8]) > myAlgo.run() > result = > myAlgo.getResult() > > print(result.getPhysicalSpaceDesignPoint()) > print(result.getHasoferReliabilityIndex()) > print(result.getEventProbability()) > print(result.getLimitStateVariable()) > print(result.getStandardSpaceDesignPoint()) > print(result.getImportanceFactors()) > On Fri, Aug 4, 2017 at > 11:38 AM, Douglas Long <douglaslon...@gmail.com> > wrote: > Hey Folks, > I am > attempting to recreate a FORM example.http://www2.mae.ufl.edu/ > haftka/stropt/Lectures/FORM. pdfI am trying to > get BETA = 2.48 as in the example linked > above. > > here is my code but my results are > different. I have tried many different > solutions.any help would be greatly > appreciated. > Thanks,Dougimport > openturns as ot > > > myFunction = > ot.NumericalMathFunction(['P', > 'L', > 'W', > 'T'], > ['d'], > ['W*T - > P*L/4']) > > distributions_list = [ > ot.Normal(0.0001, 2), > ot.Normal(600000, 0.1), > ot.Normal(10, 0.00002), > ot.Normal(8, 100000) > ] > copula = > ot.IndependentCopula(4) > compose_distribution = ot.ComposedDistribution( > distributions_list, copula) > > > vect = > ot.RandomVector(compose_ distribution) > output = ot.RandomVector(myFunction, vect) > myEvent = ot.Event(output, ot.Less(), 0) > > myCobyla = ot.Cobyla() > myAlgo = > ot.FORM(myCobyla, myEvent, [0.0001,600000,10,8]) > myAlgo.run() > result = > myAlgo.getResult() > > print(result. > getPhysicalSpaceDesignPoint()) > print(result. > getHasoferReliabilityIndex()) > print(result. > getEventProbability()) > print(result. > getLimitStateVariable()) > print(result. > getStandardSpaceDesignPoint()) > print(result. > getImportanceFactors()) > > -- > > Douglas > Long > douglaslon...@gmail.com > > > > > -- > Douglas Long > douglaslon...@gmail.com > _______________________________________________ > OpenTURNS users mailing list > users@openturns.org > http://openturns.org/mailman/listinfo/users > > -----La pièce jointe associée suit----- > > > -- Douglas Long douglaslon...@gmail.com
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