Hi,
I would like to compute the reliability index of FRP confined concrete column under static pushover loadings. Therefore, I utilized ConfinedConcrete01 to model concrete, in which the FRP properties can be defined. Next, I tried to connect FRP properties with corresponding random variables through parameters (e.g. parameter 1 randomVariable 1 element 1 section 1 material 1 $FRPmodulus, where $FRPmodulus should be an object argument representing $ful in ConfinedConcrete01). Here came the problem. It was found that there was no object argument representing FRP modulus. I looked up the setParameter() in ConfinedConcrete01.cpp and found that like Concrete01 only fc, epsco, fcu and epscu could be assigned as parameters in ConfinedConcrete01. Then how could I set the FRP modulus as a random variable and conduct FORM or sensitivity analysis of static pushover?
Thanks a lot for your help!!
Reliability analysis of static pushover
Moderators: silvia, selimgunay, mhscott, Moderators
Re: Reliability analysis of static pushover
It looks like the setParameter method was copied from Concrete01. Is the FRP modulus one of the input parameters (or does it correspond directly to one of them) for ConfinedConrete01? If so, I can update the set/updateParameter methods for you.
Re: Reliability analysis of static pushover
Thanks a lot for your timely reply and useful tips. FRP strength and modulus are input parameters for ConfinedConcrete01. (uniaxialMaterial ConfinedConcrete01 $tag ... <-wrap ... $ful $Es0w>..., where $ful and $Es0w are ultimate strength and elastic modulus of FRP material). But they are not arguments of ConfinedConcrete01 Class, though the relation between FRP properties and arguments in attSet() are sort of straightforward.
Therefore, If I wanna incorporate FRP properties and use Finite Difference Method to get parameter gradients, should I just update the set/updateParameter() functions? If so, maybe I can update them by myself. In my opinion, if Direct Differentiation Method is NOT used, one doesn't need to create getStressSensitivity() and commitSensitivity() functions. Am I right?
As for FDM, the "-pert $PerturbationFactor" seems to be useless, since I cannot understand how the user-provided perturbation factor enters RVParameter::getPerturbation(), where only 0.001*myRV->getStdv() is returned. Also I conducted some simple reliability analyses and found the $PerturbationFactor doesn't influence the results. Is this a problem to be fixed?
The last problem is to build the sources on a 64bit PC. I can build the sources successfully on 32bit Windows, but get linking problems on 64bit machine. I know this question should not appear here and I have also posted on http://opensees.berkeley.edu/community/ ... =4&t=60718 with more details, but without replies. So could you please help me out of this, it's quite frustrating? Sorry for throwing all these questions to you at one time and thank you in advance!
Therefore, If I wanna incorporate FRP properties and use Finite Difference Method to get parameter gradients, should I just update the set/updateParameter() functions? If so, maybe I can update them by myself. In my opinion, if Direct Differentiation Method is NOT used, one doesn't need to create getStressSensitivity() and commitSensitivity() functions. Am I right?
As for FDM, the "-pert $PerturbationFactor" seems to be useless, since I cannot understand how the user-provided perturbation factor enters RVParameter::getPerturbation(), where only 0.001*myRV->getStdv() is returned. Also I conducted some simple reliability analyses and found the $PerturbationFactor doesn't influence the results. Is this a problem to be fixed?
The last problem is to build the sources on a 64bit PC. I can build the sources successfully on 32bit Windows, but get linking problems on 64bit machine. I know this question should not appear here and I have also posted on http://opensees.berkeley.edu/community/ ... =4&t=60718 with more details, but without replies. So could you please help me out of this, it's quite frustrating? Sorry for throwing all these questions to you at one time and thank you in advance!