Use a Python script as limit-state function

In one of the previous posts, we showed you how to work with in-line Python functions directly in STRUREL. Did you know? You can also use a Python script as limit-state function in STRUREL.

Again, we use the example limit-state function RS that we already used in the past: Our stochastic model consists of the two random variables R and S, where R represents the resistance of a system of interest and S is the system load. The symbolic expression for the corresponding limit-state function in the native syntax of STRUREL would be:

FLIM(1) = R-S

However, if you have Python installed on your system and if the Python interface of STRUREL is configured correctly, you could also use the following expression:

FLIM(1) = pythons("my_model")

where my_model.py is a Pyhton script file located in the same directory as the iti-file of STRUREL.

For the example at hand, the Python script file should look as follows:

res = R - S

where the variable names R and S must match the names of the random variables of the stochastic model of STRUREL. The variable res must contain the value of the limit-state function, where the value of res is later retrieved by STRUREL.

By means of the STRUREL command pythons, you can integrate any limit-state function written in Python directly in your reliability analysis performed with STRUREL.

Use a Matlab script as limit-state function

In one of the previous posts, we showed you how to work with in-line Matlab functions directly in STRUREL. Did you know? You can also use a Matlab script as limit-state function in STRUREL.

Again, we use the example limit-state function RS that we already used in the past: Our stochastic model consists of the two random variables R and S, where R represents the resistance of a system of interest and S is the system load. The symbolic expression for the corresponding limit-state function in the native syntax of STRUREL would be:

FLIM(1) = R-S

However, if you have Matlab installed on your system and if the Matlab interface of STRUREL is configured correctly, you could also use the following expression:

FLIM(1) = matlabs("my_model")

where my_model.m is a Matlab script file located in the same directory as the iti-file of STRUREL.

For the example at hand, the Matlab script file should look as follows:

function [lsfval] = my_model(INPUT)

R = INPUT(1);
S = INPUT(2);

lsfval = R - S

end

The ordering of the random variables in the vector INPUT corresponds to the order in which they appear in the stochastic model of STRUREL.

Alternatively, the Matlab script file could look as follows:

function [lsfval] = my_model(INPUT)

global R;
global S;

lsfval = R - S

end

where the variable names R and S must match the names of the random variables of the stochastic model of STRUREL.

By means of the STRUREL command matlabs, you can integrate any limit-state function written in Matlab-Syntax directly in your reliability analysis performed with STRUREL.

How to use in-line Matlab in Strurel

In the last post, we showed you how to work with in-line Python functions directly in STRUREL. Did you know? You can also use in-line Matlab functions directly in a symbolic expression in STRUREL.

For example, assume a problem for which you have the two random variables R and S in your stochastic model, where R represents the resistance of a system of interest and S is the system load. The symbolic expression for the corresponding limit-state function in the native syntax of STRUREL would be:

FLIM(1) = R-S

However, if you have Matlab installed on your system and if the Matlab interface of STRUREL is configured correctly, you could also use the following expression:

FLIM(1) = matlabf("R-S")

Sure, calling the Matlab interpreter for this simple demonstration example is like taking a sledgehammer to crack a nut. However, the interface-function matlabf is a tool that gives you access to the full power of Matlab directly in the symbolic expression of STRUREL.

How to use in-line Python in Strurel

Did you know? You can use in-line Python functions directly in a symbolic expression in STRUREL.

For example, assume a problem for which you have the two random variables R and S in your stochastic model, where R represents the resistance of a system of interest and S is the system load. The symbolic expression for the corresponding limit-state function in the native syntax of STRUREL would be:

FLIM(1) = R-S

However, if you have Python installed on your system and if the Python interface of Strurel is configured correctly, you could also use the following expression:

FLIM(1) = pythonf("R-S")

Sure, calling the Python interpreter for this simple demonstration example is like taking a sledgehammer to crack a nut. However, the interface-function pythonf is a tool that gives you access to the full power of Python directly in the symbolic expression of Strurel.

Version 9.5 of COMREL is available!

The new release of COMREL comes with numerous improvements. The most notable new features are: (i) Limit-state functions coded in Python can now directly be analyzed. (ii) You can now easily develop your own interfaces to external programs by employing the new Sturel Add-On (SAO) feature. (iii) The COMREL manual is now directly integrated into the graphical user interface.

Improved GUI of COMREL in upcoming version

The release of Comrel 9.5 is in the offing. In the new version, the documentation is now directly embedded in the graphical user-interface (GUI). Moreover, the symbolic expressions editor (that is used to define limit-state functions) now comes with an ‘undo & redo’ feature that allows you to easily revert erroneous edits.

The application also comes with improved usability in shortcuts.

Presented Strurel at the UNCECOMP conference in Rhodos

The 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP) took place at Rhodes Island, Greece. We presented the different modules of Strurel.

Abstract: Strurel is a leading commercial general-purpose software package for probabilistic modeling and structural reliability assessment. Strurel includes software modules with state-of-the-art computational methods for component and system reliability analysis. These include the First and Second Order Reliability methods (FORM/SORM) and sampling based method including Monte Carlo simulation, subset simulation, importance sampling, line sampling, directional simulation and adaptive importance sampling. Strurel can handle static as well as time-dependent problems, and supports a wide range of probabilistic models encountered in structural reliability. It also includes a set of tools for the calibration of safety factors in structural design. Strurel comes with an easy to use graphical user interface and additionally enables coupling of limit-state functions with user-defined system models through an interface with external programs.
The computational core of Strurel has been coupled with the finite element package SOFiSTiK in a new module called RELY that comes as part of the SOFiSTiK software package. RELY is specifically designed to perform reliability analysis employing SOFiSTiK finite element models. In RELY, the engineering system of interest is modeled using the full capabilities of the SOFiSTiK finite element package; existing SOFiSTiK finite element models can be readily employed for reliability analysis.
We demonstrate Strurel and RELY on two example applications. Firstly, a reliability analysis using a limit-state function for a pressure vessel coded in Matlab is conducted in Strurel. Secondly, a reliability analysis of a design concept for a submerged floating tube bridge is performed with RELY.