Workshop 04: Component Reliability Analysis#
This workshop was assigned using GitHub Classroom, accessed via this link. If the link is not working, the files can be downloaded as a zip file. This workshop was not submitted for a grade/feedback.
Instructions for the assignment are provided below (based on the README.md
file from the repository).
The solution can be found in the following sub-pages:
Report: the Markdown report with questions about the analysis
Analysis: the Jupyter notebook where calculations were made (includes additional explanation)
Instructions (README.md
)#
The purpose of this assignment is to illustrate two commonly used algorithms for finding the failure probability of a component (component reliability problem).
Context
This workshop will apply component reliability analysis to an equation describing stability of a beam. The context to keep in mind is that you are responsible for designing the beam to withstand a specific loading situation; the challenge is that several aspects of the problem are uncertain (the random variables). Fortunately someone has already prepared several key ingredients for you: the random variables, multivariate distribution and limit-state function. Your job is to carry out the analysis for finding the failure probability.
Instructions:
work through the notebook
Analysis.ipynb
answer the questions in the file
Report.md
commit your files back to the repository
Even though you do not have to turn in this assignment (see below), we recommend you add answers to the Report.md
so you can refer back to this in the future, or to collaborate with your group members.
The solution will be added to the HOS Workbook after the workshop is completed at tudelft-citg.github.io/HOS-workbook/2025/workshops/03.
Python Environment#
To complete this assignment you will need the following packages: numpy
, matplotlib
, scipy
, and openturns
. The solution also uses sympy
to check analytic expressions.
See the Workbook page tudelft-citg.github.io/HOS-workbook/2025/component/openturns.html for instructions on how to use the OpenTURNS package.
If you are having trouble installing or using OpenTURNS, it may be easier to create a new environment. To help with this, a file openturns_env.yml
is included with the assiignment files and will create an environment named openturns25
using the following command in a terminal:
conda env create -f openturns_env.yml
Grading#
This assignment is not graded; you do not have to turn it in. However, we recommend you clone the repository and push your changes back to GitHub to save and track your work; especially if you are working with other students. In addition, if you need to contact Robert for help outside of class, you should include the URL link to your repository in an email.
Attribution#
This assignment is not mean for distribution outside of the course (yet!). Please contact Robert Lanzafame if you would like to reuse this material.