Welcome to the course! Our aim in this course is to explore how probability theory can be applied to estimate the likelihood of structural failure. This course is part one in a two-part series. In this first course we’ll focus on establishing a sound understanding of the fundamental concepts in reliability theory.

In part 2, we’ll delve deeper into the statistical modelling of extreme events and focus on numerical techniques that unlock reliability analysis for even more complex problems.

Section 2 - Safety and Reliability Fundamentals

In section 2, we start by simply discussing our current semi-probabilistic approach to design. We’ll revisit some of the most common failure mechanisms before refreshing our memory of the fundamentals of probability theory.

The concepts of a probability density function and cumulative distribution function will be central to everything we do in this course - so we’ll spend time making sure these concepts are clear early on.

We wrap up section two with our first coding session of the course. Like most EngineeringSkills courses - Python will be used more or less as a high-powered calculator. So if you’re not familiar with Python, don’t worry, you’ll pick up the basics by just following me through the lectures. Pretty soon, you’ll have the basics under your belt and that’s all you’ll need.

Section 3 - The First Order Second Moment Method

In this course, we’ll introduce two techniques for evaluating structural reliability - we cover the first of these in section 3. This is the First Order Second Moment Method. This will give us our first opportunity to calculate failure probability and will introduce us to most of the core concepts that we’ll continue to rely on through the rest of the course.

Section 4 - The First Order Reliability Method

The first order second moment method is really just a stepping stone to get us to our second method which we cover in section 4. This is the First Order Reliability Method. This iterative approach to evaluating reliability is a significant improvement on our first order second moment method and addresses the key weaknesses that we’ll identify in this method.

The first order reliability method will be your go-to method and is routinely used in practice for evaluating reliability. Through sections 3 and 4 you’ll solidify your understanding by applying the theory we develop directly in worked examples. As we work through these worked examples we’ll build a library of utility functions that you can import and apply in your own analyses.

When you’ve completed this course, you’ll have a completely new suite of tools and techniques for reliability modelling and have a much greater appreciation for the role natural variability plays in structural behaviour and how to accommodate this in your analysis and design.

Getting Q&A support

All lectures have a dedicated discussion thread where you can post support requests. If you have questions as you work through the course, feel free to post them in the discussion thread for the relevant lecture.

Then, either myself or possibly another learner will respond. If your question relates to a specific part of the lecture, please provide a time-stamp to help me respond as efficiently as possible.

Getting up and running with Python

As I mentioned, we’ll use Python throughout the course. This will give us a convenient platform on which to implement our calculations and will also give us access to some really helpful tools for working with probability distributions.

If you don’t have any previous experience with Python and need some help getting your computer setup for coding, you can follow the links below. These will redirect you to other lectures that will walk you through setting up your local development environment.

Ok, with all that said, let’s crack on with the course!