Reliability, resilience and robustness in structural engineering design

Course

Date & Time

9 September 2027
10:00 - 17:30 BST

Location

Online

Price

Member early booking: £330 + VAT
Member: £370 + VAT
Standard: £485 + VAT

Early booking discount

Available until one month prior

Book a Place

This interactive online course shares current state-of-the-art frameworks for the adoption of resilience-based design in professional practice, demonstrating advantages compared to a traditional prescriptive design and providing examples of how they benefit the client.

Learning outcomes

By the end of the course, you should be able to:

Differentiate between reliability, risk and resilience when quantifying structural performance
Appreciate the role of robustness and resilience in the design of structures
Understand the role of aleatory and epistemic uncertainties in the design of structures
Decide which design situations are best suited for the adoption of performance-based approaches, and justify their use in practice
Break down the application of performance-based design into sequential stages; from assessing the relevant hazards to estimating the resulting losses
Recommend a range of structural and non-structural solutions to enhance resilience and robustness

Intended for

Graduate engineer
Mid-career engineer
Senior engineer/Team leader/Manager
Academic/Researcher
Other built environment professionals and engineers

Caroline is a Partner at PA Consulting and leads their resilience business. Caroline has a background in asset and infrastructure resilience with over 26 years of professional experience including 12 years in counter terrorism, blast mitigation and physical security and seven years in earthquake engineering and dynamics.

Andre is a Chartered Structural Engineer (Portugal) and Lecturer in Structural Engineering at Loughborough University. His research focuses on structural dynamics, including structural health monitoring, human-structure interaction, and railway infrastructure modelling. He specialises in advanced probabilistic methods to quantify uncertainty and improve data interpretation and damage detection.

Contact

Email - [email protected]