The combined length of the sewerage and clean water pipe infrastructure in the UK is estimated to be about 800,000 km. It is prone to failure due to its age and the inadequacies of the current pipe inspection methods. Fibre-optic cable sensing is an attractive way to continuously monitor this infrastructure to detect critical changes. This paper reviews the existing fibre-optic sensor (FOS) technologies to suggest that these technologies have better sensing potential than traditional inspection and performance monitoring methods. This review also discusses the requirements for retrofitting an existing pipeline with an FOS. It also demonstrates that there is a need for further research into methods applicable to non-pressurised pipelines, as there is very little existing literature that focuses on partially filled pipes and pipes with gravity fed flows.

This paper presents a novel adaptation of the conventional approximate Bayesian computation sequential Monte Carlo (ABC-SMC) sampling algorithm for parameter estimation in the presence of uncertainties, coined combinatorial ABC-SMC. Inference of this type is used in situations where there does not exist a closed form of the associated likelihood function, which is replaced by a simulating model capable of producing artificial data. In the literature, conventional ABC-SMC is utilised to perform inference on continuous parameters. The novel scheme presented here has been developed to perform inference on parameters that are high-dimensional binary, rather than continuous. By altering the form of the proposal distribution from which to sample candidates in subsequent iterations (referred to as waves), high-dimensional binary variables may be targeted and inferred by the scheme. The efficacy of the proposed scheme is demonstrated through application to vibration data obtained in a structural dynamics experiment on a fibre-optic sensor simulated as a finite plate with uncertain boundary conditions at its edges. Results indicate that the method provides sound inference on the plate boundary conditions, which is validated through subsequent application of the method to multiple vibration datasets. Comparisons between appropriate forms of the metric function used in the scheme are also developed to highlight the effect of this element in the schemes convergence.

Meetings are core mechanisms through which engineers coordinate complex technical work, make decisions, review designs, manage risk, and collaborate with diverse stakeholders. Yet, meeting skills are rarely taught explicitly in engineering programmes, despite strong evidence that structured facilitation, inclusive participation, and effective documentation significantly improve both team performance and project outcomes. This chapter provides you with a practical, research-informed framework for embedding meeting skills into curricula through scaffolded learning, authentic engineering scenarios, and progressive independence. Drawing on professional standards and empirical studies across engineering institutions, we define meeting skills as a set of transferable competencies that include preparation, facilitation, communication, decision making, and follow-up. The chapter offers concrete examples, implementation strategies, and recommendations based on practitioner experience, enabling you to support your students in developing meeting practices that mirror real engineering environments. Ultimately, meeting skills strengthen technical coordination, foster inclusive team cultures, and prepare graduates for the communication demands of modern engineering practice.