Non Destructive Testing of Drystone Walls

Abstract

Drystone structures have been widely used throughout the UK and other parts of the world for hundreds of years. Many of these structures are still in use today with many of the existing drystone structures within the UK being over 100 years old.Drystone construction techniques have formed over the years to make best use of stone properties, enabling these structures to resist the loadings upon them. Typical construction styles can often be attributed to certain types of stone, each with their own characteristics. Within these styles subtle variations can be found, often specific to an area, which work best with the properties of the local stone types. The predominant use of drystone structures also influences the way in which they are built in a particular area. This has been demonstrated in comparing the construction within the UK to that in the Cevennes area of France.The existing retaining wall stock needs to be assessed by the authorities that manage them. Many of these walls support highways and infrastructure, so adequate assessment and monitoring of these structures is vital to ensuring these services are maintained. Assessment of a structure mainly relies on engineering judgement, often with little to no prior knowledge of its behaviour or details of its construction.This thesis studies a wide number of walls both in the UK and France to understand qualitatively the construction of these structures, and how the material used together with local practise influences the overall construction. This in turn influences the ways in which loads are resisted by each of the main construction types.Following from this it goes on to look at practical ways in which assessment could be aided by identifying features within a wall that are known to assist or hinder a wall’s performance. The main technique developed for this is thermal imaging. Through practical studies and thermal modelling, a number of proposals have been put forward regarding the best times of day for using this technique. The type of features that may be identified has also been examined and discussed.

Date of Award	6 Jun 2018
Original language	English
Awarding Institution	University of Bath
Supervisor	Paul McCombie (Supervisor) & Kevin Briggs (Supervisor)