Britain’s railway embankments, flood defences, and motorway cuttings are failing more often than engineers can predict—Network Rail alone saw 143 earthwork collapses in 2015, more than two per week. These long linear assets—10,200 km of flood defences, 80,000 km of highways, and 15,800 km of railway—are ageing, more heavily used, and facing increasingly extreme weather. Current design and management rely on past experience, which cannot predict future performance under these new conditions. Emergency repairs cost ten times more than planned works, which themselves cost ten times maintenance. The human stakes are high: 748,000 properties face at least a 1-in-100 annual chance of flooding, and derailment from slope failure is the railway’s greatest infrastructure risk. ACHILLES combines laboratory experiments, field data, numerical modelling, and cost-benefit analysis to understand exactly why and when these assets fail. If successful, it will produce new design tools, deterioration models, and a decision-making framework that lets asset owners prioritise spending on monitoring and repairs. The goal is fewer unanticipated failures, lower repair costs, and safer, more reliable transport and flood protection—infrastructure that quietly keeps the country running.
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Infrastructure is fundamental to our economy and society, e.g. being one of the 10 pillars of the recently launched UK Industrial Strategy. Long linear (geotechnical) assets (LLAs) are a major component of this infrastructure and fundamental to the delivery of critical services over long distances (e.g. road & railway slopes, pipeline bedding, flood protection structures). Central government infrastructure investment will rise by almost 60% to £22 billion p.a. by 2022 (ONS). This will support both the development of new infrastructure, and the repair of existing infrastructure. At present, there are 10,200 km of flood defences in Great Britain; 80,000 km of highways; 15,800 km of railway). Failure of these assets is common-place (e.g. in 2015 there were 143 earthworks failures on Network Rail - >2 per week), the resulting cost of failure is high (e.g. for Network Rail, emergency repairs cost 10 times planned works, which cost 10 times maintenance), and vulnerability to these failures is significant (748,000 properties with at least a 1-in-100 annual chance of flooding; derailment from slope failure is the greatest infrastructure-related risk faced by our railways). However, the exact reasons for - and timing of - failure is, at present, poorly understood. This leads to unanticipated failures that cause severe disruption and damage to reputation. Current approaches to design and asset management perpetuate this situation as they are based on past experience, which cannot be extrapolated to future performance: the infrastructure is older, ever more intensively used and subject to increasingly extreme weather patterns. Together, these factors significantly increase the likelihood of failures in the future causing reduced performance and poorer service. Climate change has been identified as one of the factors driving this change. There is an exciting opportunity to bring together new advances in research and technology with design and asset management practices from different LLAs to reduce the risks posed to infrastructure systems by deterioration and future change. Current techniques can estimate future rates of deterioration that might lead to failure in transport infrastructure slopes, but are difficult to scale up, do not capture all drivers of deterioration relevant to all LLAs, are poor at dealing with uncertainty and heterogeneity, and lack rigorous validation against representative field data. Different asset owners have access to vast quantities of failure and condition data from their networks (recently enabled by technological advances in data capture and storage) but use different approaches to address failure based on historical data. ACHILLES proposes a research programme that brings these approaches together, coupled with statistical advances to enable rigorous use of network data, and economics to assess the value of design, monitoring and mitigation options. Our long-term vision is for the UK's infrastructure to deliver consistent, affordable and safe services, underpinned by intelligent design, management and maintenance. ACHILLES proposes a Programme to address this challenge by combining laboratory/field experimentation, numerical modelling and simulation, statistical data and cost benefit analysis, and activities to enable its outcomes to be adopted by LLA owners/operators: Deeper understanding of material and asset deterioration and how to model and predict New design tools to account for deterioration; and assessment tools to characterise Strategies to mitigate deterioration from material to asset scale Decision-making framework to prioritise spending on design, monitoring and/or interventions that accounts for heterogeneity and uncertainty, and informs appropriate business cases Better understanding of the importance of characterising heterogeneity and uncertainty for infrastructure decision making processes Knowledge and tools to incorporate data analytics into asset assessment and monitoring
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