There is overwhelming evidence that the development of new, technically sound, engineered and fit-for-purpose critical physical infrastructure is vital for economic growth and stability. With many countries targeting significant levels of capital investment in energy, transport, communications, flood management and water and waste water infrastructure, there is a vital need for asset management frameworks that can provide both robust and resilient asset support. Currently, asset management tools focus predominantly on data management, deterioration modelling, condition assessment, risk, as well as economic factors (such as whole-life costing and developing investment plans). Some also consider the vulnerabilities of a network to climate change and extreme weather events such as flooding. However, rather than taking a long term view, asset management strategies are often short term, typically five years or less. What is needed is a long-term approach, which will ensure assets are safe, secure and resilient to what the future may hold in 20, or even 50 years’ time. The thesis describes the development of a ‘Resilience Assessment Framework’ which provides a platform to appraise resilience of geotechnical assets in the planning stage of asset management by considering how geotechnical assets (specifically for transport infrastructure) designed and built today will perform in the light of socio-economic, environmental, political, technological changes and shock events in the future. This framework intends to assist in strategic level decision-making by enabling long term planning and management of geotechnical assets and help future proof transport infrastructure. The proposed framework is validated using two real case studies to demonstrate its use and applicability in the field of geotechnical asset management.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:685375 |
| Date | January 2016 |
| Creators | Shah, Janvi Pankaj |
| Publisher | University of Birmingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.bham.ac.uk//id/eprint/6644/ |
Page generated in 0.0015 seconds