Flood Resilient Bridge Modelling and Design

Lead Research Organisation: University of Bristol
Department Name: Civil Engineering

Abstract

Transport systems are responsible for moving people and goods, delivering services and ensuring connection within and among urban areas. Flood events are the most frequent cause of damage to infrastructure compared to any other natural hazard. Bridges located over waterways are particularly prone to failure during flood events and constitute one of the current research priorities. Many of the strategic bridges are not designed to cope with the current increasing pressures of a changing climate, and their frequency of use has outstripped their design specification.

This project tackles the challenge of improving bridge resilience to floods by investigating how hydrodynamic forces damage bridges and disrupt their functionality. The research draws on risk-based principles to re-think infrastructure and to support the near future of our cities through resilient measures against flooding events (e.g. retrofitting). The project will be tailored to the candidate's interest, and may also include aspects of: smart bridges, sensoring and monitoring, network analysis, climate change. Results will be accessible to local stakeholders, providing a series of risk-based information to inform decision-making. The candidate will be expected to conduct work with industrial and academic partners and should have excellent interpersonal skills.

Publications

10 25 50
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Degan Di Dieco G (2022) A taxonomy of bridges at risk of flooding: towards bridge classes and damage models in Proceedings of the Institution of Civil Engineers - Bridge Engineering

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/T517872/1 01/10/2020 30/09/2025
2444849 Studentship EP/T517872/1 01/10/2020 31/03/2024 Giuseppe Degan Di Dieco
 
Description Many communities around the world are facing increasing flood-induced damage to bridges due to climate change
and rising urbanisation. It is thus crucial to understand how different bridge types suffer from flooding and how this
may affect surrounding networks. Despite the large body of literature for seismic and hurricane taxonomies, few
classifications exist for bridges at flood risk. In this work, existing global bridge classifications were reviewed in order
to derive a bridge-flood taxonomy. The review revealed that existing studies mainly classify bridges according to the
superstructure material, whereas subclasses consider superstructure and substructure components. A taxonomy of
20 attributes for riverine roadway bridges susceptible to flood hazards is proposed in this paper. Its applicability
for three bridge datasets in the UK was verified. The results showed that the considered datasets have data for
13 attributes, which can be used to derive regional bridge classes. In general, the taxonomy is functional for
standardising different bridge datasets and applying/developing damage models for given bridge portfolios of
flood-prone countries. Future works could apply the taxonomy to additional bridge datasets within a network for
risk assessments; the proposed taxonomy could also be extended to allow integration with functionality and
restoration models.
Frequency and intensity of hydrological hazards have increased. Consequently, riverine
bridges are suffering damage due to flooding. Fragility functions are used to estimate such
damage conditioned on hazard intensity. However, flood fragility functions are limited for riverine
bridges, and generally lack for masonry bridges. This paper presents a methodology to derive
flood fragility functions for masonry arch bridges accounting for component failure modes. Demand
and capacity of bridge components are derived from existing analytical expressions, and
account for aleatory uncertainties via Monte Carlo simulations. The methodology is illustrated
using a UK masonry bridge, which collapsed due to winter flood-induced scour. The investigated
bridge is divided into its components (e.g., arches, pier) and a scour fragility function is derived
for the arch, based on a lognormal cumulative distribution fitting to the derived failure probability
data. Future research will develop scour fragility functions for other bridge components.
Exploitation Route All the developed codes are freely available for anyone to use and reproduce the proposed methodologies and obtained results.
Open source software were used, therefore, software costs were reduced to the minimum.
Sectors Transport
URL https://www.turing.ac.uk/events/turings-cabaret-dangerous-ideas-leeds
 
Description What do you get if you combine top academics, contentious research and a comedian compère? Answer: the Cabaret of Dangerous Ideas (CoDI)! This year, The Alan Turing Institute and CoDI are joining forces to bring the nation what it never knew it always wanted: edgy, exciting AI and data science-based entertainment with a comedy twist. Hosted by comedian Susan Morrison, and now in its tenth year, CoDI is ninety minutes of rapid-fire research from some of the finest minds in the country. In this special series, Turing Fellows will take to the stage in various locations around the country to challenge ideas around AI, data science and technology. Audience members will have the opportunity to ask their burning questions and join in the discussion. Investing in an uncertain world: a forecaster's tip Is there such a thing as a secure investment? In a world of war, climate change, pandemics, financial crashes and natural hazards, is anything really risk-free? Can we use AI to minimise risk? Are forecasts and predictions an art or a science? Giuseppe Degan Di Dieco, University of Bristol, tells you where he would invest his own money!
First Year Of Impact 2022
Sector Leisure Activities, including Sports, Recreation and Tourism,Culture, Heritage, Museums and Collections
Impact Types Cultural