Civil Infrastructure Systems

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Lydia Dorsey
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1 Civil Infrastructure Systems Mike Mulheron Director Research, CCE Future Infrastructure Forum September 2011 EPSRC Network on Resilient and Sustainable Infrastructure

2 Relevant Expertise Marios Chryssanthopoulos Gerry Parke Mike Mulheron Boulent Imam Imran Rafiq Juan Sagasetta Peter Clarke, Matt Leach, Paul Smith, David Jesson, Steve Ogin, Prashant Kumar

3 Research Themes Managing current assets Water distribution networks (cast iron) Rail infrastructure (wrought iron) Steel structures (durability and maintenance) Concrete structures (durability and maintenance) Facing future challenges New materials (ECC high ductility, self-healing) Surface modifications (self-assembling bio-films) Non-destructive assessment (NMR) Smart Infrastructure Management Climate change (weather prediction and mitigation) Low CO 2 systems (energy, material security) User impact on infrastructure robustness (Agent-based models) Policy and law (Centre for Environmental Strategy)

4 Multi-scale approach Materials level properties and degradation Component level micro environment Structure level component interaction Network/Stock level structure interdependencies Quantifying Reliability and Consequences Risk Management

5 Cast Iron Water Main Metallography Mechanical Testing

6 Modelling Reinforced Concrete Modelling for Normal / High performance concrete Development & utilisation of fracture mechanics-based material models through laboratory testing. Modelling interaction between steel and concrete, i.e. Bond Modelling tensioning softening of concrete f t u 1 Bond stress, u (MPa) Proposed modification Confined concrete, uncorroded rebar G F /h ε u max 0.7u ma u ps βu max Corroded rebar Unconfined concrete u f s a s max s 1 s 2 s 3 Slip, s (mm)

7 Deteriorating Components Micro-cracking related strength reduction in RC. Corrosion related strength and ductility reduction in steel. Degradation of bond between the two materials. Location of corrosion and implications on performance. EPSRC Doctoral Training Grant

NLFEA of Deteriorated Beams ε u Concrete in

8 NLFEA of Deteriorated Beams ε u Concrete in compression ε co σ ε 1/3f c f c, D f c Elastic-perfectly plastic law for steel σ f y,uncorroded f y,corroded ε Bond stress u max Bond stress-slip slip law Proposed modification 0.7u max Uncorroded Corroded rebar s max s 2 Slip (mm)

NLFEA of Deteriorating Beams Crushing of corrosion damaged top cover beam S114a 40 Total load (kn) 30 20 10 0 (a) (b) (c) S114a - FE

9 NLFEA of Deteriorating Beams Crushing of corrosion damaged top cover beam S114a 40 Total load (kn) (a) (b) (c) S114a - FE S114b - FE S114c - FE (a) (b) (c) Mid-span deflection (mm) Damage localization reliability assessment of degraded RC members

10 Health-monitoring based Deterioration Management Uncertainty Sources Incomplete knowledge Future occurrence Idealised modelling Testing / monitoring corrosion in RC members Reliability of instruments / testing methods Past performance of member Improving confidence in assessment through qualitative / quantitative methods. Bayesian event updating method

11 Performance monitoring - NMR water concentration 0 day day 1 day day 3 days days millimetres

12 Performance updating

13 Strengthening and repair methods Load (kn) Full Steel Beam Reduced Steel Beam Beam Deflection (mm) Co-PATCH EU FP7

Monitoring Debonding in Repairs -35 Use of Chirped Fibre Bragg Grating sensor:

composite-composite and composite-metal bonded joints Detecting defects in poorly

1550 1555 1560 Wavelength, nm -35-40 -45-50 40,000-55 -60 1530 1535 1540 1545 1550

14 Monitoring Debonding in Repairs -35 Use of Chirped Fibre Bragg Grating sensor: Intensity, db , Monitoring debond initiation and growth in composite-composite and composite-metal bonded joints Detecting defects in poorly bonded joints Increasing Cycles Intensity, db Intensity, db Wavelength, nm , Wavelength, nm , Wavelength, nm

15 Deterioration assessment of metallic bridges Global vs Local analysis Fatigue / Corrosion / Damage scenarios Load modelling Probabilistic analysis / reliability / risk System modelling

16 Deterioration assessment of metallic bridges

17 Assessment of NDE performance Variable Distribution Type a d POD* Inspection a g Uniform Repair a fail Derived Mixed S r S max Rayleigh Gumbel Load Detection Probability DPI MPI CW ECT ACFM Crack size (mm)

18 Asset Management for Metallic Bridges Reliability-based planning of inspection and repair actions for metallic bridges Cost optimisation of maintenance activities Life-cycle assessment FP7 Grant MAINLINE - Whole Life Environmental and Economic Asset Management on Rail Infrastructure European Grant BriFaG Bridge Fatigue Guidance

19 FP7 Grant MAINLINE 1. Facilitate the utilisation of improved assessment and life extension without increasing risk, 2. Improve existing damage and deterioration mechanisms and their effect on asset performance, 3. Identify and implement new cost effective replacement/renewal construction methods and logistics, bearing in mind the logistics and operational constraints across an expanding railway network, and the associated political aspirations towards a sustainable low carbon society, 4. Identify and compare new surveying and monitoring technologies in order to complement or replace existing techniques, 5. Develop methods for determining the whole life environmental and economic impact from track and infrastructure maintenance and renewal through the use of various scenarios and management policies.

(NR) WP 6 Dissemination, training & exploitation (UIC) WP 3 Replacement of obsolete

20 20 WP 7 Management (UIC) WP 8 Scientific and Technical Coordination (UIC) WP1 Life extension (LTU) WP2 Degradation & structural models (Surrey) WP 5 Asset whole life (NR) WP 6 Dissemination, training & exploitation (UIC) WP 3 Replacement of obsolete infrastructure (DB) WP 4 Monitoring & examination techniques (MAV) MAINLINE Project

21 Whole-Life Performance of Structures Modelling deterioration and its effects Predicting load demands Quantifying safety reserves Optimizing maintenance strategies Cost of Maintenance Routine Preventative Essential Time

22 Health Monitoring Structures Member 4 Inspection Cost Repair cost LCC x C R Strategy A Strategy B Strategy C Strategy D

23 Inspection Planning for Bridge Stocks

Inspection Planning for Bridge Stocks Risk ranking Bridge Type Brick Arch Stone Arch Cast Iron Riveted Steel Welded Steel Concrete Environment Mild Severe Consequence Consequence Low High

24 Inspection Planning for Bridge Stocks Risk ranking Bridge Type Brick Arch Stone Arch Cast Iron Riveted Steel Welded Steel Concrete Environment Mild Severe Consequence Consequence Low High Low High Inspectability Inspectability Inspectability Inspectability Easy Hard Easy Hard Easy Hard Easy Hard 1.00 (M1) 1.17 (M2) 1.33 (M3) 1.67 (M4) 1.17 (S1) 1.33 (S2) 1.67 (S3) 2.00 (S4)

25 Inspection Planning for Bridge Stocks Modelling deterioration using Bayesian Belief Network

26 Inspection Planning for Bridge Stocks SCMI Estimation of Risk-Time Profile Development of Inspection intervals SCMI M,6 Target SCMI Mild SCMI S,6 Severe T S 6 T M Time (Years)

27 CI Trunk Mains Networks Aged, complex, buried infrastructure Delivers millions of tonnes of water/day, (24/7) > 6,000 s of km > 50% > 100 years service, > 30% > 150 years service Develop trunk burst prediction models Reduce risk of the occurrence of bursts Minimise impact of bursts Consequence modelling Assess methods of mitigation Minimal intervention, high return Water industry funding 1M, plus 240k from EPSRC IDC s.

Individual buildings and bridges. Groups, portfolios, networks.

28 Damage and Loss Estimation Consequence models Modelling damage and collapse of structures under extreme loads (e.g. earthquakes). Individual buildings and bridges. Groups, portfolios, networks. Simplified methods for loss estimation. Uncertainty in loss prediction Meters 1000 YEARS GREEN YELLOW RED EU FP7 Less-LOSS

29 Resilience to Environmental Change Bridge scour Corrosion / deterioration Temperature stress cycling EPSRC Grant EP/I00744X Bridge reliability under the influence of changing environmental and demand conditions

Risk-based Assessment of Bridge Infrastructure

Transportation network analysis Traffic delay /

30 Risk-based Assessment of Bridge Infrastructure Bridge infrastructure resilience to hazards Consequence modelling for failures (human, economic, environmental, societal) Transportation network analysis Traffic delay / re-routing modelling Casualty modelling from infrastructure failures

31 SmartEN: Smart Management of Human Environment WP1: Wireless sensors networks WP2: Sensor Signal Processing WP3: Non-Destructive Evaluation Optimum Sensor Locations and Requirements for NDE Combined Monitoring and Inspection Systems Assessment and Long Term Performance Modelling Performance Model Updating Based on Sensor Information Damage identification WP4: Smart Proactive Management Proactive Management Strategies Life Cycle Design and Assessment Multi-objective Optimisation EU FP7 Marie Curie

32 Transmission Tower Collapse

33 Resilience Response Analysis B B A Shell element model 2. (ABAQUS) A

34 Vertical displacement at point B Overall comparison of time-displacement response for column removal case (t = 0.01T assoc ) Time (sec) Shell element model 2 Beam element Shell model 2 Shell model 1 Shell element model 1 Beam element model

35 Summary Managing current assets Characterising and modelling deterioration Performance assessment and prediction Structural health monitoring Reliability and consequence modelling Risk-based asset management Infrastructure resilience Facing future challenges Impact of climate change Consequence modelling Smart Infrastructure management Multi-scale life cycle analysis

Ultimate strength prediction for reinforced concrete slabs externally strengthened by fiber reinforced polymer (FRP)

Ultimate strength prediction for reinforced concrete slabs externally strengthened by fiber reinforced polymer (FRP) Abstract This paper presents the potential use of externally bonded fiber reinforced