TRIMM is supported by funding from the 7th

Framework Programme Call: SST.2011.5.2-2. Theme: Advanced and cost effective road

infrastructure construction, management and maintenance

M. Ralbovsky, AIT (Austria), 24.10.2014

Part 1: Advanced Bridge Monitoring Techniques◦ Monitoring goals◦ Overview of WP3◦ Summary of techniques and their benefits◦ Recommended applications

Part 2: Damage Identification using Model-Updating◦ Scope and principle◦ Uncertainties◦ Damage identification

Accurate Bridge Condition Assessment If possible, prediction of future condition development

What for?: Efficient, sustainable and cost-effective maintenance decision making, at both the network and project level

How?: Advanced sensing and evaluation technologies that improve current inspection practices in three aspects:◦ Objectivity and repeatability: hardware and software◦ Sensitivity and accuracy: enhancing capabilities of inspection◦ Up-to-date information: continuous real-time information

Human perception Sensor perception

Camera-based system

Acoustic Emission monitoring

Corrosion monitoring

Mechanical response monitoring (deformation, strain, vibration)

Bridge inspection practice:◦ Visual inspection◦ If necessary, accompanied by isolated non-destructive test

Monitoring techniques complement (not replace) traditional inspection◦ Example: different quantities describing cracking of concrete

Visual inspection MonitoringCrack type Cracking activityCrack form Cracking to Load correlationCrack width Reduction of effective stiffnessat bridge parts that are visible

also at bridge parts that are not visible

Image-Based Inspection

Corrosion monitoring

Acoustic Emission

Mechanical response monitoring (deformation, strain, vibration)

Visual condition

Chemical degradation

Mechanicalcondition

Reproducible visual condition evaluation

Corrosion front depth Corrosion rate

Cracking activity

Functionality of joints and bearings

Partial or total failure of structural elements

Technique Result

T3.1: Image-Based Bridge Inspection

T3.3: Corrosion monitoring

T3.2: Traffic Loading and Acoustics MonitoringT3.4: Monitoring of Joints and BearingsT3.5: Integrated Bridge Monitoring Method

Visual condition

Chemical degradation

Mechanicalcondition

0

1020

3040

506070

8090

100

0 50 100 150 200 250

Depth (m

m)

t (days)

Measured by multidepth sensors

Measured by chemical analysis

Identified Condition Indicators:◦ Corrosion front depth [mm]

Depth in concrete, at whichreinforcement corrosion starts

◦ Corrosion rate [µm/year]Yearly reduction of reinforcement bar diameterAccumulated diameter loss

Condition Rating and recommended maintenance actionsCorrosion

rate (µm/Y)

Condition index Maintenance measures

0.0 – 1.0 1 Very good Maintenance of surface coating in order to keep steelsurface in passive condition

1.0 – 5.0 2 Good Renewal of surface coating, reprofilation of concrete(increasing concrete cover, replace of contaminated orcarbonated concrete, realkalisation of carbonatedconcrete, electrochemical chloride extraction)

5.0 – 15.0 3 Acceptable

15.0 –30.0 4 Poor Reprofilation of concrete, replacement of elements,

cathodic protection> 30.0 5 Very poor

Techniques:◦ AE: Detection of acoustic waves produced by cracking activity◦ Bridge-Weigh-In-Motion (B-WIM): Level of traffic load

Cracking activity increases at higher traffic loads → normal condition Cracking activity increases at constant traffic loads → progressing

damage

Exploitation: helps in decision making at end of bridge service life◦ Partial or temporal bridge closure◦ Bridge replacement

Increase of cracking activity at constant load level detected?◦ No: bridge can keep operating without restrictions◦ Yes: Detailed inspection, using also local NDE-techniques

Evt. impose traffic limitation or bridge closure

Techniques:◦ Influence lines identified from B-WIM measurements◦ Resonant frequencies identified from vibraton measurements

Scope: functionality of joints and bearings Detection of movement restrictions◦ Possible causes: Exceedance of max./min. gap distance Lateral offset of finger plates, finger

deformations, etc.

Recommended action if movement restriction is detected:◦ Bridge inspection◦ Repair

Aim: detection of partial or total failure of structural elements◦ Rupture in cable-stays or prestressing tendons◦ Anchorage defects, Connector defects◦ Crack development

Technique:◦ Measurement of deformation and vibration◦ Finite-Element model updating

Result:◦ Identification of damaged structural element Incl. elements that are hidden / not accessible to visual inspection

◦ Quantification of defect by identified effective stiffness Recommended action if damage is detected:◦ Bridge inspection◦ Repair of damaged element(s)

Reduction of repair and maintenance costs◦ Identification of defects that could not be detected otherwise

(early stage of corrosion, functionality of hidden elements, ...)◦ Timely warning of detected damage progress Continuous and almost real-time information Repair in early stage of damage progress → lower repair costs

Reduction of failure costs◦ Reduction of failure probability by early damage detection

Extension of service life of deficient concrete bridges

Bridges with potentially high repair costs

Bridges with high failure costs◦ Large bridges, key structures in the network

Concrete bridges near end of service life

External influencesCorrosive substances

Traffic volume

Bridge Current condition

Durability

Repair costsCosts if defects occur

Benefit by application of monitoring

Scope: Monitoring-based identification of mechanical damages◦ Partial or total failure of structural elements◦ Loss of prestressing force◦ Connector defects ◦ Cracking◦ Permanent deformation

Challenges:◦ Integration of different measurement types (dynamic: vibration,

static: deflection, strain, tilt, environmental: temperature)◦ Automated data processing and FE-model updating◦ Evaluation of uncertainties and error propagation

Measurement of bridge mechanical behaviour during operation Comparison to expected (calculated) behaviour Optimization of Finite-Element model◦ Identification of damage(s) that can best explain the measured

bridge behaviour

Comparision of bridge response to:◦ Permanent loads◦ Temperature changes◦ Dynamic loads

DeflectionCracking

Settlement

Tendon failure

Tendon failure

Measurement data

Technical Indicators

Distributions of corrected Technical

Indicators

Parametric FE-model Distributions of Condition Indicators

Limit States Updated Reliability and Serviceability

Future Reliability and Serviceability

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Model updating

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Sensor specifications not practicable for modelling of uncertainties due to constantly high variance

Practicable method for uncertainty modelling was proposed that considers:◦ Sensor linearity◦ Sensor hysteresis◦ Signal long-term drift

Resulting variance is much smaller◦ and is dependent on recorded

signal amplitudes and time

Measured values replaced by normal distributions

Signal ± accuracy range

Signal ± 1 σ Signal ± 1 σ

Purpose: removing temperature effectsso they do not interfere with damageidentification

◦ Using data from “learning” periodand regression techniques

◦ Subtract temperature effects from data

Evaluation of residual errors◦ Compensation is not perfect◦ Errors are smaller if changes within short

period are used for damage detection

Temperature influence

Changes within short periods

Changes within long periods

Resi

dual

err

or

Influence of measurement uncertainties on damage identification Evaluation using Monte-Carlo Simulation Using distributions of measued values Sample generations using

Latin Hypercube Sampling (LHS) Repeated model updating for

all generated samples

Result:statistical distributionsof identified damages

Structural damages simulated by modification of measured data◦ Cable-stay defects◦ Loss of prestress force◦ Concrete cracking

Identified damage represented by statistical distribution of extent

Guadiana River Bridge, Portugal

Smaller measurement uncertainties

Simulated 10 % reduction of effective stiffness of

one cable pair

Larger measurement uncertainties

Based on evaluation of changes in long time period◦ Larger variance◦ Stable, less distinct shift

Based on evaluation of changes in short time period◦ Smaller variance◦ Short, distinct peak

Damages that appearquickly are easier todetect

Identified (black) and simulated (red) damage

Simulated extent: 0.05

Possibility and requirement to define evaluation thresholds

Two thresholds (green and red line) Categories:◦ Healthy (green): identified condition

PDF primarily below first threshold◦ Action needed (red): identified

condition PDF primarily above second threshold

◦ Uncertain or action notneeded (grey): otherwise

Thresholds can be adjusted retroactively

What to do if damage (condition: red) was detected? No automatic decisions Perform special inspection with focus on identified damage location◦ Purpose: validate damage identification◦ False-positive damage identifications are not excluded

Decide if repair and/or reassessment is necessary Identified condition of structural elements may be used in

reassessment calculations

Thanks to all WP3 partners