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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
Dat
a le
vel
Mod
elle
vel
Asse
ssm
ent
leve
l
Post
proc
essi
ng
Unce
rtai
nty
eval
uatio
n,Te
mpe
ratu
re
com
pens
atio
n
Model updating
Prog
nosi
s
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