weigh-in-motion on bridges

Realization:

Author:

WEIGH-IN-MOTION ON BRIDGES

Aleš Žnidarič

ZAG - Slovenian National Building and Civil Engineering Institute

Ljubljana, Slovenia

What is Bridge WIM?

B-WIM is a device that uses instrumented road structures – bridges or culverts – to weigh vehicles in motion.

3 facts: ■ involves existing instrumented structures

■ can be used as any other WIM system

■ gives extra information for bridge assessment

Bridge WIM

3 periods: 1. Before 1994: US B-WIM system, CULWAY 2. 1994-2000 EU research projects:

– COST 323 (Weigh-in-motion of road vehicles) – WAVE (Weighing-in-motion of axles and vehicles for

Europe)

3. After 2000: – SiWIM – developments of new algorithms – Japan, Korea

B-WIM before 1994

□ born in 1979 by F. Moses (CWRU, Cleveland, USA) □ BWS, CULWAY □ limitations:

■ limited types of bridges ■ poor axle weight accuracy ■ multiple presence of vehicles

□ advantages: ■ accurate GVW results ■ no ‘off-scale’ weighing ■ easy instrumentation with little disturbance ■ portability ■ for bridge assessments

B-WIM during European projects

□ objectives: ■ to increase their accuracy

■ to extend their applicability to: □ short slab bridges

□orthotropic deck bridges

□ longer span box girder bridges

■ to develop new algorithms

B-WIM today

□ a fully operational SiWIM system used on >1000 sites in 16 countries

□ main features: ■ accuracy, including SA and AG ■ connectivity, cameras etc. ■ portability ■ easy and fast installation ■ free-of-axle detector (FAD) installation ■ bridge assessment

□ Australia, Japan…

BWIM shema

Strain measurements Axle detection

ST500 Strain transducer

ST-500 S.N. 10122150100001

R R ST 500 SN 10122150100001

220

30 85 90 15

13

Calibration

With pre-weighed vehicles

With vehicles from traffic flow

2.5 + 3.0-m integral culvert

Canada

9-m long, integral-type slab bridge

France

Millau bridge

France

292 m long, 9-span beam-deck bridge

Oman

12+20+12 m long, 3-span beam-deck underpass

USA

SiWIM features

1. Influence lines

2. FAD – Free-of-axle Detector installation

3. Multiple presence of vehicles on the bridge

4. Influence of pavement roughness and calibration methods

1. Influence lines

□ key structural parameter that is directly related to the quality of B-WIM measurements

□ only measured/experimental influence lines

□ SiWIM calculates measured IL from any vehicle: ■ Powell’s multidimensional non-linear optimisation

■ accounts for: □ shape of the influence line

□ axle load ratio

■ several ILs are averaged

1. SiWIM influence lines

IL = Response of a structure under a moving load

2. FAD – Free-of-Axle Detector installation

□ key advantage of B-WIM systems: ■ no disturbance of traffic

■ fast and easy installation and maintenance

■ improved portability

□ not all bridges are appropriate for FAD

□ over 75% of installations in 2009 were FAD


Installation with axle detectors


Installation without axle detectors

3. Multiple presence (MP) of vehicles

□ B-WIM measures global effects thus MP is a challenge □ options:

■ selection of shorter bridges ■ measurements of local effects ■ implementation of 2D influence surface instead of IL =>

demanding calibration

□ applied solution: STRIPs ■ grouping of sensors under each lane ■ larger systems of equations but ■ unchanged calibration procedure

3. Multiple presence (MP) of vehicles

GVW Axle 1 Axle 2 Multiple

3-axle static (t) 20,56 5,16 15,4 5-axle static (t) 33,90 7,24 8,94 17,72

3-axle alone* 0,7% -2,6% 1,8% 5-axle alone** 0,0% 0,6% 3,4% -2,0%

3-axle MP 2,7% -36,2% 15,7% 5-axle MP -6,7% 7,2% -11,2% -10,2%

3-axle MP strips 2,3% 0,2% 3,0% 5-axle MP strips -0,1% 5,8% 3,2% -4,1%

Strip example: 32-m simply supported span, 2-lanes, opposing traffic

* average of 6 vehicle runs ** average of 4 vehicle runs

□ although less than pavement WIM systems, B-WIM is affected by pavement roughness

□ higher level calibration (per vehicle type and axle configuration) improves accuracy of the results

4. Pavement roughness and calibration

E(40)

D+(20)

E(30)

B(10)

Other features

□ Cameras (with LPR) – pre-selection

□ Solar or fuel-cell power supply

□ Remote controlled

□ Post-processing of data

□ Synchronised measurements between axle loads and other quantities (bridge monitoring)

Conclusions on BWIM

□ major developments in recent years □ main advantages:

■ complete portability ■ no interference with traffic ■ accuracy ■ bridges are difficult to avoid

□ disadvantages: ■ an appropriate bridge is needed (MP, FAD) ■ requires well-trained personnel (bridges can be

damaged or unusual)

Conclusions

□ key challenges: ■ Increase FAD axle identification on all types of

bridges to over 99%: □measurements other than bending strains

□new algorithms (Wavelet transformation)

■ inclusion of external algorithms

■ facilitation of its use

□ SiWIM III is coming…

BWIM AND ITS APPLICATIONS IN BRIDGE ASSESSMENT

Why SiWIM in bridge assessment?

□ It provides the same data as pavement WIM systems, plus: ■ can be used on a specific bridge to improve its

assessment

■ the only system that directly compares bridge loading with load effects

■ in addition to weighing sensors it can perform synchronised measurements with any other sensor

Safety assessment

□ verification that a structure has adequate capacity to safely carry or resist specific loading

□ Ultimate Limit State approach:

Rating factor:

AALLDDR

d GGGRSR γγγγ

⋅+⋅+⋅≥≥

DAFGGRRF

LL

DDd

×××−×Φ

=γ

γ>1.0

35

Traffic load effects

Structural behaviour ■ Influence lines

■ Load distribution factors

Loading schemes ■ Design

■ Assessment

■ Site-specific

2- axle trucks

3- axle trucks Trailers Semi-trailers Buses Others All vehicles

Traffic load modelling

Input: traffic data (axle loads, spacings), headways

2-axle trucks 3-axle trucks Trailers Semi-trailers Buses Others All vehicles

Vransko (25.9.2006 14:59:18 to 21.11.2006 12:27:19) - Lane 1


Simulation of maximum expected load effects

0102030405060708090

100

Total moment of two vehicles [kNm]

event - 1011 kNm

1 day - 1695 kNm

1 week - 1915 kNm

1 month - 2102 kNm

1 year - 2424 kNm

5 years - 2671 kNm

10 years - 2759 kNm

25 years - 2849 kNm

50 years - 2910 kNm

75 years - 2947 kNm

100 years - 2973 kNm

Expected maximum traffic loading

0102030405060708090

100

Total shear of two vehicles [kN]

event - 323 kN

1 day - 523 kN

1 week - 582 kN

1 month - 628 kN

1 year - 707 kN

5 years - 774 kN

10 years - 801 kN

25 years - 832 kN

50 years - 851 kN

75 years - 861 kN

100 years - 868 kN

Expected maximum traffic loading


Simulation of maximum expected load effects

Load testing

Loading of the bridge to learn about its behaviour in order to: 1. know how loading is converted to load effects 2. optimise bridge assessment by finding reserves

in structural model Types of load test: ■ proof ■ diagnostic ■ soft

Soft load testing

□ the lowest level of load application □ uses bridge WIM to provide:

■ “normal” traffic data ■ information about structural behaviour bridge ■ “quick&cheap”:

□no need for pre-weighed vehicles □no need to close the traffic

□ no risk of overloading/damaging of structure □ not suitable for ULS verifications

□ 9.2 m slab bridge

□ built in 1970‘s

□ simply supported

Experimental influence lines

557.3 kNm



□ not simply supported


557.3 kNm





260.0 kNm




□ influence of thickness of the superstructure


244.3 kNm M = 44% × MTHEOR


250.9 kNm






□ location of maximum moment


□ considerable decrease in bending moments

□ some increase in shear

Load distribution factors

□ distribution of traffic loading to different structural elements Lane Factors

□ generally less dependent of wheel location at midspan than at support

□ to update torsional characteristics of the model

Dynamic loading on bridges

□ DAF: ratio between maximum (dynamic) and static loadings

□ problem: combining the extremes of dead load and dynamic effects => very high DAF

□ options: ■ DAF from (design) codes – conservative ■ realistic values (SAMARIS and ARCHES projects):

□ theoretical studies on extreme expected DAF (UCD) □measurements of thousands DAFs with SiWIM (ZAG)

Dynamic amplification

1 day = 4120 events

DAF – 24.8 m beam/deck bridge

DAF – 11.65 m slab

DAF – 7×25.0m beam/deck bridge

Result of using BWIM

□ Realistic traffic load model □ Realistic DAF □ SLT – optimised influence lines and load factors □ Higher reliability of inputs

DAFGGRRF

LL

DDd

×××−×Φ

=γ

γ

Soft load testing results

□ 20 posted pre-analysed bridges: ■ without SLT RF from 0.35 to 0.87

■ with SLT RF from 0.73 to 1.52

■ increase of RF from 1.30× to 2.84×

□ 18 bridges rated as safe for normal traffic loads after applying SLT

□ biggest savings on smaller older bridges with questionalbe boundary conditions

Conclusions – Bridge Assessment

B-WIM measurements can be extremely efficient when updating the structural model: □ Structural behaviour:

experimental (measured) influence lines, load distribution factors and dynamic amplifications can significantly differ from the theoretical ones

□ Traffic loading generally « than in theory: ■ site-specific static load models ■ measured DAF will likely be below 1.10

ARCHES 2009, arches.fehrl.org

SiWIM in Brazil

5 fixed installations for DataTax Pre-checking of weights of vehicles on the borders between the states at normal speed, to confirm the weights with the documents

Thanks for listening!

weigh-in-motion on bridges

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