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Structural Health Monitoring (SHM) of Timber Beams and Girders
Presentation for: FWPA, 2 April 2014
Dr John C Moore MIEAust MIPWEA Adjunct Lecturer in Civil Engineering, University of New England, NSW.
1 Gostwyck, NSW (Moore 2013)
• Bridges
• Interpret Data
• Measuring elasticity
• Prediction of girder failure
• Understand girder degradation path
0 5 1 0 1 5 2 0 2 5 3 0
0
0 . 0 5
0 . 1
0 . 1 5
0 . 2
0 . 2 5
Load & Strength Magnitude
Pro
babi
lity
Den
sity ← Load
Distribution
← StrengthDistribution
FailureRegion
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
2A, 15 years 2B, 45 years
123
4
Ironbark
2A
2B
Introduction and Background
3
New timber composite bridge
4
New bridge at Bretti, NSW with: • Timber girders; • Steel piles; and • Concrete deck Built by RTA & Gloucester Shire in 2010
Leslies Bridge, The original low level bridge at Bretti NSW over the Manning River.
Method to determine Safety Index
1. Record all vehicle mid-span deflections 2. Use a vehicle of known mass and determine
girder elasticity 3. Convert elasticity to a stress distribution 4. Convert deflection to a stress distribution 5. Compare the two stress distributions 6. Determine the probability of failure and
Safety Index 5
TSING MA BRIDGE, HONG KONG
(Nye, 2013; Wikipedia, 2013; Yau, Chan, & Thambiratnam, 2013)
Opened: 1997 Span : 1377 m Sensors: 282 Cost: AUD 1B
6
TIMBER BEAM BRIDGES
Powers Creek, Armidale Span 9 m c. 1930 - 2010
Munsies Bridge, Gostwyck 6 Spans 10 m Opened 1938 7
Timber bridge design (Dare, 1903)
8
Modern design (RTA, 2007)
9
(Glencross-Grant, c. 1975)
Somerton bridge across the Peel river, Tamworth NSW (Ingall, 2008) 10
Diagrammatic section through a degraded girder
11
Second moment of Area for a solid circular girder:
Diagrammatic section through a degraded girder; after excessive loading
12
Second moment of Area for two contiguous girders of semi-circular cross-section:
And the ratio between the two conditions is:
Typical girder, Load-v-Deflection curve
0 20 40 60 80 120
050
150
250
350
Deflection, d (m
App
lied
Load
, P (k
N
13
Proof load test, 50% ultimate load
14
0 20 40 60 80 100 120
050
100
150
200
250
300
350
Deflection, d (mm)
App
lied
Load
, P (k
N)
Measured data 50% load regression 50% prediction limits
Proof load test, 70% ultimate load
15
0 20 40 60 80 100 120
050
100
150
200
250
300
350
Deflection, d (mm)
App
lied
Load
, P (k
N)
Measured data 50% load regression 50% prediction limits
Proof load test, 80% ultimate load
16
0 20 40 60 80 100 120
050
100
150
200
250
300
350
Deflection, d (mm)
App
lied
Load
, P (k
N)
Measured data 50% load regression 50% prediction limits
Nominal maximum girder load
17
0 20 40 60 80 100 120
050
100
150
200
250
300
350
Deflection, d (mm)
App
lied
Load
, P (k
N)
<< Nominal maximum girder load
Ultimate load
SHM: Recording vehicle activity
(Moore, 2012) 18
Daily vehicle activity
(Moore, 2009, 2012) 19
Determine girder baseline MoE • Measure bridge:
– Span – Girder shape – Girder Diameters – Decking
• Weigh vehicle – Front axle mass – Rear axle mass
• Measure mid-span deflection of each girder
• Calculate MoE
(Moore, 2012)
(Moore, 2012)
Traffic load distribution
0 1 2 3 4 5
020
040
060
080
0
Stress (MPa)
Freq
uenc
y (X
10
21
Girder load tests
22
RTA, 1990
Wilkinson, 2008
23 Data from 338 girders removed from service (Moore, 2012)
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
24
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MPa
14 GPa >
25
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)36 GPa >
86 MPa
14 GPa >
26
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MPa
14 GPa >
Data AS 1720:2000/H2.1; 5th percentile
27
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MPa
14 GPa >
Girder strength distribution
0 5 1 0 1 5 2 0 2 5 3 0
0
0 . 0 5
0 . 1
0 . 1 5
0 . 2
0 . 2 5
Strength Magnitude (MPa)
Pro
babi
lity
Den
sity
← StrengthDistribution
28
Traffic load and girder strength distributions
0 5 1 0 1 5 2 0 2 5 3 0
0
0 . 0 5
0 . 1
0 . 1 5
0 . 2
0 . 2 5
Load & Strength Magnitude (MPa)
Pro
babi
lity
Den
sity ← LoadDistribution
← StrengthDistribution
29
Failure region
0 5 1 0 1 5 2 0 2 5 3 0
0
0 . 0 5
0 . 1
0 . 1 5
0 . 2
0 . 2 5
Load & Strength Magnitude (MPa)
Pro
babi
lity
Den
sity ← LoadDistribution
← StrengthDistribution
FailureRegion
30
0 50 100 150 200
020
040
060
080
0
Stress (MPa)
Freq
uenc
y (X
10
Applied stress G6-MU MoR
0 5 10 150.
000
0.00
20.
004
0.00
60.
008
0.01
0
Stress (MPa)
Freq
uenc
y (X
10
Applied stress G6-MU MoR
Failure region
Failure rate: 2 in107
Fmax = 11.6 MPa
Failure rate: 2 in 107; Safety Index = 5.1 31
32
Probability of failure Safety Index
1 in 103 3.1
1 in 104 3.7
1 in 105 4.3
1 in 106 4.8
1 in 107 5.2
NORMSINV(probability) calculates the inverse of the normal cumulative distribution function
12
34
5
Probability of failure
Safe
ty In
dex
100 101 102 103 104 105 106 107
0 1 2 3 4 5 60.
00.
20.
40.
60.
81.
0
Stress (MPa)
Freq
uenc
y (X
10
Applied stress G4-MU MoR
Failure region
Failure rate: 1157 in107
Fmax = 8.6 MPa
0 50 100 150 200
010
020
030
040
050
060
0
Stress (MPa)
Freq
uenc
y (X
10
Applied stress G4-MU MoR
Failure rate: 1157 in 107; Safety Index = 3.7 33
Interpretation of Safety Index
• Total cost of system failure = cost of an individual failure x number of failures
• If the failure cost is small a higher failure rate can be tolerated
– In such a case a failure rate of 1 in 103 and a safety index of 3.1 is generally acceptable
• A high failure cost necessitates a low failure rate
– In this type of case a failure rate of 1 in 106 and a safety index of 4.8 or higher is expected
– To achieve a lower failure rate can require excessive design and construction costs
34
Failure examples • Small increased deflection of a bridge
– Condition: Deflection may exceed design standard of 600:1 (No component is expected to break or deform)
– Limit state: 1 in 103; safety index > 3.1
• Large increase in deflection – Condition:
Structural strength in question (Components may break or deform)
– Limit state: 1 in 106; safety index > 4.8
35
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
< 14 GPa
Jarrah
Radiata Pine
Tallowwood
Ironbark
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
Tabulated MoR and MoE data
37 (Bolza & Kloot, 1963, p. 54)
38
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
Excised samples174 Species of timber (CSIRO)
Radiata Pine
Ironbark
Clustering – Ironbark girders
• Condition State 1. No decay, CS-1 2. Minor decay, CS-2 3. Medium decay, CS-3 4. Advanced deterioration, CS-4
• Failure mode 1. Mid-span bending failure, FM-1 2. Non mid-span bending failure, FM-2
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MPa
14 GPa >
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
Ironbark Girders Ironbark Girders
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
Ironbark Girders, CS-1, FM-1
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
1
Mean Ironbark,CS-1,FM-1 Mean Ironbark,CS-1,FM-1
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
12
1 IB,CS-1,FM-1 2 IB,CS-2,FM-1
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
1 IB,CS-1,FM-1 2 IB,CS-2,FM-1 3 IB,CS-2,FM-2
123
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
123
41 IB,CS-1,FM-1 2 IB,CS-2,FM-1 3 IB,CS-2,FM-2 4 IB,CS-3&4,FM-2
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
123
4
Ironbark
1 IB,CS-1,FM-1 2 IB,CS-2,FM-1 3 IB,CS-2,FM-2 4 IB,CS-3&4,FM-2
0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
2A, 15 years 2B, 45 years
123
4
Ironbark
2A
2B
CONCLUSIONS • Girder MoE and MoR can be experimentally
determined
• Probability of failure can be calculated
• A bridge safety limit can be continuously quantified using a SHM system
48 0 10 20 30 40 50
050
100
150
200
MoE (GPa)
MoR
(MPa
)
86 MP
14 GPa >
2A, 15 years 2B, 45 years
123
4
Ironbark
2A
2B
