dynamic strain monitoring for detecting fracture ...

The 6th International Conference on Structural Health Monitoring of Intelligent Infrastructure Hong Kong | 9-11 December 2013

DYNAMIC STRAIN MONITORING FOR DETECTING FRACTURE DAMAGE AT BEAM-ENDS IN STEEL MOMENT-RESISTING FRAMES X. Li1, M. Kurata2, and M. Nakashima2 Department of Architecture and Architectural Engineering, Kyoto University, Kyoto, Japan 2 Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan

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ABSTRACT Information reported by the post-earthquake rapid damage inspection of public, credible shelters, residential, and office buildings is essential for avoiding unnecessary disorder in economic and social recovery after a devastating earthquake. Structural health monitoring (SHM) systems that are designed to provide objective data in an autonomous way using the sensing systems installed on buildings is promising for enhancing the current inspection practices. The damage detection methods commonly embedded in SHM systems utilizing the global characteristics of buildings (e.g., modal properties and maximum floor responses) are hardly competent to give reliable and adequate information for local damage on individual structural elements as such local damage has no clear relationship with the global vibrational characteristics of buildings. Thereby, the detection of local damage such as buckling and fracture around beam-to-column connections that would result in substantial reduction in the strength and stiffness of structural components requires the development of an alternative strategy. This paper firstly presents a strain-based damage index for detecting local damage at beam-ends in steel moment-resisting frames with strainbased monitoring strategies. Second, a developed damage detection scheme was numerically studied utilizing a 9story steel moment-resisting frame designed for the SAC project. Finally, the effectiveness of the developed damage index was verified through a series of vibration testing using a 5-story steel testbed frame that can simulate fracture at beam-to-column connections. In the testing, dynamic strain responses of the testbed frame was collected through a wireless sensing network interfaced with piezoelectric strain sensors. KEYWORDS Structural health monitoring; steel moment-resisting frame; local damage detection; dynamic strain sensing INTRODUCTION In the 1994 Northridge earthquake and 1995 Kobe earthquake, a large number of steel buildings suffered with buckling and fractures at welded beam-to-column connections (Nakashima et al., 1995; Gates et al., 1995; Mahin et al., 1998). The post-earthquake inspection for the connection damage with non-destructive evaluation (NDE) techniques such as visual examination and ultrasonic testing required extensive costs and labors involved in the removal of fire-proofing and architectural finishes. Structural health monitoring (SHM) systems that monitor structural dynamic responses and vibrational properties using sensors installed on buildings have a potential to reduce such inspection efforts. The damage detection methods embedded in current SHM systems utilize the changes of modal properties and maximum inter-story drift ratios for damage assessment by monitoring global responses (e.g., floor accelerations and velocities). However, such damage detection methods are hardly competent to give reliable and adequate information for local damage (e.g., local buckling and fractures) on individual elements as such local damage has no direct relation to the global characteristics of buildings due to the strong nonlinearity in the structural behaviors under large deformation and the inherent uncertainties in material properties (Ji et al., 2011; Chung et al., 2011). A SHM system that only provides vague outputs that increases confusion in inspections and associated decision-makings is not desirable.

This paper presents the development of a local damage detection methodology for steel moment-frame buildings that can provide accurate damage assessments for beam-end fractures. For monitoring dynamic strains of structural members, a wireless dynamic strain sensing system consisted of PVDF (polyvinylidene difluoride) piezo films and Narada wireless units was developed. The performance of the presented local damage detection methodology was numerically and experimentally studied through a 9-story steel moment-resisting frame designed for the SAC project and a series of vibration tests on 5-story steel testbed frame constructed in the structural laboratory at DPRI, Kyoto University.

Strain time-history a

Before fracture

STRAIN-BASED LOCAL DAMAGE DETECTION

Figure 1 schematically demonstrates the proposed methodology of local damage detection for individual members in steel moment-resisting frames by monitoring strain responses. In steel moment-resisting frame, the distribution of bending moment changes by local damage in structural members. The structural members with damage sustain a smaller amount of bending moment than that originally sustained at the undamaged condition due to the reduction of bending stiffness relative to surrounding members. The top plot in Figure 1 illustrates such phenomena observed in a case where the second moment of inertia of a beam end at the second floor in a three-story steel moment-resisting frame is reduced by 50%. In the re-distributed moment, a limited part of the frame with only the several neighboring members is affected. The comparison of original distribution and re-distribution of bending moments provides useful information on detecting local damage in individual elements but it is not feasible to measure bending moments in real buildings. Instead, the constructed damage index directly utilizes dynamic strain responses as sources for approximating bending moments, assuming the amplitude of strain at one location in a member is proportional to that of the bending moment carried by the member.

a

b

b

a

After fracture a

fracture

fracture a Before Strain time-history a a b b

Before fracture a b

Before fracture a

Strain response b

b

fracture

a b

a

Before earthquake a b

After fracture

Strain time-history a

a

b

Damage

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a

fracture

After fracture

fracture

Strain time-history b a After fracture

b

a

Damage index b

a

b

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b

a

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After earthquake

b

DI 

Rid  Ri  100% Ri

Figure 1 Strain-based local damage detection In steel moment-resisting frames, according to equivalent static force approach and structural modal analysis method (Chopra, 2001), the distribution of elastic strain (measured outside damage probable region of structural members) associated with the dominant modes vibration is weakly dependent on the characteristics of external excitations, and only relates to structural properties corresponding to the dominant modes. Thereby, seismic damages in individual members can be detected by a comparative study of dynamic strain responses on individual members under various loadings (aftershocks and even ambient excitations) before and after destructive earthquakes. The extent of damage in individual members is expressed by a damage index DI as follows: R d  Ri (1) DI  i  100% Ri where and conditions.

corresponding to the elastic strains in the ith dominant mode vibration at undamaged and damaged

NUMERICAL DAMAGE DETECTION SCHEME FOR SAC 9-STORY BUILDING SAC 9-story building The 9-story building used for this study was designed by Brandow & Johnston Associates (1996) for the SAC Phase II Steel Project. Although not actually constructed, the building met seismic code and represented typical medium-

rise buildings designed for the Los Angeles, California region (FEMA-355C, 2000; Ohtori et al., 2004). The 9-story building is 45.73 m by 45.73 m in plan, and 37.19 m in elevation (see Figure 2). The bays are 9.15 m on center, in both directions, with five bays each in the N-S and E-W directions. The lateral load resisting system of the building is comprised of four perimeter steel moment-resisting frames. The interior bays of the structure contain gravity frame with composite floors. The member sizes of the frame A shown in Figure 2(b) is listed in Table 1. The columns of the steel moment-resisting frame are 345 Mpa (50 ksi) wide flanges. The column bases are modeled as pins to connect the ground. The floor system consists of 248 Mpa (36 ksi) steel wide flange beams acting compositely with floor slab. The inertial effects of each floor are assumed to be evenly carried by each perimeter moment-resisting frame through the floor system. Hence, each frame resists one-half of the seismic mass. The seismic mass of the ground level is 9.65×105 kg, for the second floor is 1.01×106 kg, for the third through ninth floor is 9.89×105 kg, and for the tenth floor is 1.07×106 kg. F

A

D C

8 @ 3.96

5 bays @ 9.15

E

B

5 bays @ 9.15

N (a) Building plan (units: m)

Story/Floor -1/1 1/2 2/3 3/4 4/5 5/6 6/7 7/8 8/9 9/Roof

3.65 5.49

B A

Damage

Ground

(b) Frame A elevation (units: m) Figure 2 SAC 9-story building.

Table 1 Member sizes of frame A. Columns Exterior Interior W14x370 W14x500 W14x370 W14x500 W14x370, W14x370 W14x500, W14x455 W14x370 W14x455 W14x370, W14x283 W14x455, W14x370 W14x283 W14x370 W14x283, W14x257 W14x370, W14x283 W14x257 W14x283 W14x257, W14x233 W14x283, W14x257 W14x233 W14x257

Girder W36x160 W36x160 W36x160 W36x135 W36x135 W36x135 W36x135 W30x99 W27x84 W24x68

Numerical simulation for damage detection The frame A was numerically studied using a structural analysis code, SAP2000. In this study, bending moment responses in steel members were directly utilized to compute the damage indices in Equation (1) instead of strain responses. Beam end damage (see Figure 2(b)) was simulated by the reduction of the second moment of inertia at the beam end. The monitored points A and B were at 1.0 m away from the columns. The frame was excited with two excitations (Figure 3): (1) a white noise (WN) with RMS of 2 gal; (2) a minor earthquake (ME) with maximum acceleration of 24 gal. Figure 4 shows the bending moment responses and their power spectral densities of the point A under the undamaged condition for two excitations. The power spectral densities indicate that the structural vibration was mainly dominated by the first three modes. The bending moment responses of points A and B associated with the first three modes were respectively used for calculating the damage indices of the damage near point B under two

different excitations. Point A was the reference position where was considered to be away from damage location. Since the first three frequencies of all conditions were close to 0.40, 1.10, and 1.90 Hz, the band-pass filters of 0.200.60, 0.90-1.30, and 1.70-2.10 Hz were separately selected to obtain the bending moment responses associated with the first three mode motions. Figure 5(a) shows that as the second moment of inertia decreases at the beam end, the damage index drops from 0 to −100% for two excitations. The plot implies the independency of the damage index on the type of external excitations (e.g., white noise and earthquake ground motion). Figure 5(b and c) indicate that the damage indices separately extracted from the first three mode vibrations are identical for each external excitation. This fact implies that damage index can be extracted from any dominant mode motions. 10

30 20

Acc./gal

Acc./gal

5 0 -5 -10

10 0 -10 -20

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30 Time/sec.

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-30

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(a) White noise

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30 Time/sec.

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(b) Minor earthquake Figure 3 Input motions.

1.2

-5 -10

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20 40 Time/sec.

60

0.8 0.4 0

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(a) White noise

2

4 6 8 Frequency/Hz

10

10

PSD

0

1.2

20

Moment/KN-m

PSD

5

0 -10 -20

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20 40 Time/sec.

60

0.8 0.4 0

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2

4 6 8 Frequency/Hz

(b) Minor earthquake Figure 4 Bending moment responses. Damage index (%)

0 -20 -40 -60 white noise minor earthquake

-80 -100

0

20 40 60 80 100 Decrease of second moment of inertia (%)

(a) DI extracted from the first mode motion 0

-20 -40 -60

1st mode 2nd mode 3rd mode

-80 -100

0

20 40 60 80 100 Decrease of second moment of inertia (%)

Damage index (%)

0

Damage index (%)

Moment/KN-m

10

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1st mode 2nd mode 3rd mode

-80 -100

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20 40 60 80 100 Decrease of second moment of inertia (%)

(b) DI extracted from white noise responses (c) DI extracted from minor earthquake responses Figure 5 Numerical simulation results.

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EXPERIMENTAL VERIFICATION USING 5-STORY STEEL FRAME TESTBED Steel frame testbed The 5-story steel frame testbed with the dimension of 1×4×4.4 m was constructed in the structural laboratory at DPRI, Kyoto University (Figure 6(a)). The plan of the frame was one bay by two bays. The member sizes of the testbed frame are summarized in Table 2. Removable connections where beams and columns were connected to joints using four removable links at flanges and one pair of removable links at a web (Figure 6(b)) was installed for simulating fracture damage were at the 2nd, 3rd and 5th floors in the longitudinal frame. 4m

Member Beam Column

4.4m

(b) Removable links at a joint

Bracing

Table 2 Member sizes. Location Size (SS400 steel) 1st - 5th stories H-100x100x6x8 1st - 5th stories H-100x60x6x8 M10 steel rod, x1st - 5th stories bracing

(a) Overview Figure 6 Testbed frame. Wireless dynamic strain sensor network A wireless dynamic strain sensor network that consists of a dense array of PVDF sensors (DT1-028k, Measurement Specialties, 2013) interfaced with Narada wireless sensing units (Civionics, LLC, 2013) was developed to measure dynamic strain responses in the steel frame (Figure 7). Figure 8 shows the locations of twenty PVDF sensors deployed to a frame of the steel testbed. All sensors were attached with strong adhesive on one side of the bottom flange of beams at 330 mm away from the center line of columns. The location of the sensors were outside probable yielding zones near beam-to-column connections so that elastic strain responses of the beams were measured and sensors remained functional even with severe damage around the connections. Excitations and damage patterns The steel testbed frame was excited at the fifth floor using a modal shaker (APS-113, APS Dynamics) firmly fixed to the steel mass plates by four machine bolts (Figure 8). For each structural condition, the steel frame was excited in the longitudinal direction using three loadings: (1) ambient excitation (AmbE); (2) small amplitude white noise (WN1); and (3) large amplitude white noise (WN2). In the structural laboratory where the testbed frame located, the level of ambient excitation mainly caused by ground microtremor was around 0.49 gal in RMS at the top floor. When the two white noise excitations with the frequency range of 1-50Hz were input for the undamaged condition, the typical acceleration responses of the top floor in terms of RMS were 3.32 and 8.45 gal for WN1 and WN2, respectively. Two types of seismic damage, i.e. entire bottom flange fracture, and entire bottom flange and web fracture were simulated. Figure 9 shows the section of a removable connection and two levels of damage, and the geometric relationship of the defined damage categories to the position of PVDF sensors. In the level 1 (L1) damage, all two links of the bottom flange of the connections were removed. In the level 2 (L2), a web link in addition to bottom flange links were removed. Table 3 summarizes these damage categories with their reduction factors on the second moment of inertia about the strong axis of the beam section.

Transceiver

Wireless unit

PVDF sensor PVDF

Narada unit Narada transceiver (a) Wireless sensor network Figure 7 Wireless PVDF sensing system.

Shaker

(b) Setup views

Flange link with dog-bone shape

L1 Outside Sensor

Inside Web link with rectangular shape

L2 Figure 8 Beam connection and sensor location Table 3 Damage categories and their descriptions. Damage Reduction Descriptions categories of EIx (%) All links of bottom flange L1 68.5 are removed All links of bottom flange L2 99.8 and web are removed

Figure 9 Connection section and damage categories Table 4 Damage cases and their descriptions. As detected Influence sources Damage cases Location Category Location Category Case 1 B2 L1 Case 2 B3 L1 B2 L2 Case 3 B3 L1 B4 L2 Case 4 B2 L2 Case 5 B3 L2 B2 L2 Case 6 B3 L2 B4 L2

Damage cases Figure 8 shows twelve removable connections on beams, which was able to simulate seismic fracture at beam ends. Six damage cases were considered for evaluating the performance of the damage detection method (Table 4). In Case 1, damage L1 was simulated at B2; and in Case 4, damage L2 was also simulated at B2. In these cases, individual damage L1 (or L2) was studied. The influences of neighboring damage on damage index were considered in Cases 2 and 3 for detecting damage L1, and in Cases 5 and 6 for detecting damage L2. In these cases, damage L2 at B2 (or B4) were as influence sources for damage detection of L1 (or L2) at B3. B2 lay on the closest end of the neighboring beam; B4 lay on the other end of the same beam. For example, the influences of damage L2 at B2 on the detection of damage L1 at B3 were studied in Case 2. Results and discussions For each PVDF sensor, strain time history was recorded for 75 seconds with the sampling rate of 100 Hz. The structural vibration was mainly dominated by the first mode. The first natural frequency of the steel frame is close to

3 Hz for all considered conditions. The strain responses associated with the first mode was used for computing the damage index. Considering the slight changes in the first natural frequency for all damage cases, the band-pass filter of 2.70-3.30 Hz was selected to obtain the dynamic strain associated with the first mode. Then the RMS values of all filtered strain responses were normalized with the RMS value of the reference strain data measured at the beam of the top floor (S20 in Figure 8) which was considered to be away from damage probable positions. Figure 10 shows the damage index estimated for the undamaged and two representative damage cases (Case 4 and 6) with three excitations. At the undamaged condition, the variation of DI was smaller than 10% for all input excitations (Figure 10(a)). Figure 10(b) shows the results for Case 4 where all links of bottom flange and web were removed at B2. The DI of −90% at S2 clearly indicated the existence of severe damage at B2. Furthermore, the DI of +30% at S3 also indicated the existence of damage at their neighbors. The maximum difference of DI at S2 for three excitation inputs was only 7.3%, implying the weak dependency of the damage index on the characteristics of external excitations. As seen in Figure 10(c), the verification tests were also successful for damage Case 6.

(a) Undamaged

Damage cases Case 1 Case 2 Case 3 Damage cases Case 4 Case 5 Case 6

(b) Case 4

(c) Case 6 Figure 10 Damage index for each sensor. Table 5 Damage index for damage L1. Damage index (%) AmbE WN1 WN2 Mean -59.6 -60.4 -59.6 -59.9 -34.8 -34.1 -33.5 -34.1 -50.3 -50.9 -50.4 -50.5 Table 6 Damage index for damage L2. Damage index (%) AmbE WN1 WN2 Mean -87.1 -93.8 -94.0 -91.6 -90.4 -91.6 -91.3 -91.1 -92.4 -99.1 -99.0 -96.8

Standard deviation 0.5 0.7 0.3

Standard deviation 3.9 0.6 3.8

The damage index for damage L1 and L2 as detected in Table 4 are separately summarized in Table 5 and 6. Case 1 show that the value of DI was about −60% for detecting individual damage L1. Case 3 indicate that the values of DI were around −50% for damage L1 at B3, implying that the influences of the entire bottom flange and web fracture (L2) at the other end of the same beam on the detection of damage L1 are 10% for DI values, whereas Case 2 indicates large influences from the entire bottom flange and web fracture (L2) at the closest end of the neighboring beam on detecting damage L1 as the values of DI increased to −34% for detecting damage L1 at B3. Case 4 show that the values of DI were about −90% for detecting individual damage L2. Cases 5 and 6 imply that there were negligible effects from the nearby serious damage on the detection of damage L2. In summary, when the entire bottom flange of beam end fractures, the DI value of the sensor placed on one side of the bottom flange was between −50% and −60%, but the DI increased to −34% in the extreme cases in which a

serious level damage occurred at the closest end of the neighboring beam. In contrast, when fractures occur at the entire bottom flange and web of beam ends, the DI value of the same sensor was always smaller than −85%. This clear discrete distribution of damage index values for the two different damage levels would facilitate the detection of the aforementioned fracture damage at beam ends in steel buildings. CONCLUSIONS This paper presented the development of a local damage detection methodology for steel buildings using wireless dynamic strain sensors. The performance of the method was experimentally verified using a 5-story steel frame testbed that was able to simulate fracture damage at member ends. The notable findings are summarized as follows: (1) The wireless strain sensing system composed of PVDF sensors and Narada wireless units had excellent performances for monitoring dynamic strain in steel buildings under various loadings including ambient excitations. (2) In the numerical example and vibration tests, the independency of damage index on the characteristics of external excitations and mode motions was also verified. (3) In the simulation of seismic damage, fractures at beam ends were successfully detected by the damage index values extracted from the sensors placed on one side of bottom flanges. Furthermore, the clear discrete distribution of damage index values for different damage extent enables pattern recognition methods to detect various fractures at beam ends in steel buildings. ACKNOWLEDGMENTS The authors would like to gratefully acknowledge the assistance offered by Dr. Tang Zhenyun and Ms. Mayako Yamaguchi in the experimental studies of the project. REFERENCES Chopra, A. K. (2001). Dynamics of structures: theory and applications to earthquake engineering, 2th edition, Prentice Hall. Chung, Y., Nagae, T., Matsumiya, T., and Nakashima, M. (2011). “Seismic resistance capacity of beam-column connections in high-rise buildings: E-Defense shaking table test”, Journal of Earthquake Engineering & Structural Dynamics 40(6), 605-622. Civionics, LLC, (2013). http://civionics.com/. FEMA-355C (2000). State of the art report on systems performance of steel moment frames subject to earthquake ground shaking. Gates, W. and Morden, M. (1995). “Lessons from inspection, evaluation, repair and construction, surveys and assessment of damage to buildings affected by the Northridge earthquake”, Report SAC 95-06, SAC Joint Venture, Sacramento. Ji, X., Fenves, G., Kajiwara, K., and Nakashima, M. (2011). “Seismic damage detection of a full-scale shaking table test structure”, Journal of Structural Engineering 137(6), 14-21. Measurement Specialties, Inc (2013). www.meas-spec.com. Mahin, S. (1998). “Lessons from damage to steel buildings during the Northridge earthquake”, Engineering Structures, 20(4-6), 261-270. Nakashima, M. (1995). “Reconnaissance report on damage to steel buildings structures observed from the 1995 Hyogoken-Nanbu (Hanshin/Awaji) earthquake”, Abridged English edition, Steel Committee of Kinki Branch, the Architectural Institute of Japan (AIJ). Ohtori, Y., Christenson, R. E., Spencer, B. F., and Dyke, S. J. (2004). “Benchmark control problems for seismically excited nonlinear buildings”, Journal of Engineering Mechanics, 130(4), 366-385.