Nondestructive testing of externally reinforced structures for seismic retrofitting using flax fiber reinforced polymer (FFRP) composites

C. Ibarra-Castanedo*a, S. Sfarrab, D. Paolettib, A. Bendadaa and X. Maldaguea

aComputer vision and systems laboratory, Université Laval, 1065, av. de la Médecine, Quebec City (Quebec) G1V 0A6, Canada, {IbarraC, Bendada, MaldagX}@gel.ulaval.ca; bLAS.E.R. Laboratory,

Dept. of Industrial and Information Engineering and Economics (DIIIE), University of L'Aquila, Italy, {Stefano.Sfarra, Domenica.Paoletti}@univaq.it

ABSTRACT

Natural fibers constitute an interesting alternative to synthetic fibers, e.g. glass and carbon, for the production of composites due to their environmental and economic advantages. The strength of natural fiber composites is on average lower compared to their synthetic counterparts. Nevertheless, natural fibers such as flax, among other bast fibers (jute, kenaf, ramie and hemp), are serious candidates for seismic retrofitting applications given that their mechanical properties are more suitable for dynamic loads. Strengthening of structures is performed by impregnating flax fiber reinforced polymers (FFRP) fabrics with epoxy resin and applying them to the component of interest, increasing in this way the load and deformation capacities of the building, while preserving its stiffness and dynamic properties. The reinforced areas are however prompt to debonding if the fabrics are not mounted properly. Nondestructive testing is therefore required to verify that the fabric is uniformly installed and that there are no air gaps or foreign materials that could instigate debonding. In this work, the use of active infrared thermography was investigated for the assessment of (1) a laboratory specimen reinforced with FFRP and containing several artificial defects; and (2) an actual FFRP retrofitted masonry wall in the Faculty of Engineering of the University of L’Aquila (Italy) that was seriously affected by the 2009 earthquake. Thermographic data was processed by advanced signal processing techniques, and post-processed by computing the watershed lines to locate suspected areas. Results coming from the academic specimen were compared to digital speckle photography and holographic interferometry images.

Keywords: natural fibers, flax fiber reinforced polymer, seismic retrofitting, active infrared thermography, holographic interferometry, digital speckle photography, nondestructive testing composites.

1. INTRODUCTION Composites materials are constituted by a combination of two or more materials having significantly different physical properties. The interest for this kind of materials is mainly due to the fact that the new structure possess enhanced characteristics, i.e. they are usually lightweight and less prompt to corrosion than monolithic materials without significantly loosing or sometimes even improving strength and stiffness. Fiber-reinforced polymers (FRP) are a classical configuration of engineered composite materials constituted of a combination of synthetic fibers, e.g. carbon, glass, or aramids, glued together in a matrix of thermoplastic materials, typically epoxy resin although several other can be found. Typical applications include aerospace components, automotive and nautical parts, and building retrofitting, among many others.

There is a renewed interest in using natural fibers, as an alternative to synthetic fibers, due to their lower cost, fairly good mechanical properties (high specific strength, comparable specific tensile properties, low density) as well as their non-abrasive, eco-friendly (reduced energy consumption, less health risk, renewability, recyclability) and bio-degradability characteristics[1],[2]. In addition, natural fibers are easier to handle and have good thermal and acoustic insulation properties[3].

Natural fibers have been used as a filler material in cement pastes, concrete and mortar [4]-[6], in a manner similar to what has been done for hundreds of years by many ancient cultures to reinforce construction materials such as clay and mud * Clemente.Ibarra-Castanedo@gel.ulaval.ca; phone 1 418 656-2131 ext. 4786; fax 1 418 656-3159; mivim.gel.ulaval.ca

Thermosense: Thermal Infrared Applications XXXV, edited by Gregory R. Stockton, Fred P. Colbert, Proc. of SPIE Vol. 8705, 87050U · © 2013 SPIE · CCC code: 0277-786X/13/$18 · doi: 10.1117/12.2017875

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for the construction of walls and buildings. With the addition of the fibers, naturally brittle materials such as concrete, become more ductile and lightweight.

Hybrid composites composed of both synthetic and natural fibers have also been considered in order to reduce costs and weight without significant reduction of performance[7]. In one comparative investigation between glass and natural fiber composites, it was concluded that the use of natural fibers ensures a lower environmental impact, reduces the amount of polluting base polymers (given the higher fiber content for equivalent performance), improves fuel efficiency and reduces emissions; and might result in energy and carbon credits[8]. Furthermore, although glass composites are stronger than most natural fiber composites, glass is very brittle, which under a dynamic load (such as in seismic waves), the disconnection of fibers (composite) and brick (masonry) could have severe consequences. It is clear that a more ductile kind of fibers such as jute would have a significant improvement for both strength and ductility, as some studies have demonstrated[10].

Of course, there are a number of drawbacks linked to the use of natural fibers in composites, an important one being the incompatibility between the hydrophilic natural fibers and the hydrophobic thermoplastic matrices, which could lead to undesirable properties of the composites. It is therefore necessary to modify the fiber surface by employing chemical modifications to improve the adhesion between fiber and matrix[1].

Natural fibers can be divided in three groups according to their origin: animal, mineral and vegetable, with the later being the most widely investigated given their abundance compared to the others[7]. Natural fibers from vegetable sources can be subdivided into three distinct groups: leaf (abaca, cantala, curaua, date palm, henequen, pineapple, sisal, banana); bast (flax, kenaf, hemp, jute, ramie); and seeds/fruits (cotton, coir, kapok, oil palm). Bast fibers (collected from the stem of the plants) are particularly interesting for retrofitting applications due to their good mechanical properties[7].

Flax fiber reinforced polymer (FFRP) composites are particularly interesting for seismic retrofitting due to their high strength-to-weight ratio and large deformation capabilities[9]. It has been cited as the natural fiber (among 20 other commonly used natural fibers) offering the best combination of cost, weight, strength and stiffness for structural applications[3].

In this paper, an experimental FFRP retrofitted specimen containing several artificial defects of different types was inspected by square pulse thermography (SPT) and lock-in thermography (LT), in order to assess the performance of these two techniques for the detection and characterization (depth estimation) of potential defects (air gaps and foreign material inclusions). SPT was then applied for the inspection of a retrofitted wall in the Faculty of Engineering of l’Aquila University (Italy).

Thermographic data was processed using different processing techniques, such as thermographic data reconstruction (TSR), pulsed phase thermography (PPT), and correlation operators. In addition, post-processing was also performed by computing the watershed lines to locate suspected areas. Selected results are herein presented.

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5Al A

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2. EXPERIMENTAL SETUP 2.1 Experimental specimen with artificial defects

The investigated experimental specimen consists of a concrete FFRP (FIDFLAX UNIDIR 430 HS43®) retrofitted column with 14 artificial defects distributed at different locations over four faces as indicated in Figure 1. Table 1 summarizes the characteristics of the different defects included in the experimental specimen: type, size, depth and thickness, as reported by the manufacturer.

The specimen was inspected by SPT and LT. A schematization of the experimental setup is presented in Figure 2.

(a) (b)

(c) (d) (e)

Figure 1. Experimental specimen (a) front view of Side A; schematic representation of defect distribution on (b) Side A; (c) Side B; (d) Side C; and (e) Side D.

IR camera

Specimen

Data display, storing and processing

Synchronization

Lamp

Figure 2. Experimental setup.

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Table 1. Defect characteristics.

Defect Type Size Reported depth

Reported thickness Reported location

A1 Battery 15x50 4 15 Concrete

A2 Void D=30 4 10 Concrete

A3 Teflon 40x20 2 2 Mortar-FFRP

A4 Sponge 40x40 1 5 Mortar-FFRP

B1 Void 50x40 20 20 Concrete

B2 Ceramic 35x30 3 10 FFRP-concrete

B3 Teflon 50x15 2 2 Mortar-FFRP

C1 Cork 40x20 4 20 Concrete

C2 Chesnutt D=30 2 20 Concrete

C3 Teflon 50x20 2 2 Mortar-FFRP

D1 Void 60x35 4 15 Concrete

D2 Steel 40x20 4 5 FFRP-Concrete

D3 Teflon 50x20 2 2 Mortar-FFRP

D4 Sponge 35x40 1 2 Mortar-FFRP

2.2 Retrofitted wall in the Faculty of Engineering, L’Aquila University

The City of L’Aquila, Italy has a long an unfortunate history of being struck by destructive earthquakes. The last major earthquake (5.8 on the Richter scale) hit the City in April 6, 2009. The impact of this event can still be seen and felt in L’Aquila. Nearly 300 people died and is estimated that between 3000 and 11000 buildings were affected, several of which collapsed, some were rebuilt, but most of them are still waiting to be repaired.

The building of the Faculty of Engineering of L’Aquila University was partially destroyed during this earthquake. Figure 3 presents three photographs of the main entrance to the building chronologically disposed from after the earthquake to today.

The building is currently in the process of reconstruction, the reopening is scheduled for September 2013. Several internal walls have being retrofitted using FFRP (FIDFLAX UNIDIR 430 HS43®). Figure 4 shows a view of one of such walls right after the earthquake (Figure 4a) and after retrofitting (Figure 4b).

An area of 400x190 mm2 (shown in Figure 5) was inspected by square pulse thermography using an infrared lamp (Helios Infrared IRK HP1, 2kW) by heating the area of interest during 10 minutes and recording also the cooling for 10 more minutes.

Data was acquired during heating and cooling (a total of 20 minutes) using a long-wave infrared camera (FLIR S65 HS, 7.5-13 μm, 320x240 pixels), and processed using different processing techniques. Results are presented and discussed in the following section.

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(a) (b) (c)

Figure 3. View of the main entrance to the Faculty: (a) after the earthquake; (b) during reconstruction; and (c) after reconstruction.

(a) (b)

Figure 4. View of the inspected area: (a) after the earthquake; and (b) after reconstruction/retrofitting.

(a) (b)

Figure 5. (a) In situ acquisition setup; (b) close up view of the retrofitted area inspected by active thermography.

IInnssppeecctteedd aarreeaa

IInnssppeecctteedd aarreeaa PPrroocceesssseedd aarreeaa

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3. EXPERIMENTAL RESULTS 3.1 Experimental specimen with artificial defects

A series of tests were performed on the 4 faces of the specimen using SPT and LT configurations. Two examples are presented in Figure 6 for face A.

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Figure 6. (a) Raw thermogram at t=354 s acquired during square pulse heating (15 minutes heating, 2 x 500 W, 60 minutes recording); (b) thermal profiles for the corresponding areas for defect A4 and a sound area next to it; (c) raw thermogram at t=354 s acquired during periodic heating (f=0.0125 Hz, 200 to 600 W modulation); and (d) corresponding thermal profiles for the areas of interest (A4 and Sa).

The thermogram sequences obtained both by SPT and LT were processed using the PPT algorithm. The resulting SPT and LT phasegrams at selected frequencies are presented in Figure 7 and Figure 8, respectively. As can be observed from these results, there is a close resemblance between SPT and LT phasegrams for equivalent frequencies. It should be recalled though that the manner in which data is acquired by SPT is different than the way LT is obtained. In SPT, a single test (heating: 15 minutes, cooling: 45 minutes) was necessary to obtain the results presented in Figure 7. As a drawback, high frequency phasegrams contain an important amount of noise, which do not allow to produce clear images, i.e. with good enough signal-to-noise ratio (SNR). On the other hand, 9 different tests were required to obtain the phasegrams in Figure 8, with the advantage of having large SNR in all cases (low and high frequencies). The drawback however, as it is well-known, is that long acquisitions times were required, especially for low frequency modulation. For instance, at one end, a modulation frequency of 0.05 Hz necessitates only 20 s in order to record 1 cycle, while at the other end, a modulation frequency of 0.00027 Hz requires 60 minutes to record 1 cycle. In all cases, at least 2 cycles were recorded to assure that a quasi-stationary regime was attained, as shown in Figure 6d.

As these images show, only one defect is detected (defect A4, see Figure 1 and Table 1, which consist of a 40x40x5 mm3 sponge reportedly located at a depth of 1 mm. Based on the information presented in Table 1, it should be possible to detect the other three defects present in this side of the specimen as well, since they are supposedly located at a maximum depth of 4 mm through two different layers: an outer lime plaster layer (~1-2 mm) and an FFRP layer (~2 mm). Nevertheless, this was not the case. In order to further investigate the reason of this discrepancy, depth estimation was carried out using the definition of thermal diffusivity μ, given by the following equation:

bfz

⋅=⋅=

παμ 8.18.1

(1)

where fb [Hz] is the blind frequency defined as the limiting frequency at which a defect located at a particular depth presents enough (phase or amplitude) contrast to be detected on the frequency spectra.

From eq.(1) it is possible to compute the depth that could be reached by a thermal wave at a particular modulating frequency, i.e. the blind frequency fb. This relationship is valid for both, lock-in [12] and pulsed [13] thermography data.

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-

-

i

For instance, the depth that could be attained using a high frequency modulated thermal wave (f=0.05 Hz, last phasegram in Figure 8) through lime plaster (7.54x10-7 m2/s)[11] would be around ~3 mm. Either the LT phasegram nor the SPT (although noise is omnipresent) phasegrams show any indication of defect A4 at a modulating frequency of 0.05 Hz. First signs of defect A4 are seen at a frequency of 0.0125 Hz, which means that the blind frequency for this defect should be between 0.0125 and 0.025 Hz. From eq. (1), the corresponding depth for lime mortar for these frequencies is in the range: 5.6 to 7.9 mm, i.e. much deeper than the reported 1 mm depth. The other three faces of the specimen were inspected in a similar manner, only defects A4 and D4 (not shown), both corresponding to sponges reportedly at ~1 mm depth (see Figure 1 and Table 1), were detected.

f=0.000265 Hz f=0.00053 Hz f=0.0013 Hz

f=0.0024 Hz f=0.005 Hz f=0.008 Hz

f=0.0125 Hz f=0.0247 Hz f=0.05 Hz

Figure 7. SPT phasegram at selected frequencies. Data obtained from a single experiment: square pulse 15 minutes heating, using 2 halogen lamps (1 kW) at 50% power (2 x 500 W) and recording for 60 minutes.

f=0.00027 Hz f=0.0005 Hz f=0.0013 Hz

f=0.0025 Hz f=0.005 Hz f=0.0075 Hz

f=0.0125 Hz f=0.025 Hz f=0.05 Hz

Figure 8. LT phasegram at selected frequencies.

For comparison, the specimen was inspected using optical techniques as well. Figure 9 presents two results obtained by holographic interferometry (Figure 9a) and digital speckle photography (Figure 9b). As for active thermography, optical techniques are capable of detecting only defect A4.

ffiirrsstt ssiiggnnss ooff ddeeffeecctt AA44

sshhaallllooww ffeeaattuurree

bbaarreellyy vviissiibbllee

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(a) (b) Figure 9. Inspection by optical techniques: (a) holographic interferometry; and (b) digital speckle photography.

A destructive test was carried out given that not only no defect other than the two sponges was detected even using very low modulating frequencies (theoretically capable of reaching depths of several millimeters trough lime mortar), together with the fact that the depth estimation from eq. (1) did not fitted the reported depth values for neither of the two detected defects in two different faces of the specimen.

Figure 10 presents a series of photographs taken while removing the mortar layer from the specimen. As can be seen in Figure 10a, a green plastic grid was installed in the mortar in order to provide additional strength. It was noticed also that the inclusion of the grid contributed to formation of a thin air layer between the mortar and the FFRP composite (see Figure 10b), no bonding was observed between these two layers. Furthermore, the mortar layer was much thicker than the 1-2 mm reported thickness (see Figure 10c). Measured values ranged between 4 and 7 mm. A plaster thickness of approximately 6 mm was measured right above defect A4 (see Figure 10d), which is in the depth range of the estimation presented above, i.e. between 5.6 to 7.9 mm.

After completely removing the plaster layer, only defects A4 and D4 (the two sponges, which are the only two detected defects) were directly exposed (see Figure 10e), the glue layer appeared more or less uniform although the FFRP composite could be clearly seen through the glue only at some locations (see Figure 10f).

(a) (b) (c)

(d) (e) (f)

Figure 10. Destructive test on the experimental specimen: (a) Green grid under the plaster; (b) thin air gap between mortar and FFRP composite; (c) variable mortar thickness (between 5 and 7 mm) over the 4 specimen faces; (d) a thickness of ~6 mm was measured over defect A4; (e) defects D4 and A4 directly exposed after mortar removal; and (f) the FFRP is seen through the glue layer at some specific areas.

Summarizing, the active thermography results together with the optical testing images and the observations gained after destructive testing, the reported mortar thickness do not correspond to the measurements performed during mortar removal. Depth calculations through eq. (1) are in agreement with what it was visually observed during the destructive test, i.e. the mortar thickness is approximately 6 mm over defect A4, 5 to 7 mm all over the specimen. The thin air gap

AA44

AA44 DD44 FFFFRRPP

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between the mortar and the FFRP composite acts as a thermal barrier, impeding defect detection at locations deeper than this interface (mortar-FFRP).

Even though the experimental specimen was elaborated in order to validate in situ measurement, the observed configuration do not correspond to the retrofitting application in the Faculty of Engineering of L’Aquila University (discussed in the next paragraph). A new series of tests will be performed after reapplying a mortar layer closer to the configuration of the real application.

3.2 Retrofitted wall in the Faculty of Engineering, L’Aquila University

A section (400x190 mm2) from a retrofitted wall in the Faculty of Engineering of L’Aquila University was inspected by SPT (10 minutes heating, 10 minutes cooling). Figure 11a shows a thermogram from the raw (unprocessed) sequence, while Figure 11b presents the thermal profiles for the areas highlighted in Figure 11a corresponding to a detected defect (trapped air) and a sound area next to it.

In addition, the PPT algorithm was applied to the cooling phase (ten last minutes in Figure 11b) to both raw thermographic data (points and crosses in Figure 11c), and to synthetic data obtained by TSR using a 6th degree polynomial fitting. The main goal of combining TSR with PPT was to produce de-noised temperature profiles (by TSR) from which the defect depth could be estimated (by quantitative PPT). From these profiles, the blind frequency was estimated to be fb=0.065 Hz. With this value, the depth of the defect, apparently trapped air under the FFRP composite layer, can be estimated using eq. (1). If the defect is located between the mortar and the FFRP layers, the thermal diffusivity of lime mortar must be employed for the depth calculations. On the contrary, if the defect was produced during the installation of the FFRP composite, which is a more probable hypothesis, the thermal diffusivity would actually be a combined value of the two layers: lime mortar and FFRP composite. Considering this, using the diffusivity of FFRP (1.5x10-7 m2/s)[14] and lime mortar will results in defect depths ranging between 1.5 and 3.5 mm, respectively for the given fb, it can be supposed that the actual depth should be between these values.

Defect

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(b) (c) Figure 11. (a) Raw thermogram at t=594 s acquired during square pulse heating (10 minutes heating, 10 minutes cooling, 2000 W); and (b) corresponding thermal profiles for the detected defect and a sound area; and (c) corresponding phase profiles after applying the PPT algorithm (during the 10 minutes cooling) to raw data (points) and to synthetic data (6th polynomial fitting by TSR).

The detected defect appears very clear since early in the sequence and for long time (see Figure 11b). However, there are other less evident suspect features appearing in the thermogram that should be addressed as well. Figure 12 presents the different steps undergone to identify additional potential flaws in this inspected area. Watershed analysis was applied for this purpose, departing from the thermographic correlation image, which was obtained by processing the entire thermographic sequence by correlation operators[15] (see Figure 12a).

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As can be seen from the images in Figure 12, there are three additional regions that seem to correspond to defective areas. In particular, defect A appear to be caused by the imperfect adhesion of the FFRP in the concavity between consecutive bricks; defect B is located at the border line between the reinforced brick and a layer of mortar (see Figure 5); and defect C is probably due to a lack of uniformity during the application of the FFRP with a straightening roll. All defects are shown in Figure 13. Defect D correspond to the flaw (air gap) shown in Figure 11.

(a) (b) (c) (d)

(e) (f) (g) (h)

Figure 12. (a) Thermographic correlation image; (b) binary image; (c) watershed distance transform; (d) superposition of watershed transform and the correlation image; (e) watershed gradient image; (f) watershed marker controlled image; (g) gradient and marker controlled image; and (h) superposition of watershed gradient and marked controlled image and the correlation image.

Figure 13. Map of detected defects in the retrofitted wall section of the Faculty of Engineering, L’Aquila University.

4. CONCLUSIONS An experimental specimen containing several artificial defects was constructed and tested by active infrared techniques in order to fine-tune the in situ measurements of retrofitted wall in a building from L’Aquila University. Only two of the 14 defects were detected by active thermography and optical techniques (holography interferometry and digital speckle photography). In addition, it was found that the reported depth locations (~1-2 mm) of the artificial defects did not correspond to depth estimations (~6 mm) obtained from the thermal diffusivity equation and the lock-in thermography results.

The experimental specimen was subjected to a destructive examination, from which it was confirmed that the depth estimations were in good agreement with the exact location (~4 to 7 mm) of the defects. A new series of active thermography experiments will be performed on the same specimen after reapplying a lime mortar layer with a thickness closer to what it is found in the real application (~2 mm).

DD

AACC

BB

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In parallel, a section of a retrofitted wall in the Faculty of Engineering of L’Aquila University was inspected by square pulse thermography, leading to the detection of 4 anomalies: defect A, caused by the imperfect adhesion of the FFRP in the concavity between consecutive bricks; defect B, located at the border line between the reinforced brick and a layer of mortar; defect C, probably due to a lack of uniformity during the application of the FFRP with a straightening roll; and defect D, an air gap possibly located beneath the FFRP layer. Detection of defects A, B and C was possible by performing watershed analysis to the thermographic correlation image. Depth estimation of defect D was carried out through a combination of quantitative PPT and TSR.

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