Accepted Manuscript

Visualization of Hidden Delamination and Debonding in Composites through

Noncontact Laser Ultrasonic Scanning

Byeongjin Park, Yun-Kyu An, Hoon Sohn

PII: S0266-3538(14)00184-5

DOI: http://dx.doi.org/10.1016/j.compscitech.2014.05.029

Reference: CSTE 5829

To appear in: Composites Science and Technology

Received Date: 15 December 2013

Revised Date: 30 April 2014

Accepted Date: 25 May 2014

Please cite this article as: Park, B., An, Y-K., Sohn, H., Visualization of Hidden Delamination and Debonding in

Composites through Noncontact Laser Ultrasonic Scanning, Composites Science and Technology (2014), doi: http://

dx.doi.org/10.1016/j.compscitech.2014.05.029

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1

Visualization of Hidden Delamination and Debonding in

Composites through Noncontact Laser Ultrasonic Scanning

Byeongjin Park1, Yun-Kyu An

2* and Hoon Sohn

1

1Department of Civil and Environmental Engineering, KAIST, Daejeon, South Korea

2International Institute for Urban Systems Engineering, Southeast University, Nanjing, China

b.park@kaist.ac.kr, ayk2028@gmail.com, hoonsohn@kaist.ac.kr

*Corresponding author

ABSTRACT

This study proposes a complete noncontact laser ultrasonic wavefield imaging technique to

automatically detect and visualize hidden delamination and debonding in composite

structures. First, ultrasonic wavefield is obtained from a target structure by scanning a

Nd:YAG pulse laser beam for ultrasonic wave generation and measuring the corresponding

ultrasonic responses using a laser Doppler vibrometer. Then, hidden damages are identified

and visualized through adoption of a standing wave filter, which can isolate damage-induced

standing waves from the obtained wavefield. The proposed technique has following

advantages over the existing techniques: (1) It does not require any sensor installation; (2) It

is noninvasive, rapidly deployable and applicable to harsh environments; and (3) It can

visualize damage with high spatial resolution without any baseline data, which enables

automated and intuitive damage diagnosis. The feasibility of the proposed technique is

demonstrated by visualizing a debonding in a carbon fiber reinforced plastic aircraft wing and

a delamination in a glass fiber reinforced plastic wind turbine blade. Furthermore, the effects

of temperature and static loading variations on the proposed technique are also examined.

Keywords: D. Nondestructive Testing, D. Ultrasonics, B. Debonding, B. Delamination,

Laser ultrasonic imaging

2

1. Introduction

There is an increasing demand and wide adoption of composite materials on various

industries including aircraft and wind turbine, because composite materials have numerous

advantages such as lightweight, high strength, corrosion/chemical resistances and non-

conductivity. However, these composite structures are inherently vulnerable to delamination

and debonding damages, because they are fabricated by bonding multilayers of laminates

with resins. Although such defects can pose serious problems on the structural safety and

integrity, their detection is a challenging task because they often occur between internal

laminates and are invisible from external surfaces.

Thus, a number of damage detection techniques have been proposed so that these

hidden damages can be effectively detected. One of the most widely used damage detection

techniques for composite inspection is an ultrasonic technique because it is sensitive to small

damages and capable of penetrating into internal laminates. Kessler et al. [1] and Sundaresan

et al. [2] generated and measured ultrasonic waves on a composite coupon and a wind turbine

blade using piezoelectric transducers (PZTs), and hidden damages were identified by

comparing the measured signals with baseline signals previously collected from the pristine

condition of the structures. However, this comparison usually leads to increased false alarms

due to operational and environmental variations. Then, Yeum et al. proposed a baseline-free

delamination detection technique for a composite plate by measuring the speed change of a

fundamental anti-symmetric Lamb wave mode using a concentric dual PZT network [3].

However, the aforementioned techniques often require a dense array of sensors to identify

and localize small defects. Furthermore, there are practical issues associated with the

deployment of a large number of discrete contact-type sensors: (1) Dense sensor installation

is not only high cost but also labor-intensive; (2) Permanently installed sensors will

deteriorate over time and become the weakest links in the inspection system, and their

3

maintenance and replacement might be a challenging work especially when they are installed

in hidden locations or embedded from the initial fabrication stage of structures; and (3)

Conventional contact-type sensors are not applicable under harsh environments such as high

temperature and radioactive conditions.

Alternatively, a number of noncontact damage detection techniques are available.

The noncontact techniques are advantageous over contact techniques because they can be

rapidly deployed in the field and applicable to a structure under harsh environments.

Furthermore, damage can be readily visualized and located because multiple spatial responses

with high spatial resolution can be more effectively measured by noncontact techniques than

spatially limited contact-type sensors. Through-transmission ultrasonic C-scan using air-

coupled ultrasonic transducers [4] or noncontact lasers [5] are widely adopted noncontact

techniques. However, they require the transmitter and receiver to be on the opposite sides of

the target structure, which is challenging to be achieved in real applications. Then, Schilling

et al. applied X-ray tomography for detecting internal damages in glass/epoxy and

graphite/epoxy composites [6], but their real field application is limited due to their radiation

issue. Although infrared thermography techniques also have been investigated as the

noncontact technique for damage detection of composites, their detectability is often limited

to damages in a thin structure or near-surface [7-8].

Recently, laser ultrasonic wavefield imaging techniques have been proposed. Laser

ultrasonic wavefield images can be constructed by two different scanning schemes: (1)

generating ultrasonic waves using a fixed actuator and measuring them using a scanning laser

beam or (2) generating ultrasonic waves using a scanning laser beam and measuring them

using a fixed sensor. Sohn et al. used the first scheme for delamination detection in a

composite plate, and developed an automated damage diagnosis algorithm using a Laplacian

filter and standing wave extraction [9]. Then, Chia et al. applied the second scheme to

4

visualize debondings in a composite aircraft wing [10]. More recently, complete noncontact

laser scanning techniques were proposed for hidden crack detection in aluminum structures

[11, 12], but there has been no prior study for complete noncontact laser ultrasonic wavefield

imaging technique for real scale composite structures yet.

In this study, a noncontact laser ultrasonic wavefield imaging technique is further

advanced and applied to full-scale composite structures. The developments of this study have

following merits over the aforementioned techniques: (1) It does not require any sensor

installation; (2) Damage in composite structures can be evaluated without relying on baseline

data obtained from the pristine condition of a target structure, making it possible to minimize

false alarms due to operational and environmental variations and provide automated and

instantaneous damage alarms; and (3) Even incipient damage can be visualized thanks to its

high spatial resolution. To achieve these advantages, a noncontact laser ultrasonic wavefield

imaging system and the corresponding signal processing algorithm, called a standing wave

filter, are developed. Then, the performance of the proposed system is experimentally

examined by visualizing debonding in a carbon fiber reinforced plastic (CFRP) aircraft wing

and delamination in a glass fiber reinforced plastic (GFRP) wind turbine blade under varying

temperature and static loading conditions.

This paper is organized as follows. Section 2 proposes an advanced noncontact laser

ultrasonic wavefield imaging system, and Section 3 presents a standing wave filter which can

extract and visualize only damage information from the measured ultrasonic wavefields. In

Sections 4 and 5, the effectiveness of the proposed technique is demonstrated by visualizing a

debonding in a CFRP aircraft wing and a delamination in a GFRP wind turbine blade. Finally,

this paper concludes with a brief summary and discussions in Section 6.

2. Noncontact Laser Ultrasonic Wavefield Imaging System

5

Figure 1 shows an overall schematic of the noncontact laser ultrasonic wavefield

imaging system composed of excitation, sensing, vision and control units. The system

operates in the following steps:

Figure 1. Schematic of the noncontact laser ultrasonic wavefield imaging system. All units

are synchronized and controlled by a personal computer in the control unit.

Step (1): All the sequences of target excitation and sensing points over the scanning region to

be inspected are predetermined by a computer program coded using Visual C++.

Step (2): The laser beams are fired to the target excitation and sensing points by rotating

mirrors inside galvanometers in excitation and sensing units, respectively. Initially, an actual

laser beam position can be different from the desired target location because the

galvanometer can control the laser beam only in 2D plane (angles in x-y coordinate) while

the target surface is often in 3D. Then, a CCD camera in the vision unit takes an image of the

target structure including the radiated excitation and sensing beams, and the image is

transmitted to the control unit and processed to find the actual laser beam locations. Finally,

the discrepancy between the actual and target beam positions is reduced below a certain level

(0.5 mm in this system) by adjusting the galvanometers precisely.

Step (3): Once the laser beams are correctly positioned onto the target excitation and sensing

6

points, ultrasonic waves generated by the excitation laser beam at the first excitation point are

simultaneously measured by the sensing unit at the corresponding sensing point. Here, both

units are synchronized so that instantaneous data acquisition can be accomplished. Then, the

measured ultrasonic responses are transmitted to the personal computer in the control unit.

Step (4): Steps (2) and (3) are repeated until ultrasonic responses are all acquired from the

entire predetermined scanning points. Each response is assigned to the corresponding

excitation point coordinate. Then, ultrasonic wavefield images are constructed by assembling

all the assigned responses as a function of time, and processed for automated damage

visualization in the control unit.

The excitation unit is composed of a Nd:YAG pulse laser and a galvanometer. The

Nd:YAG pulse laser (Quantel Ultra Laser) used in this system has a wavelength of 532 nm, a

peak power of 3.7 MW, a pulse duration of 8 ns, and a repetition rate of 20 Hz. The

galvanometer (Scanlab Scancube10), with an angular resolution of 7.4 10-4

° and

equivalent spatial resolution of 0.026 mm at 2 m focal distance, is installed in front of the

Nd:YAG laser to control its beam direction for scanning. When a pulse laser beam is emitted

onto an infinitesimal area of a target structure, a localized heating of the surface causes

thermoelastic expansion of the material and generates ultrasonic waves [13-14]. Parameters

for the laser ultrasonic generation, such as the peak power, pulse duration and beam size,

should be carefully designed to avoid surface damage called ablation [15]. In contrast to

metallic structures, composite structures are more vulnerable to ablation because of its lower

thermal conductivity [16]. Thus, more precaution is necessary to avoid it. Ready proposed an

approximate expression for the power density causing ablation [17]:

(1)

where is the latent heat required to vaporize the material, is the material

density, is the thermal diffusivity and is the laser pulse duration. For example, for a

7

typical CFRP [18] and GFRP [19] composite material, is around 108 W/cm

2 and 3×10

7

W/cm2, respectively. Note that this ablation threshold can be different on material properties

and fiber composition of the target composite structure.

The sensing unit is composed of a laser Doppler vibrometer (LDV) for ultrasonic

measurement and a galvanometer for scanning. The LDV (Polytec PSV-400) uses He-Ne

continuous wave (CW) laser source of 633 nm wavelength and has a maximum sensitivity of

10 mm/s/V with a maximum frequency of 350 kHz. When a laser beam is reflected from a

vibrating target surface, the frequency of the returned laser beam is shifted. LDV measures

this frequency shift and relates it to the out-of-plane velocity of the target surface based on

the Doppler effect [20]. The accuracy of the velocity measurement highly depends on the

intensity of the returned laser beam. Thus, the incident angle of the laser beam should be

carefully controlled to maximize the returned beam intensity and minimize speckle noises

[21]. Because of the poor reflective and highly rough surface conditions of composite

materials, often a special surface treatment is necessary to improve the reflectivity of

composite surfaces [20].

To precisely control the Nd:YAG and CW laser beams to target points, a CCD

camera in the vision unit is used in conjunction with the galvanometers. The camera (Basler

acA1600-20gc) used in this study has a 2.0 mega pixel resolution, which achieves 0.3 mm

spatial resolution at 1.0 m distance from the camera. Two distinctive laser colors, green (532

nm) and red (633 nm), are used for the Nd:YAG and CW laser beams, respectively, so that

their positions can be simultaneously identified through proper image processing.

The control unit manages the entire system and synchronizes each unit. This controls

the galvanometers in the excitation/sensing units, processes the image taken from the vision

unit to adjust laser beam locations more precisely, and visualizes ultrasonic wavefield. For

the construction of ultrasonic wavefield images, two scanning schemes are available: (1)

8

fixed laser excitation/scanning laser sensing (FL/SL) and (2) scanning laser excitation/fixed

laser sensing (SL/FL). These two schemes produce similar wavefield images based on the

dynamic linear reciprocity [22]. In this study, SL/FL scheme is used because it is known to be

more effective than FL/SL [11]. Once the ultrasonic signals are collected over the entire

scanning area, they are processed for ultrasonic wavefield construction and automated

damage diagnosis using MATLAB® codes developed and installed in the personal computer

of the control unit.

3. Development of a Standing Wave Filter for Hidden Delamination and Debonding

Visualization

(a)

(b)

Figure 2. Schematics of (a) delamination and (b) debonding induced standing waves.

and denote forward and backward propagating waves, respectively.

Figure 2 shows schematics of the interactions between propagating ultrasonic waves

and delamination/debonding. When ultrasonic waves propagating along a structure encounter

delamination, some portion of the ultrasonic waves are trapped inside the delamination due to

multiple reflections from the delamination boundary, while the others are transmitted through

delamination. The multiple reflections inside the delamination boundary generate momentary

standing waves as long as the waves propagating to the opposite directions have the same

9

frequency [9, 23]. Similarly, the boundary of the debonding produces standing waves

although the leaking of waves is more significant than delamination.

In this study, delamination and debonding are visualized by extracting the standing

wave components from the total wavefield ( . Figure 3 provides an overview of the

proposed standing wave filter.

Step (1): is collected in the time-space (t-s) domain using the noncontact ultrasonic

wavefield imaging system.

Step (2): is transformed from the t-s domain to the frequency-wavenumber (f-k) domain

using a 3D Fourier transform (FT):

(2)

where denotes the f-k domain representation of , and and refer to

wavenumbers in the and axes, respectively.

Step (3): The propagating waves can be decomposed from using the following window

function ( :

(3)

where .

is the f-k domain representation of the wave propagation corresponding to (1) , (2)

, (3) and (4) directions.

Step (4): reconverted back to the t-s domain through an inverse 3D FT:

10

(4)

where denotes the t-s domain representation of .

Step (5): Standing wave energy (SWE) can be isolated by simply extracting the energy of

propagating waves from the total wave energy as following:

(5)

Then, the cumulative SWE (CSWE) image up to time point is visualized by assembling

CSWE values from all spatial points of interest:

(6)

To minimize noise components in the constructed CSWE image, thresholding using

an extreme value statistics is employed here [11]. First, cumulative noise energy (CNE) is

computed by applying the standing wave filter to the pre-triggered portion of each ultrasonic

response, i.e. only noise response, obtained from each spatial point. Note that only difference

between CNE and CSWE is that CNE is computed prior to the ultrasonic excitation to

estimate the noise floor. Then, the probability density function of CNE is estimated by fitting

a Weibull distribution to CNE value obtained from all spatial points, and a threshold value

corresponding to a one-sided 99% confidence interval is established. Finally, the final CSWE

image shows only CSWE values beyond the threshold value, highlighting the damage

location, as shown in Step (5) of Figure 3.

11

Figure 3. Overview of a standing wave filter for hidden damages visualization in

composites

12

4. Debonding Visualization in a CFRP Aircraft Wing

To examine the performance of the proposed damage visualization technique, a

CFRP aircraft wing with a debonding was prepared as shown in Figure 4. Figure 4 (a) shows

the overview of a mock-up wing segment, and the upper curved skin segment with a fitting

lug used for the test is shown in Figure 4 (b). The curved upper composite skin has

dimensions of 1200 510 1.864 mm3 and consists of 10 plies with a layup of

. Note that here means a specially designed single ply

containing both +45° and -45° orientated fibers. The elastic modulus and , shear

modulus , and poisson ratio of this CFRP material are 131.0 GPa, 8.2 GPa, 4.5 GPa,

and 0.281 respectively. Hidden debonding with approximately 10 mm diameter was

introduced by local heating between the upper skin and one of the stringers inside the wing

segment as shown in Figure 4 (b). Then, the upper skin surface of 50 50 mm2 marked in

Figure 4 (a) was scanned by the Nd:YAG laser beam with 2 mm spatial resolution for

ultrasonic wave generation, and the corresponding ultrasonic responses were measured at a

single sensing point by the LDV with a retroreflective tape. Here, the retroreflective tape was

used to improve the reflectivity of the target sensing point. Debonding on the opposite side of

the scanned surface was positioned at the center of the scanning region, and the sensing point

was positioned 30 mm away from left vertical boundary of the scanning region as shown in

Figure 4 (a). The power of the excitation laser was set to 1 MW, resulting in power density of

8 × 106 W/cm

2. The generated ultrasonic waves were measured by a 14 bit digitizer with a

sampling frequency of 5.12 MHz for 200 s, and averaged 50 times in the time domain to

improve a signal-to-noise ratio. The measurement sensitivity was set to 10 mm/s/V, and a

bandpass filter ranged from 10 kHz to 300 kHz was employed. Figure 5 shows that the LDV

and Nd:YAG laser were installed 1.6 m and 2.0 m apart from the specimen, respectively.

13

(a)

(b)

Figure 4. A CFRP aircraft wing segment with a fitting lug: (a) Overview of the CFRP

aircraft wing segment and the scanning region, and (b) the inside view of the wing segment

with debonding between the upper skin and one of the stringers.

Figure 5. Overall test setup for debonding visualization in the CFRP aircraft wing segment.

Figure 6 shows the representative at 22.50 s, 34.80 s, and 47.11 s obtained

from the target scanning region. The red and blue colors in the images represent positive and

negative out-of-plane velocities, respectively. Ultrasonic waves propagate from left to right,

14

and the interaction with the debonding can be observed at 47.11 s.

Figure 6. Raw ultrasonic wavefield images obtained from the CFRP aircraft wing segment

at 22.50 s, 34.80 s and 47.11 s. Red and blue colors correspond to positive and negative

out-of-plane velocities, respectively. (Color in online)

(a) (b) (c)

Figure 7. f-k domain representations of the wavefield images obtained from the CFRP

aircraft wing segment: (a) , (b) and , and (c) and .

To extract debonding-induced standing wave components, the standing wave filter is

applied. First, is transformed to using Equation (2), and then is decomposed

into using Equation (3). The corresponding results are displayed in Figure 7. The

and , and and representing forward and backward ultrasonic propagations in x

axis are clearly observed in Figures 7 (b) and (c), respectively. Subsequently, is

reconverted into using Equation (4). Here, let us define and consider forward

propagating waves and backward propagating waves in x

axis for the sake of simplicity, because x directional wave propagation is dominant in this

15

example. The resultant and at 22.50 s, 34.80 s and 47.11 s are shown in Figure

8. Figure 8 (a) shows that (left to right) is dominant, while only (right to left)

reflected from the debonding can be seen in Figure 8 (b).

(a)

(b)

Figure 8. Decomposed t-s domain wavefield images obtained from the CFRP aircraft wing

segment at 22.50 s, 34.80 s, and 47.11 s: (a) and (b) . The debonding-reflected

waves are clearly observed at 47.11 s of .

Next, the CSWE image was constructed using Equation (6). Here, the threshold

value of 2.7 × 10-9

is obtained using an extreme value statistic to minimize noise components

as explained in the Step (5) in Section 3. Note that this threshold is instantaneously

established from only currently measured data depending on certain applications. A

cumulative total wave energy (CTWE) image was also constructed to examine the

effectiveness of the standing wave filter. CTWE was calculated by the following equation and

its image is constructed by assembling CTWE values from all spatial points of interest.

16

(7)

Figure 9 compares the CTWE and CSWE images obtained from the target scanning

region of the CFRP aircraft wing segment. The red color in the images represents high energy

concentration (Color in online). Although high energy around the debonding is observed in

the CTWE image of Figure 9 (a), the incident wave energy hinders damage diagnosis. On the

other hand, Figure 9 (b) shows that only the debonding location is clearly highlighted by

eliminating other noise components in the CSWE image, making it possible to achieve

intuitive damage diagnosis without any prior knowledge of debonding.

(a) (b)

Figure 9. Comparison of (a) CTWE and (b) CSWE images obtained from the CFRP aircraft

wing segment

5. Delamination Visualization in a GFRP Wind Turbine Blade under Varying

Temperature and Static Loading Conditions

An actual 10 kW wind turbine blade was prepared as another test specimen for the

validation of the proposed standing wave filter as shown in Figure 10 (a). The target blade

has rough dimensions of 3500 500 3 mm3, is made of GFRP materials, consists of 6

plies with a layup of . The elastic modulus , shear modulus , and poisson

ratio of the GFRP material are 24.65 GPa, 8.52 GPa, and 0.476 respectively. A 15 mm

17

diameter Teflon tape was inserted between the 3rd

and 4th

ply during fabrication of the blade

to simulate internal delamination. The LDV and Nd:YAG laser were installed 1.1 m apart

from the specimen. The Nd:YAG laser scanned a squared region of 50 50 mm2 with 2 mm

spatial resolution as shown in Figure 10 (b). The corresponding ultrasonic responses were

measured at a single point by the LDV with a retroreflective tape. The excitation laser power,

power density, the number of averaging, the bandpass filter range were set to 2 MW, 1.6 107

W/cm2, 40 times, and 130 kHz to 200 kHz respectively. All the other parameters were

identical to the ones used in the previous section.

(a)

(b)

Figure 10. Full scale wind turbine blade with simulated delamination: (a) 10 kW GFRP

composite wind turbine blade and (b) simulated delamination and the laser scanning region.

The standing wave filter again successfully visualizes delamination-induced standing

waves in the wind turbine blade. Figure 11 compares CTWE and CSWE images obtained

from the scanning region of the blade shown in Figure 10 (b). In CSWE image, the incident

wave energy and other noise components in CTWE image are clearly eliminated and only the

delamination location is accentuated. Here, the computed threshold value is 4.3 × 10-4

.

18

Additional tests were conducted to examine the performance of the proposed

technique under varying environmental conditions. Indeed, real in-situ structures are often

exposed to temperature variation and external loading such as wind loading. Figure 12

compares the ultrasonic signals generated at the center of the scanning region and measured

at the sensing point shown in Figure 10 (b) under varying temperature and static loading

conditions. Compared to the signal obtained in Condition 1 (25 °C without static loading), the

time delay of the first peak arrival was observed as the temperature of the blade increased up

to 45 °C using a ceramic heater (Condition 2). With a static loading of 0.47 kN (Condition 3),

no time delay was observed but the wave amplitude decreased compared to Condition 1.

(a) (b)

Figure 11. Comparison of (a) CTWE and (b) CSWE images obtained from the GFRP wind

turbine blade.

Figure 12. Representative ultrasonic signals generated at the center of the scanning region

and measured at the sensing point under different temperature and static loading conditions:

50 60 70 80 90 100 110 120 130 140 150

-5

0

5

Time ( s)

Ou

tpu

t (m

V)

Condition 1 (25°C / 0.00 kN)

Condition 2 (45°C / 0.00 kN)

Condition 3 (25°C / 0.47 kN)

19

Condition 1 (Red solid line, 25 °C without loading), Condition 2 (Blue dashed line, 45 °C

without loading) and Condition 3 (Green dotted line, 25 °C with 0.47 kN loading).

Figure 13 displays the CTWE and CSWE images on Conditions 2 and 3. Although

CSWE images obtained from Conditions 1 to 3 show different results, they still enable

intuitive and automated damage visualization without false alarms. These results reveal the

robustness of the proposed technique against the operational and environmental variations.

(a) (b)

(c) (d)

Figure 13. Comparison of CTWE and CSWE images obtained under varying temperature

and loading conditions of the GFRP composite wind turbine blade: CTWE from (a)

Condition 2 and (b) Condition 3, and CSWE from (c) Condition 2 and (d) Condition 3.

6. Conclusion

In this study, a noncontact laser ultrasonic wavefield imaging technique is developed

20

for delamination and debonding detection and visualization, and successfully visualized a

debonding in a real scale CFRP composite aircraft wing and a delamination in a GFRP

composite wind blade structure. Furthermore, it turned out that no false alarm is indicated

even under varying temperature and static loading conditions. However, further studies are

needed before applying the developed technique to real structures under various operating

conditions. First, the high dependency of laser sensing on the target surface condition still

requires a special surface treatment such as the use of a retroreflective tape. In addition, the

inspection time might be prohibitively long for large structure scanning due to high spatial

resolution. Since this technique visualizes only damage-induced standing waves which are

not spatially propagated, its damage detectability highly relies on the spatial resolution.

Although higher spatial resolution can enhance its damage detectability, there is a trade-off

between the spatial resolution and the inspection time. Then, a special caution should be paid

in handling the high power laser (Class 4) used for ultrasonic generation, and its long term

effects on the composite’s health should be investigated. Further performance validations on

more realistic defects are also warranted to be investigated in the following work.

ACKNOWLEDGEMENT

This work was supported by the New & Reliable Energy (20123030020010) of the Korea

Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea

government Ministry of Trade, Industry and Energy, the Leap Research Program (2010-

0017456) of National Research Foundation (NRF) funded by Ministry of Science, ICT and

Future Planning, and the Scientific Research Fund of Southeast University (3250254202).

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