Reconstruction of fiber Bragg grating strain profile used to monitor the stiffness degradation of the adhesive layer in carbon fiber

Abstract

The adhesive-bonded joint of carbon fiber–reinforced plastic is one of the core components in aircraft structure design. It is an effective guarantee for the safety and reliability of the aerospace aircraft structure to use effective methods for monitoring and early warning of internal failure. In this article, the mapping relation model between the strain profiles of the adherend of the carbon fiber–reinforced plastic single-lap adhesive joint and the stiffness degradation evolution of adhesive layer was achieved by finite element software ABAQUS. The fiber Bragg grating was embedded in the adherend between the first and second layers at the end of the adhesive layer to calculate the reflection spectrum of fiber Bragg grating sensor region with improved T-matrix method for reconstruction of the adherend strain profile of fiber Bragg grating sensing area with the help of genetic algorithm. According to the reconstruction results, the maximum error between the ideal and reconstructed strain profile under different tension loads did not exceed 7.43%, showing a good coincidence degree. The monitoring method of the stiffness degradation evolution of adhesive layer of the carbon fiber–reinforced plastic single-lap joint based on the reconstruction of the adherend strain profile of fiber Bragg grating sensing area thus was figured out.

Keywords

Reconstruction strain profile stiffness degradation carbon fiber–reinforced plastic single-lap joint fiber Bragg grating

Introduction

The carbon fiber–reinforced plastic (CFRP) single-lap adhesive joint is one of the core components in aircraft structure design.¹ Compared with the mechanical connection, the adhesive bonding connection has advantages, such as light weight, no damage to the fiber structure, good continuity, and flexible design.^2,3 However, due to the new bonding interface in the CFRP single-lap adhesive joints and its more complex damage modes, the correct understanding of the failure mode of the CFRP single-lap adhesive joint and the effective monitoring and early warning of internal failure of the adhesive layer are effective guarantee for the safety and reliability of the aerospace aircraft structure.^4,5 Currently, many techniques have been applied to monitor the structural damage, such as sensor with a piezoelectric element, resistance wire, fatigue life wire, intelligent coating, and vacuum comparison sensor. Because of its advantages of small volume, light weight, high sensitivity, easy embedment, good compatibility with composite materials, and capability of multipoint measurement, fiber Bragg grating (FBG) sensor was considered very suitable to monitor the failure of the CFRP single-lap adhesive joint.^6,7

The health monitoring of adhesive joints has been studied by many scholars using FBG. J Palaniappan et al.^8,9 embedded FBG in the boundary region of carbon fiber layer to monitor the debonding behavior and simulated the reflection spectrum of FBG with the help of OptiGrating software. Then, they made empirical study on monitoring of the adhesive layers debonding by virtue of the relationship between the variation of FBG reflection spectra and the debonding length. But the monitoring results indicated that the accuracy was poor with the error of debonding length being approximately 2 mm. S Minakuchi et al.¹⁰ embedded the FBG sensors in the adhesive layer of the single-lap joint to judge the adhesive debonding status based on whether the spectrum was returned to the previous shape after it got deformed due to the effect of inhomogeneous strain. But this method had some limitations: (1) it can only judge debonding status and (2) does not monitors the debonding position and its length when the debonding was initiated. Trilaksono et al.¹¹ studied the mapping relationship between the change of FBG reflection spectrum and the growth of adhesive joint debonding failure. S Takeda et al.¹² applied the FBG sensors in composite repair patches to monitor its debonding, the length of which was indicated by the ratio of low-band reflection spectrum peak intensity to high-band reflection spectrum peak intensity. SF Yuan et al.¹³ studied the monitoring methods of fatigue crack propagation length and angle in the aerospace aluminum alloy repairing structure based on FBG reflection spectrum characteristic and established the relationship between reflectance spectrum deformation and crack propagation with the neutral network, which realized the accurate monitoring of repaired structure crack propagation.

In summary, in this study, the composite adhesive joint damages are mostly monitored relying on mapping relationship between the variation of FBG reflection spectrum and damage growth, and rarely relying on mapping relationship between the strain profiles of FBG sensing area and the failure of adhesive joints. However, in view of the large strain gradient which generally appeared around the damage area of adhesive joint, at the time of damage (non-uniform strain), the information with respect to the strain profile is more accurate and intuitive to reflect the initiation and evolution of failure than the mapping relationship between deformation and failure of the reflection spectrum. Hence, the mapping relationship between the strain profile and failure evolution is of great significance for the structural damage monitoring. Traditional wavelength demodulation was used to identify strain through the detection of the central wavelength shifts of the reflected spectrum, which can only measure the average strain of the sensing area. This would certainly cause such loss of strain gradient information regarding strain field in the damage area that may inevitably lead to a big error of the strain identification, which would make it very difficult to accurately judge and predict the failure of the adhesive joint. Therefore, in order to monitor the failure of CFRP adhesive-bonded joints more accurately and effectively, it is very necessary to study the mapping relationship model between the evolution of adherend strain profile of CFRP single-lap joint and the failure evolution of adhesive layer and to find the method used to measure non-uniform strain in the CFRP single-lap adhesive joints.

This article first applied the finite element (FE) analysis software to obtain the mapping relationship model between the evolution of adherend strain profile of CFRP single-lap joint and the stiffness degradation evolution of adhesive layer and accordingly determined the distribution of FBG which was then embedded in the adherend between the first and second layers at the end of the adhesive layer instead of the adhesive layer. Furthermore, it calculated the reflection spectrum of FBG sensor with the improved transfer matrix method and used the calculated spectra in the reconstruction of the adherend strain profile of FBG sensing area with the method of genetic algorithm (GA), realizing the monitoring of strain profile in the cohesive zone. In addition, this article, according to mapping relationship model between the evolution of adherend strain profile of CFRP single-lap joint and the stiffness degradation evolution of adhesive layer, determined the stiffness degradation evolution of adhesive layer in theory.

FE simulation

FE simulation of the CFRP single-lap joint

A CFRP single-lap joint FE model established is shown in Figure 1. The CFRP single-lap joint consisted of two CFRP plates, two end tabs, and an adhesive layer. T300-1200 carbon fiber was considered for the composite adherends of the single-lap joints, and EPOTECH3321A epoxy resin was considered for the resin. Araldite 2015 was used for the adhesive layer and the end tabs were made of aluminum alloy, of which the elasticity modulus was 70 GPa and Poisson’s ratio was 0.33. The elastic properties of the unidirectional lamina y and adhesive Araldite 2015 are shown in Tables 1 and 2, modeled in the FE analysis. The thickness of CFRP plates depended on their layer scheme: [0]₁₂.

Figure 1.

Schematic diagram of the single-lap CFRP adhesive joints.

Table 1.

Elastic orthotropic properties of a unidirectional carbon–epoxy ply aligned in the fibers direction (x direction; y and z are transverse and through-thickness directions, respectively).

E_x = 107.1 GPa	v_xy = 0.26	G_xy = 1.94 GPa
E_y = 5.12 GPa	v_xz = 0.26	G_xz = 1.94 GPa
E_z = 5.12 GPa	v_yz = 0.35	G_yz = 1.9 GPa

Table 2.

Cohesive parameters of the adhesive Araldite 2015 for CZM modeling.

Property	Value
Young’s modulus, E (GPa)	1.85
Shear modulus, G (GPa)	0.56
Tensile failure strength, $t_{n}^{0}$ (MPa)	21.63
Shear failure strength, $t_{s}^{0}$ (MPa)	17.9
Toughness in tension, $G_{n}^{c}$ (N/mm)	0.43
Toughness in shear, $G_{s}^{c}$ (N/mm)	4.7

CZM: cohesive zone model.

The FE software ABAQUS established a CFRP single-lap joint FE model by the application of cohesive zone models (CZMs).^14–17 The dimensions and loading model of the CFRP single-lap joint are shown in Figure 1. x-Direction displacement constraints were added at the left end of the CFRP single-lap joint, and tensile load was applied at the right end in a total of 50 load steps with each step applying 200 N tension. The models were built with eight-node SC8R elements for the adherends, eight-node COH3D8 elements for the adhesive layer, and eight-node C3D8R elements for the end tabs.

According to a series of papers,^14–17 the bilinear CZM was used to describe the degradation of element stiffness as shown in Figure 2. In this article, a damage variable D was introduced to characterize the failure propagation of the material. K is the stiffness of the element before its degradation and $K_{0}$ is the stiffness of the element during the degradation.

Figure 2.

Bilinear cohesive zone model.

In the figure, $σ_{m}$ and $δ_{m}$ are the critical stress and the critical displacement, respectively, of the element before its stiffness degradation; $σ_{m}^{0}$ and $δ_{m}^{0}$ are the critical stress and critical displacement, respectively, of the element during degradation; and $δ_{m}^{\max}$ is the critical displacement of the element at the time of failure. The relationship between K and $K_{0}$ is show as below

K_{0} = (1 - D) K

(1)

\frac{σ_{m}^{0}}{δ_{m}^{0}} = (1 - D) \frac{σ_{m}}{δ_{m}}

(2)

D = 1 - \frac{δ_{m} σ_{m}^{0}}{δ_{m}^{0} σ_{m}} = 1 - \frac{δ_{m}}{δ_{m}^{0}} \frac{(δ_{m}^{\max} - δ_{m}^{0})}{(δ_{m}^{\max} - δ_{m})} = \frac{δ_{m}^{\max} (δ_{m}^{0} - δ_{m})}{δ_{m}^{0} (δ_{m}^{\max} - δ_{m})}

(3)

In the FE software ABAQUS, the scalar stiffness degradation (SDEG) is equivalent to D. From Figure 2, it can be seen that the SDEG variable ranges from 0 (anywhere in the elastic part of the mixed-mode CZM law) to 1 (failure of the CZM element) when the SDEG > 0, which means that the stiffness of the CZM elements begins to degenerate. Based on the changes of the SDEG, the evolution of the stiffness degradation of the adhesive layer can be determined. These analyses aimed at presenting a mapping relation between the strain profiles of the adherend and the stiffness degradation evolution of adhesive layer. The stiffness degradation evolution of the adhesive layer is presented in Figure 3.

Figure 3.

SDEG of the cohesive under different loads.

Figure 3 shows that when the load is around 1200 N, and SDEG > 0, the stiffness just starts to degrade. And with an increase in the load, the stiffness degradation of the adhesive layer gradually extends from the ends to the middle. When the load is 5800 N and SDEG at the ends of the adhesive layer just equals 1, it is exactly the right moment for complete stiffness degradation of the adhesive layer at the ends.

Considering the fact that the closer to adhesive surface, the more the information of the adherend strain profile got affected by the adhesive layer; this article established a path, as shown in Figure 4 (the red line), to check the changes in strain profiles of the adherend between the first and second layers as the load changes.

Figure 4.

The path of the adherend strain profile.

The results and discussion of the FE simulation

The longitudinal strains (E11) along the centerline at the position of the optical fiber were extracted from the results and are plotted in Figures 5 –8.

Figure 5.

The strain distribution along the path of the adherend strain profile under the loads of 400, 600, 800, and 1000 N from the finite element analysis.

Figure 6.

The strain distribution along the path of the adherend strain profile under the loads of 1000, 2000, 3000, 4000, 5000, and 6000 N from the finite element analysis.

Figure 7.

Magnified view of the strain distribution along the path of the adherend strain profile under the loads of 1000, 2000, 3000, 4000, 5000, and 6000 N from the finite element analysis.

Figure 8.

The strain distribution along the path of the adherend strain profile under the loads of 6000, 7000, and 8000 N from the finite element analysis.

Figure 5 shows the strain profiles’ curve along the adhesive area under the loads ranging from 400 to 1000 N. As seen in Figure 5, before the stiffness degradation of the adhesive layer, with an increase in the load, the adherend strain at the end of the adhesive (as shown in the red rectangle) is gradually increased, and the peak of the adherend strain is near the end of the adhesive layer.

Figure 6 shows the strain profiles’ curve along the adhesive area under the loads ranging from1000 to 6000 N. Figure 7 is an enlarged view of the dotted rectangle of Figure 6. As seen in Figures 6 and 7, with the adhesive stiffness degradation, the peak of the adherend strain (as shown in the red rectangle) is shifted from the ends of the adhesive layer to the middle of it. The adherend strain near the end of the adhesive layer gradually becomes smaller. When the stiffness at the end of the adhesive layer is completely degraded, the adherend strain near the end of the adhesive layer tends to zero.

Figure 8 shows the strain profiles’ curve along the adhesive area under the loads ranging from 6000 to 8000 N. As seen in Figure 8, after the stiffness at the end of the adhesive layer is completely degraded, with an increase in the tensile load, the adherend strain near the end of the adhesive layer is tend to be stable (as shown in the blue rectangle). Since the end of the adhesive layer is completely failed, the adherend strain near the failure region of the adhesive layer is no longer affected by the adhesive. The mapping relation between the strain profiles of the adherend and the stiffness degradation evolution of adhesive layer may be summarized as follows:

When the strain peaks were at the ends of the adhesive, and the adherend strain at the end of the adhesive layer increased as the load becomes larger, the stiffness of the adhesive layer had not yet degraded.

With an increase in the load, the peak of the adherend strain was shifted from the ends of the adhesive to the middle of it, and the adherend strain near the end of the adhesive layer gradually became smaller. It means the stiffness at the end of the adhesive was being degraded.

With an increase in the tensile load, the adherend strain near the end of the adhesive layer was tend to be stable. It means the stiffness at the end of the adhesive layer was already completely degraded.

The adherend strain profiles near the end of the adhesive layer reflected the evolution of the stiffness degradation. Therefore, this article embedded FBG in the adherend between the first and second layers at the end of the adhesive layer to monitor the changes of the adherend strain profile at the end of the adhesive layer and to determine whether the adhesive layer was failed or not according to the mapping relation between the changes of the adherend strain profiles of the CFRP single-lap joint and the stiffness degradation evolution.

From the above, it can be seen that the adherend strain profiles near the end of the adhesive layer were non-uniform. However, the conventional wavelength demodulation was performed to identify the strain by the shifts of the center wavelength of the reflection spectrum, which can only measure the average strain of the sensing area. This would certainly cause such loss of strain gradient information regarding strain field in the damage area that may inevitably lead to a big error of the strain identification, which would make it very difficult to accurately determine and predict the damage and failure of the adhesive joint. Many scholars have conducted the exploratory study on reconstruction of non-uniform strain field with FBG reflection spectrum^18–21 that has initially demonstrated that it was feasible to do so at the adherend cohesive zone of CFRP adhesive joint, which, in this article, was realized through two processes. It first calculated the reflection spectrum of the FBG sensing area by the improved transfer matrix method and then reconstructed the adherend strain profile of FBG sensing area by GA method based on the reflection spectrum calculation.

The non-uniform strain profile reflection spectrum calculation of the FBG sensors with the improved transfer matrix method

Transfer matrix (T-matrix) is formulated by approximating the applied strain as a piecewise continuous function, calculating the average period in each grating segment due to the applied strain, and substituting this local period back into the coupling coefficient in the formulation. This method is broadly adopted to calculate the non-uniform strain profile along the grating for constructing the reflection spectrum with the corresponding strain field. Where the numerical simulation is conducted with the improved transfer matrix method, its convergence rate is very fast. But since the T-matrix method in numerical simulation ignores the gradient of non-uniform strain field, the simulation results are less precise when the strain gradient is large, while Runge–Kutta method can also be used in the calculation of the non-uniform strain, which would obtain more precise results but takes a longer time. Improved transfer matrix method^21–23 combines these two methods: it can not only retain the fast convergence of the transfer matrix method but also inherit the accuracy of Runge–Kutta method.

The FBG shall be deemed as non-uniform if it is affected by the non-uniform strain field. The basic idea of the improved T-matrix method is to divide a non-uniform grating into N segments, each is thought to be approximately uniform. $Λ_{i} (1 \leq i \leq N)$ and $n_{effi} (1 \leq i \leq N)$ are, respectively, the average value of the period $Λ_{i} (z)$ and effective refractive index $n_{eff} (z)$ along the length of the FBG, which are show as follows

Λ_{i} = \frac{1}{Δ z} \int_{z_{i}}^{z_{i + 1}} Λ_{1} (z) dz

(4)

n_{effi} = \frac{1}{Δ z} \int_{z_{i}}^{z_{i + 1}} n_{eff 1} (z) dz

(5)

Λ_{1} (z) = Λ_{0} \frac{{[1 + (1 - p_{e}) ε (z)]}^{2}}{1 + (1 - p_{e}) ε (z) - (1 - p_{e}) z ε' (z)}

(6)

n_{eff 1} (z) = n_{eff} - 0.5 n_{eff}^{3} [p_{12} - v (p_{11} + p_{12})] ε (z)

(7)

where $Λ_{0}$ is the initial period of the grating and $p_{e}$ is the effective strain-optic coefficient constant of the Bragg grating. $n_{eff}$ is the mode effective index of refraction of the optical fiber and $p_{11}$ and $p_{12}$ are the effective strain-optic coefficients. v is Poisson’s ratio of the fiber.

According to the weak-guide conditions and coupled-mode theory, the general “DC” self-coupling coefficient $σ_{i}$ is obtained as follows

σ_{i} = \frac{2 π}{λ} (n_{e f f i} + {\bar{δ n}}_{e f f}) - \frac{π}{Λ_{i}}

(8)

where $λ$ is the center wavelength of the reflect spectrum, ${\bar{δ n}}_{eff}$ is the “DC” index change spatially averaged over a grating period.

The uniform transmission characteristics of each grating can be expressed with the corresponding transfer matrix $F_{i}$ as follows

F_{i} = [\begin{matrix} {F_{i}}^{1} - {F_{i}}^{2} & - {F_{i}}^{3} \\ {F_{i}}^{3} & {F_{i}}^{1} + {F_{i}}^{2} \end{matrix}]

(9)

{F_{i}}^{1} = \cosh (γ_{i} Δ z)

(10)

{F_{i}}^{2} = i \frac{σ_{i}}{γ_{i}} \sinh (γ_{i} Δ z)

(11)

{F_{i}}^{3} = i \frac{k}{γ_{i}} \sinh (γ_{i} Δ z)

(12)

k = \frac{π {\bar{δ n}}_{eff}}{λ}

(13)

where k is the “AC” coupling coefficient.

Therefore, through the calculation of the transfer matrix $(F_{i})$ for each piece of the grating with their strain values $(ε (z))$ , the transmission characteristics of the entire grating are obtained as follows

[\begin{matrix} R_{M} \\ S_{M} \end{matrix}] = F [\begin{matrix} R_{0} \\ S_{0} \end{matrix}], F = F_{M} \cdot F_{M - 1} \dots F_{2} \cdot F_{1}

(14)

The reflectivity of the grating can be calculated as follows

r (λ) = {| \frac{S_{M}}{R_{M}} |}^{2}

(15)

Table 3 shows the parameters of Bragg grating sensor for the calculation of the FBG reflection spectrum.

Table 3.

Parameters of Bragg grating sensor.

Parameter	Value
Length (L)	6 mm
Mode effective index of refraction $(n_{eff})$	1.45
Mean index variation $({\bar{δ n}}_{eff})$	10e−5
Initial center wavelength $(λ_{D})$	1550 nm
Effective strain-optic constant $(P_{e})$	0.26
Fringe visibility (s)	1
Initial conditions	$R_{0} = 1$ ; $S_{0} = 0$

As shown in Figure 9, FBG sensor is embedded in an adherend of the CFRP single-lap adhesive joint between first and second layers at the centerline of the cohesive zone. Because the adherend strain profiles near the end of the adhesive layer reflect the evolution of the stiffness degradation of the adhesive layer, the end of the FBG sensor should be aligned with the end of the adherend. The length direction of the adhesive layer is shown in Figure 9.

Figure 9.

The position of the embedded FBG sensor.

The spectra of the embedded FBG under 2000, 4000, 6000, and 7000 N tensile loads were calculated, respectively, by the improved T-matrix method, as shown in Figure 10, for reconstruction of the adherend strain profile of FBG sensing area.

Figure 10.

The strain profiles and the corresponding spectrum.

The reconstruction of FBG sensor strain profiles with GA

GA modeling approach

GA is an optimization algorithm based on natural biological evolution model.^18,19 Recently, it has been developed by many scholars to solve the problem with the goal of reconstruction of FBG sensor strain profiles^18,19 by population selection, crossover, and mutation.^23,24

This article used the existing MATLAB GA toolbox to realize the reconstruction of the adherend strain profile of FBG sensing area and generate the random strain profile $ε_{k} = [ε_{k} (1), ε_{k} (2), \dots, ε_{k} (n)]$ , where $k = 1, 2, \dots, M$ , M is the population size, n is the number of independent variables, $ε_{k}$ indicates the individual strain profile in current population. $ε_{k} (n)$ is the nth variable of the kth individual in current population. It then set up the initial control parameters (population selection, crossover type and percentage, and mutation type and percentage) for the GA and took the difference between the reflection spectra corresponding to the ideal strain profile and the reconstructed strain profile as the fitness function, which reflected the closeness of the reconstructed strain profile and the ideal strain profile, and the quality of individuals in the current population. The higher the degree of consistency, the closer the reconstructed non-uniform strain profile was to the ideal strain profile. The fitness function is calculated as follows

F_{k} = sum ‖ \frac{r_{k} - r_{0}}{\min (r_{0})} ‖^{2}

(16)

where $F_{k}$ is the fitness value of the kth individual. $r_{k}$ is the reflection spectrum of the kth non-uniform strain profile. $r_{0}$ is the reflection spectrum of the ideal strain profile.

Considering that the FBG, generally, can only measure the strain ranging between −10⁻³ and 10⁻³, the appropriate strain constraints of $ε_{k} (n) \in (- 10^{- 3}, 10^{- 3})$ was applied to the strain profile to be reconstructed. Table 4 shows the parameters of GA used in the reconstruction of FBG strain profiles.

Table 4.

Parameters of genetic algorithm used in the reconstruction of FBG strain profiles.

Parameter	Value
Number of variables (n)	21
Population size (M)	200
Generations	500
Selection	Roulette
Crossover	Two point, fraction 0.8
Mutation	Gaussian, fraction 0.2 Scale 1, shrink 1

FBG: fiber Bragg grating.

Reconstructed results and discussion

The strain profile in the sensing area of the CFRP single-lap joint adherend was so reconstructed, respectively, under the typical tensile loads of 2000, 4000, 6000, and 7000 N applied during the stiffness degradation as to verify the reliability of such reconstruction based on GA. The results of strain profile reconstruction are show in Figure 11 and Table 5.

Figure 11.

Ideal strain profile and reconstructed strain profile.

Table 5.

Reconstructed results of strain profiles of the FBG.

Tension loads (N)	Errors between the ideal and reconstructed strain profiles under the tension loads
Tension loads (N)	Maximum error $(μ ε)$	Reconstructed error (%)
2000	1.72	5.1
4000	0.65	3.25
6000	3.79	7.43
7000	4.31	4.8

FBG: fiber Bragg grating.

Figure 11 shows the comparison between the ideal strain profile and the reconstructed strain profile under different loads. It can be clearly seen that the reconstructed strain profile, as shown in Table 5, is consistent with the ideal strain profile without losing the variation characteristics of the ideal strain profile. Table 5 shows that the maximum error between the ideal and the reconstructed strain profiles under different tension loads does not exceed 7.43%, showing a good coincidence degree. Thus, adherend strain profile of the CFRP single-lap joint may be monitored theoretically based on the reconstruction of the FBG non-uniform strain profiles.

This section embedded the FBG in the adherend between the first and second layers at the end of the adhesive layer instead of the adhesive layer to reconstruct the strain profile of FBG sensing area with the help of GA and determined the stiffness degradation evolution of adhesive layer of the CFRP single-lap joint based on the mapping relation between the strain profiles of the adherend and the stiffness degradation evolution of adhesive layer, thus capable of monitoring the stiffness degradation evolution of adhesive layer of the CFRP single-lap joint by the reconstruction of the adherend strain profile of FBG sensing area.

Conclusion

The mapping relation between the strain profiles of the adherend and the stiffness degradation evolution of adhesive layer was achieved using FE software. The FBG was embedded in the adherend between the first and second layers at the end of the adhesive layer instead of the adhesive layer to calculate the reflection spectrum of FBG sensor region with improved T-matrix method and then to reconstruct the adherend strain profile of FBG sensing area with the help of GA. The maximum error between the ideal and reconstructed strain profiles under different tension loads does not exceed 7.43%, showing a good coincidence degree. According to the mapping relation between the strain profiles of the adherend and the stiffness degradation evolution of adhesive layer, the stiffness degradation evolution of adhesive layer of the CFRP single-lap joint was determined. Thus, the stiffness degradation evolution of adhesive layer of the CFRP single-lap joint can be monitored by the reconstruction of the adherend strain profile of FBG sensing area.

Footnotes

Academic Editor: Xiaotun Qiu

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (Project No. U1537103), the Fundamental Research Funds for the Central Universities (Project No. WUT: 2016III032), the Significant Science and Technology Innovation Project of Hubei Province, China (Project No. 2014AAA005), and the Independent Innovation of Foundation of Wuhan University of Technology (Project No. 155204009).

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