A fastmultipole accelerated method of fundamental solutions for 2D broadband scattering of SH waves in an infinite half space
Zhongxian Liu^{1} , Zhikun Wang^{2} , Linping Guo^{3} , Dong Wang^{4} , Fengjiao Wu^{5}
^{1, 2, 3, 4, 5}Tianjin Key Laboratory of Civil Structure Protection and Reinforcement, Tianjin Chengjian University, Tianjin, China
^{1}School of Engineering, University of Mississippi, Mississippi, USA
^{4}Hebei Building Research Technical Co. Ltd, Shijiazhuang, China
^{1}Corresponding author
Journal of Vibroengineering, Vol. 21, Issue 1, 2019, p. 250264.
https://doi.org/10.21595/jve.2018.19515
Received 7 December 2017; received in revised form 19 June 2018; accepted 10 August 2018; published 15 February 2019
JVE Conferences
The traditional method of fundamental solution (TMFS) is known as an effective method for solving the scattering of elastic waves, but the TMFS is inefficient in solving largescale or broadband frequency problems. Therefore, in order to improve the performance in efficiency and memory requirement for treating practical complex 2D broadband scattering problems, a new algorithm of fast multipole accelerated method of fundamental solution (FMMFS) is proposed. Taking the 2D scattering of SH waves around irregular scatterers in an elastic halfspace as an example, the implementation steps are presented in detail. Based on the accuracy and efficiency verification, the FMMFS is applied to solve the broadband frequency scattering of plane SH waves around group cavities, inclusions, a Vshaped canyon and a semielliptical hill. It shows that, compared with TMFS, the FMMFS has great advantages in reducing the consumed CPU time and memory for 2D broadband scattering. Besides, the FMMFS has excellent adaptability both for broadfrequency and complexshaped scattering problems.
Keywords: the scattering of SH waves, fast multipole, method of fundamental solution (MFS), broadband frequency scattering, largescale scattering.
1. Introduction
The scattering of elastic waves is an attractive and significant topic in many fields such as in earthquake engineering, geophysics, civil engineering, etc. In general, the calculation methods for the wave scattering include the analytical methods and numerical methods. The analytical methods are mainly referred to the wave function expansion methods [18]. The numerical methods include finite difference methods (FDM) [9, 10], finite element methods (FEM) [11, 12], boundary element methods (BEM) [1320], and more works can be found in a review by SanchezSesma et al. [21] and by Manolis and Dineva [22].
Among different boundarytype methods, the method of fundamental solution (MFS) not only reduces the dimension of problem and automatically satisfy the boundary conditions at infinite, but also is a meshless method. In the MFS, the approximate solution of the partial differential equation is constructed by the linear combination of a series of Green’s functions. In order to avoid singularities, the fictitious wave sources are placed at some distance to the physical boundaries of scatters. The densities of the fictitious sources are firstly obtained by the boundary integral equations discretized through boundary collocation points. So, the MFS can also be regarded as a special indirect boundary integral equation method which is very similar to the Trefftz method [23].
Due to the excellent numerical accuracy and simplicity of usage, the MFS (also named indirect boundary integral equation method) has been widely applied in the field of wave scattering in an elastic medium [2432]. However, just as other boundarytype numerical methods, the MFS suffers a large difficulty in treating largescale models. A significant weakness of MFS is that the calculation efficiency of solving highDOF problem (such as large scale, broadband frequency or multibody scattering) is seriously affected by its dense characteristic of the equation matrix. Chen et al. [33] greatly improved the computational efficiency of MFS using a sparse storage method, but the method still has some limitations to overcome this weakness. Some researchers tried to combine the FMM with the MFS in recent years. In essence, The FMM separates source points from collocation points of the kernel function expressions to change the Green’s function calculation from onetoone interaction to grouptogroup interaction. Then the FMM can substantially reduce the memory requirement and improve the computational efficiency [3436]. The FMMFS has been developed for solving many largescale practical engineering problems [3739]. The memory of MFS can be reduced to $O$ ($N$) by the latest development of FMM, and the computation amount is reduced to $O$ ($N\mathrm{l}\mathrm{o}\mathrm{g}2N$) order. It should be noted that the references mentioned above are all about the potential problems, the static analysis or the acoustic simulation. According to the author’s knowledge, the FMMFS applied to elastic waves scattering problem in solid and the corresponding research are still rare at present. It is worth mentioned that there have been some reports related to the FMMBEM [40, 41], but the associated BEM is largely different from the meshless MFS.
In this paper, in order to overcome the disadvantage of traditional MFS and solve largescale elastic wavemotion problems in a halfspace, a new algorithm of the FMMFS is proposed and validated. The method is based on the single layer potential theory, and introduces the fast multipole expansion to construct the Green’s functions matrix. The virtual source density is obtained through GMRES iteration, of which the solving process is direct, and it is convenient for numerical implementation. Taking the 2D scattering of SH waves around an irregular scatter in an elastic halfspace as an example, the implementation steps are presented in detail, and then several typical examples indicate the excellent accuracy and efficiency of the method. Finally, the scattering of plane SH waves by randomly distributed cavity or inclusion group, by a canyon and hill topography in a halfspace are solved and discussed.
2. The traditional MFS
Fig. 1 shows the calculation model. Assuming the incident waves are plane SH waves $\lambda $, $\mu $ are the two parameters of Lame constant, and $\rho $ is the medium density $k$ is the shear wave number, defined as $k=\omega /\beta $, where $\omega $ is the circular frequency of seismic waves, $\beta $ is the velocity of shear waves. The steadystate motion equation in isotropic homogeneous medium $D$ is as follows:
where ${u}_{z}$ is the antiplane displacement. Note that the time factor $\mathrm{e}\mathrm{x}\mathrm{p}\left(\mathrm{i}\omega t\right)$ is omitted in Eq. (1) and thereafter.
According to numerical experience, the wave sources can be placed within 0.40.6 times of the relevant radius of the scatterer for low frequency waves (nondimensional frequency $ka\le 2\pi $, $a$ is the scatterer radius); while for high frequency wave ($ka>2\pi $), the wave sources should better be placed within 0.70.9 times of the relevant radius of the scatterer.
Firstly, the wave field should be separated. And the total displacement field and the stress field in the elastic halfspace can be expressed as:
where ${u}_{z}^{ff}$ and ${\sigma}_{nz}^{ff}$ are antiplane displacement and shear stress of the freefield under incident plane SH waves. ${u}_{z}^{ss}$ and ${\sigma}_{nz}^{ss}$ are displacement and stress of the scattered wave field. The scattered field in $D$ is constructed by the virtual sources $S$. Consequently, the boundary condition can be written as:
According to the single layer potential theory, virtual sources on $S$ produce the scattered field in the halfspace. Related displacement and stress are expressed as follows:
In which $x\in D$, $y\in S$. ${\varphi}_{z}\left(y\right)$ is the strength of shearwave line source corresponding to $y$ position on virtual sources $S$. ${G}_{k}(x,y)$ and ${T}_{k}(x,y)$ are the displacement Green's functions and stress Green’s functions in the elastic halfspace which can be introduced as:
where ${H}_{0}^{\left(2\right)}(\u2022)$ is the Hankel function of the second kind with order 0, ${n}_{x}$ and ${n}_{y}$ are the unit normal vectors, $r=\leftxy\right$, $r\mathrm{\text{'}}=\leftxy\mathrm{\text{'}}\right$. As is shown in Fig. 2, $y\mathrm{\text{'}}$ is the mirror point of $y$.
Fig. 1. The calculation model
Set $N$ observed points on boundary $B$, and $M$ points on the virtual sources $S$. We choose the unit center physical quantity instead of unit physical quantity, then the linear system of equations become:
Eq. (9) can be reformatted as:
where $A$ is the dense nonsymmetric coefficients matrix, $X$ is the densities of fictitious sources on virtual boundary. $b$ denotes the response related to the free field on the boundary.
To speed up the calculation, a new algorithm of fast multipole fundamental solution method (FMMFS) is presented. This method can greatly shorten the calculation time and reduce the needed memory. Combining General Minimize Residual Methods (GMRES) [42] with the fast multipole expansion technique [43], largescale or highfrequency scattering of elastic waves can be solved effectively.
3. The new fast multipole for MFS
In traditional method of fundamental solution, it is difficult to calculate the approximate solutions for largescale or highfrequency problems using the GMRES iterative algorithm. As shown in Fig. 2, consider a large number of cracks and inclusions existing in the actual complex terrain. For such problems, integration equations with high DOFs need to be calculated.
Fig. 2. The calculation model of largescale or multiscatter problem
To solve the Eq. (10), the large coefficients matrix $A$ is needed to storage. But the memory requirement is so high that this algorithm loses its practical value. The tree structure is used as the main storage and computing object in the FMMFS, which can expand and transfer the kernel function. By taking the GMRES iterative algorithm, we can multiply $X$ and the tree structure instead of the large coefficients matrix $A$. Then results are obtained by controlling iterative precision. Different kernel functions apply to different expansion methods. In this paper, the plane wave expansion theorem is taken to expand the kernel function ${H}_{0}^{\left(2\right)}(\u2022)$ in Eq. (7) as:
where, $\left\overrightarrow{y{y}_{0}}\right<\left\overrightarrow{{y}_{0}{x}_{0}}\right$ and $\left\overrightarrow{{x}_{0}x}\right<\left\overrightarrow{{y}_{0}{x}_{0}}\right\text{,}$${y}_{0}$is the center of multipole expansion, ${\widehat{k}}_{n}=(\mathrm{c}\mathrm{o}\mathrm{s}{\varphi}_{n},\mathrm{s}\mathrm{i}\mathrm{n}{\varphi}_{n})\text{,}$${\varphi}_{n}=2\pi n/(2p+1)\text{,}\text{}\varphi $ is the angle between $\overrightarrow{{y}_{0}{x}_{0}}$ and $X$ axis, $\phi =\pi \pi $, $r=\left\overrightarrow{{y}_{0}{x}_{0}}\right$, and the number $p$ of truncated.
Therefore, it can be shown that Eq. (6) can be rewritten as:
$\left.+\sum _{n=0}^{2p}{M}_{n}\left(\overrightarrow{{y}^{\text{'}}{y}_{c}^{\text{'}}}\right)\times \left(\frac{\partial {T}_{n}\left(\overrightarrow{{y}_{c}^{\text{'}}x}\right)}{\partial {n}_{x}}+\frac{\partial {T}_{n}\left(\overrightarrow{{y}_{c}^{\text{'}}x}\right)}{\partial {n}_{y}}\right)\right].$
In which ${M}_{n}\left(\overrightarrow{y{y}_{c}}\right)$ and ${M}_{n}\left(\overrightarrow{{y}^{\mathrm{\text{'}}}{y}_{c}^{\mathrm{\text{'}}}}\right)$ are the multipole moments and can be expressed as:
${M}_{n}\left(\overrightarrow{y{y}_{c}}\right)$ and ${M}_{n}\left(\overrightarrow{{y}^{\text{'}}{y}_{c}^{\text{'}}}\right)$ in Eq. (15) are only related to ${y}_{c}$ and ${y}_{c}^{\text{'}}$. Furthermore, it needs to calculate only once for arbitrary collocation points $x$ for satisfying conditions.
Fig. 3. Related points for FMMFS expansion
As shown in Fig. 3, new multipole moments can be obtained when points for expansion moved from ${y}_{z}$, ${y\mathrm{\text{'}}}_{z}$ to ${y}_{c}$, ${y\mathrm{\text{'}}}_{c}$. The M2M transfer can be written as:
From equations above, the multipole moments do not need to be calculated again, but the calculated coefficient should be translated into new multipole moments.
Assuming a point ${x}_{c}$,which is close to point $x$, satisfying $\left\overrightarrow{x{x}_{c}}\right<\left\overrightarrow{{y}_{c}{x}_{c}}\right$. And the local expansion to Eq. (15) can be expressed as:
where, ${L}_{n}\left(\overrightarrow{y{x}_{c}}\right)$ and ${L}_{n}\left(\overrightarrow{{y}^{\mathrm{\text{'}}}{x}_{c}}\right)$ can be obtained by M2L transformation of multipole moments ${M}_{n}\left(\overrightarrow{y{y}_{c}}\right)$ and ${M}_{n}\left(\overrightarrow{{y}^{\mathrm{\text{'}}}{y}_{c}^{\mathrm{\text{'}}}}\right)$, as follows:
Finally, the local expansion transmission of L2L can be expressed as:
Take the scattering of SH waves by a cavity in a half space as an example, the implementation procedures is listed as follows.
Step 1. Discretization. Discrete the boundary $S$ and $B$, the same as in the TMFS, and then automatically generate the adaptive tree structure (See Fig. 4).
Fig. 4. The adaptive tree structure
a) Construction of quadtree structure
b) Virtual wave source point
c) Boundary point
Step 2. Upward pass. Translate information from the source points$y$, $y\mathrm{\text{'}}$ to the leaf cells. Eq. (16) and Eq. (17) are expanded in the center of leaves to generate multipole expansion moments. And then the multipole expansion point can be moved to the corresponding parent cell (M2M). Eq. (18) and Eq. (19) constitute the transfer relationship. In this step, transfer can be repeated several times to the parent cells. If satisfying the accuracy conditions, upward pass can be carried out ($l\ge $ 2) (see Fig. 4(a), (b)).
Step 3. Downward pass. The multipole expansion moments of each level cell on the tree structure can be transferred into corresponding local expansion moments (M2L), and Eq. (21) and Eq. (22) can be applied to build this relationship. Transfer the local expansion moments of each level cell in the tree structure to the leaf cell by using Eq. (23). So far, all local expansion moments at leaf cells can be translated to the boundary points $x$ through local expansion. The total expansion and transfer processes are completely given.
Step 4. Nearsource calculation. The contributions of the near field virtual source points can be calculated by the TMFS.
Step 5. Iterations. Update the unknown vector in the system $AX=b$ until the solution converges within a given tolerance using the GMRES solver.
4. Accuracy and computational efficiency
Taking the wave scattering around a cavity in halfspace as an example, the accuracy and numerical stability of FMMFS are tested and compared with analytical solution [44]. As is shown in Fig. 1, assuming the radius of the circular hole is $a$, the number of collocation points on boundary $B$ is $N=$ 2000 ($M=N$), the embedment depth is $d=\text{2}a$, shear modular is $\mu $, surface width is $L=\text{8}a$, the incident angle of SH waves is $\theta =$ 90°,and the dimensionless frequency is $ka=$ 020, the expansion terms$p=$10, the iterative error is $\epsilon =$10^{3}. Fig. 5 illustrates the displacement amplitude on the surface by FMMFS compared with that by analytical solution. Table 1 shows the displacement amplitude on the surface center for the vertical incident SH waves ($\theta =$ 90°) under different degrees of freedom. The comparison illustrates that the results by FMMFS agree well with those by analytical solution, and have good numerical stability.
Fig. 5. Comparisons between the displacement amplitude on the surface by FMMFS and that of analytical solution
Table 1. Numerical stability of displacement amplitudes
DOFs

Displacement amplitude ($x/a=$ 0, $ka=\pi $)


FMMFS

TMFS


100

2.706531

2.706835

500

2.706502

2.706782

1000

2.706532

2.706774

5000

2.706553

2.706772

10000

2.706521

2.706772

Exact

2.706772

–

To test the efficiency of FMMFS, the scattering of plane SH wave is considered by a cylindrical cavity in an elastic half space. Model parameters are as above and the DOFs increase from 100^{}to 50000. As shown in Fig. 6, complexity of the TMFS is $O\left({N}^{2}\right)$ about total CPU time, and the calculation time has reached 9147s when the DOFs are only 10000. However, the complexity of the FMMFS is $O\left(N\right)$, and the calculation time is only 30 s when the DOFs reach 50000. Near field calculation becomes unnecessary due to low frequency, sources with small radius and the tree structure with fine mesh. Fig. 7 illustrates comparison of memory between TMFS and the present FMMFS. The storage requirement of TMFS increases rapidly with the increase of DOFs. When the DOFs reaches 10000, the memory is more than 1.5 GB. However, the required memory will be greatly reduced when using the FMMFS. For 50000 DOFs, the occupied memory is only 66 MB for the FMMFS. Therefore, compared with the TMFS, both the CPU time and memory performance are greatly improved by FMMFS. These advantages speed up fast solution of 2D largescale or broadband scattering problem of elastic waves.
Fig. 6. Total CPU time used to solve the wave scattering
Fig. 7. Total memory used to solve the wave scattering
Fig. 8. The surface displacement amplitude for incident SH waves
a)
b)
c)
d)
5. Numerical examples
5.1. The scattering of SH wave by cavities group
The FMMFS can be used to calculate the scattering of seismic waves for shallow underground cavities distributed randomly in a half space. 30 m under the surface of the ground, 100 random cavities are established to simulate fracture within the scope of 60 m×120 m. Radiuses of circular cavities are ranging from 1.5 m to 3 m and 10,00 boundary points are set on the surface of each cavity. The total number of DOFs reaches 10^{5}. The dimensionless frequency is set as $ka=$ 150300. The iterative error is $\epsilon =$ 10^{3}, and $\theta =$ 0°, 30°, 60°,90°. Fig. 8 shows the surface displacement amplitude of cavities. The consumed CPU time is 803 s and the storage of main matrix is 2011 MB.
Numerical results show that random cavities have significant effect on the scattering of SH waves. As shown in Fig. 8, for vertical incidence of the SH waves, the displacement amplitudes of the surface is greatly decreased, for example, the displacement amplitude near $x=$ 0 is only about 0.1. For the oblique incidence of SH waves, there is obvious amplification effect on the incident side and the amplitude close to two times of freefield displacement, but the displacement on the side behind the wave is significantly decreased. Therefore, random cavities group has a strong “barrier effect” on incident wave. Fig. 9 shows displacement amplitudes around the cavities under SH wave incidence. It can be seen that the coherence effect of scattering waves among cavities is very strong. The displacement amplitude reached more than 4.0 when the incident wave is close to the horizontal incidence. For the vertical incidence, the displacement amplitude around cavities is more than 1.5 times of the free field displacement amplitude. Therefore, for the safety of tunnel and underground pipeline engineering, crossing the cavities zone should be avoided, especially in the side of the incident wave.
Fig. 9. The displacement amplitude around the cavities group for incident SH waves ($ka=$ 150300)
a)$\theta =$ 0°
b)$\theta =$ 30°
c)$\theta =$ 60°
d)$\theta =$ 90°
5.2. The scattering of SH wave by inclusions group
The scattering of plane SH wave is considered by inclusions group in a 30$a$×40$a$ domain, where $a$ is radius of the inclusion. Fig. 10 illustrates the results of displacement amplitude with variation of incident wave frequency. Calculation parameters are set to be: density ratio between the inclusion and the half space ${\rho}_{2}/{\rho}_{1}=$ 2/3, Poisson’s ratio ${\upsilon}_{1}=$ 0.25, ${\upsilon}_{2}=$ 0.30. DOFs = 61000. The tolerance for convergence is set to $\epsilon =$10^{3}. In this calculation, the CPU time is about 205 seconds and the memory usage is about 1.3 GB, $ka=$ 0.5$\pi $, 1.0$\pi $, 2.0$\pi $, 5.0$\pi $.
Assume incident plane waves propagating along $y$direction. Fig. 10 plots the contours of displacement amplitude around inclusions group under SH wave incidence for $ka=$ 0.5$\pi $, 1.0$\pi $, 2.0$\pi $, 5.0$\pi $, and shearwave speed ratio ${\beta}_{2}/{\beta}_{1}=$ 1/2. It demonstrates that the scattering effect of elastic wave by inclusions seems more obvious as the frequency increases. For $ka=$ 1.0$\pi $, the normalized displacement amplitude reaches up to 5.3, more than five times that of incident wave, which is mainly due to coherent effects of multiple scattering wave among inclusions group.
Fig. 10. The displacement amplitude around the inclusions group for incident SH waves ($\theta =$ 0°)
a)$ka=$ 0.5
b)$ka=$ 1.0
c)$ka=$ 2.0
d)$ka=$ 5.0
5.3. The scattering of SH wave by a Vshaped canyon
Displacement amplitude on the surface of a Vshaped canyon under incident highfrequency SH waves are shown in Fig. 12 and Fig. 13. The discrete number of canyon surface is $N=$ 200359, the calculation time is about 732 s, and the consumed memory is 2.4 GB. The parameters are set to be: the wideness of the Vshaped canyon 2 km, the incident frequency 20 Hz, the shear wave velocity 400 m/s, the dimensionless frequency $ka=$ 100$\pi $, $b$/$a=$ 1.0, 2.0, and the iterative error $\epsilon =$ 10^{6}, incident angle $\theta =$ 0°, 45°, 90° (Fig. 11).
Fig. 11. Diffraction of plane SH waves by a Vshaped canyon
Numerical results show that the left of the canyon appears significant displacement amplification effect with the incidence of highfrequency SH waves (left incidence), about twice the size of freefield displacement amplitude ratio. And the right side shows a very long “shadow zone”, indicating canyon has a shielding effect under the incident waves. Under oblique incidence, the amplification effect of canyon is particularly remarkable. With vertical incidence, the displacement amplitude at the corner of the Vshaped canyon is about 3.0, 50 % more than the freefield displacement. For high frequency wave incidence, the displacement response varies widely even in a small spatial scale, and displacement response of the canyon is violent on the side of the incident wave. Thus, to analyze the seismic response of bridge or dam located in canyon, the amplification effect of seismic waves scattering and uneven spatial distribution should be considered, and special attention should be paid to the highfrequency wave of oblique incidence. Calculation of the seismic responses of an engineering structure in a canyon may produce large error if using a uniform seismic input.
Fig. 12. The surface displacement amplitude around a Vshaped canyon for incident SH waves ($b$/$a=$ 1.0)
Fig. 13. The surface displacement amplitude around a Vshaped canyon for incident SH waves ($b$/$a=$ 2.0)
5.4. The scattering and focusing of SH wave by a semielliptical hill
Fig. 14 illustrates the contour of displacement amplitude around a semielliptical hill under incident highfrequency SH waves. The parameters are set to be: the wideness of the hill 1km, the incident frequency 5 Hz, the shear wave velocity 500 m/s, the dimensionless frequency $ka=$ 10$\pi $, $b$/$a=$ 1.0, 2.0,5.0 and the iterative error $\epsilon =$ 10^{6}, incident angle $\theta =$ 60°, 90°.
The results show that the seismic response characteristics of the hill are significantly dependent on the incident wave angle and the aspect ratio of the hill. For the high steep hill, the focal effect of the seismic wave near the top is the most significant, such as for $b$/$a=$ 5.0, the displacement peak reaches 8.3, and the corresponding semicircular hill displacement peak is 5.5. As for the spatial distribution feature, displacement amplification area is widely distributed on the semicircular hill, but is mainly concentrated in the hill surface for the high steep hill. Thus, in actual violent earthquakes, the damage of high and steep slopes is usually serious. In addition, due to the coherence effect of the surface creeping wave, reflected wave and direct wave, the wave crest and wave node of the displacement response appear alternately on the surface of the hill, which is more significant for a highsteep hill. Considering the change of incident angle, the focusing position is also greatly shifted for oblique incidence, and the range of displacement amplification of a high and steep hill is enlarged. Correspondingly, the peak displacement is smaller than that of vertical incidence. The similar focusing phenomenon has also been observed by Chen et al. [45]. Note that the accurate solution to the highfrequency wave scattering by a highsteep hill also illustrate excellent adaptability of the FMMFS for treating practical problems.
Fig. 14. The surface displacement amplitude around a semielliptical hill for incident SH waves ($ka=$ 10$\pi $)
a)$b$/$a=$ 1, $\theta =$90°
b)$b$/$a=$ 1, $\theta =$ 60°
c)$b$/$a=$ 2, $\theta =$ 90°
d)$b$/$a=$ 2, $\theta =$ 60°
e)$b$/$a=$ 5, $\theta =$ 90°
f)$b$/$a=$ 5, $\theta =$ 60°
6. Conclusions
Combined with the new fast multipole expansion technique, the largescale or highfrequency scattering problem of SH waves by 2D superficial irregularities or heterogeneity in a solid halfspace is solved by the proposed FMMFS. By using the plane wave expansion of SH wave potential function, requirement of the CPU time and memory of multipole and local expansion is substantially reduced. The accuracy of this method is verified by comparing with exact solution. It is demonstrated that the FMMFS can effectively solve practical complex scattering problem. Numerical results also show several interesting scattering characteristics of the highfrequency elastic waves generated by a Vshaped canyon, a semielliptical hill and inclusions (cavities) group. All these numerical examples indicate that the proposed FMMFS has favorable numerical accuracy and efficiency, providing a novel effective method for the simulation of largescale and highfrequency wave propagation problems for arbitraryshaped scatters.
Acknowledgements
This work was supported in part by the National Natural Science Foundation of China (No. 51578372), and the Science and Technology Support Program Key Project of Tianjin (No. 17YFZCSF01140).
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