Design and 3D printing of continuous fiber reinforced heterogeneous composites

Journal Pre-proofs Design and 3D Printing of Continuous Fiber Reinforced Heterogeneous Composites Zhanghao Hou, Xiaoyong Tian, Junkang Zhang, Lu Zhe, Ziqi Zheng, Dichen Li, Andrei V. Malakhov, Alexander N. Polilov PII: DOI: Reference:

S0263-8223(19)33041-7 https://doi.org/10.1016/j.compstruct.2020.111945 COST 111945

To appear in:

Composite Structures

Received Date: Revised Date: Accepted Date:

12 August 2019 11 January 2020 17 January 2020

Please cite this article as: Hou, Z., Tian, X., Zhang, J., Zhe, L., Zheng, Z., Li, D., Malakhov, A.V., Polilov, A.N., Design and 3D Printing of Continuous Fiber Reinforced Heterogeneous Composites, Composite Structures (2020), doi: https://doi.org/10.1016/j.compstruct.2020.111945

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© 2020 Published by Elsevier Ltd.

Design and 3D Printing of Continuous Fiber Reinforced Heterogeneous Composites Zhanghao Hou1, Xiaoyong Tian1＊, Junkang Zhang1, Lu Zhe1, Ziqi Zheng1, Dichen Li1, Andrei V. Malakhov2, Alexander N. Polilov2 1State

Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, 28 Xian Ning west road, Xi’an, 710049, China

2Mechanical

Engineering Research Institute of the Russian Academy of Sciences, Maly Kharitonyevsky Pereulok 4, Moscow, 101990, Russia

＊Corresponding author: [email protected]

Acknowledgments This work was supported by National Key R&D Program of China (2017YFB1103401, 2016YFB1100902); National Natural Science Foundation of China (51575430, 51811530107)

and Russian Foundation for Basic Research (18-08-00372, 18-58-53020).

Design and 3D Printing of Continuous Fiber Reinforced Heterogeneous Composites ABBREVIATION Fiber Reinforced Composites: FRCs Continuous Fiber Reinforced Composites: CFRCs. Continuous Fiber Reinforced Heterogeneous Composites: CFRHCs

ABSTRACT The local properties of continuous fiber reinforced heterogeneous composites (CFRHCs) can be tailored through fiber arrangement design to maximize load and fiber utilization efficiency. Design method and integrated manufacturing process for CFRHCs have been investigated in the current research, based on 3D printing of continuous fiber reinforced composites (CFRCs). Based on the tensile and compressive properties of 3D printed CFRCs, the optimal design method of CFRHCs under process constraints and actual working conditions was studied. The mapping relationship between fiber volume content and process parameters was studied, and a digital transition from optimized design to 3D printing solutions was implemented. The flexural strength of the optimized CFRHCs is 207 MPa, and the maximum increase ratio is 115% compared with other heterogeneous designs with the same fiber volume content. The failure process of CFRHCs was analyzed by the simulation model, and the damage mechanism of CFRHCs under bending load was revealed. The optimization design and integrated manufacturing solution of the CFRHCs have potential applications in aerospace, automotive and other fields. Keywords: Continuous fiber reinforced composite; Heterogeneous material; 3D printing; Optimized design;

1.

Introduction

The vast majority of human-made parts are uniform in microstructure and material composition. In contrast, most of the structures that have evolved over time in nature are composites and have heterogeneous features with variable fiber orientation and content [1], such as crab exoskeletons [2-4], bamboo [5-7] and turtle shells [8]. These heterogeneous composites often have the advantages of low density, high strength, high toughness and high material utilization efficiency, which provide some inspirations to the design of continuous fiber reinforced composites (CFRCs) with light weights, high strength and high fiber utilization efficiency for engineering applications. Local properties of CFRCs can be adjusted by locally controlling fiber content [9-12]. Li et al. [13] prepared gradient continuous ultra-high molecular weight polyethylene fiber reinforced polyethylene composite laminates by a film-stacking technique with hot compaction, and found that CFRCs with proper gradient fiber direction and structure could improve the overall performance of composite structures. However, traditional fabrication processes always have limitations in the fabrication of complicated continuous fiber reinforced heterogeneous composites (CFRHCs), which hinders the development and application of CFRHCs. Conventional processes like filament winding, vacuum forming, and hot-press molding could be used to fabricate of CFRHCs. However, in all these conventional processes, complicated molding and prepregs with different fiber content are required, and the process is expensive and time-consuming, and difficult for automated manufacturing of CFRHCs with complex structures [14]. In recent years, 3D printing of CFRCs has developed rapidly, providing a basis for the integrated manufacturing of CFRHCs [15-17]. Based on the 3D printing process of CFRCs, fiber orientation could be freely controlled according to the designed fiber path. Yusuke Yamanaka et al. [18] proposed an optimized design method for curved fiber reinforced composites for 3D printing. The finite element analysis showed that the fracture stress of the optimized sample increased by 73%. However, only theoretical planning and numerical calculation was conducted. Most available 3D printing processes for CFRCs cannot realize controllable fiber content due to the utilization of prepreg filaments [19, 20]. In 2016, Tian et al. [21] proposed a 3D printing process for CFRCs using dry fiber and plastic filament as raw materials, in which the fiber content can be controlled by adjusting the resin feed rate. However, how to utilize the strong controllability of fiber in this process to realize the optimal design and integrated manufacturing of CFRHCs based on actual working conditions and process constraints has not been studied yet. Therefore, design method and integrated manufacturing process of CFRHCs with variable fiber contents will be investigated in the current research by using 3D printing process. Based on the tensile and compressive properties of 3D printed CFRCs, the optimal design method of CFRHCs has been studied. The mapping relationship between fiber content and process parameters has been established, and a digital transition from optimized design to 3D printing solutions has been implemented. The characteristics of 3D printed CFRHCs, such as bending resistance, stress distribution, damage process and fracture mode, were analyzed systematically by experiments to verify the feasibility of the proposed design method.

2.

Design strategy for CFRHCs

2.1. Numerical analysis model of CFRHCs In this paper, the fiber content of the composite sample has been designed according to the stress distribution under actual working conditions. The finite element simulation method was used to analyze the stress distribution of the CFRHCs in ABAQUS software, taking samples under bending load as examples. The sample was a rectangular laminate with a size of 80mm  10mm  4mm, as shown in Fig. 1. The finite element analysis model was established according to the standard GB/T 1449-2005. The indenter and the fixed supports were set as rigid bodies, and the face-to-face contact constraint was adopted between the indenter and the sample, the fixed support and the sample. The fixed supports were set to a fully fixed constraint and a vertical downward displacement was applied to the indenter to simulate the bending experiment. The fiber content of each layer was optimized to improve the flexural strength of the sample under the constraint of a constant overall fiber content. The number of layers in the thickness direction of the finite element model should be consistent with the number of layers in 3D printing, as shown in Fig. 1. The layer thickness in the printing process was 0.1mm, so the number of layers printed was set to 40. In the finite element analysis model, the material properties of each layer can be set according to the design scheme. The material properties required for simulation include the elastic and strength properties of a CFRCs with different fiber volume contents, as shown in Table 1，where, Vf is the fiber volume content, and the fitting functions obtained by the experiment were suitable for the fiber volume content in the range of 6.7% - 40%.

Fig. 1 Finite element analysis model.

Table 1 Mechanical properties of 3D printed CFRCs.

Material properties

Value

Modulus (fiber direction), E1 Modulus (transverse direction), E2

E1  Vf   80.463Vf  6.9645

In-plane shear modulus, G12

G12  Vf  

Poisson’s ratio, 12

12  Vf   0.33Vf  0.37(1 Vf )

Tensile strength (fiber direction), XT

Tensile strength (transverse

E2  Vf   10.727Vf  2.5702Vf 1.632 2

2.1 0.952 2.1(1 Vf )  0.952Vf

Units

Source

GPa GPa

GB/T 3354-2014 GB/T 3354-2014

GPa

Mixing rule, [22] Mixing rule, [22]

XT  Vf  1436.8Vf  24.127

MPa

GB/T 3354-2014

YT  Vf  29.33Vf 19.235

MPa

GB/T 3354-2014

direction), YT Compressive strength (fiber direction), X C

XC  Vf  114.79Vf 113.27

MPa

GB 1448-2005

Compressive strength (transverse direction), YC

YC  Vf  149.19Vf  88.781

MPa

GB 1448-2005

In-plane shear strength, S12

S12  Vf  39.828Vf  23.86

MPa

GB/T 3355-2014

The Hashin failure criterion [23] was adopted as the failure criterion, and the failure mode judgments are shown in Table 2. Table 2 Hashin failure form criterion.

Failure mode

Discriminant method

Fiber tensile damage mode

  11    12       1,  11  0  X T   S12 

Fiber compression damage mode

  11    =1,  11  0  XC 

Matrix tensile damage mode

  22    12       1,  22  0  YT   S12 

Matrix compression damage mode

2 2 2    22   YC    12  22         1   1,  22  0  YC  S12   2 S12   S12 

2

2

2

2

2

2.2. Design procedure of CFRHCs The fiber content of each layer was optimized in order to improve the flexural strength of the sample at a certain fiber volume content in the current research. The overall design process is shown in Fig. 2a. The length direction of the sample was set to the fiber direction (as shown in Fig. 3), and the initial fiber volume content of the sample was uniformly set to 15%. The load was applied and calculated to obtain the bending strength and stress distribution of the sample. The stiffness distribution of the sample changes after the fiber volume content is redesigned, so iterative calculations are needed to evaluate the performance of the new design structure, and then the optimal design is obtained by iteration. When the bending strength tended to be stable (the bending strength changes less than 1% in three consecutive iterations), the iterative optimization process was terminated, and the fiber content distribution design at this time was determined as the final solution. Finally, the printing parameters (the feed rate of plastic filament, layer thickness and hatch spacing) were designed according to the mapping relationship between fiber volume content and process parameters in 3D printing, and the CFRHCs structure was printed.

Fig. 2 Fiber content design process, (a) Overall design process, (b) Fiber content design process based on stress distribution, (c) Fiber content design process based on tensile stress layer.

Fig. 3 Fiber distribution in a single layer.

The core of this method is the design of fiber content based on stress distribution and process constraints. The design process is shown in Fig. 2b. Among them, n is the single layer number, Vf,n、 σn,.max and σn,.min are the fiber content, maximum stress and minimum stress of the nth layer, Vf,.max and Vf,.min are the maximum fiber content and minimum fiber content allowed by the 3D printing, respectively. Firstly, the maximum stress σn,.max and the minimum stress σn,min in the length direction of each layer were extracted from the stress field obtained by finite element analysis. Positive and negative numbers represent tensile and compressive stresses respectively. The stress extracted in this paper refers to the stress value in the fiber direction (length direction). The stress type (tension or compression) of each layer can be determined according to the stress distribution of each layer. As the compressive properties of 3D printed CFRCs decrease with the increase of fiber content, the

fiber content of the compressed layer is set to the minimum fiber content allowed by 3D printing if the single layer is mainly compressed. If the single layer is mainly subjected to tensile stress, it is designed in accordance with Fig. 2c. The proportion of each layer under tension is calculated by using the maximum tensile stress of each layer. R n  n / T,sum

where, σn is the maximum stress in the nth layer, σT,sum is the total stress of all the tension layers, and Rn is the ratio of the stress of the nth layer to the total stress of all the tension layers. Then, the fiber content corresponding to each layer can be calculated: Vf ,sum  Vf ,set  N T  (Vf ,set  Vf ,min )  N C Vf ,n  R n  Vf ,sum

where, Vf,sum is the total fiber content of all pooled layers, Vf,set is the set fiber content, Vf,min is the minimum fiber content allowed by the 3D printing, NT is the number of pooled layers, and NC is the number of compressed layers. According to Fig. 2c, the single layer with fiber content beyond the allowable range of the process is classified. If the fiber content of the single layer is less than the minimum fiber content allowed by the 3D printing, the fiber content of this layer is set to the minimum fiber content allowed by the 3D printing. If the fiber content of the single layer is greater than the maximum fiber content allowed by the 3D printing, the fiber content of this layer is set to the maximum fiber content allowed by the 3D printing. In order to make the average fiber content of the final structure consistent with the set fiber content, the fiber content of the remaining layers was iterated according to the proportion of each layer.

3.

Experimental procedure

3.1. Materials and equipment A COMBOT-Ⅰ printer (Fig. 4a) (Shananxi Fibertech Technology Development Co., Ltd, China) was adopted to fabricate the CFRHCs in this study. Fig. 4b shows the working process and the key parameters of the extrusion process by receiving thermoplastic polymer and continuous fiber to build a CFRHCs structure, where hatch spacing is the central distance between two adjacent lines. The COMBOT- Ⅰ printer does not have the function of cutting fibers during printing. The Shananxi Fibertech company has other 3D printers with the function of cutting fibers. The principle is to add a cutting device above the print head. The specimens in this paper were printed using a continuous fiber.

Fig. 4 Equipment and scheme of 3D printing for the CFRHCs, (a) the setup for the 3D printing of the CFRHCs, (b) the scheme of the printing process [21].

Continuous aramid-fiber has excellent stability in 3D printing process. So in this study, Kevlar ○R

fiber (linear density of 145 dtex, density of 1440 Kg/m3, cross-sectional area of 0.01 mm2) from DuPont Corp. in the U.S.A was used as the reinforcement material, and polylactide (PLA/1.75 mm, density of 1240 Kg/m3, material compensation coefficient of 1.18) from FLASHFORGE Corp. in China was used as the thermoplastic material. The CFRHCs were fabricated by changing the hatch spacing, as shown in Fig.3. The other process parameters were set to a layer thickness of 0.1 mm, a printing speed of 300 mm/min, a nozzle temperature of 210℃, and without heating of the substrate.

3.2. Method for regulating fiber content In the 3D printing of CFRCS, as shown in Fig. 4b, fiber volume content can be calculated according to the following equation: (1) v f =Sf /  LH  where H is the hatch spacing, L is the layer thickness, and Sf is the cross-sectional area of the fiber bundle. Thus, fiber volume content of the printed parts could be determined and regulated by changing values of the layer thickness (L) and hatch spacing (H). In this paper, the layer thickness was fixed and the hatch spacing has been used to regulate the fiber content of the designed composite specimens. Under the condition of equal material volume for feeding and extrusion in the printing nozzle, a material balance equation can be established: R 2m E  d  HL  Sf 

where Rm is the radius of the resin filament, δ is the material compensation coefficient, and d is the length of the printing, and E is the feed length of plastic filament. Thus, the feed length can be deduced from the above equation as E  d  HL  Sf  /  R 2m 

Furthermore, the feed rate of plastic filament (FE) can be obtained by calculating the feed length in the unit interval: FE  F  HL  Sf  /  R 2m 

where F is the print speed.

3.3. Measurements In order to study the effect of heterogeneous fiber distribution on mechanical properties, three-point bending experiments were performed. The bending tests were carried out on a universal testing machine (PLD-5KN, LETRY Corp., China) according to the standard GB/T 1449-2005 on the printed specimens with a size of 80mm×10mm×4 mm. Fiber distribution of the printed CFRHCs were observed with a Hitachi S-3000N SEM. Samples for SEM were prepared using a diamond yarn cutter (CHSX5632, Taizhou Chen Hong NC equipment manufacturing Co., Ltd., China). For each experimental group, five specimens were prepared to obtain an average value of the targeted properties. In order to observe the pore distribution of the 3D printed CFRCs, a micro X-ray

three-dimensional imaging system (Y. CHEETAH, Analyses Co., Ltd., Germany) was utilized. In order to improve the detection accuracy of the micro X-ray three-dimensional imaging system, the sizes of the sample were 5mm×5mm×1mm.

4.

Results and discussion

4.1. Results 4.1.1. Optimization iterative process During the iterative process, the stress (the maximum stress along the fiber direction in the single layer) distribution, fiber content distribution and hatch space distribution of the sample are shown in Fig. 5. The stress in the upper layer is significantly reduced and the stress in the lower layer is significantly increased after an iterative optimization, as shown in Fig. 5a. Subsequent iterations have a very small effect on the stress distribution. Fig. 5b shows the change in fiber content. After one iteration, the fiber content of the upper layer is set to the minimum fiber content allowed for 3D printing, and the number of layers is about 50% of the total number of layers. The lower area, which is about 20% of the total layers, is set to the maximum fiber content allowed for 3D printing. The fiber content in the intermediate transition zone increases from top to bottom in a gradient distribution. As the number of iterations increases, the number of layers in the transition zone gradually decreases. As shown in Fig. 5c, the hatch space is consistent with the trend of fiber content. The transition area of the hatch space is smaller than the transition area of the fiber content as seen from the cloud image. As in Eq. (1), the hatch space is inversely proportional to the fiber content when the layer thickness is constant. When the fiber content with a larger value is changing, the corresponding hatch space changes little, so the transition zone appears to be smaller than the fiber content.

Fig. 5 The iterative process, (a) changes in stress distribution, (b) changes in fiber content distribution, and (c) changes in hatch space distribution.

The optimized design of the sample is completed after four iterations. The change in flexural strength during the iteration is shown in Fig. 6, where n (n = 0, 1, ..., 4) is the of the iterations number. After an iterative optimization, the flexural strength is significantly improved, and then the flexural strength does not continue to increase as the iteration number increases. The flexural strength of the unoptimized sample was 200 MPa. After four iterations, the strength of the sample reached 251 MPa, which was 25% higher than that before optimization.

Fig. 6 The change in flexural strength during the iteration process.

4.1.2. Experimental verification After optimization, the fiber content distribution of the sample (G1) is shown in Fig. 7. Two kinds of CFRHCs and one homogeneous CFRCs with the same average fiber volume content (15%) were designed as control groups. In order to study the influence of the direction of force on CFRHCs, G3 has a high fiber content in the upper layer and a low fiber content in the lower layer, which is symmetrical with G1. G2 has a low fiber content on the outer layer and a high fiber content on the intermediate layer. G4 has a uniform fiber volume content of 15%.

Fig. 7 The schematic representation of CFRHCs fabricated in this experiment.

In order to verify the performance of the optimized structure, the flexural performance of the

optimized structure G1 and the unoptimized structure G4 were compared. As shown in Fig. 8, the flexural strength and flexural modulus of G1 are 207 MPa and 9 GPa, which are 11% and 13% higher than G4, respectively. Compared with the control group, G1 has higher flexural strength and flexural modulus, and G2 has the worst flexural strength and flexural modulus. The flexural strength and flexural modulus of G1 are 115% and 105% higher than G2.

Fig. 8 Influence of heterogeneous fiber content distribution on flexural properties.

4.1.3. Microstructure and fracture mode of 3D printed CFRHCs In order to analyze the fiber distribution characteristics of the 3D printed CFRHCs, the cross section of the specimens was observed. The microstructure of G1 and G2 are shown in Fig. 9, where G3 is the same as G1. During the cutting process of the sample, the resin was melted and then adhered to the surface of the fiber, so the fiber area was relatively rough and the resin area were relatively smooth. In the high fiber content zone, the fiber bundles are macroscopically connected due to the small hatch space. The fiber distribution is consistent with the design, and each sample is completed in one printing process, which indicates that 3D printing provides effective technical support for the integrated manufacturing of CFRHCs. The 3D printed continuous fibers are distributed in the specimens in bundles, so that the resin accumulation region and the fiber bundle region appear in the specimens. During the printing process, it is difficult for the resin to enter the inside of the fiber bundle, which will reduce the mechanical properties of the part [21]. For this reason, prepreg filament can further improve the mechanical properties of the printed part. The failure mode of the CFRHCs under bending load is shown in Fig. 10, the main failure modes of G1 and G2 are interlaminar shear where the fiber content changes suddenly. The main failure mode of G3 and G4 is matrix fracture.

Fig. 9 Microstructures of cross section of the printed CFRHCs.

Fig. 10 Failure mode of the printed CFRHCs.

Porosity has an important influence on the properties of CFRCs, so the pore distribution of 3D printed CFRCs was characterized. Fig. 11 is the pore distribution of the 3D printed CFRCs. The porosity of the 3D printed CFRCs is 0.27% when the fiber volume content is 10%. In 3D printing, CFRCs are manufactured filament by filament, and the overlap between filaments depends on the extrusion force of the material from the nozzle. This extrusion force is small, so linear porosity tends to appear between the filaments.

Fig. 11 Pore distribution of 3D printed CFRCs at 10% fiber content.

4.2. Discussion 4.2.1. Damage process of CFRHCs The mechanical response process and damage process of G1 under bending load were simulated and analyzed. Fig. 12a shows the stress-strain curves of G1 under bending load for experiment and simulation, respectively. The results of experiments and simulations are consistent across the overall trend. Fig. 12b is the damage state of G1 at different times. The failure mode can be divided into four types as shown in Table 2. The value in the legend represents the degree of damage. When it is 1, it indicates that failure of the corresponding mode has occurred. The simulation results are in good agreement with the experimental results in the initial elastic deformation stage, as shown in Fig. 12a. Since the compressive strength of the CFRCs is lower than the tensile strength, fiber compression failure behavior occurs first in the upper layer at TA, as shown in Fig. 12b. After that, the overall stiffness of G1 decreases. As the load continues to increase, fiber tensile damage failure occurs in the lowermost layers at TB. After that, the fiber compression failure expanded from the top to the bottom, the fiber tensile failure expanded from the bottom to the top, and the sample yielded at the time of TC. A matrix tensile failure is accompanied by the yielding process. In summary, the tensile and compressive failure of the fiber is the main reason for the failure of the sample.

Fig. 12 The damage process of G1. (a) Stress-strain graphs of G1 from both simulations and experiments. (b) The process of damage change.

4.2.2. Effect of heterogeneous design on stress distribution Fig. 13a is the stress distribution state of homogeneous design before optimization. The upper layer is mainly subjected to compressive stress, while the lower layer is subjected to tensile stress, and the stress value in the middle layer (called the neutral layer) is small. In the process of optimization design, as the longitudinal compressive properties of 3D printed CFRCs decrease with the increase of fiber content, the minimum fiber content allowed by the process is arranged in the upper region, which improves the compressive capacity of the upper region, and effectively reduces fiber usage and improves the printing efficiency. As the longitudinal tensile properties of 3D printed CFRCs increase with the increase of fiber content, the fiber content in the lower layer of the optimized structure is the highest, which improves the bearing capacity of the lower layer to the tensile stress. According to the stress distribution and material characteristics, the design can effectively improve the strength of the structure. On the contrary, G3 places the high fiber content on the upper layer, and it is difficult for the bottom layer to withstand large tensile stress due to the low fiber content, so the bending resistance is lower than G1 and G4. G2 has a high fiber content in the neutral layer, which is the location with the least force, and does not play the high-performance characteristics of high fiber content, so the performance is much lower than G1 and G4. In summary, the load carrying capacity of the structure and the efficiency of use of the material can be improved by designing the local fiber content based on the local stress distribution.

Fig. 13 Stress distribution in each layer of laminated plate under bending load. (a) Optimizing the stress distribution of the front laminated structure. (b) Stress distribution of optimized laminated structures.

CFRHCs with discontinuous changes in fiber content distribution are more susceptible to delamination failure. As shown in Fig. 13, the stress change of G4 from top to bottom is smoother than G1. Especially in the lower layer, G1 has a large change in stress where the fiber content changes greatly, which tends to cause local stress concentration and cause delamination damage.

With the increase of interlaminar bonding strength of 3D printed CFRCs [24], the performance of the optimized CFRHCs will be further improved. Under bending load, the layer that is neither subjected to tensile stress nor compressive stress is a neutral layer. In homogeneous structures, the neutral layer is in the middle, as shown in Fig. 13a. After optimization, the neutral layer of the CFRHCs is shifted to the direction of high modulus, as shown in Fig. 13b. Therefore, the position of the neutral layer can be adjusted by the non-uniform design of the fiber content. In this paper, the integrated manufacturing of CFRHCs is realized by regulating the process parameters in the 3D printing of CFRCs, which provides a rapid manufacturing method for the design of complex CFRHCs structures. The optimized design method is based on the stress distribution of the part after loading, and can realize the design of complex structures under different loads. At the same time, the optimized design method takes into account the manufacturing characteristics (layered manufacturing) and process constraints of 3D printing, and the optimized results can be fabricated by the 3D printing of CFRCs. Digital solutions for complex CFRHCs from design to manufacturing are realized.

5.

Conclusions

In this paper, based on the tensile and compressive properties of 3D printed CFRCs, an optimal design method of CFRHCs under process constraints and actual working load was proposed. The mapping relationship between fiber volume content and process parameters in 3D printing was studied. The rapid integrated automatic manufacturing of CFRHCs was realized by dynamic control of resin feed rate. The CFRCs laminated structure was optimized under bending load. The flexural strength of the optimized CFRHCs is 207 MPa, and the maximum increase ratio is 115% compared with other heterogeneous designs with the same fiber content. This proves that the proposed optimization method and printing scheme can effectively improve the load-carrying capacity and fiber utilization efficiency of CFRCs, and has potential applications in aerospace, high-speed trains and other fields.

References [1] Studart AR. Biological and bioinspired composites with spatially tunable heterogeneous architectures. Advanced Functional Materials 2013;23:4423-36. [2] Chen P, Lin AY, McKittrick J, Meyers MA. Structure and mechanical properties of crab exoskeletons. Acta Biomaterialia 2008;4:587-96. [3] Raabe D, Sachs C, Romano P. The crustacean exoskeleton as an example of a structurally and mechanically graded biological nanocomposite material. Acta Materialia 2005;53:4281-92. [4] Yang Y, Chen Z, Song X, Zhang Z, Zhang J, Shung KK, et al. Biomimetic anisotropic reinforcement architectures by electrically assisted nanocomposite 3D printing. Advanced Materials 2017;29:1605750. [5] Habibi MK, Samaei AT, Gheshlaghi B, Lu J, Lu Y. Asymmetric flexural behavior from bamboo’s functionally graded hierarchical structure: underlying mechanisms. Acta Biomaterialia 2015;16:178-86. [6] Zou M, Xu S, Wei C, Wang H, Liu Z. A bionic method for the crashworthiness design of

thin-walled structures inspired by bamboo. Thin-Walled Structures 2016;101:222-30. [7] Wang F, Shao J, Keer LM, Li L, Zhang J. The effect of elementary fibre variability on bamboo fibre strength. Materials & Design 2015;75:136-42. [8] Achrai B, Wagner HD. Micro-structure and mechanical properties of the turtle carapace as a biological composite shield. Acta Biomaterialia 2013;9:5890-902. [9] Vaidya UK, Chawla KK. Processing of fibre reinforced thermoplastic composites. International Materials Reviews 2013;53:185-218. [10] Al Abadi H, Thai H, Paton-Cole V, Patel VI. Elastic properties of 3D printed fibre-reinforced structures. Composite Structures 2018;193:8-18. [11] Melenka GW, Cheung BKO, Schofield JS, Dawson MR, Carey JP. Evaluation and prediction of the tensile properties of continuous fiber-reinforced 3D printed structures. Composite Structures 2016;153:866-75. [12] Jang J, Han S. Mechanical properties of glass-fibre mat/pmma functionally gradient composite. Composites Part A: Applied Science and Manufacturing 1999;30:1045-53. [13] Li L, Liu X, Zhou X, Hong J, Zhuang X, Yan X. Mechanical properties of unidirectional continuous fiber self-reinforced polyethylene graded laminates. Polymer Composites 2015;36:128-37. [14] Fujihara K, Huang Z, Ramakrishna S, Hamada H. Influence of processing conditions on bending property of continuous carbon fiber reinforced PEEK composites. Composites Science and Technology 2004;64:2525-34. [15] Hou Z, Tian X, Zhang J, Li D. 3D printed continuous fibre reinforced composite corrugated structure. Composite Structures 2018;184:1005-10. [16] Parandoush P, Lin D. A review on additive manufacturing of polymer-fiber composites. Composite Structures 2017;182:36-53. [17] Yang C, Tian X, Liu T, Cao Y, Li D. 3d printing for continuous fiber reinforced thermoplastic composites: mechanism and performance. Rapid Prototyping Journal 2017;23:209-15. [18] Yamanaka Y, Todoroki A, Ueda M, Hirano Y, Matsuzaki R. Fiber line optimization in single ply for 3D printed composites. Open Journal of Composite Materials 2016;06:121-31. [19] Goh GD, Dikshit V, Nagalingam AP, Goh GL, Agarwala S, Sing SL, et al. Characterization of mechanical properties and fracture mode of additively manufactured carbon fiber and glass fiber reinforced thermoplastics. Materials & Design 2018;137:79-89. [20] Melenka GW, Cheung BKO, Schofield JS, Dawson MR, Carey JP. Evaluation and prediction of the tensile properties of continuous fiber-reinforced 3D printed structures. Composite Structures 2016;153:866-75. [21] Tian X, Liu T, Yang C, Wang Q, Li D. Interface and performance of 3D printed continuous carbon fiber reinforced PLA composites. Composites Part A: Applied Science and Manufacturing 2016;88:198-205. [22] Kawabata S. Measurement of the transverse mechanical properties of high-performance fibres. The Journal of The Textile Institute 1990;81:432-47. [23] Koricho EG, Khomenko A, Fristedt T, Haq M. Innovative tailored fiber placement technique for enhanced damage resistance in notched composite laminate. Composite Structures 2015;120:378-85. [24] Luo M, Tian X, Shang J, Zhu W, Li D, Qin Y. Impregnation and interlayer bonding behaviours of 3D -printed continuous carbon-fiber-reinforced poly-ether-ether-ketone composites. Composites

Part A: Applied Science and Manufacturing 2019;121:130-8.

Author Statement Zhanghao Hou: Methodology, Formal analysis, Writing - Original Draft Preparation, Data Curation. Xiaoyong Tian: Conceptualization Ideas, Writing - Review & Editing, Project administration, Supervision, Funding acquisition. Junkang Zhang: Validation Verification, Visualization Preparation. Lu Zhe: Software Programming. Ziqi Zheng: Investigation. Dichen Li: Resources. Andrei V. Malakhov: Writing - Review & Editing. Alexander N. Polilov: Writing - Review & Editing.