Research progress in multi-scale modeling of processing mechanics and mechanism in additive manufacturing technology of continuous fiber reinforced thermoplastic composites

YAN Xin; WANG Shenru; LIU Siqin; CHANG Baoning; LIU Fei; ZHU Yingdan; ZHANG Wuxiang; DING Xilun

doi:10.13801/j.cnki.fhclxb.20240722.005

Volume 41 Issue 9

Sep. 2024

Turn off MathJax

Article Contents

Article Navigation > Acta Materiae Compositae Sinica > 2024 > 41(9): 4502-4517

YAN Xin, WANG Shenru, LIU Siqin, et al. Research progress in multi-scale modeling of processing mechanics and mechanism in additive manufacturing technology of continuous fiber reinforced thermoplastic composites[J]. Acta Materiae Compositae Sinica, 2024, 41(9): 4502-4517. doi: 10.13801/j.cnki.fhclxb.20240722.005

Citation:

YAN Xin, WANG Shenru, LIU Siqin, et al. Research progress in multi-scale modeling of processing mechanics and mechanism in additive manufacturing technology of continuous fiber reinforced thermoplastic composites[J]. Acta Materiae Compositae Sinica, 2024, 41(9): 4502-4517. doi: 10.13801/j.cnki.fhclxb.20240722.005

Citation:

YAN Xin, WANG Shenru, LIU Siqin, et al. Research progress in multi-scale modeling of processing mechanics and mechanism in additive manufacturing technology of continuous fiber reinforced thermoplastic composites[J]. Acta Materiae Compositae Sinica, 2024, 41(9): 4502-4517. doi: 10.13801/j.cnki.fhclxb.20240722.005

PDF( 5673 KB)

Research progress in multi-scale modeling of processing mechanics and mechanism in additive manufacturing technology of continuous fiber reinforced thermoplastic composites

doi: 10.13801/j.cnki.fhclxb.20240722.005

YAN Xin^{1, 2},
WANG Shenru¹,
LIU Siqin¹,
CHANG Baoning²,
LIU Fei^{1
,
,},
ZHU Yingdan^{3
,
,},
ZHANG Wuxiang^{1, 2
,
,},
DING Xilun^{1, 2}

1.
School of Mechanical Engineering and Automatic, Beihang University, Beijing 100191, China
2.
Ningbo Institute of Technology, Beihang University, Ningbo 315832, China
3.
Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology, Ningbo Institute of Material Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China

Funds: National Natural Science Foundation of China (12372106; 52205003); Zhejiang Provincial Natural Science Foundation of China (LD22E050011); Ningbo Key Projects of Science and Technology Innovation 2025 Plan (2022Z070; 2023Z054)

Received Date: 2024-05-31
Accepted Date: 2024-07-05
Rev Recd Date: 2024-06-27

Available Online: 2024-07-23

Publish Date: 2024-09-15

Abstract

Abstract

Continuous fiber-reinforced thermoplastic composites offer exceptional mechanical and chemical properties, attracting widespread attention in both academia and industry. To meet the automation requirements for high-performance complex structural components, additive manufacturing technologies for continuous fiber-reinforced thermoplastic composites have garnered significant interest. These manufacturing methods include Fused Deposition Modeling and automated fiber placement. The additive manufacturing process involves multi-scale physical phenomena, presenting a complex interplay that is not yet fully understood. The inherent properties of thermoplastic polymers, such as their high melting points and viscosities, further complicate processing, posing substantial challenges in the control of manufacturing processes. Addressing the intricate mechanical challenges within the manufacturing process can be facilitated through the application of multi-scale process mechanics simulations. The integration of these simulations with theoretical and empirical research aids in forging a clear correlation between manufacturing process parameters and the quality of the final product. This provides theoretical support for optimizing process parameters and equipment module design. However, the implementation of multi-scale process simulation requires in-depth comprehension and precise description of physical phenomena. It also involves the design of sophisticated algorithms and the construction of intricate models, thereby increasing the difficulty and challenge of the simulation. This paper reviews recent studies employing various numerical modeling approaches to investigate the processing mechanisms of continuous fiber reinforced thermoplastic composites during the AFP and FDM processes. It also outlines potential promising directions in the field.
- continuous fiber-reinforced thermoplastic composites,
- additive manufacturing,
- process mechanics,
- process mechanism,
- multi-scale modeling
Long Abstrsct
Innovation Points

FullText(HTML)

References(115)

References

[1]	RAJAK D K, PAGAR D D, MENEZES P L, et al. Fiber-reinforced polymer composites: Manufacturing, properties, and applications[J]. Polymers, 2019, 11(10): 1667. doi: 10.3390/polym11101667
[2]	PRASHANTH S, SUBBAYA K, NITHIN K, et al. Fiber reinforced composites-a review[J]. Journal of Materials Science, 2017, 6(3): 2-6.
[3]	BARILE M, LECCE L, IANNONE M, et al. Thermoplastic composites for aerospace applications[M]. Revolutionizing Aircraft Materials and Processes. Springer, 2020: 87-114.
[4]	VALINO A D, DIZON J R C, ESPERA JR A H, et al. Advances in 3D printing of thermoplastic polymer composites and nanocomposites[J]. Progress in Polymer Science, 2019, 98: 101162. doi: 10.1016/j.progpolymsci.2019.101162
[5]	胡记强, 王兵, 张涵其, 等. 热塑性复合材料构件的制备及其在航空航天领域的应用[J]. 宇航总体技术, 2020, 4(4): 61-70. HU Jiqiang, WANG Bing, ZHANG Hanqi, et al. Fabrication of thermoplastic composite components and their application in aerospace[J]. As-tronautical Systems Engineering Technology, 2020, 4(4): 61-70(in Chinese).
[6]	DONOUGH M J, ST JOHN N A, PHILIPS A W, et al. Process modelling of in-situ consolidated thermoplastic composite by automated fibre placement—A review[J]. Composites Part A: Applied Science and Manufacturing, 2022, 163: 107179. doi: 10.1016/j.compositesa.2022.107179
[7]	CAI R, JIN T. The effect of microstructure of unidirectional fibre-reinforced composites on mechanical properties under transverse loading: A review[J]. Journal of Reinforced Plastics and Composites, 2018, 37(22): 1360-1377. doi: 10.1177/0731684418796308
[8]	TIAN X, TODOROKI A, LIU T, et al. 3D printing of continuous fiber reinforced polymer composites: development, application, and prospective[J]. Chinese Journal of Mechanical Engineering: Additive Manufacturing Frontiers, 2022, 1(1): 100016. doi: 10.1016/j.cjmeam.2022.100016
[9]	陈玉丽, 马勇, 潘飞, 等. 多尺度复合材料力学研究进展[J]. 固体力学学报, 2018, 39(1): 1-68. CHEN Yuli, MA Yong, PAN Fei, et al. Research progress in multi-scale mechanics of composite materials[J]. Acta Mechanica Solida Sinica, 2018, 39(1): 1-68(in Chinese).
[10]	XIA H, LU J, DABIRI S, et al. Fully resolved numerical simulations of fused deposition modeling. Part I: fluid flow[J]. Rapid Prototyping Journal, 2018, 24(2): 463-476. doi: 10.1108/RPJ-12-2016-0217
[11]	GUAN X, PITCHUMANI R. Modeling of spherulitic crystallization in thermoplastic tow-placement process: spherulitic microstructure evolution[J]. Composites Science and Technology, 2004, 64(9): 1363-1374. doi: 10.1016/j.compscitech.2003.10.023
[12]	TIERNEY J, GILLESPIE JR J W. Modeling of heat transfer and void dynamics for the thermoplastic composite tow-placement process[J]. Journal of Composite Materials, 2003, 37(19): 1745-1768. doi: 10.1177/002199803035188
[13]	ZHANG J, YANG W, LI Y. Process-dependent multiscale modeling for 3D printing of continuous fiber-reinforced composites[J]. Additive Manufacturing, 2023, 73: 103680. doi: 10.1016/j.addma.2023.103680
[14]	GHNATIOS C, FAYAZBAKHSH K. Warping estimation of continuous fiber-reinforced composites made by robotic 3D printing[J]. Additive Manufacturing, 2022, 55: 102796. doi: 10.1016/j.addma.2022.102796
[15]	GUO H, YANG X, LI T. Molecular dynamics study of the behavior of a single long chain polyethylene on a solid surface[J]. Physical Review E, 2000, 61(4): 4185. doi: 10.1103/PhysRevE.61.4185
[16]	WANG S, YAN X, CHANG B, et al. Atomistic modeling of the effect of temperature on interfacial properties of 3D-printed continuous carbon fiber-reinforced polyamide 6 composite: From processing to loading[J]. ACS Applied Materials & Interfaces, 2023, 15(48): 56454-56463.
[17]	OROMIEHIE E, PRUSTY B G, COMPSTON P, et al. Automated fibre placement based composite structures: Review on the defects, impacts and inspections techniques[J]. Composite Structures, 2019, 224: 110987. doi: 10.1016/j.compstruct.2019.110987
[18]	GRANT C. Automated processes for composite aircraft structure[J]. Industrial Robot: An International Journal, 2006, 33(2): 117-121. doi: 10.1108/01439910610651428
[19]	JAYASEKARA D, LAI N Y G, WONG K-H, et al. Level of automation (LOA) in aerospace composite manufacturing: Present status and future directions towards industry 4.0[J]. Journal of Manufacturing Systems, 2022, 62: 44-61. doi: 10.1016/j.jmsy.2021.10.015
[20]	MARSH G. Automating aerospace composites production with fibre placement[J]. Reinforced Plastics, 2011, 55(3): 32-37. doi: 10.1016/S0034-3617(11)70075-3
[21]	GAN D, DAI J S, DIAS J, et al. Singularity-free workspace aimed optimal design of a 2T2R parallel mechanism for automated fiber placement[J]. Journal of Mechanisms, 2015, 7(4): 041022.
[22]	ZHANG X, XIE W, HOA S V, et al. Design and analysis of collaborative automated fiber placement machine[J]. International Journal of Advanced Robotics, 2016, 1(1): 1-14.
[23]	ASSADI M, FIELD T. AFP processing of dry fiber carbon materials (DFP) for improved rates and reliability[J]. SAE International Journal of Advances and Current Practices in Mobility, 2020, 2(3): 1196-1201. doi: 10.4271/2020-01-0030
[24]	Coriolis. Coriolis C5 Compact-Fiber placement machine for 2D net shape blanks[EB/OL]. [2024-03-15]. https://www.coriolis-composites.com/fiber-placement-machines/coriolis-c5-compact/.
[25]	邵忠喜. 纤维铺放装置及其铺放关键技术研究[D]. 哈尔滨: 哈尔滨工业大学, 2010. SHAO Zhongxi. Research on key technology of fiber placement machine[D]. Harbin: Harbin Institute of Technology, 2010(in Chinese).
[26]	张小辉, 朱玉祥, 张少秋, 等. 先进复合材料自动铺丝技术研究进展[J]. 航空制造技术, 2018, 61(7): 54-61. ZHANG Xiaohui, ZHU Yuxiang, ZHANG Shaoqiu, et al. Research progress on automated fiber placement technology[J]. Aeronautical Manufacturing Technology, 2018, 61(7): 54-61(in Chinese).
[27]	ZHANG W, LIU F, TAO J, et al. Overview of current design and analysis of potential theories for automated fibre placement mechanisms[J]. Chinese Journal of Aeronautics, 2022, 35(4): 1-13. doi: 10.1016/j.cja.2021.04.018
[28]	Markforged. The digital forge platform[EB/OL]. [2024-03-15]. http://markforged.com/.
[29]	YANG C, TIAN X, LIU T, et al. 3D printing for continuous fiber reinforced thermoplastic composites: mechanism and performance[J]. Rapid Prototyping Journal, 2017, 23(1): 209-215. doi: 10.1108/RPJ-08-2015-0098
[30]	PRüß H, VIETOR T. Design for fiber-reinforced additive manufacturing[J]. Journal of Mechanical Design, 2015, 137(11): 111409. doi: 10.1115/1.4030993
[31]	ZHANG K, ZHANG W, DING X. Multi-axis additive manufacturing process for continuous fibre reinforced composite parts[J]. Procedia CIRP, 2019, 85: 114-120. doi: 10.1016/j.procir.2019.09.022
[32]	SHANG J, ZHANG W, LIU F, et al. Z-direction performance and failure behavior of 3D printed continuous fiber reinforced composites with sinusoidal structure[J]. Composites Science and Technology, 2023, 239: 110069. doi: 10.1016/j.compscitech.2023.110069
[33]	AZAROV A, ANTONOV F, VASIL’EV V, et al. Development of a two-matrix composite material fabricated by 3D printing[J]. 2017, 10: 87-90.
[34]	PERVAIZ S, QURESHI T A, KASHWANI G, et al. 3D printing of fiber-reinforced plastic composites using fused deposition modeling: A status review[J]. Materials, 2021, 14(16): 4520. doi: 10.3390/ma14164520
[35]	WICKRAMASINGHE S, DO T, TRAN P. FDM-based 3D printing of polymer and associated composite: A review on mechanical properties, defects and treatments[J]. Polymers, 2020, 12(7): 1529. doi: 10.3390/polym12071529
[36]	ADAM L, LIETAER O, MATHIEU S, et al. Numerical simulation of additive manufacturing of polymers and polymer-based composites[M]. Structure and Properties of Additive Manufactured Polymer Components. Elsevier, 2020: 115-146.
[37]	PENUMAKALA P K, SANTO J, THOMAS A. A critical review on the fused deposition modeling of thermoplastic polymer composites[J]. Composites Part B: Engineering, 2020, 201: 108336. doi: 10.1016/j.compositesb.2020.108336
[38]	陈吉平, 李岩, 刘卫平, 等. 连续纤维增强热塑性树脂基复合材料自动铺放原位成型技术的航空发展现状[J]. 复合材料学报, 2019, 36(4): 784-794. CHEN Jiping, LI Yan, LIU Weiping, et al. Development of AFP in-situ consolidation technology on continuous fiber reinforced thermoplastic matrix composites in aviation[J]. Acta Materiae Compositae Sinica, 2019, 36(4): 784-794(in Chinese).
[39]	TURNER B N, STRONG R, GOLD S A. A review of melt extrusion additive manufacturing processes: I. Process design and modeling[J]. Rapid Prototyping Journal, 2014, 20(3): 192-204.
[40]	PAQUET E, VIKTOR H L. Molecular dynamics, monte carlo simulations, and langevin dynamics: a computational review[J]. BioMed Research International, 2015, 2015(1): 183918.
[41]	LEE D C, KWON G, KIM H, et al. Three-dimensional Monte Carlo simulation of the electrical conductivity of carbon nanotube/polymer composites[J]. Applied Physics Express, 2012, 5(4): 045101. doi: 10.1143/APEX.5.045101
[42]	LIU B, HUANG Y, JIANG H, et al. The atomic-scale finite element method[J]. Computer Methods in Applied Mechanics and Engineering, 2004, 193(17-20): 1849-1864. doi: 10.1016/j.cma.2003.12.037
[43]	ZHANG M, JIANG B, CHEN C, et al. The effect of temperature and strain rate on the interfacial behavior of glass fiber reinforced polypropylene composites: A molecular dynamics study[J]. Polymers (Basel), 2019, 11(11): 1766. doi: 10.3390/polym11111766
[44]	WANG X Q, JIAN W, BUYUKOZTURK O, et al. Degradation of epoxy/glass interface in hygrothermal environment: An atomistic investigation[J]. Composites Part B: Engineering, 2021, 206: 108534. doi: 10.1016/j.compositesb.2020.108534
[45]	YAN Y, XU J, ZHU H, et al. Molecular dynamics simulation of the interface properties of continuous carbon fiber/ polyimide composites[J]. Applied Surface Science, 2021, 563: 150370. doi: 10.1016/j.apsusc.2021.150370
[46]	DRISSI-HABTI M, EL ASSAMI Y, RAMAN V. Multiscale toughening of composites with carbon nanotubes—continuous multiscale reinforcement new concept[J]. Journal of Composites Science, 2021, 5(5): 135. doi: 10.3390/jcs5050135
[47]	JIANG B, ZHANG M, FU L, et al. Molecular dynamics simulation on the interfacial behavior of over-molded hybrid fiber reinforced thermoplastic composites[J]. Polymers (Basel), 2020, 12(6): 1270. doi: 10.3390/polym12061270
[48]	YAN X, CAO P, TAO W, et al. Atomistic modeling at experimental strain rates and timescales[J]. Journal of Physics D: Applied Physics, 2016, 49(49): 493002. doi: 10.1088/0022-3727/49/49/493002
[49]	BRENKEN B, BAROCIO E, FAVALORO A, et al. Fused filament fabrication of fiber-reinforced polymers: A review[J]. Additive Manufacturing, 2018, 21: 1-16. doi: 10.1016/j.addma.2018.01.002
[50]	NGO S I, LIM Y-I, HAHN M-H, et al. Prediction of degree of impregnation in thermoplastic unidirectional carbon fiber prepreg by multi-scale computational fluid dynamics[J]. Chemical Engineering Science, 2018, 185: 64-75. doi: 10.1016/j.ces.2018.04.010
[51]	BANERJEE R, RAY S S. Role of rheology in morphology development and advanced processing of thermoplastic polymer materials: A review[J]. ACS Omega, 2023, 8(31): 27969-28001. doi: 10.1021/acsomega.3c03310
[52]	AUSIAS G, DOLO G, CARTIÉ D, et al. Modeling and numerical simulation of laminated thermoplastic composites manufactured by laser-assisted automatic tape placement[J]. International Polymer Processing, 2020, 35(5): 471-480. doi: 10.1515/ipp-2020-350509
[53]	GAROFALO J, WALCZYK D. In situ impregnation of continuous thermoplastic composite prepreg for additive manufacturing and automated fiber placement[J]. Composites Part A: Applied Science and Manufacturing, 2021, 147: 106446. doi: 10.1016/j.compositesa.2021.106446
[54]	WANG F, WANG G, NING F, et al. Fiber–matrix impregnation behavior during additive manufacturing of continuous carbon fiber reinforced polylactic acid composites[J]. Additive Manufacturing, 2021, 37: 101661. doi: 10.1016/j.addma.2020.101661
[55]	YASHIRO S. Application of particle simulation methods to composite materials: a review[J]. Advanced Composite Materials, 2017, 26(1): 1-22. doi: 10.1080/09243046.2016.1222508
[56]	MORIKAWA D, SENADHEERA H, ASAI M. Explicit incompressible smoothed particle hydrodynamics in a multi-GPU environment for large-scale simulations[J]. Computational Particle Mechanics, 2021, 8: 493-510. doi: 10.1007/s40571-020-00347-0
[57]	LIU M, LI S. On the modeling of viscous incompressible flows with smoothed particle hydro-dynamics[J]. Journal of Hydrodynamics, Ser. B, 2016, 28(5): 731-745.
[58]	YANG D, WU K, WAN L, et al. A particle element approach for modelling the 3D printing process of fibre reinforced polymer composites[J]. Journal of Manufacturing and Materials Processing, 2017, 1(1): 10.
[59]	HE L, LU G, CHEN D, et al. Three-dimensional smoothed particle hydrodynamics simulation for injection molding flow of short fiber-reinforced polymer composites[J]. Modelling and Simulation in Materials Science and Engineering, 2017, 25(5): 055007. doi: 10.1088/1361-651X/aa6dc9
[60]	MURMU U K, ADHIKARI J, NASKAR A, et al. Mechanical properties of crystalline and semicrystalline polymer systems[J]. Encyclopedia of Materials: Plastics and Polymers, 2022, 2: 917-927.
[61]	NING N, FU S, ZHANG W, et al. Realizing the enhancement of interfacial interaction in semicrystalline polymer/filler composites via interfacial crystallization[J]. Progress in Polymer Science, 2012, 37(10): 1425-1455. doi: 10.1016/j.progpolymsci.2011.12.005
[62]	LU X, DETREZ F, ROLAND S. Numerical study of the relationship between the spherulitic microstructure and isothermal crystallization kinetics. Part I. 2-D analyses[J]. Polymer, 2019, 179: 121642. doi: 10.1016/j.polymer.2019.121642
[63]	DURIN A, CHENOT J-L, HAUDIN J-M, et al. Simulating polymer crystallization in thin films: Numerical and analytical methods[J]. European Polymer Journal, 2015, 73: 1-16.
[64]	RUAN C, OUYANG J, LIU S. Multi-scale modeling and simulation of crystallization during cooling in short fiber reinforced composites[J]. International Journal of Heat and Mass Transfer, 2012, 55(7-8): 1911-1921. doi: 10.1016/j.ijheatmasstransfer.2011.11.046
[65]	GRÁNÁSY L, PUSZTAI T, BÖRZSÖNYI T, et al. Phase field theory of crystal nucleation and polycrystalline growth: A review[J]. Journal of materials research, 2006, 21(2): 309-319. doi: 10.1557/jmr.2006.0011
[66]	BAHLOUL A, DOGHRI I, ADAM L. An enhanced phase field model for the numerical simulation of polymer crystallization[J]. Polymer Crystallization, 2020, 3(4): e10144.
[67]	FAN M, HE W, LI Q, et al. PTFE crystal growth in composites: A phase-field model simulation study[J]. Materials, 2022, 15(18): 6286. doi: 10.3390/ma15186286
[68]	RAABE D, GODARA A. Mesoscale simulation of the kinetics and topology of spherulite growth during crystallization of isotactic polypropylene (iPP) by using a cellular automaton[J]. Modelling and Simulation in Materials Science and Engineering, 2005, 13(5): 733. doi: 10.1088/0965-0393/13/5/007
[69]	FANG H, WANG X, GU J, et al. A novel crystallization kinetics model of transcrystalline used for crystallization behavior simulation of short carbon fiber-reinforced polymer composites[J]. Polymer Engineering & Science, 2019, 59(4): 854-862.
[70]	SPINA R, SPEKOWIUS M, HOPMANN C. Multiphysics simulation of thermoplastic polymer crystallization[J]. Materials & Design, 2016, 95: 455-469.
[71]	HALL K W, SIRK T W, KLEIN M L, et al. A coarse-grain model for entangled polyethylene melts and polyethylene crystallization[J]. The Journal of Chemical Physics, 2019, 150(24).
[72]	ELHAJJAR R, GRANT P N, ASHFORTH C. Composite structures: effects of defects[M]. 2018.
[73]	MEHDIKHANI M, GORBATIKH L, VERPOEST I, et al. Voids in fiber-reinforced polymer composites: A review on their formation, characteristics, and effects on mechanical performance[J]. Journal of Composite Materials, 2019, 53(12): 1579-1669. doi: 10.1177/0021998318772152
[74]	PITCHUMANI R, RANGANATHAN S, DON R, et al. Analysis of transport phenomena governing interfacial bonding and void dynamics during thermoplastic tow-placement[J]. International Journal of Heat and Mass Transfer, 1996, 39(9): 1883-1897. doi: 10.1016/0017-9310(95)00271-5
[75]	POLYZOS E, KATALAGARIANAKIS A, POLYZOS D, et al. A multi-scale analytical methodology for the prediction of mechanical properties of 3D-printed materials with continuous fibres[J]. Additive Manufacturing, 2020, 36: 101394. doi: 10.1016/j.addma.2020.101394
[76]	SENTHIL K, AROCKIARAJAN A, PALANINATHAN R, et al. Defects in composite structures: Its effects and prediction methods—A comprehensive review[J]. Composite Structures, 2013, 106: 139-149. doi: 10.1016/j.compstruct.2013.06.008
[77]	张恒, 张雄, 乔丕忠. 近场动力学在断裂力学领域的研究进展[J]. 力学进展, 2022, 52(4): 852-873. doi: 10.6052/1000-0992-22-023 ZHANG Heng, ZHANG Xiong, QIAO Pizhong. Advances of peri-dynamics in fracture mechanics[J]. Advances in Me-chanics, 2022, 52(4): 852-873(in Chinese). doi: 10.6052/1000-0992-22-023
[78]	NISHIKAWA M, MATSUDA N, HOJO M. Fiber-reinforced composites modeling using peridynamics[M]. Peridynamic Modeling, Numerical Techniques, and Applications. Elsevier, 2021: 309-326.
[79]	WU K. Computational modelling of fluid-solid interaction problems by coupling smoothed particles hydrodynamics and the discrete element method[D]. Leeds: University of Leeds, 2017.
[80]	XIA H, LU J, TRYGGVASON G. Fully resolved numerical simulations of fused deposition modeling. Part II–solidification, residual stresses and modeling of the nozzle[J]. Rapid Prototyping Journal, 2018, 24(6): 973-987. doi: 10.1108/RPJ-11-2017-0233
[81]	LIU Y, MUKHERJEE S, NISHIMURA N, et al. Recent advances and emerging applications of the boundary element method[J]. Applied Mechanics Reviews, 2011, 64(3): 030802. doi: 10.1115/1.4005491
[82]	曹忠亮, 富宏亚, 付云忠, 等. 基于自动铺放技术的热塑性复合材料原位固化成型研究进展: 热传导行为及层间性能[J]. 材料导报, 2019, 33(5): 894-900. doi: 10.11896/cldb.201905022 CAO Zhongliang, FU Hongya, FU Yunzhong, et al. A review of robotic prepreg placement and in-situ consolidation for manufacturing fiber-reinforced thermoplastic composites: Heat transfer behavior and interlaminar properties[J]. Materials Reports, 2019, 33(5): 894-900(in Chinese). doi: 10.11896/cldb.201905022
[83]	KOLLMANNSBERGER A, LICHTINGER R, HOHENESTER F, et al. Numerical analysis of the temperature profile during the laser-assisted automated fiber placement of CFRP tapes with thermoplastic matrix[J]. Journal of Thermoplastic Composite Materials, 2017, 31(12): 1563-1586.
[84]	SUN Q, RIZVI G, BELLEHUMEUR C, et al. Effect of processing conditions on the bonding quality of FDM polymer filaments[J]. Rapid Prototyping Journal, 2008, 14(2): 72-80. doi: 10.1108/13552540810862028
[85]	RODRíGUEZ J F, THOMAS J P, RENAUD J E. Mechanical behavior of acrylonitrile butadiene styrene fused deposition materials modeling[J]. Rapid Prototyping Journal, 2003, 9(4): 219-230. doi: 10.1108/13552540310489604
[86]	FAN C, SHAN Z, ZOU G, et al. Interfacial bonding mechanism and mechanical performance of continuous fiber reinforced composites in additive manufacturing[J]. Chinese Journal of Mechanical Engineering, 2021, 34(1): 21. doi: 10.1186/s10033-021-00538-7
[87]	LI Z, YANG T, DU Y. Dynamic finite element simulation and transient temperature field analysis in thermoplastic composite tape lay-up process[J]. Journal of Thermoplastic Composite Materials, 2015, 28(4): 558-573. doi: 10.1177/0892705713486135
[88]	BRASINGTON A, FRANCIS B, GODBOLD M, et al. A review and framework for modeling methodologies to advance automated fiber placement[J]. Composites Part C: Open Access, 2023, 10: 100347. doi: 10.1016/j.jcomc.2023.100347
[89]	YADAV N, SCHLEDJEWSKI R. Review of in-process defect monitoring for automated tape laying[J]. Composites Part A: Applied Science and Manufacturing, 2023, 173: 107654. doi: 10.1016/j.compositesa.2023.107654
[90]	ÇELIK O, PEETERS D, DRANSFELD C, et al. Intimate contact development during laser assisted fiber placement: Microstructure and effect of process parameters[J]. Composites Part A: Applied Science and Manufacturing, 2020, 134: 105888. doi: 10.1016/j.compositesa.2020.105888
[91]	CHENG J, ZHAO D, LIU K, et al. Modeling and impact analysis on contact characteristic of the compaction roller for composite automated placement[J]. Journal of Reinforced Plastics and Composites, 2018, 37(23): 1418-1432. doi: 10.1177/0731684418798151
[92]	DU J, WEI Z, WANG X, et al. An improved fused deposition modeling process for forming large-size thin-walled parts[J]. Journal of Materials Processing Technology, 2016, 234: 332-341. doi: 10.1016/j.jmatprotec.2016.04.005
[93]	PHAN D D, HORNER J S, SWAIN Z R, et al. Computational fluid dynamics simulation of the melting process in the fused filament fabrication additive manufacturing technique[J]. Additive Manufacturing, 2020, 33: 101161. doi: 10.1016/j.addma.2020.101161
[94]	THIEN N P, TANNER R I. A new constitutive equation derived from network theory[J]. Journal of Non-Newtonian Fluid Mechanics, 1977, 2(4): 353-365. doi: 10.1016/0377-0257(77)80021-9
[95]	FU Y, YAO X. Multi-scale analysis for 3D printed continuous fiber reinforced thermoplastic composites[J]. Composites Science and Technology, 2021, 216: 109065. doi: 10.1016/j.compscitech.2021.109065
[96]	SIMACEK P, ADVANI S G, GRUBER M, et al. A non-local void filling model to describe its dynamics during processing thermoplastic composites[J]. Composites Part A: Applied Science and Manufacturing, 2013, 46: 154-165. doi: 10.1016/j.compositesa.2012.10.015
[97]	JEBAHI M, DAU F, CHARLES J-L, et al. Multiscale modeling of complex dynamic problems: an overview and recent developments[J]. Archives of Computational Methods in Engineering, 2016, 23: 101-138. doi: 10.1007/s11831-014-9136-6
[98]	SUN S, HAN Z, ZHANG J, et al. Multiscale collaborative process optimization method for automated fiber placement[J]. Composite Structures, 2021, 259: 113215. doi: 10.1016/j.compstruct.2020.113215
[99]	LIU F, WANG S, ZHANG W, et al. Mechanical and interfacial analysis of 3D-printed two-matrix continuous carbon fibre composites for enhanced structural performance[J]. Composites Part A: Applied Science and Manufacturing, 2024, 180: 108105.
[100]	TOHIDI S D, ROCHA A M, DOURADO N, et al. Influence of transcrystalline layer on finite element mesoscale modeling of polyamide 6 based single polymer laminate composites[J]. Composite Structures, 2020, 232: 111555. doi: 10.1016/j.compstruct.2019.111555
[101]	CHENG Z-Q, LIU H, TAN W. Advanced computational modelling of composite materials[J]. Engineering Fracture Mechanics, 2024, 305: 110120.
[102]	NIKNAFS S, SILANI M, CONCLI F, et al. A coarse-grained concurrent multiscale method for simulating brittle fracture[J]. International Journal of Solids and Structures, 2022, 254: 111898.
[103]	MARKESTEIJN A, KARABASOV S, SCUKINS A, et al. Concurrent multiscale modelling of atomistic and hydrodynamic processes in liquids[J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2014, 372(2021): 20130379. doi: 10.1098/rsta.2013.0379
[104]	WANG C, TAN X P, TOR S B, et al. Machine learning in additive manufacturing: State-of-the-art and perspectives[J]. Additive Manufacturing, 2020, 36: 101538. doi: 10.1016/j.addma.2020.101538
[105]	WANIGASEKARA C, OROMIEHIE E, SWAIN A, et al. Machine learning based predictive model for AFP-based unidirectional composite laminates[J]. IEEE Transactions on Industrial Informatics, 2019, 16(4): 2315-2324.
[106]	BISHARA D, XIE Y, LIU W K, et al. A state-of-the-art review on machine learning-based multiscale modeling, simulation, homogenization and design of materials[J]. Archives of Computational Methods in Engineering, 2023, 30(1): 191-222. doi: 10.1007/s11831-022-09795-8
[107]	XIAO S, HU R, LI Z, et al. A machine-learning-enhanced hierarchical multiscale method for bridging from molecular dynamics to continua[J]. Neural Computing and Applications, 2020, 32: 14359-14373. doi: 10.1007/s00521-019-04480-7
[108]	INGÓLFSSON H I, BHATIA H, AYDIN F, et al. Machine learning-driven multiscale modeling: bridging the scales with a next-generation simulation infrastructure[J]. Journal of Chemical Theory and Computation, 2023, 19(9): 2658-2675. doi: 10.1021/acs.jctc.2c01018
[109]	FONTES A, SHADMEHRI F. Data-driven failure prediction of Fiber-Reinforced Polymer composite materials[J]. Engineering Applications of Artificial Intelligence, 2023, 120: 105834. doi: 10.1016/j.engappai.2023.105834
[110]	TANG Y, WANG Q, CHENG L, et al. An in-process inspection method integrating deep learning and classical algorithm for automated fiber placement[J]. Composite Structures, 2022, 300: 116051. doi: 10.1016/j.compstruct.2022.116051
[111]	CAI R, WEN W, WANG K, et al. Tailoring interfacial properties of 3D-printed continuous natural fiber reinforced polypropylene composites through parameter optimization using machine learning methods[J]. Materials Today Communications, 2022, 32: 103985. doi: 10.1016/j.mtcomm.2022.103985
[112]	SHEN T, LI B. Digital twins in additive manufacturing: a state-of-the-art review[J]. The International Journal of Advanced Manufacturing Technology, 2024, 131: 63-92.
[113]	WANG Y, TAO F, ZUO Y, et al. Digital-twin-enhanced quality prediction for the composite materials[J]. Engineering, 2023, 22: 23-33. doi: 10.1016/j.eng.2022.08.019
[114]	POLINI W, CORRADO A. Digital twin of composite assembly manufacturing process[J]. International Journal of Production Research, 2020, 58(17): 5238-5252. doi: 10.1080/00207543.2020.1714091
[115]	SOORI M, AREZOO B, DASTRES R. Digital twin for smart manufacturing, A review[J]. Sustainable Manufacturing and Service Economics, 2023, 2: 100017.