The paper describes a numerical XCT image-based finite element approach for characterizing the mechanical behavior influenced by the meso-morphological features of biaxial non-crimp fabric reinforced polymer composite (BNCFRP). The resolution of 49.8190 µm and the combination of CPS3 (matrix) and CPS4R (yarn) ensure lower calculation time. The crack evolution process and failure patterns are influenced by various meso-structures. Therefore, the volume fractions of sub-phases were statistically analyzed through batch processing of numerical simulations on 1381 images. The results from 2D image-based finite element models show that the failure strength has a strong correlation with the internal structure and the mean simulated stress-strain curves differ from experimental results in terms of stiffness and failure stress, with errors of 7% and 13%, respectively. However, the 3D image-based finite element model demonstrates superior accuracy in estimating mechanical properties, with errors remaining below 2%.
PalanikumarKMudhukrishnanM. Technologies in additive manufacturing for fiber reinforced composite materials: a review. Curr Opin Chem Eng2020; 28: 51–59.
2.
McIlhaggerAArcherEMcIlhaggerR. Manufacturing processes for composite materials and components for aerospace applications. In: Polymer composites in the aerospace industry. Amsterdam, Netherlands: Elsevier, 2020, pp. 59–81.
3.
SayamARahmanANMMRahmanMS, et al.A review on carbon fiber-reinforced hierarchical composites: mechanical performance, manufacturing process, structural applications and allied challenges. Carbon Lett2022; 32: 1173–1205.
4.
ChenHCaoXZhangX, et al.Automatic segmentation framework of X-Ray tomography data for multi-phase rock using Swin Transformer approach. Sci Data2023; 10: 812.
5.
LiuTFanCKeZ, et al.A real micro-structural model to simulate the transversal compression behaviors of unidirectional composites based on the μ-CT detection. Compos Commun2022; 32: 101184.
6.
ZhengKCaoXJiangZ, et al.Improved XCT image automatic segmentation for quantitative characterization of the meso-morphological features in the damaged braided composite fabric. Compos Sci Technol2024; 247: 110395.
7.
DadrasHBarbaz‐IsfahaniRSaber‐SamandariS, et al.Experimental and multi‐scale finite element modeling for evaluating healing efficiency of electro‐sprayed microcapsule based glass fiber‐reinforced polymer composites. Polym Compos2022; 43: 5929–5945.
8.
DadrasHTeimouriABarbaz-IsfahaniR, et al.Indentation, finite element modeling and artificial neural network studies on mechanical behavior of GFRP composites in an acidic environment. J Mater Res Technol2023; 24: 5042–5058.
9.
JinLHuHSunB, et al.A simplified microstructure model of bi-axial warp-knitted composite for ballistic impact simulation. Compos B Eng2010; 41: 337–353.
10.
SaeedifarMSalehMNEl-DessoukyHM, et al.Damage assessment of NCF, 2D and 3D woven composites under compression after multiple-impact using acoustic emission. Compos Appl Sci Manuf2020; 132: 105833.
11.
ShipshaABurmanM. Failure mechanisms in NCF composite bolted joints: experiments and FE model. Compos B Eng2020; 192: 107950.
12.
StanleyWFBandaruAKRanaS, et al.Mechanical, dynamic-mechanical and wear performance of novel non-crimp glass fabric-reinforced liquid thermoplastic composites filled with cellulose microcrystals. Mater Des2021; 212: 110276.
13.
García-RodríguezSCostaJBarderaA, et al.A 3D tomographic investigation to elucidate the low-velocity impact resistance, tolerance and damage sequence of thin non-crimp fabric laminates: effect of ply-thickness. Compos Appl Sci Manuf2018; 113: 53–65.
14.
SobhaniASaeedifarMNajafabadiMA, et al.The study of buckling and post-buckling behavior of laminated composites consisting multiple delaminations using acoustic emission. Thin-Walled Struct2018; 127: 145–156.
15.
AmeriBMoradiMMohammadiB, et al.Investigation of nonlinear post-buckling delamination in curved laminated composite panels via cohesive zone model. Thin-Walled Struct2020; 154: 106797.
16.
ZhengTGuoLSunR, et al.Investigation on the compressive damage mechanisms of 3D woven composites considering stochastic fiber initial misalignment. Compos Appl Sci Manuf2021; 143: 106295.
17.
KhanMKJunaediHAlshahraniH, et al.Enhanced open-hole strength and toughness of sandwich carbon-Kevlar woven composite laminates. Polymers2023; 15: 2276.
18.
PanZMaHWuZ, et al.Micro-XCT characterization and numerical analysis of bending damage mechanism in carbon fiber plain, twill and winding composite tubes. Fibers Polym2020; 21: 874–897.
19.
LiuKMengLZhaoA, et al.A hybrid direct FE2 method for modeling of multiscale materials and structures with strain localization. Comput Methods Appl Mech Eng2023; 412: 116080.
20.
LiuKLiuJLWangZ. A damage threshold prediction model of CFRP panel by hail impact based on delamination mechanism. Eng Fract Mech2020; 239: 107282.
21.
WangZZhaoMLiuK, et al.Experimental analysis and prediction of CFRP delamination caused by ice impact. Eng Fract Mech2022; 273: 108757.
22.
ZhangXHaoHShiY, et al.Static and dynamic material properties of CFRP/epoxy laminates. Constr Build Mater2016; 114: 638–649.
23.
GhazimoradiMTrejoEAButcherC, et al.Characterizing the macroscopic response and local deformation mechanisms of a unidirectional non-crimp fabric. Compos Appl Sci Manuf2022; 156: 106857.
24.
YangBChenYLeeJ, et al.In-plane compression response of woven CFRP composite after low-velocity impact: modelling and experiment. Thin-Walled Struct2021; 158: 107186.
25.
GoS-HKimH-GShinH-J, et al.The impact fracture behaviors of CFRP/EVA composites by drop-weight impact test. Carbon Lett2017; 21: 23–32.
26.
SafriSSultanMCardonaF. Impact damage evaluation of glass-fiber reinforced polymer (GFRP) using the drop test rig–an experimental based approach. ARPN J Eng Appl Sci2015; 10: 9916–9928.
27.
BandaruAKChouhanHBhatnagarN. High strain rate compression testing of intra-ply and inter-ply hybrid thermoplastic composites reinforced with Kevlar/basalt fibers. Polym Test2020; 84: 106407.
28.
HwangY-TChoiK-HKimJ-I, et al.Prediction of non-linear mechanical behavior of shear deformed twill woven composites based on a multi-scale progressive damage model. Compos Struct2019; 224: 111019.
29.
NaghdinasabMFarrokhabadiAMadadiH. A numerical method to evaluate the material properties degradation in composite RVEs due to fiber-matrix debonding and induced matrix cracking. Finite Elem Anal Des2018; 146: 84–95.
30.
IsmailYYangDYeJ. A DEM model for visualising damage evolution and predicting failure envelope of composite laminae under biaxial loads. Compos B Eng2016; 102: 9–28.
31.
WuWLiW. Parametric modeling based on the real geometry of glass fiber unidirectional non-crimp fabric. Textil Res J2019; 89: 3949–3959.
32.
ZhangWYanSYanY, et al.A parameterized unit cell model for 3D braided composites considering transverse braiding angle variation. J Compos Mater2022; 56: 491–505.
33.
SinchukYShishkinaOGueguenM, et al.X-ray CT based multi-layer unit cell modeling of carbon fiber-reinforced textile composites: segmentation, meshing and elastic property homogenization. Compos Struct2022; 298: 116003.
34.
JiaYYuGDuJ, et al.Adopting traditional image algorithms and deep learning to build the finite model of a 2.5 D composite based on X-Ray computed tomography. Compos Struct2021; 275: 114440.
35.
NairSNDasariAYueCY, et al.Failure behavior of unidirectional composites under compression loading: effect of fiber waviness. Materials2017; 10: 909.
36.
ChandaASinhaSKDatlaNV. The influence of fiber alignment, structure and concentration on mechanical behavior of carbon nanofiber/epoxy composites: experimental and numerical study. Polym Compos2021; 42: 1155–1173.
37.
WangJZhouHLiuZ, et al.Statistical modelling of tensile properties of natural fiber yarns considering probability distributions of fiber crimping and effective yarn elastic modulus. Compos Sci Technol2022; 218: 109142.
38.
LiXShonkwilerSMcMainsS. Detection of resin-rich areas for statistical analysis of fiber-reinforced polymer composites. Compos B Eng2021; 225: 109252.
39.
HydeAHeJCuiX, et al.Effects of microvoids on strength of unidirectional fiber-reinforced composite materials. Compos B Eng2020; 187: 107844.
40.
Pérez-RamosAFigueiridoB. Toward an “Ancient” virtual World: improvement methods on X-ray CT data processing and virtual reconstruction of fossil skulls. Front Earth Sci2020; 8: 345.
41.
HuangYYangZLiuG. X-ray computed tomography image-based meso-scale dynamic fracture of concrete under compression: Monte Carlo simulations. In: “Proceedings of the 9th international conference on fracture mechanics of concrete and concrete structures (FraMCoS-9)”, Berkeley, USA, 29 May–1 June, 2016.
42.
Szyszkiewicz-WarzechaKStecJDejaJ, et al.3D multi-ion corrosion model in hierarchically structured cementitious materials obtained from nano-XCT data. Materials2023; 16: 5094.
43.
ZhengKChenHWuC, et al.An improved dataset augmentation approach for deep learning-based XCT images segmentation in layered composite fabric. Compos Struct2023; 317: 117052.
44.
ZhengKWuCChenH, et al. Improved 3D image segmentation for X-ray tomographic data of biaxial warp-knitted composites. Journal of Reinforced Plastics and Composites. 2023; 44: 344–357.
45.
ChamisCC.Simplified composite micromechanics equations for strength, fracture toughness, impact resistance and environmental effects. Sampe Quarterly. 1984; 44: 0036-0821.
46.
ChamisCC. Mechanics of composite materials: past, present, and future. Composites Technology and Research1989; 11: 3–14.
47.
GuptaNYeRPorfiriM. Comparison of tensile and compressive characteristics of vinyl ester/glass microballoon syntactic foams. Compos B Eng2010; 41: 236–245.
HooputraHGeseHDellH, et al.A comprehensive failure model for crashworthiness simulation of aluminium extrusions. Int J Crashworthiness2004; 9: 449–464.
50.
CamanhoPPDávilaCG. Mixed-mode decohesion finite elements for the simulation of delamination in composite materials. 2002.
51.
PanZWuZXiongJ. Localized temperature rise as a novel indication in damage and failure behavior of biaxial non-crimp fabric reinforced polymer composite subjected to impulsive compression. Aero Sci Technol2020; 103: 105885.
52.
WanYWangYGuB. Finite element prediction of the impact compressive properties of three-dimensional braided composites using multi-scale model. Compos Struct2015; 128: 381–394.
53.
Nguyen-VanVWickramasingheSGhazlanA, et al.Uniaxial and biaxial bioinspired interlocking composite panels subjected to dynamic loadings. Thin-Walled Struct2020; 157: 107023.
54.
ZhangFLiuKWanY, et al.Experimental and numerical analyses of the mechanical behaviors of three-dimensional orthogonal woven composites under compressive loadings with different strain rates. Int J Damage Mech2014; 23: 636–660.
55.
FabriAPionS. CGAL: the computational geometry algorithms library. In: Proceedings of the 17th ACM SIGSPATIAL international conference on advances in geographic information systems 2009, Seattle, Washington, 4–6 November 2009, pp. 538–539.
56.
WanYSunBGuB. Multi-scale structure finite element analyses of damage behaviors of multi-axial warp-knitted composite materials subjected to quasi-static and high strain rate compressions. J Text Inst2016; 107: 879–904.
