研究生: |
李曉南 Li, Xiaonan |
---|---|
論文名稱: |
基於對含缺陷複合材料的無損檢測來改進對缺陷的探傷,表徵與評估 Improving the detection, characterization and assessment of defective composites based on non-destructive measurements |
指導教授: |
克裏斯蒂安, 威爾
Christian, Will 帕特森, 伊恩 Patterson, Eann 王偉中 Wang, Wei-Chung |
口試委員: |
陳元方
Chen, Yuan-Fang 沃瑞爾, 尼克 Warrior, Nick 帕特爾, 莫裏克 Patel, Maulik 德芙萊西卡, 克塞尼婭 Dvurecenska, Ksenija 張禎元 Chang, Jen-Yuan |
學位類別: |
博士 Doctor |
系所名稱: |
工學院 - 動力機械工程學系 Department of Power Mechanical Engineering |
論文出版年: | 2024 |
畢業學年度: | 111 |
語文別: | 英文 |
論文頁數: | 128 |
中文關鍵詞: | 複合材料 、波紋缺陷 、無損檢測 |
外文關鍵詞: | Composite materials, Fibre waviness, Non-destructive evaluation |
相關次數: | 點閱:2 下載:0 |
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本論文總結了應用非破壞性檢測技術對於碳纖維增強複合材料的結構分析。由於碳纖維增強複合材料具備了較高的強度和較低的重量,因此該材料被廣泛應用於航天領域。但是,在製造複合材料過程中引入的一些缺陷會影響到複合材料部件的在實際應用中的表現。本論文的研究目的爲應用非破壞性檢測技術改善對航天複合材料部件的結構分析,以此來改進對缺陷在工業界內的檢測方法和提高對部件破壞行爲的分析手段。
本論文研發出一項創新的技術可以用來檢測碳纖維增強層壓板內的缺陷。這項技術的實現基於對含有面內波紋缺陷的共振行爲的研究。首先,振幅變動電子光斑影像干涉術和模態分析法結合起來獲取到了複合材料層壓板的振型。其次,在振型中可識別的節線區域的輪廓線被提取出來。提取輪廓線應用了專門爲此編寫的一套算法,該算法基於密度空間的聚類分析(Density-based spatial clustering of applications with noise)。傅裏葉描述子被用來分解提取到的輪廓線,以此來降低數據維度和進行數據對比。振型輪廓線的區別被用來識別缺陷是否存在於碳纖維層壓板內。這項對比節點區域輪廓線的技術可以極大地簡化條紋圖像的對比,來達到損傷檢測的目的。這項技術在驗證有限元模型的有效性方面同樣顯示出很大的潛力。
本論文也探討了應用有限元模型進行預測波紋缺陷導致的殘餘應變的研究。有限元模型預測的準確性可以通過與實驗數據進行對比得出。在此基礎上,本論文發明了一項創新的方法用來識別對超聲波C掃描數據進行處理的最佳算法。這些算法可以通過表徵超聲波C掃描數據獲得碳纖維的方向,以此來繪製出纖維取向圖。有限元模型的建立基於纖維取向圖,而纖維取向圖可以通過三種算法得到,分別是:拉冬變換(Radon transform), 二維快速傅裏葉變換(2D fast Fourier transform),和索貝爾濾波器(Sobel filters)。試樣表面的殘餘應變可以通過對試樣在靜態下的面外位移的計算得到,面外位移可以通過數字影像相關法測量得到。模型預測得到的殘餘應變圖與實驗得到的殘餘應變圖可以被正交多項式分解成特徵向量來降低數據維度和進行量化對比。實驗數據與應用到優化參數的模型預測結果符合程度良好。通過對三種算法得到的有限元模型的預測表現進行對比,拉冬變換(Radon transform)表現最佳。
本論文研究了有缺陷的碳纖維層壓板在受力情況下的表現。四種不同程度的缺陷被引入到試樣中。通過四點彎折實驗,這些試樣被折斷。數字影像相關法(DIC)測量得到了在加載過程中試樣的上、下表面産生的逐漸變化的應變。對於含有少量缺陷的試樣,分層損傷是主要的破壞方式。對於含有大量缺陷的試樣,碳纖維的微屈曲先在缺陷區域發生,然後在受力面是壓應力的板層進行擴展,與此同時局部的分層損傷也會産生。有限元模型被用來預測斷裂行爲。內聚力模型被用來預測分層損傷,哈辛-羅特姆(Hashin-Rotem)斷裂準則應用到了UMAT(用戶自定義材料子程序)裡來模擬層內損傷。該模型有效地預測了含有不同程度缺陷的複合材料的斷裂行爲。這項關於分層損傷和微屈曲的研究對於了解含有面內波紋缺陷的複合材料的斷裂行爲至關重要。這些研究成果對於設計和維修含有面內波紋缺陷的複合材料部件來阻止上述斷裂行爲的産生也很重要。
This thesis summarises the research on the development of structural assessment of carbon fibre reinforced composites using non-destructive based techniques. Carbon fibre reinforced composites are widely used in the aerospace industry because of their high stiffness and low weight. However, the performance of composite parts is affected by defects induced during the manufacturing stage. The aim of this thesis is to improve the structural assessment of aerospace composites based on non-destructive measurements, such that defect identification in industry can be enhanced and better analysis of component failure can be achieved.
A novel technique for identifying defects in carbon fibre reinforced plates has been developed when investigating the resonance behaviour of defective composites with in-plane fibre waviness. Amplitude-fluctuation electronic speckle pattern interferometry combined with modal analysis were used to obtain the mode shapes of composite plates first. Then the contours of the nodal regions visible in the mode shapes were extracted using a specially developed algorithm based on density-based spatial clustering of applications with noise. Fourier descriptors were used to decompose the contours to reduce data dimensionality and make comparisons. The differences in contours can be used for identifying the presence of defects. This technique for nodal region comparison was found to greatly simplify the comparison of fringe patterns for the purpose of damage assessment and could potentially be used as part of validation procedures for finite element models.
This thesis also investigates the prediction of residual strains caused by fibre waviness using finite element models. Based on the prediction accuracy by comparing with experimental data, a novel method for identifying the most effective algorithm for characterising fibre orientation for the geometric ply map using ultrasonic C-scan data has been developed. Finite element models were generated based on the fibre-orientation data from three different algorithms: the Radon transform, 2D fast Fourier transform, and Sobel filter. Residual strains on the surface of the specimens were obtained from calculations based on the out-of-plane displacements measured using a digital image correlation system. The predicted and measured residual strain maps were decomposed into feature vectors using orthogonal polynomials to reduce data dimensionality and make quantitative comparisons. The measured residual strains and the predictions based on models using optimised parameters showed good agreement. The differences in performance were quantified based on the accuracy of the predicted residual strains, which showed that the Radon transform performed best.
The performance of defective composites under mechanical loadings were investigated. Four severities of in-plane waviness were induced in composite specimens. The specimens were loaded to failure using four-point bending tests, and progressive changes in strain in both the bottom and top ply of the specimen during the tests were obtained using digital image correlation (DIC). For specimens with lower level of waviness, delamination was the dominant failure mode. For specimens with higher level of waviness, micro-buckling of carbon fibres occurred first at the defective regions then propagated through the surface of the ply under compression, and local delaminations were also observed. Finite element analysis was used to predict the failure behaviour. A cohesive zone model was used to model the delaminations and Hashin-Rotem damage criterion was applied via a UMAT (User Material Subroutine) to model the intra lamina failure. The model was shown to be effective for predicting the failure of different severities of waviness. The investigation on the delaminations and micro buckling behaviour is crucial for understanding the failure mechanism of composites containing in-plane fibre waviness. The results should also be useful in designing and repairing composite components with in-plane fibre waviness to prevent potential occurrence of such damages.
References
1. Games S, inventor; Owens Illinois Glass Co, assignee. Method and apparatus for making glass wool. United States1933.
2. Bunsell AR, Harris B. Hybrid carbon and glass fibre composites. Composites. 1974;5(4):157-64.
3. Mehdikhani M, Gorbatikh L, Verpoest I, Lomov SV. Voids in fiber-reinforced polymer composites: A review on their formation, characteristics, and effects on mechanical performance. Journal of Composite Materials. 2019;53(12):1579-669.
4. Liu SK, Sun W, Jing H, Dong ZX. Debonding Detection and Monitoring for CFRP Reinforced Concrete Beams Using Pizeoceramic Sensors. Materials. 2019;12(13).
5. Krishnamoorthy A, Mercy JL, Vineeth KSM, Salugu MK. Delamination Analysis of Carbon Fiber Reinforced Plastic (CFRP) Composite plates by Thermo graphic technique. Materials Today-Proceedings. 2015;2(4-5):3132-9.
6. Kimura M, Watanabe T, Takeichi Y, Niwa Y. Nanoscopic origin of cracks in carbon fibre-reinforced plastic composites. Scientific Reports. 2019;9.
7. Christian WJR, DiazDelaO FA, Atherton K, Patterson EA. An experimental study on the manufacture and characterization of in-plane fibre-waviness defects in composites. Royal Society Open Science. 2018;5(5).
8. Wang W-C, Su C-W, Liu P-W. Full-field non-destructive analysis of composite plates. Composites Part A: Applied Science and Manufacturing. 2008;39(8):1302-10.
9. Gibson RF. Principles of Composite Materials Mechanics. 2 ed. Boca Raton: CRC Press; 2007.
10. Kulkarni P, Mali KD, Singh S. An overview of the formation of fibre waviness and its effect on the mechanical performance of fibre reinforced polymer composites. Composites Part A-Applied Science and Manufacturing. 2020;137.
11. Potter KD. Understanding the origins of defects and variability in composites manufacture. ICCM International Conferences on Composite Materials2009.
12. Parlevliet PP, Bersee HEN, Beukers A. Residual stresses in thermoplastic composites - A study of the literature - Part I: Formation of residual stresses. Composites Part A-Applied Science and Manufacturing. 2006;37(11):1847-57.
13. Pottavathri SB. EFFECT OF IN-PLANE FIBER TOW WAVINESS IN THE STRENGTH CHARACTERISTICS OF DIFFERENT FIBER REINFORCED COMPOSITES. Kansas, United States: Wichita State University; 2015.
14. Bogetti TA, Gillespie JW, Lamontia MA. Influence of Ply Waviness on the Stiffness and Strength Reduction on Composite Laminates. Journal of Thermoplastic Composite Materials. 1992;5(4):344-69.
15. Hsiao HM, Daniel IM. Elastic properties of composites with fiber waviness. Composites Part A: Applied Science and Manufacturing. 1996;27(10):931-41.
16. Garnich MR, Karami G. Finite Element Micromechanics for Stiffness and Strength of Wavy Fiber Composites. Journal of Composite Materials. 2004;38(4):273-92.
17. Zhu J, Wang J, Zu L. Influence of out-of-plane ply waviness on elastic properties of composite laminates under uniaxial loading. Composite Structures. 2015;132:440-50.
18. Lee SK, Kim MW, Park CJ, Chol MJ, Kim G, Cho J-M, et al. Effect of fiber orientation on acoustic and vibration response of a carbon fiber/epoxy composite plate: Natural vibration mode and sound radiation. International Journal of Mechanical Sciences. 2016;117:162-73.
19. Kumar Samal P, Pruthvi IS, Suresh BS. Effect of fiber orientation on vibration response of glass epoxy composite beam. Materials Today: Proceedings. 2021;43:1519-25.
20. Chan WS, Wang JS. Influence of Fiber Waviness on the Structural Response of Composite Laminates. Journal of Thermoplastic Composite Materials. 1994;7(3):243-60.
21. Wu C, Gu Y, Luo L, Xu P, Wang S, Li M, et al. Influences of in-plane and out-of-plane fiber waviness on mechanical properties of carbon fiber composite laminate. Journal of Reinforced Plastics and Composites. 2018;37(13):877-91.
22. Sitohang RDR, Grouve WJB, Warnet LL, Koussios S, Akkerman R. An experimental approach to reproduce in-plane fiber waviness in thermoplastic composites test coupons using a reverse forming method. Journal of Composite Materials. 2021;56(4):561-74.
23. Yurgartis SW. MEASUREMENT OF SMALL-ANGLE FIBER MISALIGNMENTS IN CONTINUOUS FIBER COMPOSITES. Composites Science and Technology. 1987;30(4):279-93.
24. Creighton CJ, Sutcliffe MPF, Clyne TW. A multiple field image analysis procedure for characterisation of fibre alignment in composites. Composites Part A-Applied Science and Manufacturing. 2001;32(2):221-9.
25. Sutcliffe MPF, Lemanski SL, Scott AE. Measurement of fibre waviness in industrial composite components. Composites Science and Technology. 2012;72(16):2016-23.
26. Kratmann K, Sutcliffe M, Lilleheden L, Pyrz R, Thomsen O. A novel image analysis procedure for measuring fibre misalignment in unidirectional fibre composites. Composites Science and Technology. 2009;69(2):228-38.
27. Yoshimura A, Hosoya R, Koyanagi J, Ogasawara T. X-ray computed tomography used to measure fiber orientation in CFRP laminates. Advanced Composite Materials. 2016;25(1):19-30.
28. Schmidt C, Schultz C, Weber P, Denkena B. Evaluation of eddy current testing for quality assurance and process monitoring of automated fiber placement. Composites Part B: Engineering. 2014;56:109-16.
29. Mizukami K, Mizutani Y, Todoroki A, Suzuki Y. Detection of in-plane and out-of-plane fiber waviness in unidirectional carbon fiber reinforced composites using eddy current testing. Composites Part B: Engineering. 2016;86:84-94.
30. Li X. Eddy Current Techniques for Non-destructive Testing of Carbon Fibre Reinforced Plastic (CFRP) [Dissertation]: University of Manchester; 2012.
31. Smith RA, Nelson LJ, Mienczakowski MJ, Challis RE. Automated analysis and advanced defect characterisation from ultrasonic scans of composites. Insight. 2009;51(2):82-7.
32. Smith RA, Nelson LJ, Xie N, Fraij C, Hallett SR. Progress in 3D characterisation and modelling of monolithic carbon-fibre composites. Insight. 2015;57(3):131-9.
33. Kratmann KK, Sutcliffe MPF, Lilleheden LT, Pyrz R, Thomsen OT. A novel image analysis procedure for measuring fibre misalignment in unidirectional fibre composites. Composites Science and Technology. 2009;69(2):228-38.
34. Ayres C, Bowlin GL, Henderson SC, Taylor L, Shultz J, Alexander J, et al. Modulation of anisotropy in electrospun tissue-engineering scaffolds: Analysis of fiber alignment by the fast Fourier transform. Biomaterials. 2006;27(32):5524-34.
35. Hughes RR, Drinkwater BW, Smith RA. Characterisation of carbon fibre-reinforced polymer composites through radon-transform analysis of complex eddy-current data. Composites Part B-Engineering. 2018;148:252-9.
36. Schaub NJ, Kirkpatrick SJ, Gilbert RJ. Automated Methods to Determine Electrospun Fiber Alignment and Diameter Using the Radon Transform. BioNanoScience. 2013;3(3):329-42.
37. Yang X, Ju B-f, Kersemans M. Ultrasonic tomographic reconstruction of local fiber orientation in multi-layer composites using Gabor filter-based information diagram method. NDT & E International. 2021;124.
38. Sutton MA, Wolters WJ, Peters WH, Ranson WF, McNeill SR. Determination of displacements using an improved digital correlation method. Image and Vision Computing. 1983;1(3):133-9.
39. Pan B, Dafang W, Yong X. Incremental calculation for large deformation measurement using reliability-guided digital image correlation. Optics and Lasers in Engineering. 2012;50(4):586-92.
40. Schreier H, Orteu J-J, Sutton MA. Image Correlation for Shape, Motion and Deformation Measurements. New York: Springer; 2009.
41. Catalanotti G, Camanho PP, Xavier J, Dávila CG, Marques AT. Measurement of resistance curves in the longitudinal failure of composites using digital image correlation. Composites Science and Technology. 2010;70(13):1986-93.
42. Godara A, Raabe D. Influence of fiber orientation on global mechanical behavior and mesoscale strain localization in a short glass-fiber-reinforced epoxy polymer composite during tensile deformation investigated using digital image correlation. Composites Science and Technology. 2007;67(11-12):2417-27.
43. Sun CT. Delamination Behaviour of Composite. New York: Woodhead Publishing; 2008.
44. Sun XC, Hallett SR. Failure mechanisms and damage evolution of laminated composites under compression after impact (CAI): Experimental and numerical study. Composites Part A: Applied Science and Manufacturing. 2018;104:41-59.
45. Wykes C. Use Of Electronic Speckle Pattern Interferometry (ESPI) In The Measurement Of Static And Dynamic Surface Displacements. Optical Engineering. 1982;21(3).
46. Yang L, Xie X, Zhu L, Wu S, Wang Y. Review of electronic speckle pattern interferometry (ESPI) for three dimensional displacement measurement. Chinese Journal of Mechanical Engineering. 2014;27(1):1-13.
47. Leendertz JA. Interferometric displacement measurement on scattering surfaces utilizing speckle effect. Journal of Physics E: Scientific Instruments. 1970;3(3):214-8.
48. Coggrave CR. Wholefield Optical Metrology: Surface Displacement Measurement. 2022.
49. Moore AJ, Tyrer JR. Two-dimensional strain measurement with ESPI. Optics and Lasers in Engineering. 1996;24(5-6):381-402.
50. Zhang ZY, Richardson MOW, Wisheart M, Tyrer JR, Petzing J. ESPI non-destructive testing of GRP composite materials containing impact damage. Composites Part A: Applied Science and Manufacturing. 1998;29(7):721-9.
51. Pagliarulo V, Palummo R, Rocco A, Ferraro P, Ricciardi MR, Antonucci V. Evaluation of delaminated area of polymer/Carbon Nanotubes fiber reinforced composites after flexural tests by ESPI. 2014 IEEE Metrology for Aerospace (MetroAeroSpace); Benevento, Italy: IEEE; 2014.
52. Romero G. Study of a vibrating plate: comparison between experimental (ESPI) and analytical results. Optics and Lasers in Engineering. 2003;40(1-2):81-90.
53. Wang W-C, Hwang C-H, Lin S-Y. Vibration measurement by the time-averaged electronic speckle pattern interferometry methods. Appl Opt. 1996;35(22):4502-9.
54. Dai X, Shao X, Geng Z, Yang F, Jiang Y, He X. Vibration measurement based on electronic speckle pattern interferometry and radial basis function. Optics Communications. 2015;355:33-43.
55. Wang W-C, Hsu J-S. Investigation of vibration characteristics of bonded structures by time-averaged electronic speckle pattern interferometry. Optics and Lasers in Engineering. 2010;48(10):958-65.
56. Davies GAO, Olsson R. Impact on composite structures. The Aeronautical Journal. 2016;108(1089):541-63.
57. Mukhopadhyay S, Jones MI, Hallett SR. Compressive failure of laminates containing an embedded wrinkle; experimental and numerical study. Composites Part A: Applied Science and Manufacturing. 2015;73:132-42.
58. Mukhopadhyay S, Jones MI, Hallett SR. Tensile failure of laminates containing an embedded wrinkle; numerical and experimental study. Composites Part A: Applied Science and Manufacturing. 2015;77:219-28.
59. Sitohang RDR, Grouve WJB, Warnet LL, Akkerman R. Effect of in-plane fiber waviness defects on the compressive properties of quasi-isotropic thermoplastic composites. Composite Structures. 2021;272.
60. Sitohang RDR, Grouve WJB, Warnet LL, Wijskamp S, Akkerman R. The relation between in-plane fiber waviness severity and first ply failure in thermoplastic composite laminates. Composite Structures. 2022;289.
61. Jenkin CF. Report on Materials of Construction Used in Aircraft and Aircraft Engines. London: H. M. Stationery Off.; 1920.
62. Waddoups ME. Advanced Composite Material Mechanics for the Design and Stress Analyst. Ft. Worth, Texas; 1967.
63. Hill R. A theory of the yielding and plastic flow of anisotropic metals. Proceedings of the Royal Society of London Series A Mathematical and Physical Sciences. 1948;193(1033):281-97.
64. Tsai SW. Strength Theories of Filamentary Structures Fundamental Aspects of Fiber Reinforced Plastic Composites. New York: Wiley-IntersciencE; 1968.
65. Azzi VD, Tsai SW. Anisotropic strength of composites. Experimental Mechanics. 1965;5(9):283-8.
66. Tsai SW, Wu EM. A General Theory of Strength for Anisotropic Materials. Journal of Composite Materials. 1971;5(1):58-80.
67. Tsai SW, Hahn HT. Introduction to Composite Materials1980.
68. Hashin Z, Rotem A. A Fatigue Failure Criterion for Fiber Reinforced Materials. Journal of Composite Materials. 1973;7(4):448-64.
69. Kaddour AS, Hinton MJ. Maturity of 3D failure criteria for fibre-reinforced composites: Comparison between theories and experiments: Part B of WWFE-II. Journal of Composite Materials. 2013;47(6-7):925-66.
70. Santosh KC, Lamiroy B, Wendling L. Dtw–Radon-Based Shape Descriptor for Pattern Recognition. International Journal of Pattern Recognition and Artificial Intelligence. 2013;27(03).
71. Ping Tian D. A review on image feature extraction and representation techniques. International Journal of Multimedia and Ubiquitous Engineering. 2013;8(4):385-96.
72. Susan S, Agrawal P, Mittal M, Bansal S. New shape descriptor in the context of edge continuity. CAAI Transactions on Intelligence Technology. 2019;4(2):101-9.
73. Wang W, Mottershead JE, Sebastian CM, Patterson EA. Shape features and finite element model updating from full-field strain data. International Journal of Solids and Structures. 2011;48(11-12):1644-57.
74. Zhang D, Lu G. Review of shape representation and description techniques. Pattern Recognition. 2004;37(1):1-19.
75. Arbter K, Snyder WE, Burkhardt H, Hirzinger G. Application of affine-invariant Fourier descriptors to recognition of 3-D objects. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1990;12(7):640-7.
76. Kauppinen H, Seppanen T, Pietikainen M. An experimental comparison of autoregressive and Fourier-based descriptors in 2D shape classification. IEEE Transactions on Pattern Analysis and Machine Intelligence. 1995;17(2):201-7.
77. Zhang D, Lu G. A comparative study on shape retrieval using Fourier descriptors with Different shape signatures. Journal of Visual Communication and Image Representation. 2001.
78. Dalitz C, Brandt C, Goebbels S, Kolanus D. Fourier descriptors for broken shapes. EURASIP Journal on Advances in Signal Processing. 2013;2013(1).
79. Patki AS, Patterson EA. Decomposing Strain Maps Using Fourier-Zernike Shape Descriptors. Experimental Mechanics. 2011;52(8):1137-49.
80. Lampeas G, Pasialis V, Lin X, Patterson EA. On the validation of solid mechanics models using optical measurements and data decomposition. Simulation Modelling Practice and Theory. 2015;52:92-107.
81. Sebastian C, Hack E, Patterson E. An approach to the validation of computational solid mechanics models for strain analysis. The Journal of Strain Analysis for Engineering Design. 2012;48(1):36-47.
82. CEN Workshop Agreement 16799:2014 ‘Validation of computational solid mechanics models’. 2014.
83. Dynamics D. Dantec Dynamics | Precision Measurement Systems & Sensors [Available from: https://www.dantecdynamics.com/solutions/stress-strain-espi-dic/digital-image-correlation-dic/dic-standard-3d/.
84. Gonzalez R, Woods R. Digital image processing. 4 ed. New York: Pearson; 2018.
85. Bradley D, Roth G. Adaptive Thresholding using the Integral Image. Journal of Graphics Tools. 2011;12(2):13-21.
86. Ester M, Kriegel HP, Sander J, Xu X. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second International Conference on Knowledge Discovery in Databases and Data Mining. 1996(KDD-96):226-31.
87. Schubert E, Sander J, Ester M, Kriegel HP, Xu X. DBSCAN Revisited, Revisited: Why and How You Should (Still) Use DBSCAN. ACM Transactions on Database Systems. 2017;42(3):1-21.
88. Kauppinen H, Seppanen T, Pietikainen M. An Experimental comparison of Autoregressive and Fourier-based Descriptors in 2-D Shape Classification. IEEE Transaction on Pattern Analysis and Machine Intelligence. 1995;17:201-7.
89. Nelson LJ, Smith RA. Fibre direction and stacking sequence measurement in carbon fibre composites using Radon transforms of ultrasonic data. Composites Part A-Applied Science and Manufacturing. 2019;118:1-8.
90. Timoshenko SP, Woinowsky KS. Theory of Plates and Shells. New York: McGraw-Hill; 1959.
91. Morokov E, Levin V, Chernov A, Shanygin A. High resolution ply-by-ply ultrasound imaging of impact damage in thick CFRP laminates by high-frequency acoustic microscopy. Composite Structures. 2021;256.
92. Sobel I, Feldman G. ‘A 3×3 isotropic gradient operator for image processing’, presented at the Stanford Artificial Intelligence Project (SAIP), 1968, and referenced in History and Definition of the Sobel Operator, by Irwin Sobel. 2014.
93. Gong WR, Chen JL, Patterson EA. Buckling and delamination growth behaviour of delaminated composite panels subject to four-point bending. Composite Structures. 2016;138:122-33.
94. Barnes JA, Simms IJ, Farrow GJ, Jackson D, Wostenholm G, Yates B. Thermal expansion behaviour of thermoplastic composite materials. Journal of Thermoplastic Composite Materials. 1990;3:66-80.
95. Parlevliet PP, Bersee HEN, Beukers A. Residual stresses in thermoplastic composites- A study of the literature- Part II: Experimental techniques. Composites Part A-Applied Science and Manufacturing. 2007;38(3):651-65.
96. Ran ZG, Yan Y, Li JF, Qi ZX, Yang L. Determination of thermal expansion coefficients for unidirectional fiber-reinforced composites. Chinese Journal of Aeronautics. 2014;27(5):1180-7.
97. Aggarwal CC, Hinneburg A, Keim DA. On the Surprising Behavior of Distance Metrics in High Dimensional Space. Lecture Notes in Computer Science In: Van den Bussche, J, Vianu, V (eds) Database Theory — ICDT 2001 ICDT 2001. 2001;1973.
98. Linhart H, Zucchini W. Model selection. New York: John Wiley & Sons; 1986.
99. Raschka S, Mirjalili V. Python Machine Learning. Second ed. Birmingham: Packt Publishing Ltd.; 2017.
100. Steele K, Werndl C. Model-Selection Theory: The Need for a More Nuanced Picture of Use-Novelty and Double-Counting. British Journal for the Philosophy of Science. 2018;69(2):351-75.
101. Gao G, An L, Giannopoulos IK, Han N, Ge E, Hu G. Progressive Damage Numerical Modelling and Simulation of Aircraft Composite Bolted Joints Bearing Response. Materials (Basel). 2020;13(24).
102. Dassault Systèmes Simulia Corp. SIMULIA User Assistance 2021. ABAQUS Documentation. 2021.
103. Calvo JV, Feito N, Miguélez MH, Giner E. Modeling the delamination failure under compressive loads in CFRP laminates based on digital image correlation analysis. Composite Structures. 2022;287.
104. Camanho PP, Davila CG. Mixed-Mode Decohesion Finite Elements for the Simulation of Delamination in Composite Materials. NASA/TM. 2002;No. 211737.
105. Benzeggagh ML, Kenane M. Measurement of mixed-mode delamination fracture toughness of unidirectional glass/epoxy composites with mixed-mode bending apparatus. Composites Science and Technology. 1996;56(4):439-49.
106. Camanho PP, Dávila CG. Mixed-mode decohesion finite elements for the simulation of delamination in composite materials. 2002.
107. Mottershead JE, Link M, Friswell MI. The sensitivity method in finite element model updating: A tutorial. Mechanical Systems and Signal Processing. 2011;25(7):2275-96.
108. Marwala T. Finite-element-model updating using computional intelligence techniques: Applications to structural dynamics: Springer; 2010.
109. Li X, Patterson EA, Wang W-C, Christian WJR. Prediction of Residual Strains Due to In-Plane Fibre Waviness in Defective Carbon-Fibre Reinforced Polymers Using Ultrasound Data. Journal of Nondestructive Evaluation. 2022;42(1).
110. Li XN, Sung PC, Patterson EA, Wang WC, Christian WJR. Identification of defects in composite laminates by comparison of mode shapes from electronic speckle pattern interferometry. Optics and Lasers in Engineering. 2023;163.