Image Reconstruction Modeling, Simulation and Experimental Study on Wood Fibrous Paper

References

• Cherian, B. M., A. L. Leão, S. F. Souza, L. M. M. Costa, G. M. Olyveira, M. Kottaisamy, E. R. Nagarajan, and S. Thomas. 2011. Cellulose nanocomposites with nanofibres isolated from pineapple leaf fibers for medical applications. Carbohydrate Polymers 86 (4):1790–98. doi:10.1016/j.carbpol.2011.07.009.
   Web of Science ®Google Scholar
• Conceicao, E. L. T., J. M. R. Curto, R. M. S. Simoes, and A. A. T. G. Portugal. 2010. Coding a simulation model of the 3D structure of paper. Computational Modeling of Objects Represented in Images, Proceedings 6026:299-+.
   Google Scholar
• Dimassi, M., X. Zeng, L. Koehl, X. Zeng, and A. Peruwelz. 2008. Pore network modelling using image processing techniques. International Journal of Clothing Science and Technology 20 (3):137–49. doi:10.1108/09556220810865193.
   Web of Science ®Google Scholar
• Eichhorn, S. J., J. Sirichaisit, and R. J. Young. 2001. Deformation mechanisms in cellulose fibres, paper and wood. Journal of Materials Science 36 (13):3129–3135. doi:10.1023/A:1017969916020.
   Web of Science ®Google Scholar
• Faessel, M., C. Delisée, F. Bos, and P. Castéra. 2005. 3D Modelling of random cellulosic fibrous networks based on X-ray tomography and image analysis. Composites Science and Technology 65 (13):1931–40. doi:10.1016/j.compscitech.2004.12.038.
   Web of Science ®Google Scholar
• Guillen, G. R., Y. Pan, M. Li, and E. M. V. Hoek. 2011. Preparation and characterization of membranes formed by nonsolvent induced phase separation: A review. Industrial and Engineering Chemistry Research 50 (7):3798–817. doi:10.1021/ie101928r.
   Web of Science ®Google Scholar
• Jaganathan, S., H. V. Tafreshi, and B. Pourdeyhimi. 2008. A realistic approach for modeling permeability of fibrous media: 3-D imaging coupled with CFD simulation. Chemical Engineering Science 63 (1):244–52. doi:10.1016/j.ces.2007.09.020.
   Web of Science ®Google Scholar
• Jin, M. Z., C. Q. Chen, and T. J. Lu. 2013. The mechanical behavior of porous metal fiber sintered sheets. Journal of the Mechanics and Physics of Solids 61 (1):161–74. doi:10.1016/j.jmps.2012.08.006.
   Web of Science ®Google Scholar
• Joffre, T., P. Isaksson, P. J. J. Dumont, S. Rolland du Roscoat, S. Sticko, L. Orgéas, and E. K. Gamstedt. 2016. A Method to measure moisture induced swelling properties of a single wood cell. Experimental Mechanics 56 (5):723–733. doi:10.1007/s11340-015-0119-9.
   Google Scholar
• Kulachenko, A., and T. Uesaka. 2012. Direct simulations of fiber network deformation and failure. Mechanics of Materials 51:1–14. doi:10.1016/j.mechmat.2012.03.010.
   Web of Science ®Google Scholar
• Lee, H. K., S. Simunović, and D. K. Shin. 2004. A computational approach for prediction of the damage evolution and crushing behavior of chopped random fiber composites. Computational Materials Science 29 (4):459–74. doi:10.1016/j.commatsci.2003.12.008.
   Web of Science ®Google Scholar
• Li, A., G. Shao, T. Yu, J. Su, and S.-Y. Ding. 2015. Mesoscopic numerical simulation of stratified rock failure using digital image processing. Advances in Mechanical Engineering 6. doi:10.1155/2014/106073.
   Web of Science ®Google Scholar
• Li, J., S. Li, G. Gu, H. Li, Q. Liu, Z. Fan, H. Chen, X. Han, Y. Zhao, and P. Zhang. 2016. A novel method based on digital image processing technique and finite element method for rapidly modeling optical properties of actual microstructured optical fibers. IEEE Photonics Journal 8 (6):1–14. doi:10.1109/jphot.2016.2614780.
   Web of Science ®Google Scholar
• Liu, Q., Z. X. Lu, Z. J. Hu, and J. N. Li. 2013. Finite element analysis on tensile behaviour of 3D random fibrous materials: Model description and meso-level approach. Materials Science and Engineering a-Structural Materials Properties Microstructure and Processing 587:36–45. doi:10.1016/j.msea.2013.07.087.
   Web of Science ®Google Scholar
• Liu, Y., X. Zhou, Z. You, S. Yao, F. Gong, and H. Wang. 2017. Discrete element modeling of realistic particle shapes in stone-based mixtures through MATLAB-based imaging process. Construction and Building Materials 143:169–78. doi:10.1016/j.conbuildmat.2017.03.037.
   Web of Science ®Google Scholar
• Marulier, C., P. J. J. Dumont, L. Orgéas, S. R. Roscoat, and D. Caillerie. 2015. 3D analysis of paper microstructures at the scale of fibres and bonds. Cellulose 22 (3):1517–39. doi:10.1007/s10570-015-0610-6.
   Web of Science ®Google Scholar
• Mott, L., L. Groom, and S. Shaler. 2002. Mechanical properties of individual southern pine fibers. Part II. Comparison of earlywood and latewood fibers with respect to tree height and juvenility. Wood and Fiber Science 34 (2):221–237.
   Google Scholar
• Peyrega, C., D. Jeulin, C. Delisee, and J. Malvestio. 2009. 3D morphological modelling of a random fibrous network. Image Analysis & Stereology 28 (3):129–141.
   Google Scholar
• Ridruejo, A., C. González, and J. Llorca. 2010. Damage micromechanisms and notch sensitivity of glass-fiber non-woven felts: An experimental and numerical study. Journal of the Mechanics & Physics of Solids 58 (10):1628–45. doi:10.1016/j.jmps.2010.07.005.
   Web of Science ®Google Scholar
• Tan, X., H. Konietzky, and W. Chen. 2016. Numerical simulation of heterogeneous rock using discrete element model based on digital image processing. Rock Mechanics and Rock Engineering 49 (12):4957–64. doi:10.1007/s00603-016-1030-0.
   Web of Science ®Google Scholar
• Wang, S., W. Xu, C. Shi, and Q. Zhang. 2014. Numerical simulation of direct shear tests on mechanical properties of talus deposits based on self-adaptive PCNN digital image processing. Journal of Central South University 21 (7):2904–14. doi:10.1007/s11771-014-2256-1.
   Web of Science ®Google Scholar
• Xu, H., M. Zhu, J. Marcicki, and X. G. Yang. 2017. Mechanical modeling of battery separator based on microstructure image analysis and stochastic characterization. Journal of Power Sources 345:137–45. doi:10.1016/j.jpowsour.2017.02.002.
   Web of Science ®Google Scholar
• Xu, Y., H. Li, S. Li, X. Guan, and C. Lan. 2016. 3-D modelling and statistical properties of surface pits of corroded wire based on image processing technique. Corrosion Science 111:275–87. doi:10.1016/j.corsci.2016.05.015.
   Web of Science ®Google Scholar
• Yue, Z. Q., S. Chen, and L. G. Tham. 2003. Finite element modeling of geomaterials using digital image processing. Computers and Geotechnics 30 (5):375–97. doi:10.1016/s0266-352x(03)00015-6.
   Web of Science ®Google Scholar
• Zhang, L., Z. Ren, and Q. Lu. 2016. Simulation of mesofracture process of asphalt mixture using digital image processing and extended finite-element method. Journal of Testing & Evaluation 45 (1):20160143. doi:10.1520/JTE20160143.
   Web of Science ®Google Scholar
• Zhang, Y., Z. X. Lu, Z. Y. Yang, D. H. Zhang, J. J. Shi, Z. S. Yuan, and Q. Liu. 2017. Compression behaviors of carbon-bonded carbon fiber composites: Experimental and numerical investigations. Carbon 116:398–408. doi:10.1016/j.carbon.2017.02.012.
   Web of Science ®Google Scholar