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Issue title: Some highlights on fuzzy systems and data mining
Guest editors: Shilei Sun, Silviu Ionita, Eva Volná, Andrey Gavrilov and Feng Liu
Article type: Research Article
Authors: Wang, Monan* | Sun, Lei | Yang, Ning | Mao, Zhiyong
Affiliations: Mechanical & Power Engineering College, Harbin University of Science and Technology, Harbin, China
Correspondence: [*] Corresponding author. Monan Wang, Mechanical & Power Engineering College, Harbin University of Science and Technology, Harbin, China. Tel.: +86 451 86390530; Fax: +86 451 86390500; E-mail: qqwmnan@163.com.
Abstract: In this study, a fracture-healing model based on the mechanical environment and blood supply conditions was proposed to simulate and predict the complex regenerative repair process for tissues. A three-dimensional finite element model was established to describe fracture callus mechanics based on tetrahedral units. The blood perfusion was regarded as a spatio-temporal state variable and was included into the model to simulate a revascularization process. The dynamic model described the callus mechanics and biological processes of tissue differentiation by using a combination of a finite element method and fuzzy logic. The callus healing process was simulated time-discretely by an explicit Euler integration iterative loop over equidistant time steps and was implemented via Visual Studio 2012. Finally, the model predicted the value of interfragmentary of two groups with different axial stabilities. A comparison of the results with the experiment data indicated that the simulation results were distributed within the scope of the average deviation of the experimental data, and this corresponded well with the experiment trend and numerical value. The agreement between the simulation results and experimental results verified the accuracy of the fracture-healing model and demonstrated its advantages for simulating healing process.
Keywords: Fracture healing, three-dimensional model, fuzzy rules, tissue differentiation
DOI: 10.3233/JIFS-169180
Journal: Journal of Intelligent & Fuzzy Systems, vol. 31, no. 6, pp. 2959-2965, 2016
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