2015
DOI: 10.1142/s0219519415500591
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The Mandible Remodeling Induced by Dental Implants: A Meshless Approach

Abstract: This work aims to evaluate the prediction efficiency of a recently developed numerical approach in the mandible bone tissue remodeling process. The remodeling algorithm, seeking the minimization of the strain energy density, includes a phenomenological anisotropic material law capable of predicting the bone tissue mechanical properties based on the bone apparent density. The key factor of the proposed numerical approach is the inclusion of a flexible and efficient meshless method, which is used to obtain the s… Show more

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Cited by 19 publications
(4 citation statements)
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“…They too could be simplified using variable order derivatives. • Mechanical solicitations also affect bone remodelling [2,3].…”
Section: Discussionmentioning
confidence: 99%
“…They too could be simplified using variable order derivatives. • Mechanical solicitations also affect bone remodelling [2,3].…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, Belinha et al [144][145][146] predicted bone density distributions on the mandible and maxillary bones as a result of the presence of dental implants, by means of a topology optimization model built on the deformation energy method using Carter's remodeling algorithm [147] within the NNRPIM meshless technique framework. Also, using the NNRPIM meshless method, Duarte et al [148,149] studied a prosthetic system consisting of two implants connected with a bar using a 2D linear elastic stress-strain model.…”
Section: Bone Remodeling and Dental Studiesmentioning
confidence: 99%
“…The NNRPIM was successfully extended to the non-linear analysis considering large deformations and elastoplasticity [24,25], to the dynamic analysis [26][27][28], to the analysis of laminated shell-like structures [29,30] and to the analysis of functionally graded plates [31]. Additionally, it is possible to find in the literature demanding non-linear biomechanical applications using the NNRPIM [17,[32][33][34][35].…”
Section: Introductionmentioning
confidence: 99%