RT Journal Article
T1 A multiscale data-driven approach for bone tissue biomechanics
A1 Mora Macías, Juan
A1 Ayensa Jiménez, Jacobo
A1 Reina-Romo, Esther
A1 Doweidar, Mohamed H.
A1 Domínguez, Jaime
A1 Doblaré Castellano  Manuel, 
A1 Sanz Herrera, José Antonio
AB The data-driven methodology with application to continuum mechanicsrelies upon two main pillars: (i) experimental characterization of stress-strainpairs associated to di erent loading states, and (ii) numerical elaborationof the elasticity equations as an optimization (searching) algorithm usingcompatibility and equilibrium as constraints. The purpose of this work isto implement a multiscale data-driven approach using experimental data ofcortical bone tissue at di erent scales. First, horse cortical bone samples arebiaxially loaded and the strain  elds are recorded over a region of interestusing a digital image correlation technique. As a result, both microscopicstrain  elds and macroscopic strain states are obtained by a homogenizationprocedure, associated to macroscopic stress loading states which are considereduniform along the sample. This experimental outcome is here referred asa multiscale dataset. Second, the proposed multiscale data-driven methodologyis implemented and analyzed in an example of application. Results arepresented both in the macroscopic and microscopic scales, with the latterconsidered just as a post-process step in the formulation. The macroscopicresults show non-smooth strain and stress patterns as a consequence of thetissue heterogeneity which suggest that a preassumed linear homogeneous orthotropicmodel may be inaccurate for bone tissue. Microscopic results show uctuating strain  elds {as a consequence of the interaction and evolutionof the microconstituents{ an order of magnitude higher than the averagedmacroscopic solution, which evidences the need of a multiscale approach forthe mechanical analysis of cortical bone, since the driving force of manybiological bone processes is local at the microstructural level. Finally, theproposed multiscale data-driven technique may also be an adequate strategyfor the solution of intractable large size multiscale FE2 computationalapproaches since the solution at the microscale is obtained as a postprocessing.As a main conclusion, the proposed multiscale data-driven methodologyis a useful alternative to overcome limitations in the continuum mechanicalstudy of the bone tissue. This methodology may also be considered as a usefulstrategy for the analysis of additional biological or technological hierarchicalmultiscale materials.
SN 0045-7825
SN 1879-2138 (electrónico)
YR 2020
FD 2020-06
LK https://hdl.handle.net/10272/23092
UL https://hdl.handle.net/10272/23092
LA eng
NO Mora-Macías, J., Ayensa-Jiménez, J., Reina-Romo, E., Doweidar, M. H., Domínguez, J., Doblaré, M., & Sanz-Herrera, J. A. (2020). A multiscale data-driven approach for bone tissue biomechanics. In Computer Methods in Applied Mechanics and Engineering (Vol. 368, p. 113136). Elsevier BV. https://doi.org/10.1016/j.cma.2020.113136
NO The authors gratefully acknowledge the support of Ministerio de Economía y Competitividad del Gobierno España, Spain through the grants DPI2014-58233-P, DPI2017-82501-P, and PGC2018-097257-B-C31; as well as Consejería de Economía y Conocimiento de la Junta de Andalucía, Spain (US-1261691, FEDER, UE).
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026