RT Journal Article
T1 Data-Driven Computational Simulation in Bone Mechanics
A1 Sanz Herrera, José A.
A1 Mora Macías, Juan
A1 Ayensa Jiménez, J.
A1 Doblaré, Manuel
AB The data-driven approach was formally introducedin the field of computational mechanics just a fewyears ago, but it has gained increasing interest and applicationas disruptive technology in many other fields of physicsand engineering. Although the fundamental bases of themethod have been already settled, there are still manychallenges to solve, which are often inherently linked to theproblem at hand. In this paper, the data-driven methodologyis applied to a particular problem in tissue biomechanics, acontext where this approach is particularly suitable due tothe difficulty in establishing accurate and general constitutivemodels, due to the intrinsic intra and inter-individualvariability of the microstructure and associated mechanicalproperties of biological tissues. The problem addressed herecorresponds to the characterization and mechanical simulationof a piece of cortical bone tissue. Cortical horse bonetissue was mechanically tested using a biaxial machine. Thedisplacement field was obtained by means of digital imagecorrelation and then transformed into strains by approximatingthe displacement derivatives in the bone virtualgeometric image. These results, together with the approximatedstress state, assumed as uniform in the small piecestested, were used as input in the flowchart of the data-drivenmethodology to solve several numerical examples, whichwere compared with the corresponding classical model-basedfitted solution. From these results, we conclude that the datadrivenmethodology is a useful tool to directly simulateproblems of biomechanical interest without the imposition(model-free) of complex spatial and individually-varyingconstitutive laws. The presented data-driven approach recoversthe natural spatial variation of the solution, resultingfrom the complex structure of bone tissue, i.e. heterogeneity,microstructural hierarchy and multifactorial architecture,making it possible to add the intrinsic stochasticity ofbiological tissues into the data set and into the numericalapproach.
PB Springer
SN 1573-9686
YR 2020
FD 2020-07
LK http://hdl.handle.net/10272/18905
UL http://hdl.handle.net/10272/18905
LA eng
NO Sanz Herrera, J. A., Mora Macías, J., Ayensa Jiménez, J. ... Doblaré, M. (2020). Data-Driven Computational Simulation in Bone Mechanics. Annals of Biomedical Engineering. DOI: https://doi.org/10.1007/s10439-020-02550-9
DS Repositorio Institucional de la Universidad de Huelva
RD 30 may 2026