An inverse procedure for characterization of material parameters of passive skeletal muscle using FEM and experimental data
More details
Hide details
School of Mechanical Engineering, Hebei University of Technology, Tianjin, China
Department of Aerospace Engineering and Engineering Mechanics, University of Cincinnati, Cincinnati, USA
Submission date: 2019-04-14
Acceptance date: 2019-10-04
Online publication date: 2020-01-15
Publication date: 2020-01-15
Journal of Theoretical and Applied Mechanics 2020;58(1):247-259
This work develops an inverse procedure which combines an improved niche genetic algorithm, finite element models and experimental data to identify material parameters of biological tissues behaving like hyperelastic materials. A novel objective function is proposed with two coefficients, which controls the contributions in a well-balanced fashion, respectively, for the small deformation stage and the large deformation stage. This allows us to obtain a global minimizer (of material constants) for the error between FEM solutions and experimental data. Moreover, simple uniaxial compression tests at two different angles (0◦ and 90◦) with respect to the muscle fiber orientation are performed on fresh muscle tissues. This enables us to obtain anisotropic properties of the muscle tissue from the present inverse procedure. The result shows that the proposed inverse procedure is stable and reliable to determine material constants in hyperelastic models for soft biological tissues like skeletal muscles considering anisotropy.
Böl M., Ehret A.E., Leichsenring K., Weichert C., Kruse R., 2014, On the anisotropy of skeletal muscle tissue under compression, Acta Biomaterialia, 10, 7, 3225-3234, DOI: 10.1016/j.actbio.2014.03.003.
Böl M., Kruse R., Ehret A.E., Leichsenring K., Siebert T., 2012, Compressive properties of passive skeletal muscle – The impact of precise sample geometry on parameter identification in inverse finite element analysis, Journal of Biomechanics, 45, 15, 2673-2679.
Chawla A., Mukherjee S., Karthikeyan B., 2009, Characterization of human passive muscles for impact loads using genetic algorithm and inverse finite element methods, Biomechanics and Modeling in Mechanobiology, 8, 1, 67-76.
Deng B., Tan K.B.C., Lu Y., Zaw K., Zhang J., Liu G.R., Geng J.P., 2009, Inverse identification of elastic modulus of dental implant-bone interfacial tissue using neural network and FEA model, Inverse Problems in Science and Engineering, 17, 8, 1073-1083, DOI: 10.1080/17415970903063151.
Du W.B., Ying W., Yan G., Zhu Y.B., Cao X.B., 2017, Heterogeneous Strategy Particle Swarm Optimization, IEEE Transactions on Circuits and Systems II Express Briefs, 64, 4, 467-471, DOI: 10.1109/TCSII.2016.2595597.
Freutel M., Galbusera F., Ignatius A., D¨urselen L., 2015,Material properties of individual menisci and their attachments obtained through inverse FE-analysis, Journal of Biomechanics, 48, 8, 1343-1349, DOI: 10.1016/j.jbiomech.2015.03.014.
Gasser T.C., Ogden R.W., Holzapfel G.A., 2006, Hyperelastic modelling of arterial layers with distributed collagen fibre orientations, Journal of the Royal Society Interface, 3, 6, 15-35.
Holzapfel G.A., Gasser T.C., Ogden R.W., 2000, A new constitutive framework for arterial wall mechanics and a comparative study of material models, Journal of Elasticity and the Physical Science of Solids, 61, 1-3, 1-48.
Im C.H., Kim H.K., Jung H.K., Choi K., 2004, A novel algorithm for multimodal function optimization based on evolution strategy, IEEE Transactions on Magnetics, 40, 2, 1224-1227, DOI: 10.1109/TMAG.2004.824805.
Ishak S.I., Liu G.R., Lim S.P., Shang H.M., 2001, Experimental study on employing flexural wave measurement to characterize delamination in beams, Experimental Mechanics, 41, 2, 157-164.
Li K.S., Yu X.L., Zhang W.S., Dong W.Y., 2013, Multimodal function optimization algorithm based on improved niche evolutionary algorithm, Journal of System Simulation, 13, 25, 6, 1170-1175.
Liu G.R., Han X., Lam K.Y., 2002a, A combined genetic algorithm and nonlinear least squares method for material characterization using elastic waves, Computer Methods in Applied Mechanics and Engineering, 191, 17, 1909-1921.
Liu G.R., Han X., Xu Y.G., Lam K.Y., 2001, Material characterization of functionally graded material by means of elastic waves and a progressive-learning neural network, Composites Science and Technology, 61, 10, 1401-1411, DOI: 10.1016/S0266-3538(01)00033-1.
Liu G.R., Lam K.Y., Han X., 2002b, Determination of elastic constants of anisotropic laminated plates using elastic waves and a progressive neural network, Journal of Sound and Vibration, 252, 2, 239-259.
Loocke M.V., Lyons C.G., Simms C.K., 2006, A validated model of passive muscle in compression, Journal of Biomechanics, 39, 16, 2999-3009.
Martins J.A.C., Pires E.B., Salvado R., Dinis P.B., 1998, A numerical model of passive and active behavior of skeletal muscles, Computer Methods in Applied Mechanics and Engineering, 151, 3-4, 419-433, DOI: 10.1016/S0045-7825(97)00162-X.
Mendes R., Kennedy J., Neves J., 2004, The fully informed particle swarm: simpler, maybe better, IEEE Transactions on Evolutionary Computation, 8, 3, 204-210.
Shabbir F., Omenzetter P., 2016, Model updating using genetic algorithms with sequential niche technique, Engineering Structures, 120, 166-182.
Silva E., Parente M., Brandăo S., Mascarenhas T., Natal J.R., 2019, Characterizing the biomechanical properties of the pubovisceralis muscle using a genetic algorithm and the finite element method, Journal of Biomechanical Engineering, 141, 1.
Silva M.E.T., Parente M.P.L., Brandˇao S., Mascarenhas T., 2018, Characterization of the passive and active material parameters of the pubovisceralis muscle using an inverse numerical method, Journal of Biomechanics, 71, DOI: 10.1016/j.jbiomech.2018.01.033.
Thierens D., 1999, Scalability Problems of Simple Genetic Algorithms, MIT Press
Yao R., Du L., Zhu L., Xiang Z., 2015, An inverse approach to identifying the in vivo material parameters of female pelvic floor muscles using MRI data, Science China Life Sciences, 58, 3, 305-308, DOI: 10.1007/s11427-014-4771-6.
Zhu F., Jin X., Guan F., Zhang L., 2010, Identifying the properties of ultra-soft materials using a new methodology of combined specimen-specific finite element model and optimization techniques, Materials and Design, 31, 10, 4704-4712, DOI: 10.1016/j.matdes.2010.05.023.
Journals System - logo
Scroll to top