@inproceedings{RuessVarduhnRanketal.2012, author = {Ruess, Martin and Varduhn, Vasco and Rank, Ernst and Yosibash, Zohar}, title = {A Parallel High-Order Fictitious Domain Approach for Biomechanical Applications}, series = {11th International Symposium on Parallel and Distributed Computing (ISPDC), 2012 : 25 - 29 June 2012, Munich, Germany ; proceedings}, booktitle = {11th International Symposium on Parallel and Distributed Computing (ISPDC), 2012 : 25 - 29 June 2012, Munich, Germany ; proceedings}, editor = {Bader, Michael}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-4673-2599-8}, doi = {10.1109/ISPDC.2012.45}, pages = {279 -- 285}, year = {2012}, language = {en} } @article{RuessTalTrabelsietal.2012, author = {Ruess, Martin and Tal, David and Trabelsi, Nir and Yosibash, Zohar and Rank, Ernst}, title = {The finite cell method for bone simulations: verification and validation}, series = {Biomechanics and modeling in mechanobiology}, volume = {11}, journal = {Biomechanics and modeling in mechanobiology}, number = {3-4}, publisher = {Springer}, organization = {Springer}, issn = {1617-7940}, doi = {10.1007/s10237-011-0322-2}, pages = {425 -- 437}, year = {2012}, language = {en} } @article{WilleRuessRanketal.2016, author = {Wille, Hagen and Ruess, Martin and Rank, Ernst and Yosibash, Zohar}, title = {Uncertainty quantification for personalized analyses of human proximal femurs}, series = {Journal of Biomechanics}, volume = {49}, journal = {Journal of Biomechanics}, number = {4}, publisher = {Elsevier}, issn = {0021-9290}, doi = {10.1016/j.jbiomech.2015.11.013}, pages = {520 -- 527}, year = {2016}, abstract = {Computational models for the personalized analysis of human femurs contain uncertainties in bone material properties and loads, which affect the simulation results. To quantify the influence we developed a probabilistic framework based on polynomial chaos (PC) that propagates stochastic input variables through any computational model. We considered a stochastic E-ρ relationship and a stochastic hip contact force, representing realistic variability of experimental data. Their influence on the prediction of principal strains (ϵ1 and ϵ3) was quantified for one human proximal femur, including sensitivity and reliability analysis. Large variabilities in the principal strain predictions were found in the cortical shell of the femoral neck, with coefficients of variation of ≈40\%. Between 60 and 80\% of the variance in ϵ1 and ϵ3 are attributable to the uncertainty in the E-ρ relationship, while ≈10\% are caused by the load magnitude and 5-30\% by the load direction. Principal strain directions were unaffected by material and loading uncertainties. The antero-superior and medial inferior sides of the neck exhibited the largest probabilities for tensile and compression failure, however all were very small (pf<0.001). In summary, uncertainty quantification with PC has been demonstrated to efficiently and accurately describe the influence of very different stochastic inputs, which increases the credibility and explanatory power of personalized analyses of human proximal femurs.}, language = {en} } @article{NguyenStoterBaumetal.2017, author = {Nguyen, Lam H. and Stoter, Stein K.F. and Baum, Thomas and Kirschke, Jan and Ruess, Martin and Yosibash, Zohar and Schillinger, Dominik}, title = {Phase-field boundary conditions for the voxel finite cell method: Surface-free stress analysis of CT-based bone structures}, series = {International Journal for Numerical Methods in Biomedical Engineering}, volume = {33}, journal = {International Journal for Numerical Methods in Biomedical Engineering}, number = {12}, publisher = {Wiley}, issn = {2040-7947}, doi = {10.1002/cnm.2880}, year = {2017}, language = {en} }