Professional Education


  • Doctor of Philosophy, Sharif University of Technology (2018)
  • Master of Science, Ferdowsi University of Mashad (2012)
  • Bachelor of Science, Ferdowsi University of Mashad (2010)

Stanford Advisors


All Publications


  • A three-dimensional micromechanical model of brain white matter with histology-informed probabilistic distribution of axonal fibers JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS Yousefsani, S., Farahmand, F., Shamloo, A. 2018; 88: 288–95

    Abstract

    This paper presents a three-dimensional micromechanical model of brain white matter tissue as a transversely isotropic soft composite described by the generalized Ogden hyperelastic model. The embedded element technique, with corrected stiffness redundancy in large deformations, was used for the embedment of a histology-informed probabilistic distribution of the axonal fibers in the extracellular matrix. The model was linked to a multi-objective, multi-parametric optimization algorithm, using the response surface methodology, for characterization of material properties of the axonal fibers and extracellular matrix in an inverse finite element analysis. The optimum hyperelastic characteristics of the tissue constituents, obtained based on the axonal and transverse direction test results of the corona radiata tissue samples, indicated that the axonal fibers were almost thirteen times stiffer than the extracellular matrix under large deformations. Simulation of the same tissue under a different loading condition, as well as that of another white matter tissue, i.e., the corpus callosum, in the axonal and transverse directions, using the optimized hyperelastic characteristics revealed tissue responses very close to those of the experiments. The results of the model at the sub-tissue level indicated that the stress concentrations were considerably large around the small axons, which might contribute into the brain injury.

    View details for DOI 10.1016/j.jmbbm.2018.08.042

    View details for Web of Science ID 000448090700031

    View details for PubMedID 30196184

  • Micromechanics of brain white matter tissue: A fiber-reinforced hyperelastic model using embedded element technique JOURNAL OF THE MECHANICAL BEHAVIOR OF BIOMEDICAL MATERIALS Yousefsani, S., Shamloo, A., Farahmand, F. 2018; 80: 194–202

    Abstract

    A transverse-plane hyperelastic micromechanical model of brain white matter tissue was developed using the embedded element technique (EET). The model consisted of a histology-informed probabilistic distribution of axonal fibers embedded within an extracellular matrix, both described using the generalized Ogden hyperelastic material model. A correcting method, based on the strain energy density function, was formulated to resolve the stiffness redundancy problem of the EET in large deformation regime. The model was then used to predict the homogenized tissue behavior and the associated localized responses of the axonal fibers under quasi-static, transverse, large deformations. Results indicated that with a sufficiently large representative volume element (RVE) and fine mesh, the statistically randomized microstructure implemented in the RVE exhibits directional independency in transverse plane, and the model predictions for the overall and local tissue responses, characterized by the normalized strain energy density and Cauchy and von Mises stresses, are independent from the modeling parameters. Comparison of the responses of the probabilistic model with that of a simple uniform RVE revealed that only the first one is capable of representing the localized behavior of the tissue constituents. The validity test of the model predictions for the corona radiata against experimental data from the literature indicated a very close agreement. In comparison with the conventional direct meshing method, the model provided almost the same results after correcting the stiffness redundancy, however, with much less computational cost and facilitated geometrical modeling, meshing, and boundary conditions imposing. It was concluded that the EET can be used effectively for detailed probabilistic micromechanical modeling of the white matter in order to provide more accurate predictions for the axonal responses, which are of great importance when simulating the brain trauma or tumor growth.

    View details for DOI 10.1016/j.jmbbm.2018.02.002

    View details for Web of Science ID 000428486800025

    View details for PubMedID 29428702

  • Edge effects in adhesively bonded composite joints integrated with piezoelectric patches COMPOSITE STRUCTURES Yousefsani, S. A., Tahani, M. 2018; 200: 187–94
  • A fresh insight into Kane's equations of motion ROBOTICA Pishkenari, H., Yousefsani, S. A., Gaskarimahalle, A. L., Oskouei, S. G. 2017; 35 (3): 498–510
  • Relief of edge effects in bi-adhesive composite joints COMPOSITES PART B-ENGINEERING Yousefsani, S. A., Tahani, M. 2017; 108: 153–63
  • On thermomechanical stress analysis of adhesively bonded composite joints in presence of an interfacial void COMPOSITE STRUCTURES Tahani, M., Yousefsani, S. A. 2015; 130: 116–23
  • An analytical investigation on thermomechanical stress analysis of adhesively bonded joints undergoing heat conduction ARCHIVE OF APPLIED MECHANICS Yousefsani, S., Tahani, M. 2014; 84 (1): 67–79