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dc.contributor.authorHe, Ge
dc.contributor.authorFan, Lei
dc.contributor.authorLiu, Yucheng
dc.date.accessioned2022-05-08T09:44:09Z
dc.date.available2022-05-08T09:44:09Z
dc.date.copyright2/15/2022 12:00:00 AM
dc.date.issued2022
dc.identifier.issn0148-0731
dc.identifier.otherbio_144_07_071005.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285518
dc.description.abstractTwo-dimensional mesoscale finite element analysis (FEA) of a multilayered brain tissue was performed to calculate the damage-related average stress triaxiality and local maximum von Mises strain in the brain. The FEA was integrated with rate-dependent hyperelastic and internal state variable (ISV) models, respectively, describing the behaviors of wet and dry brain tissues. Using the finite element results, a statistical method of design of experiments (DOE) was utilized to independently screen the relative influences of seven parameters related to brain morphology (sulcal width/depth, gray matter (GM) thickness, cerebrospinal fluid (CSF) thickness and brain lobe) and loading/environment conditions (strain rate and humidity) with respect to the potential damage growth/coalescence in the brain tissue. The results of the parametric study illustrated that the GM thickness and humidity were the two most crucial parameters affecting average stress triaxiality. For the local maximum von Mises strain at the depth of brain sulci, the brain lobe/region was the most influential factor. The conclusion of this investigation gives insight for the future development and refinement of a macroscale brain damage model incorporating information from lower length scale.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleMesoscale Simulation-Based Parametric Study of Damage Potential in Brain Tissue Using Hyperelastic and Internal State Variable Models
dc.typeJournal Paper
dc.journal.volume144
dc.journal.issue7
dc.journal.titleJournal of Biomechanical Engineering
dc.identifier.doi10.1115/1.4053205
dc.journal.fristpage71005-1
dc.journal.lastpage71005-9
dc.page9
dc.treeJournal of Biomechanical Engineering:;2022:;volume( 144 ):;issue: 007
dc.contenttypeFulltext


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