Sangam: A Confluence of Knowledge Streams

The Influence of the Specimen Shape and Loading Conditions on the Parameter Identification of a Viscoelastic Brain Model

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dc.creator Untaroiu, Costin D.
dc.date 2014-06-12T13:28:56Z
dc.date 2014-06-12T13:28:56Z
dc.date 2013
dc.date 2014-06-11
dc.date.accessioned 2023-03-01T18:54:32Z
dc.date.available 2023-03-01T18:54:32Z
dc.identifier Costin D. Untaroiu, "The Influence of the Specimen Shape and Loading Conditions on the Parameter Identification of a Viscoelastic Brain Model," Computational and Mathematical Methods in Medicine, vol. 2013, Article ID 460413, 7 pages, 2013. doi:10.1155/2013/460413
dc.identifier 1748-670X
dc.identifier http://hdl.handle.net/10919/48911
dc.identifier http://www.hindawi.com/journals/cmmm/2013/460413/cta/
dc.identifier https://doi.org/10.1155/2013/460413
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/281839
dc.description The mechanical properties of brain under various loadings have been reported in the literature over the past 50 years. Step-and-hold tests have often been employed to characterize viscoelastic and nonlinear behavior of brain under high-rate shear deformation; however, the identification of brain material parameters is typically performed by neglecting the initial strain ramp and/or by assuming a uniform strain distribution in the brain samples. Using finite element (FE) simulations of shear tests, this study shows that these simplifications have a significant effect on the identified material properties in the case of cylindrical human brain specimens. Material models optimized using only the stress relaxation curve under predict the shear force during the strain ramp, mainly due to lower values of their instantaneous shear moduli. Similarly, material models optimized using an analytical approach, which assumes a uniform strain distribution, under predict peak shear forces in FE simulations. Reducing the specimen height showed to improve the model prediction, but no improvements were observed for cubic samples with heights similar to cylindrical samples. Models optimized using FE simulations show the closest response to the test data, so a FE-based optimization approach is recommended in future parameter identification studies of brain.
dc.description Virginia Tech's Open Access Subvention Fund
dc.description Published version
dc.format application/pdf
dc.format application/pdf
dc.language en
dc.publisher Hindawi Publishing Corporation
dc.rights Creative Commons Attribution 3.0 Unported
dc.rights http://creativecommons.org/licenses/by/3.0/
dc.rights Copyright © 2013 Costin D. Untaroiu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dc.subject finite-element model
dc.subject pedestrian protection
dc.subject shear deformation
dc.subject tissue
dc.subject injury
dc.subject compression
dc.subject mathematical & computational biology
dc.title The Influence of the Specimen Shape and Loading Conditions on the Parameter Identification of a Viscoelastic Brain Model
dc.title Computational and Mathematical Methods in Medicine
dc.type Article - Refereed
dc.type Text


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