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Computational models are an important tool in understanding the underlying biomechanics of TBI but are highly dependent on the mechanical properties of soft tissue to produce accurate results. Reported material properties of brain tissue can vary by several orders of magnitude between studies, and no published set of material parameters exists for porcine brain tissue at strain rates relevant to blast. In this work, brain tissue from the brainstem, cerebellum, and cerebrum of freshly euthanized adolescent male G\u00f6ttingen minipigs was tested in simple shear and unconfined compression at strain rates ranging from quasi-static (QS) to 300\u2009s\u22121. Brain tissue showed significant strain rate stiffening in both shear and compression. Minimal differences were seen between different regions of the brain. Both hyperelastic and hyper-viscoelastic constitutive models were fit to experimental stress, considering data from either a single loading mode (unidirectional) or two loading modes together (bidirectional). The unidirectional hyper-viscoelastic models with an Ogden hyperelastic representation and a one-term Prony series best captured the response of brain tissue in all regions and rates. The bidirectional models were generally able to capture the response of the tissue in high-rate shear and all compression modes, but not the QS shear. Our constitutive models describe the first set of material parameters for porcine brain tissue relevant to loading modes and rates seen in blast injury.<\/jats:p>","DOI":"10.1115\/1.4056480","type":"journal-article","created":{"date-parts":[[2022,12,16]],"date-time":"2022-12-16T14:45:50Z","timestamp":1671201950000},"update-policy":"https:\/\/doi.org\/10.1115\/crossmarkpolicy-asme","source":"Crossref","is-referenced-by-count":16,"title":["Rate- and Region-Dependent Mechanical Properties of G\u00f6ttingen Minipig Brain Tissue in Simple Shear and Unconfined Compression"],"prefix":"10.1115","volume":"145","author":[{"given":"Gregory M.","family":"Boiczyk","sequence":"first","affiliation":[{"name":"Department of Biomedical Engineering, The University of Utah , 36 S. 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