1.74 million people are affected by Traumatic Brain Injury (TBI) in the United States annually, which emphasizes the necessity to reliably measure and predict the material behavior of the brain in response to a variety of mechanical loading scenarios. Computational head models are widely utilized to simulate and predict the response to varying head insults, and while they maintain considerable anatomical accuracy, their ability to make accurate predictions is limited by exiguous or equivocal constitutive properties. That is, a more complete understanding of the uninjured tissue response at physiological rates is essential to improve the predictive capability of these head models. Considerable scrutiny has been afforded to determine low and quasi-static strain rate behavior, and whilst not in full agreement, promising results, methodologies, and reviews are available. High and ultra-high strain rate material behavior, however, has remained elusive; largely due to the high compliance of soft materials that renders many existing high-rate characterization techniques difficult or ineffectual to employ. The equivocacy of high-rate properties crucially limits the predictive capability of these head models, specifically toward blast, high-velocity impact, and directed energy insults, thus motivating the acquisition of constitutive properties for brain tissue at rates greater than 103 1/s. To address this, we employ Thin-Layer Inertial Microcavitation Rheology, a new variation of Inertial Microcavitation Rheology (IMR), a rheological method capable of characterizing the behavior of compliant, soft materials under high-rate loading conditions (>103 1/s). Thin-layer IMR provides similar characterization capability to its predecessor, while accommodating the geometric constraints present when considering opaque materials. Here, the high-rate behavior of five distinct anatomical regions within the porcine brain are characterized using thin-layer IMR.
2025-04-09 09:00:00
