Ph.D., Mechanical Engineering, Mississippi State University, 2011.
The Centers for Disease Control (CDC) estimates that at least 5.3 million Americans live with significant disabilities as a result of traumatic brain injury (TBI). Not only are transportation collisions devastating to our society, but battlefield trauma and sports injuries are debilitating as well. Congressional reports indicate that military personnel have suffered nearly 179,000 TBI injuries due to explosive weaponry and vehicle crashes in Iraq and Afghanistan since 2000 (through March 2010). In sports, despite required use of helmets, more than 300,000 TBIs occur each year in the United States. Meanwhile, efforts to design of current structural systems intended for human use and protection, such as transportation vehicles and helmets, typically include only dummies, not actual humans, as a pertinent metric for predicting human response and product effectiveness. Furthermore, the injury metrics for dummies are force and acceleration, while real injuries in human are fracture, internal tissue damage, and rupture. This initiative is intended to overcome that shortfall with high fidelity models of the human body, coupled with other leveraged computational and experimental research programs, for multiple applications in research areas such as car crash injury and protection, optimized military vehicular design and sports and medical applications.
The constitutive (material) model (MSU TP Ver. 1.1)1,2 from our preliminary work captures both the instantaneous and long-term steady-state processes during tissue deformation and could admit tissue microstructural features within the Internal State Variables (ISVs). With the microstructural features, we can use our ISV model so that history effects could be captured and predicted. Certainly other constitutive models could be used to capture the mechanical behavior of the brain. But under multiple stress-state boundary conditions they do not typically address the stress strain behavioral differences between tension, compression, and torsion, which could be substantial. Our ISV constitutive model can be applied to more general boundary conditions and multiaxial stress states with the brain, which is relevant to football helmet-to-helmets hits, motorsports and battlefield head injuries. With this in mind, our brain mechanical model, based on MSU TP framework, is more innovative and relevant to accurately capturing the history effects and tissue damage of the brain under diverse ISs, and thus can better the performance of head protective gears when used in simulation-based design.
The current work presents the uncertainty analysis and its results of the Mississippi Irrigation Scheduling Tool (MIST) model, showing the margin of error (uncertainty) of the irrigation advice obtained through the web-based application. The basis for the verification and validation of the model is also given. The MIST calculates the daily soil water balance in a crop field from daily weather measurements, irrigation, and rainfall, taking into account crop type, planting date, soil type, tillage, and other field-specific information. The MIST water balance calculations were validated using the local weather data that consisted of a few days of rain, and significant changes in the solar radiation, relative humidity and wind speed. The final water balance results showed values within acceptable ranges and comparable to in situ measurements of soil moisture. The final relative uncertainty in the water balance value was around 9%, which is in the normal range of the margin of error. The current MIST web-based application and uncertainty quantification have been preliminarily verified and validated.
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