Publications by authors named "Tushar Gulati"

Introduction: Personal protective equipment (PPE) inhibits heat dissipation and elevates heat strain. Impaired cooling with PPE warrants investigation into practical strategies to improve work capacity and mitigate exertional heat illness.

Purpose: Examine physiological and subjective effects of forearm immersion (FC), fan mist (MC), and passive cooling (PC) following three intermittent treadmill bouts while wearing PPE.

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In this study, we extended our previously developed anatomically detailed three-dimensional (3-D) thermoregulatory virtual human model for predicting heat stress to allow for predictions of heat and cold stress in one unified model. Starting with the modified Pennes bioheat transfer equation to estimate the spatiotemporal temperature distribution within the body as the underlying modeling structure, we developed a new formulation to characterize the spatial variation of blood temperature between body elements and within the limbs. We also implemented the means to represent heat generated from shivering and skin blood flow that apply to air exposure and water immersion.

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Objective: This study aimed at assessing the risks associated with human exposure to heat-stress conditions by predicting organ- and tissue-level heat-stress responses under different exertional activities, environmental conditions, and clothing.

Methods: In this study, we developed an anatomically detailed three-dimensional thermoregulatory finite element model of a 50th percentile U.S.

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Moisture transport in a food system involving two different materials of unequal moisture content was modeled with water activity as the driving force using a porous media framework. This model was applied to a bread-barbecue chicken pocket sandwich stored in isothermal conditions. The model successfully predicted the equilibrium condition, where the two materials, bread and chicken, reached the same water activity, but not the same water content.

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Macroscopic deformable multiphase porous media models have been successful in describing many complex food processes. However, the properties needed for such detailed physics-based models are scarce and consist of primarily empirical models obtained from experiment. Likewise, driving forces such as swelling pressure have also been approached empirically, without physics-based explanations or prediction capabilities.

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