The effect of constitutive modelling of material behavior on the predictive abilities of two models of flat rolling is studied. Comparison of calculated roll forces and powers to those measured on a commerical steel mill indicates that the Orowan model is sufficiently accurate when supplied with carefully determined flow strength data. The manner of representation of that data is found to be significant. The results show that a multidimensional databank, which stores values of strength for specific strains, rates of strain and temperatures is very useful in modelling the process.
Neuropathy is a nerve-damaging disease that causes those affected to lose feeling in their otherwise functional limbs. It can cause permanent numbing to the peripheral limb of a patient such as a hand or foot. In this report, we present a real-time visualization aid for grasp realization that can be used by patients experiencing numbness of the limb. This wearable electronic device was developed on an open-source microcontroller-based platform. This is a very simple and inexpensive solution. It is referred to as a NeuroGlove, and it provides patients with a visual light scale to allow them to understand the strength of the grasp they have on any object. A soft tactile sensor was additively manufactured by utilizing a multi-material direct-print system. The sensor consists of an ionic liquid-based pressure-sensitive membrane, stretchable electrodes, and insulation membranes. The printed flexible polymeric sensor was evaluated under varying forces. Next, the fabricated sensor was integrated with a microcontroller board where it was programmed to respond in a light scale according to the applied force on the sensor. Finally, the sensor-microcontroller system was installed on a glove to demonstrate a wearable visual aid for neuropathy patients. Additive manufacturing offers the ability for customization in a design, material, and geometry that could potentially lead to printing sensors on prosthetic or robotic hands.
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