2 July 2018 Showroom Cafe
Fossil fuels will not last forever and so we need to start looking for alternatives such as renewable energy, otherwise known as energy harvesting. To make the most of these renewable sources, we need to design energy harvesting devices to be as efficient as possible. Optimising the efficiency of a device requires us to describe its behaviour and rate its performance. This is complicated by the fact that energy harvesters are multi-physics systems, and the equations and language used to describe mechanical, thermal, electrical and chemical systems is inconsistent. In addition, the inputs are often random processes, which makes their exact behaviour impossible to predict. In this talk, we will examine these challenges, and how we can solve them.
Julian Gosliga, Uni of Sheffield
Biog:
An affinity for mathematics and physics, along with a taste for practicality, led Julian to study a mechanical engineering PhD in the field of dynamics. The allure of trying to find patterns in seemingly random systems resulted in a focus on statistical mechanics, specifically when applied to energy harvesting or more general multi-physics systems. His current work involves trying to generalise the description of systems using energy-based analogies, with the aim of finding limits on the maximum power that can be absorbed by an energy harvesting system.
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