Josh graduated in the summer of 2023 with a first-class MComp degree in Computer Science from the University of Leicester. The degree focused on algorithmic design, creating customer-facing software, and managing large teams in an agile-like environment. For their Bachelor's and Master's year projects, they used large data sets from external sources and transformed those into a format that could be interacted with by the public, considering access to varying demographics. Project themes ranged from supermarket price comparisons, collecting and collating census data, and tracking and suggesting Lego kits to build.
Josh's primary motivation for joining the AAPS community was to meet with like-minded individuals to help bring a change and pursue his passion for easing the barriers between the public and viable alternatives to driving - through modern technologies.
Transportation is in transition, with new technologies such as electric vehicles, fuel cells, and hydrogen. But, for example with battery electric vehicles, the case for their environmental benefits rests on a bet -- that the negative impacts associated with producing the vehicles are outweighed by the benefits of reduced future impacts when the vehicles are driven. The negative impacts are relatively certain since they are happening now or in the near future. On the other hand, there is much greater uncertainty about the future benefits, since they are expected over the coming decade(s). Given the long time-scales involved, how should engineers be making decisions now about what technologies to develop and deploy?
One approach to answering this question is to use Life Cycle Assessment (LCA), but in its basic form this is based on historic data, which can be a poor representation of the future. An improved answer comes through the application of "Prospective LCA", which deals with the fact that, for example, the impacts of end-of-life recycling of batteries may be different in 20 years' time than it would be if it happened today, due to increased renewable energy supply in the future. But this still assumes that the vehicle will be used as intended over its lifetime, and successfully recycled in the expected way. This greater uncertainty in future benefits and impacts is not currently modelled in LCA of vehicles, making it difficult to know how much trust to place in the results during the design and decision-making process.
In this project Josh will build on current cutting-edge prospective LCA to improve the treatment of future uncertainty within these models, and apply this to design choices within future vehicles. Engagement with an industrial partner would allow the value of different ways of assessing and presenting future uncertainty to be evaluated, and linked to specific engineering decisions. Josh will gain experience of the theory of industrial ecology and life cycle assessment, and uncertainty and sensitivity analysis, set against the wider context of sustainable transport and the future of battery electric vehicles in particular. Practically, you will work with tools such as Python and Brightway2 to implement LCA calculations, Monte Carlo uncertainty simulations, and sensitivity analysis.
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