Student Profile: Vivien Yeung


Vivien Yeung

University of Wollongong

Biography

Vivien is a second-year student currently completing a Bachelor of Mathematics at University of Wollongong, with the intent to pursue Honours in 2020. Her research interests and experience are in mathematical modelling, particularly mathematical biology, though she is always looking to diversify her modelling experience and be exposed to as many
fields as possible. For her, the most incredible part about modelling is in how real-world phenomena can be represented and predicted mathematically; at times with startling
accuracy, even with relatively simple models. Modelling the baking of cake over the summer is a unique opportunity to become involved in the fascinating field of food engineering, and she is excited to develop new-found interest in this area.

Baking Cake: A Mathematical Model

Bread and bakery products have a worldwide revenue of US$272 billion. Baking involves several energy intensive processes, one of which is the heat and mass transfer of water.
When a cake bakes in the oven, its surface progressively dries, causing water and other species (e.g. CO2 produced by microorganisms everywhere in the product) to migrate from the wet core of the cake batter to the surface. By reducing final water content, the baker can reduce costs and ensure that produced goods are safe and desirable to the consumer.

The reaction engineering approach (REA) [1] is a simple yet effective drying model for heat/mass transfer of water. It captures the major physics of drying yet is relatively simple
in mathematical formulation, requiring a limited number of experiments to generate its parameters. On the other hand, existing empirical models fail to capture the major physics
of drying, and mechanistic models require too much data (due to too many parameters) for practical use in industry.

I aim to investigate the application of this emerging engineering approach to baking cake and its mathematical foundations. I also aim to analyse the derivation of model parameters from data and the effect of parameter uncertainty on predicted outcomes.

[1] Chen, X.D & Putranto, A., (2013). Modelling Drying Processes: A reaction engineering approach, Cambridge University Press, Cambridge.

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