- Research Program Mentor
PhD Doctor of Philosophy
Mechanical Engineering, Statics, Dynamics, 3D Printing, Materials Science
Predicting structure from chaos in additive manufacturing
There is great interest in increasing the number of materials which can be used for additive manufacturing (AM). Unfortunately, it is difficult and expensive to develop and test new materials, especially without the proper equipment. This project aims to develop a simple approach to predict if a material will or will not work for AM. In this project, you will use simple machine learning algorithms to predict if a certain material will work in AM. The algorithms will be tested experimentally by the project mentor. This project will also introduce students to concepts of scale-invariance and fractal surfaces.
Design for additive manufacturing
In this project, you will design a part in CAD in a traditional sense (i.e. the part could be manufactured by traditional methods, like machining). Then, you will create design constraints (e.g. the part needs to hold a certain amount of weight), and use a generative design tool like Autodesk Fusion 360 to optimize the part. The intent of this project is to hint at the future of engineering design, with inputs from both humans and machine learning algorithms.
Engineering the perfect sauna
There is a growing body of literature which suggests hot and cold therapy (i.e. sauna and ice baths) are beneficial. The problem is that there one cannot avoid the 2nd law of thermodynamics, so although these therapies are beneficial to humans, they are less beneficial to our environment. In this theoretical project, you will design the world's most energy efficient hot/cold therapy device for home use. This project will introduce, or reinforce, concepts of thermodynamics, engineering design, and sustainable materials. This project will also introduce the concept of engineering (or computational) optimization, and students will become familiar with optimization techniques such as Genetic Algorithms (GA).