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Understanding the Thermodynamics of Satellite Fuel Manufacturing from Wax, Using Computational Modelling and Lab Experiments


Term:

Spring

Department:

MAS: Media Arts and Sciences

Faculty Supervisor:

Prof Danielle Wood

Faculty email:

drwood@mit.edu

Apply by:

02/13/2020

Contact:

Daniel Erkel: derkel@mit.edu

Project Description

The Space Enabled Research Group advances justice in Earth’s complex systems using designs enabled by space. Space technology contributes to the United Nations’ Sustainable Development Goals via communication, earth observation, positioning, microgravity research, spinoffs and inspiration. Space Enabled uses five methods to apply space technology to development, including design, social science, complex systems, satellite engineering and data science. The project is part of a larger effort to understand the feasibility of in-space manufacturing of sustainable alternatives for hybrid satellite propellant made from candle- or beeswax. Tests using actual hardware have already been conducted. Under the supervision of a graduate researcher, the work of the UROP student would focus on all or parts of the following tasks: 1) Computational modelling of the fluid dynamics and heat transfer (melting and solidification) problem characterising the manufacturing process, as well as the modelling of the heat transfer phenomena occurring during various manufacturing scenarios. 2) Coding required for the set-up of the simulations and in post-processing the results. 3) Hand calculations aimed at the validation of heat transfer results obtained through simulation. 4) Correlation of simulation results with existing results from tests already conducted. 5) Lastly, the work could incorporate parts of consolidating reports.

Pre-requisites

We are looking for students with a technical background in mechanical and or aerospace engineering or computer science/data science. In addition to this technical background, we seek students with an interest in sustainable development. Prior research experience is preferred, experience in any form of computational modelling (FEA, CFD) and coding experience is desired.