Caltech Young Investigators Lecture
Abstract: The study of vehicles traveling at hypersonic speeds is extremely complex and involves many physical processes occurring over a broad range of time-scales. Advances in both computational chemistry and computational power have enabled the construction of extremely detailed models for chemical non-equilibrium effects based on ab initio quantum chemistry data, referred to as the State-to-State (StS) model. Unfortunately, due to the enormous cost of both computing data for and applying the StS model, it can only be applied to highly simplified test cases. This motivates the development of reduced order models for chemical non-equilibrium which can capture the same physics at a reduced computational cost. The model reduction framework presented, based on the maximum-entropy principle, provides a link between the ab initio quantum chemistry data and computational fluid dynamics. The objective of this work is twofold: first to present a model reduction framework for application to chemical non-equilibrium based on fundamental physics principles; and second, to use this framework to study thermochemical non-equilibrium in a variety of conditions for a gas composed of nitrogen molecules.
Bio: Robyn Macdonald received her B.S. in Aerospace Engineering from the University of Illinois at Urbana-Champaign in 2013, and will receive her PhD from UIUC in May 2019 under the guidance of Prof. Marco Panesi. She is currently a post-doctoral research fellow at the University of Minnesota working under Prof. Graham Candler. Her PhD researched focused on the development of quantum chemistry informed reduced order models for thermochemical non-equilibrium hypersonic flows. Her PhD research was supported by the National Defense Science and Engineering Graduate Fellowship, and her post-doctoral research is supported by the President's Postdoctoral Fellowship Program at the University of Minnesota.
This lecture is part of the Young Investigators Lecture Series sponsored by the Caltech Division of Engineering & Applied Science.