This work was also presented at the 2017 AIAA AVIATION Forum, and the second part, “Coarse grain modeling and direct molecular simulation of nitrogen dissociation," was named the 2018 Weaver Thermophysics Best Student Paper.
Computationally efficient and accurate models for the description of non-equilibrium flows are essential for engineering Air Force vehicles able to operate at extreme conditions. The design and development of these aircraft and their advanced propulsion systems critically depend on flow models that include chemical reactions, but without the modeling simplifications afforded by conventional approaches. The focus of this work is to develop a new model for chemistry in hypersonic flows based on data derived from first principles physics (i.e., quantum chemistry).
“The main challenge on using ab-initio based data has been the huge amount of information provided by these methods, so we need an intelligent way to reduce it,” Macdonald said. “My work combines the data from the quantum chemists and uses a Monte Carlo sampling approach with dynamic calculations to compute transition probabilities for reactions, which tells us how the composition of the gas changes in time due to these reactions.
“The second part of the work involved comparing our newly developed model with a high-fidelity approach available from collaborators at the University of Minnesota. It helped us demonstrate both the applicability and accuracy of our method. The end goal of this work is develop a model that can be used in multi-dimensional computational fluid dynamics (CFD) simulations.”
Macdonald received a bachelor’s degree in aerospace engineering from the University of Illinois in 2013 and has since then been working on a doctoral degree. She’ll graduate in December of this year.