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Title:Reduced-order model framework for thermochemical non-equilibrium hypersonic flows
Author(s):Macdonald, Robyn Lindsay
Director of Research:Panesi, Marco
Doctoral Committee Chair(s):Panesi, Marco
Doctoral Committee Member(s):Dutton, J. Craig; Hirata, So; Jaffe, Richard L
Department / Program:Aerospace Engineering
Discipline:Aerospace Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):quasi-classical trajectory
energy transfer
chemical kinetics
Abstract:The study of vehicles traveling at hypersonic speeds is extremely complex and involves many different non-equilibrium physical phenomena occurring on many different time-scales. As a result, work focused on modeling this type of flowfield has been hindered by inaccurate physical and chemical models. For example, the conventional approach to model chemical non-equilibrium, still widely used today, was developed nearly 40 years ago and relies heavily on calibration with heritage experimental data. However, advances in both computational chemistry and computational power have enabled the construction of extremely detailed models for the chemical non-equilibrium effects based on ab initio quantum chemistry data, called the state-to-state (StS) approach. Although the StS approach affords unprecedented accuracy for predictions of thermochemical non-equilibrium, it cannot be applied to study molecule-molecule interactions due to the massive computational cost. Unfortunately, due to the enormous cost of both computing data for and applying the StS approach, this method can only be used in highly simplified test cases. This motivates the development of reduced order models for chemical non-equilibrium which can capture the essential physics at a massively reduced cost. 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 atoms and molecules. In order to construct the reduced order model directly from ab initio quantum chemistry data, kinetic data is calculated directly for the model using the quasi-classical trajectory (QCT) method. This bypasses the need to compute StS kinetic data for 10^15 reactions resulting from the interaction between two nitrogen molecules, an impossible task. The model reduction framework, called the multi-group maximum-entropy quasi-classical trajectory (MGME-QCT) method, provides a crucial link between the ab initio quantum chemistry data and multi-dimensional computational fluid dynamics (CFD). The MGME-QCT method is used to construct a reduced order model for a mixture of nitrogen atoms and molecules using an ab initio potential energy surface (PES) to describe the interaction between particles. In the MGME model, energy states are lumped together into groups containing states with similar properties, and the distribution of states within each of these groups is reconstructed by leveraging the maximum entropy principle. Two types of reduced order models are constructed: one based on conventional wisdom which relies on the assumption of strict separation of rotational and vibrational energy, and one which relies on the assumption of strong rovibrational coupling. In a study of the isothermal relaxation of nitrogen molecules, it is found using these two approaches that the underlying assumptions made in conventional chemical non-equilibrium models (i.e., that vibrational and rotational modes are decoupled) result in incorrect predictions about the dissociation process. In contrast, the groups constructed assuming rovibrational equilibrium better capture the dynamics of the dissociation process. This finding is confirmed through comparison with a detailed molecular dynamics approach. Finally, the applicability of the MGME-QCT method to CFD is demonstrated through application to a handful of simple test cases including a standing shock wave, and the flow through a nozzle. These test cases demonstrate the flexibility of this approach in modeling a variety of flow regimes (e.g., both compressing and expanding flows).
Issue Date:2019-04-18
Rights Information:Copyright 2019 Robyn Macdonald
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05

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