Modeling of non-equilibruim hypersonic air flows by means of the Multi-group Maximum Entropy method
Abstract
The development of hypersonic weapons, frequently noted as a game-changing capability in military superiority,critically relies on the availability of computationally efficient and accurate models for the descriptionof non-equilibrium flows. This proposal aims to construct a reduced order model for modeling ofnon-equilibrium phenomena in high speed air flows. This work is at the interface between computationalchemistry and computational fluid dynamics and aims at developing new models based on microscopic theoryand applying them to macroscopic scales. The most physically consistent description of non-equilibrium flows relies on the solution of the master equations for each internal level of the gas particles. However, such a detailed description is impractically expensive. The proposed approach will thus leverage the maximum entropy principle, subject to a series of moment constraints, to reconstruct the logarithm of the distribution function expressed as a power series in internal energy. In order to improve the accuracy of the method, the internal energy levels are lumped in multiple groups, leveraging an adaptive kinetic-based grouping strategy to select the ’best’ arrangement of the states within each group. This approach seeks for an optimal reduced order representation of the distribution function by grouping together individual energy states that are likely to quickly equilibrate with each other, thus maximizing the accuracy of the reconstruction, and drastically reducing the computational cost. This new class of ab-initio based models has the potential to revolutionize engineering and science by enabling truly predictive simulation of nonequilibrium chemistry phenomena, over a wide spectrum of flow conditions. The new model will be implemented in a AFOSR solver, and used to investigate the hypersonic flow over a double cone configuration. Comparison with experimental data collected on the T5 facility at Caltech will serve to validate the model
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 28, 2018
- Source ID
- FA95501810388
Entities
People
- Marco Panesi
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Illinois Urbana–Champaign