Extension of the High-Order Entropy-stable Discontinuous Galerkin Solver to Non-Equilibrium Flows
                Project Details
Program
                                        Applied Mathematics and Computer Science
                                    Field of Study
                                        Computational Science and Scientific Machine Learning
                                    Division
                                         Computer, Electrical and Mathematical Sciences and Engineering
                                    Faculty Lab Link
                                        
                                    Project Description
                                Hypersonic flows encountered during atmospheric re-entry and high-speed aerospace operations demand robust CFD techniques. Under these extreme conditions, chemical non-equilibrium (CNEQ) and thermochemical non-equilibrium (TCNEQ) effects arise due to dissociation, ionization, and vibrational-electronic energy exchanges among multiple species and energy modes. Traditional CFD solvers that assume equilibrium conditions cannot accurately capture these complex physical
phenomena.
                            
                        About the Researcher
Matteo Parsani
                                  
                                        Associate Professor, Applied Mathematics and Computational Science
                                  
                                  Desired Project Deliverables
                                The entropy-stable Discontinuous Galerkin (DG) solver developed at KAUST (SSDC) has demonstrated excellent accuracy and stability for single-species flow simulations. However, to extend its applicability to non-equilibrium hypersonic regimes, we must incorporate multi-species and multi-temperature modeling capabilities that account for high-temperature chemical reactions and inter-modal energy transfer.
                            
                        Recommended Student Background
                                            At least basic programming skills and an interest to become better. Ideally, in C, Fortran, Python.
                                        
                                    
                                            Understanding of the compressible Navier–Stokes equations and fundamentals of high-speed flows is highly desira
                                        
                                    
                                            Prior coursework or hands-on work in numerical methods and CFD is an advantage, although not strictly mandatory
                                        
                                    
                                            Comfort with a Linux-based environment for software development, debugging, and potentially high-performance co
                                        
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3-6 months
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