h-index: 5 | i10-index: 2 | citations: 206 (upto December 2025)
My name is Mohammed Sayyari; I work on the regularization of the Navier-Stokes and positivity-preserving provably stable high-fidelity numerical schemes for the Navier-Stokes equations as a postdoc in the Department of Mathematics and Statistics at Old Dominion University. With a strong background in computer science, my current project integrates efficient and scalable computation with rigorous mathematical analysis to preserve the stable structure of the underlying model. Through international collaborations, I have contributed to impactful research, such as in the relaxation Runge-Kutta method, where we extended the method to include nonlinear convex functionals such as mathematical entropy. This method provides provable stability for fully-discrete schemes, in contrast to the stability of only the discrete spatial operators, common in this area of research. My long-term research plan is to develop provably stable, robust, and efficient schemes on high-performance computing (HPC) platforms for problems in fire simulation and numerical weather prediction (NWP). These schemes enhance the accuracy and stability of simulations for critical applications like climate modeling and aerospace engineering.
In addition to my research, I have consistently been passionate about teaching. Even when it was not required, I served as a Teaching Assistant during my PhD for a variety of courses spanning computer science and mathematics. For example, I assisted in creating homework and held office hours for courses such as Numerical Analysis of PDEs and Numerical Optimization. Additionally, I inaugurated the course of Numerical Methods for Internal Aerodynamics at Ruhr-Universität Bochum, creating all the course content, from slides and notes to a unique problem set and computer programming examples. I am committed to continuing learning and researching pedagogical methods. For example, I attended a course on the eight practices in teaching mathematics, where I learned key practices such as productive struggle, purposeful questioning, and eliciting evidence of student thinking.
PhD in Applied Mathematics, 2022
King Abdullah Universty of Science and Technology
MSc in Applied Mathematics, 2018
King Abdullah Universty of Science and Technology
BSc in Computer Science with a minor in Mathematics, 2016
Kansas State University
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We generalize the explicit high-order positivity-preserving entropy-stable spectral collocation schemes developed in [30, 34] for the three-dimensional (3D) compressible Navier Stokes equations to a time implicit formulation. The time derivative terms are discretized by using the first- and second-order implicit backward difference formulas (BDF1 and BDF2) that are well suited for solving steady-state and time-dependent viscous flows at high Reynolds numbers, respectively. The nonlinear system of discrete equations at each physical timestep is solved by using a dual time-stepping technique. The proposed scheme is provably entropy-stable and positivity-preserving and provides unconditional stability properties in the physical time. Numerical results demonstrating accuracy and positivity-preserving properties of the new dual time-stepping scheme are presented for supersonic viscous flows with strong shock waves and contact discontinuities.
As most papers in the community of double averaging neglect the effects of commutation errors, we demonstrate in this featured article that the effects are significant enough to affect the solution.
This paper has gained a large traction in the field because it extends the entropy-stability features previously only available at the semi-discrete level to a fully-discrete scheme.
C, C++, Fortran, Python
LaTeX, PETSc, OpenFOAM, MPI
Academic papers (7), Proposals (2)
Full courses (6), Student supervision (2)
GitHub, GitLab, BitBucket, Docker
Peer reviewer (3 journals)