TONY SAAD portrait
  • Assistant Professor, Chemical Engineering
801-585-0344
http://www.tsaad.net

Publications

  • Karam, Mokbel, and Tony Saad, 2021, High-Order Pressure Estimates for Projection-Based Navier-Stokes Solvers. Journal of Computational Physics: 110925. Published, 12/30/2021.
  • Mokbel Karam & Tony Saad (2021). BuckinghamPy: A Python software for dimensional analysis. Elsevier. Vol. 16, 100851. Published, 11/15/2021.
    https://www.sciencedirect.com/science/article/pii/...
  • Karam, M., Sutherland, J. C., & Saad, T. (2021). Low-cost Runge-Kutta integrators for incompressible flow simulations. Journal of Computational Physics, 110518. Published, 06/16/2021.
  • Hayden A. Hedworth, Tofigh Sayahi, Kerry E. Kelly & Tony Saad (2020). The effectiveness of drones in measuring particulate matter. Journal of Aerosol Science. Published, 11/02/2020.
  • Mokbel Karam, James C. Sutherland & Tony Saad (2020). PyModPDE: A python software for modified equation analysis. SoftwareX. Vol. 12. Published, 06/22/2020.
  • Joshua T. McConnell, James C. Sutherland & Tony Saad (2020). An Explicit Low-Mach Projection Method for Modeling Flows with Finite-Rate Chemistry. AIAA 2020 Fluid Dynamics Conferences. Published, 06/08/2020.
  • B. Peterson, A. Humphrey, D. Sunderland, J. Sutherland, T. Saad, H. Dasari, and M. Berzins. Automatic Halo Management for the Uintah GPU-Heterogeneous Asyn- chronous Many-Task Runtime. International Journal of Parallel Programming, 47(5):1086– 1116, Dec. 2019. (doi:10.1007/s10766-018-0619-1). Published, 12/02/2019.
  • Tony Saad & Giovanna Ruai (2019). PyMaxEnt: A Python software for maximum entropy moment reconstruction. SoftwareX by Elsevier. Vol. 10. Published, 10/21/2019.
    https://doi.org/10.1016/j.softx.2019.100353
  • M. Karam, J. C. Sutherland, M. Hansen, and T. Saad. A Framework for Analyzing the Temporal Accuracy of Pressure Projection Methods. 2019 AIAA Computational Fluid Dy- namics Conference, page 3634, 2019. (doi:10.2514/1.J055949). doi: 10.2514/1.J055949. Published, 06/03/2019.
  • Austin Richards & Tony Saad, and James C. Sutherland (2018). A Fast Turbulence Generator using Graphics Processing Units . AIAA Fluid Dynamics Conference, Atlanta, June 2018. Published, 06/29/2018.
  • Tony Saad & Mokbel Karam, James C. Sutherland (2018). An Explicit Variable-Density Projection Method for Low-Mach Reacting Flows on Structured Uniform Grids . AIAA Fluid Dynamics Conference, Atlanta, June 2018. Published, 06/29/2018.
  • Saad T., Cline D., Stoll R. & Sutherland J. (2017). Scalable tools for generating synthetic isotropic turbulence with arbitrary spectra. (pp. 327-331). Vol. 55, AIAA Journal. Published, 01/01/2017.
  • Saad T. & Sutherland J. (2016). Wasatch: An architecture-proof multiphysics development environment using a Domain Specific Language and graph theory. (pp. 639-646). Vol. 17, Journal of Computational Science. Published, 11/01/2016.
  • Saad T. & Sutherland J. (2016). Comment on "Diffusion by a random velocity field" [Phys. Fluids 13, 22 (1970)]. Vol. 28, Physics of Fluids. Published, 11/01/2016.
  • Schmidt J., Berzins M., Thornock J., Saad T. & Sutherland J. (2013). Large scale parallel solution of incompressible flow problems using Uintah and hypre. Proceedings - 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, CCGrid 2013. 458-465. Published, 08/14/2013.
  • Saad T. & Majdalani J. (2012). Some thoughts on the pressure integration requirements of the Navier-Stokes equations. Vol. 44, Fluid Dynamics Research. Published, 12/01/2012.
  • Maicke B., Saad T. & Majdalani J. (2012). On the compressible Hart-McClure and Sellars mean flow motions. Vol. 24, Physics of Fluids. Published, 09/17/2012.
  • Saad T. & Majdalani J. (2011). Viscous flows revisited in simulated rockets with radially regressing walls. 47th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit 2011. Published, 12/01/2011.
  • Saad T., Maicke B. & Majdalani J. (2011). Coordinate independent forms of the compressible potential flow equations. 47th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit 2011. Published, 12/01/2011.
  • Saad T. & Majdalani J. (2010). Pressure integration rules and restrictions for the Navier-Stokes equations. 40th AIAA Fluid Dynamics Conference. Published, 12/02/2010.
  • Saad T. & Majdalani J. (2010). Extension of Kelvin's minimum energy theorem to flows with open regions. 40th AIAA Fluid Dynamics Conference. Published, 12/02/2010.
  • Maicke B., Saad T. & Majdalani J. (2010). On the compressible Hart-McClure mean flow motion in simulated rocket motors. 46th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Published, 12/01/2010.
  • Saad T. & Majdalani J. (2010). On the Lagrangian optimization of wall-injected flows: From the Hart-McClure potential to the Taylor-Culick rotational motion. (pp. 331-362). Vol. 466. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. Published, 02/08/2010.
  • Saad T. & Majdalani J. (2009). Energy based solutions of the bidirectional vortex with multiple mantles. 45th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit. Published, 12/01/2009.
  • Saad T. & Majdalanr J. (2009). Rotational flowfields in porous channels with arbitrary headwall injection. (pp. 921-929). Vol. 25, Journal of Propulsion and Power. Published, 07/01/2009.

Research Keywords

  • low-Mach reacting flows
  • Solid Propellant Rocket Engines
  • Population Balances
  • Computational Fluid Dynamics

Presentations

  • Hedworth, H., Sohl, J., and Saad, T., Evaluating the Accuracy of UAV-Based Measurements through Experiments and Computational Fluid Dynamics Simulations. AICHE 2021 Annual Meeting, Houston, Texas. Nov. 7 - 11, 2021. Conference Paper, Refereed, Presented, 11/10/2021.
  • Can orchestras perform safely during a pandemic? A case study using CFD to model airborne viral transport. Graduate Seminar, University of Vermont. Invited Talk/Keynote, Presented, 02/19/2021.
  • How we used CFD to help the Utah Symphony Perform Safely during COVID19. Graduate Seminar, Auburn University. Invited Talk/Keynote, Presented, 01/21/2021.
  • The Utah Symphony, Reimagined, using CFD. European Research Community on Flow, Turbulence and Combustion (ERCOFTAC) Second Meeting on COVID19 and Fluid Mechanics. Invited Talk/Keynote, Presented, 01/05/2021.
    https://www.ercoftac.org/events/the-second-zoom-me...
  • Symphonies Reimagined using CFD. Notre Dame University, Lebanon. Invited Talk/Keynote, Presented, 11/30/2020.
  • The Utah Symphony, Reimagined, using CFD. Chemical Engineering Graduate Seminar, University of Utah. Invited Talk/Keynote, Presented, 11/16/2020.
  • Why CFD Needs a Facelift Invited talk at Brigham Young University. Invited Talk/Keynote, Presented, 01/23/2020. Invited Talk/Keynote, Presented, 01/23/2020.
  • Why CFD Needs a Facelift Invited talk at the Colorado School of Mines. Invited Talk/Keynote, Presented, 04/30/2019.
  • Efficient Multistage Time Integrators for Incompressible Flows using Projection Methods. Mokbel Karam, University of Utah, U.S.; Mike Hansen, Sandia National Laboratories, U.S.; James C. Sutherland and Tony Saad, University of Utah, U.S. SIAM CSE 19, Spokane, WA, Feb. 25 - March 1, 2019. Conference Paper, Refereed, Presented, 03/28/2019.
  • Exploring the Predictibility of Random Forests for the Sedov-Von Neumann-Taylor Blast Wave Solution. Mokbel Karam, University of Utah, U.S.; Fady M. Najjar and Ming Jiang, Lawrence Livermore National Laboratory, U.S.; James C. Sutherland and Tony Saad, University of Utah, U.S. SIAM CSE 19, Spokane, WA, Feb. 25 - March 1, 2019 . Conference Paper, Refereed, Presented, 03/25/2019.
  • Solving Evolutionary Differential Equations on Heterogeneous Architectures abstract Tony Saad and James C. Sutherland, University of Utah, U.S., SIAM CSE 19, Spokane, WA, Feb. 25 - March 1, 2019. Conference Paper, Refereed, Presented, 02/25/2019.
  • Karam M., Najjar F., Jiang M., Sutherland J. C., and Saad T., Applying Machine Learning to the Sedov-von Neumann-Taylor Blast Wave. Rocky Mountain Fluid Mechanics Symposium, University of Colorado Boulder,, Aug. 12 - 13, 2018. Other, Presented, 08/14/2018.
  • Karam M., Najjar F., Jiang M., Sutherland J. C., and Saad T., Applying Machine Learning to the Sedov-von Neumann-Taylor (SNT) Blast Wave. Lawrence Livermore National Laboratory Seminar, Livermore, California, Aug. 3, 2018. Invited Talk/Keynote, Presented, 08/03/2018.
  • Tony Saad, Mokbel Karam, and James C. Sutherland. "An Explicit Variable-Density Projection Method for Low-Mach Reacting Flows on Structured Uniform Grids", 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-4266). https://doi.org/10.2514/6.2018-4266 . Conference Paper, Refereed, Presented, 06/29/2018.
  • Austin Richards, Tony Saad, and James C. Sutherland. "A Fast Turbulence Generator using Graphics Processing Units", 2018 Fluid Dynamics Conference, AIAA AVIATION Forum, (AIAA 2018-3559) https://doi.org/10.2514/6.2018-3559. Conference Paper, Refereed, Presented, 06/26/2018.
  • Saad T., What are Low-Mach Reacting Flows and How to Compute Them?, Invited Talk, National Institute for Standards and Technology (NIST), May 17, 2017. Invited Talk/Keynote, Accepted, 05/02/2017.
  • Saad T., Why do Computational Scientists Complain?, University of Utah Graduate Seminar, April 19, 2017. Invited Talk/Keynote, Presented, 04/19/2017.
  • Saad, T., & Sutherland, J. C. (2017). Case Studies in Using a DSL and Task Graphs for Portable Reacting Flow Simulations. Retrieved from url link to talk abstract if any . Conference Paper, Refereed, Presented, 03/03/2017.
  • Goshayeshi, B., Saad, T., & Sutherland, J. C. (2017). Hybrid Computing In Large-Scale Multiphysics Simulation: Tabulated Properties and Particle-Cell Interpolations. Retrieved from url link to talk abstract if any . Conference Paper, Refereed, Presented, 03/03/2017.
  • Saad, T., & Sutherland, J. C. (2016). An Explicit Variable-Density Projection Method for Low-Mach Reacting Flows on Structured Uniform Grids. In AIChE Annual Meeting. San Francisco, CA, USA. Conference Paper, Refereed, Presented, 11/2016.

Research Groups

  • Giovanna Roth, Undergraduate Student. 02/01/2018 - present. Awards/Scholarships/Stipends: UROP Awardee.
  • Collin Hoggard, Undergraduate Student. 02/01/2018 - present. Awards/Scholarships/Stipends: UROP Awardee.
  • Austin Richards, Undergraduate Student. Chemical Engineering. 11/01/2017 - present. Awards/Scholarships/Stipends: UROP Awardee.
  • Mokbel Karam, Graduate Student. Chemical Engineering/PHD. 08/21/2017 - present.

Languages

  • Arabic, fluent.
  • English, fluent.
  • French, functional.
  • South Levantine Arabic, fluent.

Geographical Regions of Interest

  • Lebanon

Grants, Contracts & Research Gifts

  • DRONE SEED. PI: SAAD,TONY. UNIVERSITY OF UTAH RESEARCH FO, 06/30/2019 - 06/29/2020. Total project budget to date: $27,170.00

Software Titles

  • BuckinghamPy: A Python software for dimensional analysis. The Buckingham Pi theorem is useful in determining the dimensionless terms that describe a physical phenomenon. The number of these terms grows with the number of variables. The traditional approach in identifying dimensionless quantities for a given system can be tedious and error-prone. BuckinghamPy is a Python software that automates the generation of all possible sets of dimensionless groups in LATEX format. BuckinghamPy serves as a helpful tool for experimentalists and engineers for both educational and research purposes. Release Date: 12/01/2021. Inventors: Mokbel Karam and Tony Saad.
  • PyModPDE: A python software for modified equation analysis. The modified equation is a useful tool in the analysis of numerical methods for partial differential equations (PDEs). It gives insight into the stability, diffusion, and dispersion properties of a given numerical scheme. Its derivation, however, is rather tedious and error-prone due to the enormous amount of algebra involved. PyModPDE is a python software that uses a novel approach to generate the modified equation. It takes a discrete PDE as its input and outputs the modified equation in LATEX format. We discuss the novel approach on which PyModPDE is based and then validate the software using one and two-dimensional PDEs. PyModPDE serves as an essential tool for computational scientists and engineers for both educational and research purposes. Release Date: 08/01/2020. Inventors: Mokbel Karam and Tony Saad.
  • MaxEnt. Given a finite number of moments that describe a distribution, there an infinite number of distributions that can produce that finite number of moments. This is known as the moment inversion problem: given a finite set of moments, how does one find the "one and only" distribution that produced these monents? MaxEnt uses the Shannon's maximum information entropy principle to reconstruct the most likely distribution given a finite set of moments. It argues that the likely distribution that produced these moments is the one that maximizes the information entropy - or the one that embodies whatever knowledge we have of the distribution. Release Date: 12/12/2018.
  • CudaTurboGen. A GPU version of the synthetic turbulence generator. Release Date: 05/01/2018.
  • TurboGenPY. A python-based synthetic turbulence generator. Release Date: 01/04/2018. Inventors: Tony Saad.
  • Wave++. A scalable, parallel C++ code for computing wave propagation in complex three-dimensional terrain. The method implements wave confinement to capture sharp waves without incurring numerical errors. Release Date: 11/01/2017.
  • PyWave. 2D wave propagation software in Python using wave confinement. Release Date: 10/02/2017.
  • IsoTurb. Isotropic Turbulence Generator. See: turbulence.utah.edu. Release Date: 05/2016. Inventors: Tony Saad and James C. Sutherland.