About Saja Almohammadi Saja Almohammadi Ph.D. Student, Applied Mathematics and Computational Science uncertainty quantification Saja Almohammadi is a PhD candidate in Applied Mathematics and Computational Sciences. She is studying under supervision of Professor Omar Knio. Research Interest Saja Almohammadi's research interest include working on Uncertainty Quantification (UQ) on chemical system. Development of methods for forward UQ as applied to chemical kinetic application relevant to Rapid compression machine on iso-octane. Education Profile M.Sc. in Applied Math, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, 2014. BS Mathematics Department, King Abdelaziz University (KAU), Saudi Arabia Events Presented Events Nov 7 - Nov 13, 2021 Computational Challenges in Sampling and Representation of Uncertain Reaction Kinetics in Large Dimensions Saja Almohammadi, Ph.D. Student, Applied Mathematics and Computational Science Nov 8, 16:00 - 19:00 B3 L5 R5220 Constructing functional representations of the key quantities of interest (QoIs), the ignition delay time ( ign), of an uncertain ignition reaction in high dimension is our main goal. First, attention is focused on the ignition delay time of an iso-octane air mixture, using a detailed chemical mechanism with 3,811 elementary reactions. Uncertainty in all reaction rates is directly accounted for using associated uncertainty factors, assuming independent log uniform priors. A Latin hypercube sample (LHS) of the ignition delay times was first generated, and the resulting database was then exploited to assess the possibility of constructing polynomial chaos (PC) representations in terms of the canonical random variables parameterizing the uncertain rates.
Computational Challenges in Sampling and Representation of Uncertain Reaction Kinetics in Large Dimensions Saja Almohammadi, Ph.D. Student, Applied Mathematics and Computational Science Nov 8, 16:00 - 19:00 B3 L5 R5220 Constructing functional representations of the key quantities of interest (QoIs), the ignition delay time ( ign), of an uncertain ignition reaction in high dimension is our main goal. First, attention is focused on the ignition delay time of an iso-octane air mixture, using a detailed chemical mechanism with 3,811 elementary reactions. Uncertainty in all reaction rates is directly accounted for using associated uncertainty factors, assuming independent log uniform priors. A Latin hypercube sample (LHS) of the ignition delay times was first generated, and the resulting database was then exploited to assess the possibility of constructing polynomial chaos (PC) representations in terms of the canonical random variables parameterizing the uncertain rates.
Related Sites Omar Knio Research Group (O-Knio) Applied Mathematics and Computational Science (AMCS) Related Content Events 1
