Samy Mukadi, Professor, PhD, P.Eng
/Samy Mukadi/
Contact
ATS Assistant Lecturer, Faculty of Engineering - Chemical and Materials Engineering Dept
- lmukadi@ualberta.ca
Overview
Area of Study / Keywords
Chemically Reacting Processes Computation Fluid Dynamics Mathematical Modeling Multiphase Reactors
Courses
CH E 312 - Fluid Mechanics
Newtonian and non-Newtonian fluid behavior; hydrostatics; buoyancy, application of Bernoulli and momentum equations; frictional losses through pipes, ducts, and fittings; pipe networks; pumps; drag on submerged bodies and flow through porous media. Prerequisites: CH E 243 EN PH 131 and MATH 209. Corequisite: MATH 201.
CH E 316 - Separation Process
Design of separation processes with emphasis on the equilibrium stage concept, distillation, absorption and extraction. Design of rate based separations, membranes, membrane cascades, adsorption. Introduction to the use of process simulators for designing the separation processes. Prerequisites: CH E 343, 314. Corequisite: CH E 318.
CH E 316A - Separation Process
Design of separation processes with emphasis on the equilibrium stage concept, distillation, absorption and extraction. Design of rate based separations, membranes, membrane cascades, adsorption. Introduction to the use of process simulators for designing the separation processes. Prerequisites: CH E 343, 314. Corequisite: CH E 318.
CH E 316B - Separation Process
Design of separation processes with emphasis on the equilibrium stage concept, distillation, absorption and extraction. Design of rate based separations, membranes, membrane cascades, adsorption. Introduction to the use of process simulators for designing the separation processes. Prerequisites: CH E 343, 314. Corequisite: CH E 318.
CH E 358A - Process Data Analytics and Machine Learning
Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include linear and nonlinear regression, dimensionality reduction, classification, deep learning, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and CH E 345.
CH E 358B - Process Data Analytics and Machine Learning
Statistical analysis of process data from chemical process plants and course laboratory experiments. Topics covered include linear and nonlinear regression, dimensionality reduction, classification, deep learning, and design of experiments. Prerequisites: CH E 351 and STAT 235. Corequisites: CH E 314 and CH E 345.
CH E 445 - Chemical Reactor Analysis II
Analysis and design of non-ideal chemical reactors for industrial product synthesis. Prerequisites: CH E 314, 318 and 345.