Numerical Methods for Chemical Engineering: 1-D Reactor Modeling

Chemical engineering systems often rely on complex mathematical models that cannot be solved analytically. To design and optimize physical systems like tubular reactors, you must translate physical boundary conditions into robust numerical models. This course teaches you how to discretize partial differential equations (PDEs) and structure them as differential-algebraic equations (DAEs) for chemical processes. You will transition from theoretical transport phenomena to structured numerical systems. You will learn how to mathematically define inlet and outlet boundary conditions, manage spatial discretization grids, and solve the resulting algebraic and differential systems. What you'll learn: - Understand the core mathematical theory of transport and reaction systems in 1-D space - Discretize partial differential equations into systems of differential-algebraic equations - Apply Dankwerts boundary conditions to accurately model inlet and outlet reactor behavior - Configure spatial grids and analyze the impact of grid density on numerical stability - Solve 1-D tubular reactor models using modern numerical solvers and modern Python-based scientific libraries The course begins with foundational concepts of transport equations and boundary conditions, then guides you through the step-by-step discretization process, and concludes with practical numerical implementation strategies for steady-state and transient simulations. This course is designed for chemical engineering students and practicing process engineers looking to strengthen their numerical modeling skills. No prior experience with advanced numerical discretization is required, though a basic understanding of calculus and transport phenomena is recommended. Start building accurate, stable, and industry-relevant chemical engineering simulations today.