Numerical Methods for Chemical Engineering: Reactor Modeling

Designing and optimizing chemical reactors requires a solid grasp of how temperature and concentration change throughout a system. Numerical methods turn complex differential equations into practical, solvable models. This text-based course guides you from the fundamental principles of chemical kinetics and transport phenomena to building robust numerical simulations. You will learn how to set up and solve steady-state profiles for 1-D tubular reactors with arbitrary reaction networks. What you'll learn: - Understand the core mathematical formulations behind mass and energy balances in tubular reactors. - Formulate systems of ordinary differential equations (ODEs) for multiple chemical species and reaction steps. - Apply modern numerical solvers in Python, utilizing NumPy and SciPy to compute steady-state profiles. - Analyze temperature and concentration variations along a reactor's length under varying thermal conditions. - Implement robust error-checking and modern coding practices, including basic type hints and structured arrays, to ensure simulation reliability. The course begins with foundational definitions of reactor design and chemical kinetics, establishing a strong theoretical base. You will then progress through step-by-step written tutorials that walk you through translating these equations into clean, executable code. This course is designed for chemistry and engineering students, as well as practicing professionals looking for a beginner-friendly introduction to numerical modeling. No prior programming or advanced numerical analysis experience is required. Start reading today to master the essentials of chemical reactor simulation.