Numerical Methods for Chemical Engineers

Chemical engineering problems often involve non-linear equations, complex differential systems, and multi-component transport phenomena that are impossible to solve by hand. To design reactors, optimize separation columns, or model fluid flow, you need reliable numerical techniques. This text-only course provides a clear, step-by-step pathway to translating chemical engineering principles into robust computer models. You will start with foundational mathematical definitions before moving on to practical simulation techniques using modern Python libraries. What you'll learn: - Understand the core mathematical formulations of chemical process systems - Solve non-linear algebraic equations for chemical equilibrium and reactor sizing - Model transient systems using ordinary differential equations (ODEs) - Apply numerical integration techniques to transport phenomena and kinetics - Implement modern Python libraries like NumPy and SciPy for scientific computing - Practice writing clean, structured, and reproducible engineering code. The course begins with essential terminology and the basics of numerical errors, then guides you through algebraic systems, differential equations, and basic optimization workflows. Every concept is explained through clear text and practical code snippets. This course is designed for chemical engineering students, researchers, and practicing professionals who want to build a solid foundation in computational methods. No prior programming experience is required. Start mastering computational chemical engineering today through structured reading and practical exercises.