Numerical Methods for Chemical Engineering

Chemical engineering challenges—from reactor design to transport phenomena—often lead to complex mathematical equations that cannot be solved analytically. To find practical solutions, engineers rely on computational techniques to model, simulate, and optimize these systems. This text-based course bridges the gap between chemical engineering principles and numerical computation, giving you the skills to solve real-world engineering problems systematically. You will start with the absolute fundamentals of numerical analysis, learning how to translate physical chemical processes into solvable mathematical models. As you progress, you will explore core algorithms for solving linear and nonlinear equations, ordinary differential equations, and boundary value problems specific to chemical processes. You will also learn how to write clean, structured code to automate these calculations and analyze error propagation. What you'll learn: - Understand the foundational theory of numerical approximation and error analysis in engineering calculations - Solve systems of linear and nonlinear algebraic equations representing chemical equilibrium and mass balances - Apply numerical integration techniques to model chemical reactor kinetics and transient heat transfer - Implement numerical methods for ordinary differential equations to simulate dynamic process systems - Formulate and solve boundary value problems common in transport phenomena and fluid flow - Structure computational code using modern programming practices to ensure reproducibility and efficiency This course begins with essential mathematical terminology and basic modeling concepts before moving into practical algorithmic applications. Through written explanations, structured derivations, and step-by-step code snippets, you will build a solid computational foundation. This course is designed for undergraduate students, early-career chemical engineers, and science professionals who want to develop practical numerical modeling skills. No prior programming experience is required, though a basic understanding of calculus and introductory chemistry is recommended. Begin mastering computational chemical engineering today through structured, self-paced text lessons.