Applied Numerical Methods for Chemical Engineers

Chemical engineering processes often involve complex reactions, transport phenomena, and thermodynamics that cannot be solved with simple analytical math. To design and analyze these systems effectively, you must master the numerical methods that translate physical laws into solvable algorithms. This text-only course guides you from foundational mathematical concepts to solving real-world chemical engineering models using structured, step-by-step written explanations. By completing this course, you will gain the confidence to set up, solve, and analyze systems of differential equations, optimize process parameters, and interpolate experimental data using modern scientific computing approaches. What you'll learn: - Understand core numerical concepts, starting with error analysis and iterative calculation rules. - Convert higher-order differential equations into manageable systems of coupled first-order equations. - Apply polynomial and Lagrange interpolation techniques to estimate missing experimental data points. - Solve partial differential equations and boundary value problems (PDE-BVPs) for transport and reaction systems. - Formulate and execute process optimization algorithms to find ideal operating conditions. - Implement these numerical solutions using clean, structured code patterns and modern scientific libraries. The course begins with foundational definitions of numerical errors and iterative convergence before moving into interpolation, ordinary differential equations, optimization, and advanced boundary value problems. Every concept is explained through clear written breakdowns, mathematical formulations, and practical engineering scenarios. This course is designed for engineering students, researchers, and practicing chemical engineers who are new to numerical computation and want a structured, self-paced introduction without complex mathematical prerequisites. Start building your computational engineering toolkit today.