Numerical Methods for Chemical Engineering: Solving Nonlinear Systems

Chemical engineering problems rarely yield simple, linear solutions. To model real-world reactors, separation columns, and thermodynamic properties, you must know how to reliably resolve systems of non-linear equations. This course provides a clear, structured pathway to understanding and applying these essential numerical methods without needing a advanced mathematical background. You will transition from basic algebraic concepts to confidently setting up and solving multi-variable chemical engineering models. What you'll learn: Understand the foundational theory of non-linear systems and why analytical solutions fail in complex chemical processes; Apply Newton-Raphson and quasi-Newton methods to multi-variable systems; Formulate robust convergence criteria and handle poorly-conditioned equations; Implement modern numerical solvers using clear, structured programming practices; Debug and optimize solver performance for thermodynamic and transport models. We begin with core definitions and fundamental concepts before moving into iterative algorithms, convergence behavior, and practical chemical engineering applications. This course is designed for engineering students, researchers, and practicing professionals who want a solid, beginner-friendly foundation in numerical computation. Start building your computational engineering toolkit today.