Numerical Methods for Chemical Engineering Fundamentals

Chemical engineering challenges often involve complex systems of equations that cannot be solved analytically. To design reactors, model transport phenomena, and optimize processes, you must translate physical principles into robust numerical models. This text-based course guides you from core mathematical concepts to writing clear, functional code for engineering simulations. You will transition from theoretical equations to practical numerical solutions. By studying structured written explanations, mathematical proofs, and clean code implementations, you will develop the logical framework necessary to model real-world chemical systems. What you'll learn: - Understand the foundational theory of linear and non-linear algebraic equations in chemical processes - Solve ordinary and partial differential equations modeling heat, mass, and momentum transfer - Apply numerical integration and differentiation techniques to reactor design problems - Implement modern programming practices, including type hints and structured code formatting, to build readable simulation scripts - Practice debugging and validating numerical solutions against physical constraints - Configure optimization algorithms to find efficient operating conditions for chemical systems The course begins with foundational mathematical definitions and key numerical concepts before moving into iterative methods, error analysis, and practical coding exercises. You will explore step-by-step written breakdowns of classic transport and thermodynamic problems, learning how to structure your code for maximum clarity and accuracy. This course is designed for undergraduate students, early-career engineers, and researchers new to computational modeling in chemical engineering. No advanced programming background is required, though a basic familiarity with algebra and general chemistry is helpful. Start translating chemical theory into reliable numerical models today.