Applied Numerical Methods for Chemical Engineers

Chemical engineering problems often involve complex equations that cannot be solved analytically. To design reactors, model transport systems, and optimize chemical processes, you need reliable numerical techniques. This text-based course guides you through the foundational numerical methods used in chemical engineering. You will learn how to translate physical systems into mathematical models and solve them step-by-step using modern computational strategies. What you'll learn: Understand core mathematical modeling principles for chemical processes; Solve non-linear algebraic equations representing chemical equilibria and state equations; Apply numerical integration techniques to calculate reactor volumes and conversion rates; Formulate and solve ordinary differential equations for transient process simulation; Implement modern Python-based numerical solvers using NumPy and SciPy for engineering calculations; Analyze error propagation and convergence stability in numerical simulations. The course begins with fundamental mathematical definitions and error analysis before moving on to practical applications in thermodynamics, kinetics, and transport. You will work through detailed written walkthroughs and conceptual exercises designed to build your problem-solving confidence. This course is designed for students and entry-level engineers seeking a solid foundation in computational engineering, with no advanced programming experience required. Start mastering the numerical tools that power modern chemical engineering design today.