Numerical Methods in Chemical Engineering with Optimized MATLAB

Chemical engineering relies heavily on numerical simulations to model complex reactor dynamics, mass transfer, and thermodynamic systems. To solve these engineering problems efficiently, you need both a strong grasp of numerical algorithms and the ability to write highly optimized code. This text-based course bridges the gap between chemical engineering theory and computational execution, showing you how to translate physical models into fast, reliable MATLAB scripts. You will start by mastering the fundamental mathematical concepts and core numerical algorithms, before moving on to practical optimization techniques that prevent computational bottlenecks. By reading through detailed code walkthroughs and structured explanations, you will learn how to write cleaner, faster scripts without relying on heavy external libraries. What you'll learn: - Understand the core numerical methods used to model chemical engineering processes, including ODEs and PDEs - Apply vectorization techniques in MATLAB to eliminate slow loops and accelerate your simulations - Configure efficient solver settings for stiff and non-stiff differential equations common in chemical kinetics - Optimize memory allocation and leverage preallocation to prevent computational slowdowns - Profile your MATLAB code to identify and resolve performance bottlenecks systematically - Practice translating transport phenomena and thermodynamic equations into structured, high-performing scripts This course begins with essential mathematical definitions and foundational numerical concepts, progressing logically to advanced optimization strategies and engineering applications. It is designed for undergraduate students, researchers, and practicing engineers who have a basic familiarity with MATLAB and want to elevate their computational efficiency. Start reading today to transform your chemical engineering models into highly optimized, professional-grade simulations.