Numerical Methods for Chemical Engineering Boundary Value Problems

Chemical engineering processes frequently rely on boundary value problems to model heat transfer, mass transfer, and chemical reactions. Solving these complex systems requires robust numerical methods rather than simple analytical approximations. This course guides you from the fundamental mathematical concepts of boundary value problems to implementing efficient iterative solvers and preconditioning techniques. What you'll learn: • Understand the core mathematical formulations of boundary value problems in chemical engineering. • Apply finite difference methods to discretize partial and ordinary differential equations. • Implement iterative solvers like the Conjugate Gradient method for sparse linear systems in MATLAB. • Configure preconditioning techniques, including Incomplete Cholesky factorization, to accelerate solver convergence. • Analyze modern scientific computing workflows, including code vectorization and basic performance profiling. • Practice solving realistic heat and mass transfer models through step-by-step written exercises. This course begins with key terminology, basic conservation equations, and foundational definitions before moving into practical discretization and solver optimization. You will learn through detailed written explanations, equations, and clear code snippets. This course is designed for engineering students, researchers, and professional chemical engineers who want to build a solid foundation in numerical computing. No advanced prior programming experience is required. Start mastering the computational tools that drive chemical process simulation today.