Numerical Boundary Value Problems for Chemical Engineers in MATLAB

Many real-world chemical engineering systems, from packed-bed reactors to heat exchangers, are governed by complex boundary value problems that cannot be solved by hand. To design and optimize these systems, engineers must rely on robust numerical methods to find accurate solutions. This written course guides you through the process of formulating, discretizing, and solving these differential equations with confidence. You will transition from understanding basic transport equations to implementing highly efficient numerical algorithms. By learning how to leverage solver configurations and Jacobian sparsity patterns, you will be able to resolve highly non-linear, multi-variable engineering models without running into computational bottlenecks. What you'll learn: - Understand the physical foundations of boundary value problems in transport and reaction systems. - Formulate finite difference equations to discretize continuous engineering models. - Implement MATLAB BVP solvers such as bvp4c and bvp5c for non-linear systems. - Configure Jacobian sparsity patterns to dramatically accelerate solver computation times. - Apply boundary conditions accurately for various physical interfaces and symmetry lines. - Analyze numerical convergence and troubleshoot solver errors systematically. This course begins with essential definitions and the physical origin of boundary value problems before moving step-by-step into numerical discretization, MATLAB solver syntax, and optimization techniques. It is designed for engineering students, researchers, and professionals who want to build solid numerical modeling skills from scratch. Start reading today to master numerical simulations for chemical engineering applications.