Foundations of Computational Process Design

Designing efficient chemical and industrial processes requires more than just intuition; it demands robust computational modeling. This course introduces you to the core principles of process simulation and numerical optimization without complex prerequisites. You will transition from understanding basic chemical engineering concepts to confidently formulating mathematical models of process units. Through clear, step-by-step written explanations, you will learn how to solve material and energy balances computationally and optimize process parameters for efficiency and sustainability. What you'll learn: - Understand the foundational principles of mathematical modeling for chemical process systems. - Formulate and solve steady-state material and energy balances using numerical methods. - Apply optimization algorithms to improve process efficiency, yield, and economic viability. - Simulate key unit operations, including reactors, separation columns, and heat exchangers. - Apply modern scientific computing concepts and basic Python-based scripting for process simulation. - Integrate environmental sustainability and green engineering metrics into your design workflows. The course begins with essential definitions and thermodynamic principles before guiding you through model development, numerical equation-solving techniques, and practical optimization strategies. You will practice these concepts through structured written exercises and step-by-step mathematical walkthroughs. This course is designed for engineering students, aspiring process designers, and technical professionals new to computational modeling. No prior simulation experience is required, though a basic understanding of chemistry and algebra is helpful. Start building your computational engineering toolkit today.