Catalytic systems often involve numerous variables and complex interactions, making comprehensive models computationally expensive and challenging to analyze. Simplified models are essential for:
Reducing computational costs: Simplified models require less computational power and time. Enhancing interpretability: Simplified models are easier to understand and interpret. Facilitating experimental design: Simplified models help in designing experiments by focusing on key parameters. Improving control strategies: Simplified models are useful in developing effective control strategies for industrial processes.
