A novel, efficient and reliable method for thermal process design and optimization. Part I: theory

摘要

The design and optimization of thermal processing of foods needs accurate dynamic models through which to systematically explore new operation policies. Unfortunately, the governing and constitutive equations of thermal processing models usually lead to complex sets of highly nonlinear partial differential equations (PDEs), which are difficult and costly to solve, especially in terms of computation time. We overcome such limitation by using a powerful model reduction technique based on proper orthogonal de- composition (POD) which yields simple, yet accurate, dynamic models still based on sound first principles.