¿La intuición a veces puede traicionarte?

Francisco J. Valdés Parada; Jessica  Sánchez Vargas

Francisco J. Valdés Parada Departamento de Ingeniería de Procesos e Hidráulica. Universidad Autónoma Metropolitana- Iztapalapa.
Jessica Sánchez Vargas Departamento de Biología Molecular y Biotecnología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México

Keywords: Multiphase and multiscale models, upscaling, intuition, neuronal networks

Abstract

Modeling transport phenomena in systems that involve multiple scales can be performed without ambiguities at the continuum scale level. However, when it is necessary to account for models at higher scale levels and that involve more phases, the same level of clarity and acceptance of the transport equations is not achieved. On the one hand, a rapid solution to this situation consists of using intuitive models founded on (natural or artificial) learning. On the other hand is the rigorous derivation of models at higher scale levels. In this work, both approaches are discussed and the relation that they have. The goal is to show the reader that one approach does not exclude the other and that it is worth dedicating time to discuss both points of view to carry out (rapid or rigorous) solutions to practical problems in science and engineering.

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