PREDICCIÓN DEL SECADO DE ZANAHORIA EN LECHO FLUIDO MEDIANTE UN GEMELO DIGITAL BASADO EN ECUACIONES FENOMENOLÓGICAS

Alejandro Javier Delgado Araujo; Fausto Andrés  Reyes Estévez; Carlos Alberto Almeida; William Ricardo Venegas Toro; Alejandro Daniel Hidalgo Chafuel; Edison Fernando  García Narváez; Gilda Graciela Gordillo Vinueza; Jorge Alfonso  López Lara; Jorge Luis Santamaria Carrera

doi:10.47187/perf.v1i35.366

Authors

Alejandro Javier Delgado Araujo Universidad de la Frontera, Doctorado en Ingeniería, Temuco, Chile
Fausto Andrés Reyes Estévez Universidad Central del Ecuador, Facultad de Ingeniería Química, Departamento de Operaciones Unitarias, Quito, Ecuador
Carlos Alberto Almeida Universidad Central del Ecuador, Facultad de Ingeniería Química, Departamento de Operaciones Unitarias, Quito, Ecuador
William Ricardo Venegas Toro Escuela Politécnica Nacional, Departamento de Ingeniería Mecánica, Quito, Ecuador
Alejandro Daniel Hidalgo Chafuel Universidad Central del Ecuador, Facultad de Ingeniería Química, Departamento de Operaciones Unitarias, Quito, Ecuador
Edison Fernando García Narváez Universidad Central del Ecuador, Facultad de Ingeniería Química, Departamento de Operaciones Unitarias, Quito, Ecuador
Gilda Graciela Gordillo Vinueza Universidad Politécnica Salesiana, Grupo GILEC, Quito, Ecuador
Jorge Alfonso López Lara Empresa Pública de Hidrocarburos del Ecuador – EP PETROECUADOR, Quito, Ecuador
Jorge Luis Santamaria Carrera Universidad Central del Ecuador, Facultad de Ingeniería Química, Departamento de Operaciones Unitarias, Quito, Ecuador

DOI:

https://doi.org/10.47187/perf.v1i35.366

Keywords:

Digital twin, fluid bed drying, Aspen HYSYS® v14, carrot

Abstract

Development and implementation of a digital twin to simulate and predict the fluidized bed drying (FBD) process of carrot flakes, integrating thermodynamic equations with digital simulation techniques. Experimental and operational data were collected to validate the dryer's behavior under real-life conditions, comparing them with the results of the simulated model. The digital twin allowed critical points to be identified, operating parameters to be optimized, process efficiency to be improved, and a model to predict its behavior was provided. The results showed a change in final moisture content from 10% to 7% with the implementation of the digital twin. In addition, using the simulator results, a statistical analysis of variance (ANOVA) was carried out, indicating a first-order polynomial statistical model with a coefficient of determination 99.88. These results demonstrate that digital twins are an effective tool for optimizing industrial processes, aligning with advances in industrial automation, contributing to continuous improvement in product quality and energy sustainability.

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