Implementation of Modeling Tools for Teaching Biorefinery (Focused on Bioethanol Production) in Biochemical Engineering Courses: Dynamic Modeling of Batch, Semi-Batch, and Continuous Well-Stirred Bioreactors
Metadatos
Afficher la notice complèteAuteur
Martín Lara, María ÁngelesEditorial
MDPI
Materia
Biofuel Bioprocessing Challenge-based learning Computer-based learning Energy engineering Higher education
Date
2020Referencia bibliográfica
Martín-Lara, M.Á.; Ronda, A. Implementation of Modeling Tools for Teaching Biorefinery (Focused on Bioethanol Production) in Biochemical Engineering Courses: Dynamic Modeling of Batch, Semi-Batch, and Continuous Well-Stirred Bioreactors. Energies 2020, 13, 5772. [https://doi.org/10.3390/en13215772]
Résumé
Due to the ever-growing pressure on our planet’s natural resources to supply energy,
the production of bioethanol by fermentation of lignocellulosic biomass is increasingly important
in courses related to engineering and energy. Moreover, recent changes in the teaching–learning
paradigm make necessary the introduction of novel teaching tools where students are the protagonist
of their education. In this context, the purpose of this study is to compare the results obtained
after traditional lessons with those obtained after the implementation of various computer activities
based on modeling and simulation of bioreactors to teach biorefinery concepts focused on bioethanol
production. Berkeley Madonna was chosen as the digital simulation software package because it is
user-friendly, fast, and easy to program. This software allowed students to gain experience writing
models that let optimize fermentations in well-stirred bioreactors and others bioprocess of industrial
interest. The students (those who participated in the modeling-simulation classes and those who
participated in traditional ones) completed a questionnaire and a cognitive test at the end of the
course. Students that participated in modeling-simulation classes got a better score than students that
participated in traditional classes. Therefore, the study showed the improvement in the understanding
of the biorefinery concepts and the students improved their grades. Finally, students’ perception
about the proposed modeling-simulation learning was also analyzed and they rated the efficiency of
this new learning methodology as satisfactory. There are very few studies providing information
about educational experiences regarding the development of skills for the formulation, interpretation,
simplification, and use of mathematical models based on mass balances and simple microbial kinetics
in biochemical engineering courses. The experience described in this work can be used by professors
to plan and conduct courses based on the modeling of biochemical engineering problems.