Teaching chemical reaction engineering using EMSO simulator

Rodrigues, Rodolfo; Soares, Rafael de Pelegrini; Secchi, Argimiro Resende

doi:10.1002/cae.20255

Cited by 28 publications

(20 citation statements)

References 9 publications

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“…Its modeling language follows an object-oriented paradigm, which enables inheritance and composition. Such features allow the creation of complex models through the extension and combination of simpler ones (Rodrigues et al, 2010). Another important characteristic of this software is its extensibility through plug-ins, which enhance its fl exibility.…”

Section: Methodsmentioning

confidence: 99%

Comparing a Dynamic Fed-Batch and a Continuous Steady-State Simulation of Ethanol Fermentation in a Distillery to a Stoichiometric Conversion Simulation

Fonseca

Costa

Cruz

2017

Braz. J. Chem. Eng.

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-An autonomous sugarcane bioethanol plant was simulated in EMSO software, an equation oriented process simulator. Three types of fermentation units were simulated: a six parallel fed-batch reactor system, a set of four CSTR in steady state and one consisting of a single stoichiometric reactor. Stoichiometric models are less accurate than kinetic-based fermentation models used for fed-batch and continuous fermenter simulations, since they do not account for inhibition effects and depend on a known conversion rate of reactant to be specified instead. On the other hand, stoichiometric models are faster and simpler to converge. In this study it was found that the conversion rates of sugar for the fermentation systems analyzed were predictable from information on the composition of the juice stream.Those rates were used in the stoichiometric model, which accurately reproduced the results from both the fed-batch and the continuous fermenter system.

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Section: Methodsmentioning

confidence: 99%

Comparing a Dynamic Fed-Batch and a Continuous Steady-State Simulation of Ethanol Fermentation in a Distillery to a Stoichiometric Conversion Simulation

Fonseca

Costa

Cruz

2017

Braz. J. Chem. Eng.

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“…In Results panel (label 5), user can check the results after running the model. For more details about EMSO environment software, the reader is referred to Rodrigues et al [23]. To solve an optimization problem, the user must use a consistent model, that is, a model with zero degree of freedom, and indicate which of the model specifications should be set free, as degrees of freedom.…”

Section: Using Emso Software For Educational Purposesmentioning

confidence: 99%

Optimization of chemical engineering problems with EMSO software

Henrique

Sousa

Secchi

et al. 2017

Comp Applic In Engineering

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EMSO software, a free tool for teaching and academic research, presents a favorable environment for simulation and optimization of chemical engineering problems. Although its use in research activities have been demonstrated in the literature, its application as a supporting tool for educational purposes in process systems engineering courses has not been evaluated. The objective of this paper is to demonstrate that this software is suitable as a tool for educational purposes in process systems engineering courses at undergraduate (complementary elective subject) and graduate levels. To accomplish this task, different cases studies, encompassing different sort of programming formulations, are proposed and solved with different solvers in EMSO.

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“…Understanding the influence of parameters in a given system or process is an important issue not only in network engineering education, but also in other engineering disciplines. This is the reason why simulators are also employed in disciplines such as chemical engineering [32], electronics engineering [33], mechanical engineering [34], or metallurgical engineering [35] in order to help students understand the relationship between different types of parameters and systems or processes.…”

Section: Study Of a Sample Network Scenariomentioning

confidence: 99%

A grid service‐based Distributed Network Simulation Environment for computer networks education

Bote‐Lorenzo

Asensio-Pérez

Sánchez

et al. 2012

Comp Applic In Engineering

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This paper presents a Distributed Network Simulation Environment (DNSE) based on grid technology that, unlike the well-known ns-2 simulator, provides two important features that facilitate the study of network scenarios that require running multiple simulations. First, the DNSE is capable of automatically handling the realization of multiple distributed simulations with the aim of completing all simulations in a reasonable amount of time. Second, the DNSE integrates the realization of simulations with the analysis of their results in an intuitive GUI in order to relieve students from the burden of launching multiple simulations and handling the many output files that may be generated to study the results. The performance analysis of the DNSE shows that it can significantly reduce the time required to complete multiple simulations. Furthermore, the assessment of an experience with students evidence that the DNSE can successfully support a real learning scenario and that students prefer using the DNSE over the ns-2.

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Teaching chemical reaction engineering using EMSO simulator

Cited by 28 publications

References 9 publications

Comparing a Dynamic Fed-Batch and a Continuous Steady-State Simulation of Ethanol Fermentation in a Distillery to a Stoichiometric Conversion Simulation

Comparing a Dynamic Fed-Batch and a Continuous Steady-State Simulation of Ethanol Fermentation in a Distillery to a Stoichiometric Conversion Simulation

Optimization of chemical engineering problems with EMSO software

A grid service‐based Distributed Network Simulation Environment for computer networks education

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