Phase Stability and Equilibrium Calculations in Reactive Systems Using Differential Evolution and Tabu Search

Bonilla‐Petriciolet, Adrián; Rangaiah, Gade Pandu; Segovia‐Hernández, Juan Gabriel; Jaime-Leal, José Enrique

doi:10.1142/9789814299213_0013

Cited by 5 publications

(5 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As such, they can be considered one of the most important tools in such a package. Development of these routines in is already underway with two methods available: a rudimentary Rachford–Rice algorithm and a differential evolution algorithm . It is our intention to soon implement the more powerful but more complex flash routines developed by Michelsen and Mollerup and the HELD algorithm .…”

Section: Future Workmentioning

confidence: 99%

Clapeyron.jl: An Extensible, Open-Source Fluid Thermodynamics Toolkit

Walker

Yew

Riedemann

2022

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

Thermodynamic models are often vital when characterizing complex systems, particularly natural gas, electrolyte, polymer, pharmaceutical, and biological systems. However, their implementations have historically been abstruse and cumbersome, and as such, the only options available were black box commercial tools. In this article, we present : a pioneering attempt at an open-source fluid thermodynamics toolkit to build and make use of thermodynamic models. This toolkit is built using Julia, a modern language for scientific computing known for its ease of use, extensibility, and first-class support for differentiable programming. We currently support more models than any package available, including standard cubic (SRK, PR, PSRK, etc.), activity coefficient (NRTL, UNIFAC, etc.), COSMO-based, and the venerable SAFT equations. The property estimation methods supported are extensive, including bulk, VLE, LLE, VLLE, and critical properties. With , researchers and enthusiasts alike will be able to focus on the application and worry less about the implementation.

show abstract

Section: Future Workmentioning

confidence: 99%

Clapeyron.jl: An Extensible, Open-Source Fluid Thermodynamics Toolkit

Walker

Yew

Riedemann

2022

Ind. Eng. Chem. Res.

View full text Add to dashboard Cite

show abstract

“…We have considered a hypothetical system , consisting of six components, where four of them are involved in three independent chemical reactions and the remaining two are inert. This reactive system was analyzed at atmospheric pressure and the presence of vapor−liquid equilibrium was assumed, where both phases were considered ideal. , Although the liquid phase is considered ideal, reactive systems may exhibit reactive azeotropes. ,, The saturation pressure of the pure compounds was calculated with the Antoine equation using the parameters reported in Table . The components A 3 , A 4 , and A 5 were used as reference substances to calculate the transformed mole fractions, which are defined as X 1 = x 1 X 2 = x 2 X 6 = x 6 + x 3 + x 4 + x 5 = 1 − X 1 − X 2 …”

Section: Resultsmentioning

confidence: 99%

“…Reactive System: A 3 S A 4 , A 5 S A 4 , A 4 S A 6 , with Inert A 1 and A 2 . We have considered a hypothetical system 12,13 consisting of six components, where four of them are involved in three independent chemical reactions and the remaining two are inert. This reactive system was analyzed at atmospheric pressure and the presence of vapor-liquid equilibrium was assumed, where both phases were considered ideal.…”

Section: Resultsmentioning

confidence: 99%

“…This reactive system was analyzed at atmospheric pressure and the presence of vapor-liquid equilibrium was assumed, where both phases were considered ideal. 12,13 Although the liquid phase is considered ideal, reactive systems may exhibit reactive azeotropes. 5,6,14 The saturation pressure of the pure compounds was calculated with the Antoine equation using the parameters reported in Table 2.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A Short Method To Calculate Residue Curve Maps in Multireactive and Multicomponent Systems

Carrera-Rodríguez

Segovia‐Hernández

Bonilla-Petriciolet

2011

Ind. Eng. Chem. Res.

Self Cite

View full text Add to dashboard Cite

Reactive residue curve maps (RRCMs) are useful for the design of reactive distillation columns as a tool to establish feasible zones of reaction−separation. However, the calculation of an RRCM usually involves great computational effort due to the nonlinearity of the model equations and its iterative nature for the determination of reactive phase equilibrium. In this study, a simplified method for the generation of RRCMs is presented. This method is based on the application of reaction-invariant composition variables and assumes that the phase equilibrium constants (i.e., the relative volatilities) are independent of the temperature. Specifically, the phase equilibrium constants are calculated using a suitable estimation of the bubble temperature obtained from pure-component boiling temperatures and the reaction-invariant composition of liquid phase. These assumptions avoid iterative phase equilibrium calculations for obtaining a good approximation of RRCMs. Several reactive systems are used to identify the capabilities and limitations of the proposed method.

show abstract

“…Bonilla-Petriciolet et al (2010a) performed a series of parameter tuning simulation of DE and TS on a set of reactive separation processes (the reaction of butyl acetate production at 298.15 K and 1 atm, methyl tert-butyl ether reaction system with inert at 10 atm and 373.15 K, and the reactive system for tertamyl methyl ether synthesis at 335 K and 1.5 atm). Then, the algorithms were applied on two examples represented by (i) a hypothetical multicomponent reactive mixture undergoing three reactions and (ii) esterification reaction of ethanol and acetic acid to form ethyl acetate and water.…”

Section: De Optimization Applied To Deterministic Modelsmentioning

confidence: 99%

The use of differential evolution algorithm for solving chemical engineering problems

Drăgoi

Curteanu

2016

Reviews in Chemical Engineering

View full text Add to dashboard Cite

AbstractDifferential evolution (DE), belonging to the evolutionary algorithm class, is a simple and powerful optimizer with great potential for solving different types of synthetic and real-life problems. Optimization is an important aspect in the chemical engineering area, especially when striving to obtain the best results with a minimum of consumed resources and a minimum of additional by-products. From the optimization point of view, DE seems to be an attractive approach for many researchers who are trying to improve existing systems or to design new ones. In this context, here, a review of the most important approaches applying different versions of DE (simple, modified, or hybridized) for solving specific chemical engineering problems is realized. Based on the idea that optimization can be performed at different levels, two distinct cases were considered – process and model optimization. In both cases, there are a multitude of problems solved, from different points of view and with various parameters, this large area of successful applications indicating the flexibility and performance of DE.

show abstract

Phase Stability and Equilibrium Calculations in Reactive Systems Using Differential Evolution and Tabu Search

Cited by 5 publications

References 19 publications

Clapeyron.jl: An Extensible, Open-Source Fluid Thermodynamics Toolkit

Clapeyron.jl: An Extensible, Open-Source Fluid Thermodynamics Toolkit

A Short Method To Calculate Residue Curve Maps in Multireactive and Multicomponent Systems

The use of differential evolution algorithm for solving chemical engineering problems

Contact Info

Product

Resources

About