Genetic algorithms for optimisation of chemical kinetics reaction mechanisms

Elliott, L.; Ingham, D.B.; Kyne, A. G.; Mera, N. S.; Pourkashanian, Mohamed; Wilson, C. W.

doi:10.1016/j.pecs.2004.02.002

Cited by 150 publications

(72 citation statements)

References 30 publications

(104 reference statements)

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“…They have already been applied to the optimization of combustion and chemical kinetics problems, including heterogeneous [199] and homogeneous [200] reaction mechanisms.…”

Section: A Genetic Algorithm For Automated Optimizationmentioning

confidence: 99%

Generalized pyrolysis model for combustible solids

Lautenberger

Fernandez-Pello

2009

Fire Safety Journal

307

259

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This dissertation presents the derivation, numerical implementation, and verification/validation of a generalized model that can be used to simulate the pyrolysis, gasification, and burning of a wide range of solid fuels encountered in fires. The model can be applied to noncharring and charring solids, composites, intumescent coatings, and smolder in porous media. Care is taken to make the model as general as possible, allowing the user to determine the appropriate level of complexity to include in a simulation. The model considers a user-specified number of gas phase and condensed phase species, each having its own temperature-dependent thermophysical properties.Any number of heterogeneous (gas-solid) or homogeneous (solid-solid or gas-gas) reactions can be specified. Both in-depth radiation transfer through semi-transparent media and radiation transport across pores are considered. Volume change (surface regression or swelling/intumescence) is handled by allowing the size of grid points to change as dictated by mass conservation. All volatiles generated inside the solid escape to the ambient with no resistance to mass transfer unless a pressure solver is invoked; the resultant flow of volatiles is then calculated according to Darcy's law. A gas phase 2 convective-diffusive solver can be invoked to determine the composition of the volatiles.Oxidative pyrolysis is simulated by modeling diffusion of oxygen from the ambient into the pyrolyzing solid where it may participate in reactions. Consequently, the mass flux and composition of volatiles escaping from the solid can be calculated. To aid in determining the required input parameters, the model is coupled to a genetic algorithm that can be used to estimate the required input parameters from bench-scale fire tests or thermogravimetric analysis.

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“…They have already been applied to the optimization of combustion and chemical kinetics problems, including heterogeneous [199] and homogeneous [200] reaction mechanisms.…”

Section: A Genetic Algorithm For Automated Optimizationmentioning

confidence: 99%

Generalized pyrolysis model for combustible solids

Lautenberger

Fernandez-Pello

2009

Fire Safety Journal

307

259

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“…In the last decade, several genetic algorithms have been proposed for finding the optimal set of rate coefficients for reduced models of reaction mechanisms (12). In those formulations, the optimization problem entails the evaluation of an objective function that compares predicted and measured species concentrations.…”

Section: Application Of the Gfe To The Determination Of The Optimal Smentioning

confidence: 99%

A generalized Fisher equation and its utility in chemical kinetics

Ross

Villaverde

Banga

et al. 2010

Proc. Natl. Acad. Sci. U.S.A.

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A generalized Fisher equation (GFE) relates the time derivative of the average of the intrinsic rate of growth to its variance. The GFE is an exact mathematical result that has been widely used in population dynamics and genetics, where it originated. Here we demonstrate that the GFE can also be useful in other fields, specifically in chemistry, with models of two chemical reaction systems for which the mechanisms and rate coefficients correspond reasonably well to experiments. A bad fit of the GFE can be a sign of high levels of measurement noise; for low or moderate levels of noise, fulfillment of the GFE is not degraded. Hence, the GFE presents a noise threshold that may be used to test the validity of experimental measurements without requiring any additional information. In a different approach information about the system (model) is included in the calculations. In that case, the discrepancy with the GFE can be used as an optimization criterion for the determination of rate coefficients in a given reaction mechanism. The generalized form of Fisher equation (GFE) holds for temporal functions, which are different from zero (for chemical reaction systems this means strictly positive) with continuous second-order derivatives. These Fisher equations are exact results, which are independent of the detailed kinetics of the process: They are valid whether the evolution equations are linear or nonlinear, or local or nonlocal in space and/or time (2). Here we show that the GFE can be useful in chemical kinetics. This is tested with two chemical reaction systems, for which both the reaction mechanism and the rate coefficients are reasonably well known and correspond to experiments. The use of the GFE is new for chemical kinetics, a subject used in many fields other than chemistry, such as biology, biotechnology, chemical engineering, materials science, etc.In Generalized Form of the Fisher Equation we define the notation to write the GFE as in ref. 5. Then, in Use of the GFE for Testing Experimental Measurements we discuss the effect of noise.If the agreement with the GFE is calculated using experimentally measured concentrations-or concentrations generated with a nominal model-and rates of growth analytically calculated with a set of rate coefficients, the fit to the GFE depends on the values of these rates coefficients. For a given reaction system, optimal rate coefficients yield minimum deviation from the GFE. Hence the GFE can be used as a general criterion in optimization

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“…GAs are capable of quickly finding promising regions of the search space but may take a relatively long time to reach a fine localized solution. GAs have been previously applied to the chemical-kinetics of combustion, specially to 11 homogeneous gas-reactions [31,32,33], with some papers addressing heterogeneous reactions, like catalytic reactions [34], and polymer curing [35]. GAs and a similar methodology to the one presented here have been applied by the authors to estimate the solid-phase kinetics and physical properties for ?re modeling from bench-scale ?re experiments [36].…”

Section: Genetic Algorithms (Text Reduced 20%)mentioning

confidence: 99%

Application of genetic algorithms and thermogravimetry to determine the kinetics of polyurethane foam in smoldering combustion

Rein

Lautenberger

Fernandez‐Pello

et al. 2006

Combustion and Flame

222

155

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In this work, the kinetic parameters governing the thermal and oxidative degradation of flexible polyurethane foam are determined using thermogravimetric data and a genetic algorithm. These kinetic parameters are needed in the theoretical modeling of the foam's smoldering behavior.Experimental thermogravimetric mass-loss data are used to explore the kinetics of polyurethane foam and to propose a mechanism consisting of five reactions. A lumped model of solid mass-loss based on Arrhenius-type reaction rates and the five-step mechanism is developed to predict the polyurethane thermal degradation. The predictions are compared to the thermogravimetric measurements, and using a genetic algorithm, the method finds the kinetic and stoichiometric parameters that provide the best agreement between the lumped model and the experiments. To date, no study has attempted to describe both forward and opposed smolder-propagation with the same kinetic mechanism. Thus, in order to verify that the polyurethane kinetics determined from thermogravimetric experiments can be used to describe the reactions involved in polyurethane smoldering combustion, the five-step mechanism and its kinetic parameters are incorporated into a simple species model of smoldering combustion. It is shown that the species model agrees with experimental observations and that it captures phenomenologically the spatial distribution of the different species and the reactions in the vicinity of the front, for both forward and opposed propagation. The results indicate that the kinetic scheme proposed here is the first one to describe smoldering combustion of polyurethane in both propagation modes.

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Genetic algorithms for optimisation of chemical kinetics reaction mechanisms

Cited by 150 publications

References 30 publications

Generalized pyrolysis model for combustible solids

Generalized pyrolysis model for combustible solids

A generalized Fisher equation and its utility in chemical kinetics

Application of genetic algorithms and thermogravimetry to determine the kinetics of polyurethane foam in smoldering combustion

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