A Gibbs Energy Minimization Approach for Modeling of Chemical Reactions in a Basic Oxygen Furnace

Kruskopf, Ari; Visuri, Ville‐Valtteri

doi:10.1007/s11663-017-1074-x

Cited by 20 publications

(24 citation statements)

References 43 publications

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“…The speed of each stage of this series-parallel process (sequential-along carbon, parallel-in oxygen) is determined by the rate constants k 1 and k 2 , as well as by the concentrations of the initial, final and intermediate substances [6]. Thus, the emission of carbon monoxide can be influenced by the kinetics (rate of reaction) of the process and the conditions of thermomass exchange in the unit.…”

Section: Research Resultsmentioning

confidence: 99%

Causes of the Exceptional Emissions in the Conditions of Compliance of Technological Regulations

Olegovna¹

2019

BJSTR

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Section: Research Resultsmentioning

confidence: 99%

Causes of the Exceptional Emissions in the Conditions of Compliance of Technological Regulations

Olegovna¹

2019

BJSTR

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“…This formulation has proven to be very successful in large chemical systems involving as many as 118 components (Piro, 2011) and relatively simple ideal and nonideal solution models (Kruskopf & Visuri, 2017; Piro, Banfield, et al., 2013; Piro, Simunovic, et al., 2013), allowing to model for the first time the temporal and spatial evolution of coupled thermochemical and nuclear reactions of irradiated fuel (Piro, Banfield, et al., 2013; Piro, Simunovic, et al., 2013).…”

Section: Methodsmentioning

confidence: 99%

“…Consequently, numerous Gibbs energy minimization strategies are used depending on the problem dimensionality (number of chemical components) and complexity of the equations of state. This includes, but is not limited to, equality‐ and nonequality‐constrained linear least squares (e.g., Ghiorso, 1983, 1985), linear programming and nonlinear optimization methods (e.g., de Capitani & Brown, 1987), discretization of equations of state in composition‐order space combined with linear programming (e.g., Connolly, 1990, 2005), linear programming and Partitioning Gibbs Energy (PGE; e.g., Kruskopf & Visuri, 2017; Piro, 2011; Piro, Banfield, et al., 2013; Piro, Simunovic, et al., 2013), metaheuristic optimization methods (e.g., Burgos‐Solórzano et al., 2004; Çetin & Keçebaş, 2021; Teh & Rangaiah, 2002), and Lagrangian formulations (e.g., Piro & Simunovic, 2016; W. White et al., 1958).…”

Section: Introductionmentioning

confidence: 99%

MAGEMin, an Efficient Gibbs Energy Minimizer: Application to Igneous Systems

Riel

Kaus

Green

et al. 2022

Geochem Geophys Geosyst

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Prediction of stable mineral equilibria in the Earth's lithosphere is critical to unravel the tectonomagmatic history of exposed geological sections. While the recent advances in geodynamic modeling allow us to explore the dynamics of magmatic transfer in solid mediums, there is to date no available thermodynamic package that can easily be linked and efficiently be accounted for the computation of phase equilibrium in magmatic systems. Moreover, none of the existing tools fully exploit single point calculation parallelization, which strongly hinders their applicability for direct geodynamic coupling or for thermodynamic database inversions. Here, we present a new Mineral Assemblage Gibbs Energy Minimizer (magemin). The package is written as a parallel C library, provides a direct Julia interface, and is callable from any petrological/geodynamic tool. For a given set of pressure, temperature, and bulk‐rock composition magemin uses a combination of linear programming, extended Partitioning Gibbs Energy and gradient‐based local minimization to compute the stable mineral assemblage. We apply our new minimization package to the igneous thermodynamic data set of Holland et al. (2018), https://doi.org/10.1093/petrology/egy048 and produce several phase diagrams at supra‐solidus conditions. The phase diagrams are then directly benchmarked against thermocalc and exhibit very good agreement. The high scalability of magemin on parallel computing facilities opens new horizons, for example, for modeling reactive magma flow, for thermodynamic data set inversion, and for petrological/geophysical applications.

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“…The minimum Gibbs free energy method is effective for analyzing the thermodynamic equilibrium state of multiphase coupling systems. [37][38][39] For any multiphase closed system, when the temperature and pressure are determined, the necessary and sufficient conditions for all reactions in the system to reach equilibrium are that the total Gibbs free energy of the closed system reaches the minimum value and the mass of each element in the system is conserved. The objective function for this problem is presented in Eq.…”

Section: Model Setupmentioning

confidence: 99%

Study on Final Equilibrium State and Process of CO2 Reacting with Fe–C Melt

Zhu

Wei

et al. 2022

Metall Mater Trans B

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To study the final equilibrium state and process of CO2 injecting into the Fe–C melt with different initial carbon contents, a model was established based on the method of minimization of Gibbs free energy and the corresponding experiments were carried out in a high-temperature tube furnace. When CO2 is continuously injected into the Fe–C melt at 1873 K, the final equilibrium state of the system is such that the carbon and oxygen contents in the melt are 0.1977 and 0.0115 wt pct, respectively, and the volume ratio of CO in the gas phase is 85.75 vol pct. When the initial a[O] × a[C] in the melt is greater than those in equilibrium with CO under 0.8575 atm, the CO2 gas removes carbon from the melt. On the contrary, the role of CO2 gas is to add carbon and oxygen to the melt. At the same time, the variation of carbon and oxygen with time obtained by experiments was different from the theoretical calculation at extremely low carbon content, which requires further study.

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A Gibbs Energy Minimization Approach for Modeling of Chemical Reactions in a Basic Oxygen Furnace

Cited by 20 publications

References 43 publications

Causes of the Exceptional Emissions in the Conditions of Compliance of Technological Regulations

Causes of the Exceptional Emissions in the Conditions of Compliance of Technological Regulations

MAGEMin, an Efficient Gibbs Energy Minimizer: Application to Igneous Systems

Study on Final Equilibrium State and Process of CO2 Reacting with Fe–C Melt

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