Mathematical Modeling and Genetic Algorithm Optimization of Reactive Absorption of H<sub>2</sub>S

Bashipour, Fatemeh; Khorasani, Saied Nouri; Rahimi, Amir

doi:10.1002/ceat.201400288

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…For these reasons, η did not increase beyond 13.6, wherein the reciprocal effects of the increase and decrease of pH 0 neutralized each other. The same trend for the effect of the solution pH on the values of pollutants absorbed from the gas streams were acquired in the literature 3, 12, 31, 32. Fig.…”

Section: Resultssupporting

confidence: 75%

“…Their results showed that gas dissolution/neutralization is faster at lower NaOH concentrations. In a previous work, a rate‐based mathematical model and a genetic algorithm for the optimization of H 2 S reactive absorption into NaOH/NaOCl solution in a packed column were developed 12. Our literature survey shows that there is no comprehensive modeling study on H 2 S removal from off‐gas streams in spray columns, investigating the operating variables and optimizing the process to maximize the percentage of absorbed H 2 S.…”

Section: Introductionmentioning

confidence: 99%

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H₂S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

2015

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H 2 S removal from an off-gas stream was performed in a spray column by H 2 S reactive absorption into a NaOH solution. The individual and interactive effects of three independent operating variables on the percentage of absorbed H 2 S were investigated: the initial pH of the scrubbing solution, the initial scrubbing solution temperature, and the volumetric liquid-to-gas ratio. The optimum operating variables were determined by response surface methodology (RSM) attaining a percentage of absorbed H 2 S of 98.7 ± 0.2 %. Additionally, the process performance was modeled by an artificial neural network (ANN) to predict the percentage of absorbed H 2 S. The results showed that the experimental data agreed better with the ANN model than with the RSM results.

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Section: Resultssupporting

confidence: 75%

Section: Introductionmentioning

confidence: 99%

H₂S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

2015

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“…Optimization techniques can be developed according to different methodologies, i.e. artificial neural networks and genetic algorithm (Bashipour, Khorasani, and Rahimi 2014;Fernandes 2006), Taguchi method (Tehrani Matin, Bastani, and Kazemian 2009) and RSM (Narimani and Alaei Kadijani 2014;Yu et al 2013).…”

Section: Optimizationmentioning

confidence: 99%

Statistical analysis and optimization for direct dimethyl ether synthesis from syngas over CuO–ZnO–Al2O3/γ-Al2O3 bifunctional catalysts

Einbeigi,

Khorashadizadeh,

Atashi

2024

Preprint

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Direct synthesis of dimethyl ether has been statistically analyzed in terms of product distribution and the effect of operating conditions. The investigated catalyst system consists of a combination of methanol synthesis (CuO–ZnO–Al2O3) and methanol dehydration (γ-Al2O3). The range of operating conditions varied as: T = 200–260 0C, H2/CO = 0.67-2 and SV (Space Velocity) = 41.74-292.68 h− 1 at P = 5.1 MPa. Using data obtained from a fixed bed microreactor, the product selectivity models were developed as functions of the above parameters via response surface methodology. The models were efficiently adjusted to avoid overfitting by considering cross-validation. The effects are shown via 3D diagrams. Single and multi-objective optimizations were then employed to maximize the production of DME and CO conversion and minimize the production of methanol, hydrocarbons, and carbon dioxide. Numerical optimization was performed through desirability charge ranging from zero to one where the highest desirability satisfies optimum conditions. Accordingly, an optimum area was obtained in which a variety of different points can be acceptable. Single-objective optimization provides a vaster area while multi-objective limits the feasible process conditions range.

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“…In other words, Na 2 S production and H 2 S removal from off-gas can occur simultaneously in one process. However, when the main objective of the process is H 2 S removal from off-gas and considering the fact that NaOH solution cannot be easily regenerated, NaOH scrubbers are most often applied for removing small quantities of acid gases containing H 2 S [5,6]. The absorption of H 2 S from off-gas into NaOH solution results in production of Na 2 S through two reversible reactions:…”

Section: Introductionmentioning

confidence: 99%

Experimental Optimization and Modeling of Sodium Sulfide Production from H₂S-Rich Off-Gas via Response Surface Methodology and Artificial Neural Network

Bashipour

Rahimi

Khorasani

et al. 2017

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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-The existence of hydrogen sulfide (H 2 S) in the gas effluents of oil, gas and petrochemical industries causes environmental pollution and equipment corrosion. These gas streams, called offgas, have high H 2 S concentration, which can be used to produce sodium sulfide (Na 2 S) by H 2 S reactive absorption. Na 2 S has a wide variety of applications in chemical industries. In this study, the reactive absorption process was performed using a spray column. Response Surface Methodology (RSM) was applied to design and optimize experiments based on Central Composite Design (CCD). The individual and interactive effects of three independent operating conditions on the weight percent of the produced Na 2 S (Y) were investigated by RSM: initial NaOH concentration (10-20% w/w), scrubbing solution temperature (40-60°C) and liquid-to-gas volumetric ratio (15 9 10 À3 to 25 9 10 À3 ). Furthermore, an Artificial Neural Network (ANN) model was used to predict Y. The results from RSM and ANN models were compared with experimental data by the regression analysis method. The optimum operating conditions specified by RSM resulted in Y of 15.5% at initial NaOH concentration of 19.3% w/w, scrubbing solution temperature of 40°C and liquid-to-gas volumetric ratio of 24.6 9 10 À3 v/v.Résumé -Optimisation expérimentale et modélisation de la production de sulfure de sodium à partir d'H 2 S riche en gaz provenant de la surface d'intervention méthodologique et de réseau de neurones artificiels -La présence de sulfure d'hydrogène (H 2 S) dans les effluents gazeux rejetés par l'industrie pétrolière, gazière et pétrochimique entraîne une pollution de l'environnement ainsi que la corrosion des équipements. Ces flux gazeux, appelés effluents gazeux, présentent une forte concentration de H 2 S qui peut être employée pour produire du sulfure de sodium (Na 2 S) par absorption réactive de H 2 S. Le Na 2 S trouve une multitude d'applications dans les industries chimiques. Dans cette étude, le processus d'absorption réactive a été réalisé avec une colonne à pulvérisation. La méthode des surfaces de réponses (Response Surface Methodology, RSM) a été appliquée pour concevoir et optimiser des expériences basées sur les plans composites centrés (Central Composite Design, CCD). Les effets individuels et interactifs de trois conditions d'exploitation indépendantes sur le pourcentage en poids de Na 2 S produit (Y) ont été analysés par RSM, à savoir : la concentration de NaOH initiale (10 à 20 % p/p), la température de la solution de lavage (40 à 60°C) et le rapport du volume liquide/gaz (15 9 10

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Mathematical Modeling and Genetic Algorithm Optimization of Reactive Absorption of H₂S

Cited by 6 publications

References 28 publications

H₂S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

H₂S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

Statistical analysis and optimization for direct dimethyl ether synthesis from syngas over CuO–ZnO–Al2O3/γ-Al2O3 bifunctional catalysts

Experimental Optimization and Modeling of Sodium Sulfide Production from H₂S-Rich Off-Gas via Response Surface Methodology and Artificial Neural Network

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Mathematical Modeling and Genetic Algorithm Optimization of Reactive Absorption of H2S

Cited by 6 publications

References 28 publications

H2S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

H2S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

Statistical analysis and optimization for direct dimethyl ether synthesis from syngas over CuO–ZnO–Al2O3/γ-Al2O3 bifunctional catalysts

Experimental Optimization and Modeling of Sodium Sulfide Production from H2S-Rich Off-Gas via Response Surface Methodology and Artificial Neural Network

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Mathematical Modeling and Genetic Algorithm Optimization of Reactive Absorption of H₂S

H₂S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

H₂S Reactive Absorption from Off‐Gas in a Spray Column: Insights from Experiments and Modeling

Experimental Optimization and Modeling of Sodium Sulfide Production from H₂S-Rich Off-Gas via Response Surface Methodology and Artificial Neural Network