Simulation and optimization of a horizontal ammonia synthesis reactor using genetic algorithm

Azarhoosh, Mohammad Javad; Farivar, Foad; Ebrahim, H. Ale

doi:10.1039/c3ra45410j

Cited by 50 publications

(27 citation statements)

References 32 publications

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“…) using the fourth‐order Runge–Kutta method and estimating rate equations. Also the optimization objective function was applied to minimize the fitness function .…”

Section: Resultsmentioning

confidence: 99%

“…Then, the natural logarithm of the mean rate constants at different space velocities was plotted against 1/T and the preexponential factor and activation energy for each reaction were calculated using the Arrhenius plot. A population size of 200 was chosen with mutation probability of 0.1 and crossover probability of 0.7 (by the trial and error method to obtain the best performance and minimum error) [2,[34][35][36][37]. Gaussian and arithmetic methods were selected as mutation and crossover rules [2,[34][35][36][37].…”

Section: Preexponential Parameters and Activation Energies Of Reactiomentioning

confidence: 99%

“…A population size of 200 was chosen with mutation probability of 0.1 and crossover probability of 0.7 (by the trial and error method to obtain the best performance and minimum error) [2,[34][35][36][37]. Gaussian and arithmetic methods were selected as mutation and crossover rules [2,[34][35][36][37]. The fitness function was equal to the amount of difference between mass fraction at an experimental and computational mode that was obtained by solving the reactor model (Eq.…”

Section: Preexponential Parameters and Activation Energies Of Reactiomentioning

confidence: 99%

“…(5)) using the fourth-order Runge-Kutta method and estimating rate equations. Also the optimization objective function was applied to minimize the fitness function [34][35][36][37]. Figure 4 shows Arrhenius plots of the reactions rate constants.…”

Section: Preexponential Parameters and Activation Energies Of Reactiomentioning

confidence: 99%

See 3 more Smart Citations

A Dynamic Kinetic Model for Methanol to Light Olefins Reactions over a Nanohierarchical SAPO‐34 Catalyst: Catalyst Synthesis, Model Presentation, and Validation at the Bench Scale

Azarhoosh

Halladj

Askari

2018

Int J of Chemical Kinetics

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This study includes three main parts: synthesizing the hierarchical silicoaluminophosphate (SAPO‐34) catalyst, evaluating the performance of this modified catalyst in the methanol to light olefins (MTO) process, and providing a new dynamic kinetic model for the modified catalyst. At first, a carbon nanotube (CNT) was used as a mesopore template in the sonochemical synthesis of SAPO‐34 hierarchical catalyst. By comparing the performance of this hierarchical catalyst and the common catalyst in the MTO process, it is observed that better performance is obtained on a modified catalysts for a longer period of time. Then, nine process tests were performed in differential fixed bed reactors at different temperatures and space velocities to obtain the kinetic model of the desired catalyst in the MTO process. Finally, the dynamic kinetic model of the modified SAPO‐34 catalyst was considered for main reactions in the MTO process. In this model, the rate equations were assumed elementary and lumped, and the decreasing of the catalyst activity over time on stream was also considered. The reactions constant and catalyst activity coefficient for different reactions were obtained by simultaneous connection of the code related to the reactor model and the genetic algorithm and genetic programming codes. The results obtained from the kinetic model were consistent with the experimental results.

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“…) using the fourth‐order Runge–Kutta method and estimating rate equations. Also the optimization objective function was applied to minimize the fitness function .…”

Section: Resultsmentioning

confidence: 99%

Section: Preexponential Parameters and Activation Energies Of Reactiomentioning

confidence: 99%

Section: Preexponential Parameters and Activation Energies Of Reactiomentioning

confidence: 99%

Section: Preexponential Parameters and Activation Energies Of Reactiomentioning

confidence: 99%

See 2 more Smart Citations

A Dynamic Kinetic Model for Methanol to Light Olefins Reactions over a Nanohierarchical SAPO‐34 Catalyst: Catalyst Synthesis, Model Presentation, and Validation at the Bench Scale

Azarhoosh

Halladj

Askari

2018

Int J of Chemical Kinetics

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“…A large amount of optimisation work on multi-bed reactor systems can also be found [14][15][16][17][18]. A four-bed direct cooling reactor system for optimal operational temperature was presented by Gaines [14], whereas an indirect cooling reactor system for maximum N 2 conversion by a one-dimensional homogeneous model was analysed by Aka and Rapheel [15].…”

Section: Ammonia Synthesis Reactor Systemsmentioning

confidence: 99%

Optimisation of the Autothermal NH3 Production Process for Power-to-Ammonia

Cheema

Krewer

2019

Processes

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The power-to-ammonia process requires flexible operation due to intermittent renewable energy supply. In this work, we analyse three-bed autothermal reactor systems for design and off-design performance for power-to-ammonia application. The five reactor systems differ in terms of inter-stage cooling methods, i.e., direct cooling by quenching (2Q), combination of indirect and direct cooling (HQ and QH) and indirect cooling (2H) with variations. At optimum nominal operation conditions, the inter-stage indirect cooling (2H) reactor systems result in the highest NH3 production. For off-design performance analysis, NH3 production is minimised or maximised by varying one of the following process variables at a time: inert gas, feed flow rate or H2-to-N2 ratio. For each variation, the effect on H2 intake, recycle stream load and recycle-to-feed ratio is also analysed. Among the three process variables, the H2-to-N2 ratio provided ca. 70% lower NH3 production and 70% lower H2 intake than at nominal operation for all five reactor systems. Operation of autothermal reactor systems at significantly lower H2 intake makes them reliable for power-to-ammonia application; as during energy outage period, shutdown can be delayed.

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Sustainable ammonia production through process synthesis and global optimization

et al. 2018

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Current ammonia production technologies have a significant carbon footprint. In this study, we present a process synthesis and global optimization framework to discover the efficient utilization of renewable resources in ammonia production. Competing technologies are incorporated in a process superstructure where biomass, wind, and solar routes are compared with the natural gas‐based reference case. A deterministic global optimization‐based branch‐and‐bound algorithm is used to solve the resulting large‐scale nonconvex mixed‐integer nonlinear programming problem (MINLP). Case studies for Texas, California, and Iowa are conducted to examine the effects of different feedstock prices and availabilities. Results indicate that profitability of ammonia production is highly sensitive to feedstock and electricity prices, as well as greenhouse gas (GHG) restrictions. Under strict 75% GHG reductions, biomass to ammonia route is found to be competitive with natural gas route, whereas wind and solar to ammonia routes require further improvement to compete with those two routes. © 2018 American Institute of Chemical Engineers AIChE J, 65: e16498 2019

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Simulation and optimization of a horizontal ammonia synthesis reactor using genetic algorithm

Abstract: A new method (improved shooting method) is used for effectiveness factor calculation by the diffusion-reaction approach.

Cited by 50 publications

References 32 publications

A Dynamic Kinetic Model for Methanol to Light Olefins Reactions over a Nanohierarchical SAPO‐34 Catalyst: Catalyst Synthesis, Model Presentation, and Validation at the Bench Scale

A Dynamic Kinetic Model for Methanol to Light Olefins Reactions over a Nanohierarchical SAPO‐34 Catalyst: Catalyst Synthesis, Model Presentation, and Validation at the Bench Scale

Optimisation of the Autothermal NH3 Production Process for Power-to-Ammonia

Sustainable ammonia production through process synthesis and global optimization

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