Startseite Dynamic modeling and optimization of methanol partial oxidation to formaldehyde over Mo–Fe catalyst in an industrial isothermal reactor
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Dynamic modeling and optimization of methanol partial oxidation to formaldehyde over Mo–Fe catalyst in an industrial isothermal reactor

  • Hossein Zakeri Gheshmi , Mohammad Farsi EMAIL logo und Mohammad Reza Rahimpour
Veröffentlicht/Copyright: 13. Januar 2025

Abstract

In this research, a one-dimensional heterogeneous model is developed to simulate the partial oxidation of methanol to formaldehyde over a molybdenum-iron catalyst in an industrial isothermal reactor at dynamic condition. The considered isothermal reactor is modelled based on the mass and energy balance equations considering catalyst deactivation. Based on the simulation results, decline in the catalyst activity from 1.0 to 0.73 decreases the rate of formaldehyde production rate from 94.9 kmol h−1 to 89.63 kmol h−1 during process run time. Subsequently, a multi-objective optimization problem is programmed to enhance formaldehyde productivity and minimize the production decline during process run time. To select the effective decision variables, a sensitivity analysis is performed based on the developed dynamic model. Then, the programmed multi-objective optimization problem is replaced with a single objective by the weighted sum method, and the problem is handled by the genetic algorithm method to determine the optimal trajectory of coolant temperature. The simulation results showed that the average formaldehyde production rate increases from 92.11 kmol h−1 to 95.22 kmol h−1 when the optimal conditions are applied to the reactor.


Corresponding author: Mohammad Farsi, Department of Chemical Engineering, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz, Iran, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: The author has accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: No use of large language models, AI, and machine learning tools.

  5. Conflict of interest: The author states no conflict of interest.

  6. Research funding: No funding.

  7. Data availability: Not applicable.

References

[1] Environmental Health Criteria, Formaldehyde, World Health Organization, 1989.Suche in Google Scholar

[2] A. A. Owodunni, et al.., “Adhesive application on particleboard from natural fibers: a review,” Polym. Compos., vol. 41, p. 4448, 2020, https://doi.org/10.1002/pc.25749.Suche in Google Scholar

[3] G. Reuss, W. Disteldorf, A. O. Gamer, and A. Hilt, “Formaldehyde,” Ullmann’s Encyclopedia of Industrial Chemistry, 2000, Wiley Online Library.10.1002/14356007.a11_619Suche in Google Scholar PubMed

[4] A. M. Bahmanpour, A. Hoadley, and A. Tanksale, “Critical review and exergy analysis of formaldehyde production processes,” Rev. Chem. Eng., vol. 30, p. 583, 2014, https://doi.org/10.1515/revce-2014-0022.Suche in Google Scholar

[5] J. Thrane, U. V. Mentzel, M. Thorhauge, M. Høj, and A. D. Jensen, “A review and experimental revisit of alternative catalysts for selective oxidation of methanol to formaldehyde,” Catalysts, vol. 11, p. 1329, 2021, https://doi.org/10.3390/catal11111329.Suche in Google Scholar

[6] A. P. V. Soares, M. F. Portela, and A. Kiennemann, “Methanol selective oxidation to formaldehyde over iron-molybdate catalysts,” Catal. Rev., vol. 47, p. 125, 2005, https://doi.org/10.1081/cr-200049088.Suche in Google Scholar

[7] S. Deshmukh, M. van Sint Annaland, and J. Kuipers, “Kinetics of the partial oxidation of methanol over a fe-mo catalyst,” Appl. Catal. A: Gen., vol. 289, p. 240, 2005, https://doi.org/10.1016/j.apcata.2005.05.005.Suche in Google Scholar

[8] B. Partopour and A. G. Dixon, “Effect of particle shape on methanol partial oxidation in a fixed bed using cfd reactor modeling,” AIChE J., vol. 66, p. e16904, 2020, https://doi.org/10.1002/aic.16904.Suche in Google Scholar

[9] A. O. Olatunde, O. A. Olafadehan, and M. A. Usman, “Modeling and simulation of partial oxidation of methanol to formaldehyde on feo/moo3 catalyst in a catalytic fixed bed reactor,” Iran. J. Chem. Chem. Eng., vol. 40, p. 1800, 2021.Suche in Google Scholar

[10] H. Ghahraloud and M. Farsi, “Modeling and optimization of methanol oxidation over metal oxide catalyst in an industrial fixed bed reactor,” J. Taiwan Inst. Chem. Eng., vol. 81, p. 95, 2017, https://doi.org/10.1016/j.jtice.2017.10.003.Suche in Google Scholar

[11] A. Faliks, R. Yetter, C. Floudas, S. Bernasek, M. Fransson, and H. Rabitz, “Optimal control of catalytic methanol conversion to formaldehyde,” J. Phys. Chem., vol. 105, p. 2099, 2001, https://doi.org/10.1021/jp000951z.Suche in Google Scholar

[12] C. G. Braz, A. Mendes, J. Rocha, R. Alvim, and H. A. Matos, “Model of an industrial multitubular reactor for methanol to formaldehyde oxidation in the presence of catalyst deactivation,” Chem. Eng. Sci., vol. 195, p. 347, 2019, https://doi.org/10.1016/j.ces.2018.09.033.Suche in Google Scholar

[13] T. Moustafa, “Simulation of the industrial packed bed catalytic reactor for the partial oxidation of methanol to formaldehyde,” Dev. Chem. Eng. Miner. Process., vol. 11, p. 337, 2003, https://doi.org/10.1002/apj.5500110410.Suche in Google Scholar

[14] H. Dehnamaki and D. Iranshahi, “The effect of flow direction in a novel bifunctional reactor producing formaldehyde, benzene, and hydrogen simultaneously,” Int. J. Hydrogen Energy, vol. 44, p. 11887, 2019, https://doi.org/10.1016/j.ijhydene.2019.02.029.Suche in Google Scholar

[15] K. I. Ivanov and D. Y. Dimitrov, “Deactivation of an industrial iron-molybdate catalyst for methanol oxidation,” Catal. Today, vol. 154, p. 250, 2010, https://doi.org/10.1016/j.cattod.2010.03.051.Suche in Google Scholar

[16] K. V. Raun, “Understanding the deactivation of the iron molybdate catalyst and its influence on the formox process,” Technical University of Denmark, 2018.Suche in Google Scholar

[17] K. V. Raun, M. Thorhauge, M. Høj, and A. D. Jensen, “Modeling of molybdenum transport and pressure drop increase in fixed bed reactors used for selective oxidation of methanol to formaldehyde using iron molybdate catalysts,” Chem. Eng. Sci., vol. 202, p. 347, 2019, https://doi.org/10.1016/j.ces.2019.03.020.Suche in Google Scholar

[18] M. Farsi, A. H. Sani, and P. Riasatian, “Modeling and operability of dme production from syngas in a dual membrane reactor,” Chem. Eng. Res. Des., vol. 112, p. 190, 2016, https://doi.org/10.1016/j.cherd.2016.06.019.Suche in Google Scholar

[19] M. Sarkarzadeh, M. Farsi, and M. Rahimpour, “Modeling and optimization of an industrial hydrogen unit in a crude oil refinery,” Int. J. Hydrogen Energy, vol. 44, p. 10415, 2019, https://doi.org/10.1016/j.ijhydene.2019.02.206.Suche in Google Scholar

[20] S. Sivanandam, S. Deepa, S. Sivanandam, and S. Deepa, “Genetic algorithm optimization problems,” Introd. Genet. Algorithms, p. 165, 2008, https://doi.org/10.1007/978-3-540-73190-0_7.Suche in Google Scholar

Received: 2024-08-11
Accepted: 2024-12-20
Published Online: 2025-01-13

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Heruntergeladen am 14.10.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijcre-2024-0164/html
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