A Comprehensive Analysis of Reactor Modeling Studies for the Methanation of Carbon Oxides
Обзор
| Журнал |
Processes
ISSN: 2227-9717
|
| Вых. Данные |
Год: 2026,
Том: 14,
Номер: 4,
Номер статьи
: 659,
Страниц
: 44
DOI:
10.3390/pr14040659
|
| Ключевые слова |
reactor modeling; kinetic modeling; carbon oxides methanation; power-to-gas |
| Авторы |
Ríos Juan José
1
,
Ancheyta Jorge
2,3
,
Mantilla Angeles
1
,
Elyshev Andrey
3
,
Zagoruiko Andrey
3
|
| Организации |
| 1 |
Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada, Unidad Legaria, Instituto Politécnico Nacional, Legaria 694, Col. Irrigación, Mexico City 11500, Mexico
|
| 2 |
Escuela Superior de Ingeniería Química e Industrias Extractivas, Instituto Politécnico Nacional, Unidad Profesional Adolfo López Mateos, Zacatenco, Mexico City 07738, Mexico
|
| 3 |
School of Natural Sciences, Tyumen State University, 625003 Tyumen, Russia
|
|
Информация о финансировании (1)
|
1
|
Российский научный фонд
|
22-73-10015
|
This work presents a comprehensive analysis of reactor modeling studies for the methanation of COx, with the aim of identifying trends, evaluating modeling strategies, and suggesting a generalized modeling framework. The analysis spans a wide range of configurations, including packed/fixed-bed reactors (immobilized catalyst pellets/particles), fluidized-bed reactors, and structured catalyst reactors, as well as membrane and slurry/bubble-column configurations when applicable. This highlights the diversity of modeling approaches used, ranging from simple 1D pseudo-homogeneous models to complex 2D heterogeneous simulations. Emphasis is placed on the governing assumptions, dimensional formulations, transport phenomena, and kinetic models employed across studies. By systematically comparing these models, this work identifies the most critical modeling assumptions and parameters that govern the prediction reliability of reactor performance (e.g., conversion andtemperatureprofiles) andinformreactor design. Theproposedreactormodelintegrates insights from the literature, balancing model fidelity and computational feasibility, and serves as a foundational tool for future modeling efforts and industrial applications. This work contributes to the field by offering a unified perspective that links model complexity to physical realism, providing valuable guidance in the development of predictive tools for COx methanation systems.