Modeling of a Single-Tube Steam Methane Reformer: Choice Between Flue Gas Heating and Infrared Burner DOI

А. Б. Шигаров,

Д. И. Потемкин

Petroleum Chemistry, Journal Year: 2024, Volume and Issue: 64(11), P. 1286 - 1299

Published: Dec. 1, 2024

Language: Английский

Hydrogen integration in power grids, infrastructure demands and techno-economic assessment: A comprehensive review DOI
Surajudeen Sikiru, Habeeb Bolaji Adedayo, John Oluwadamilola Olutoki

et al.

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 104, P. 114520 - 114520

Published: Nov. 9, 2024

Language: Английский

Citations

2
Techno-economic and environmental analysis of heat sources for steam methane reforming in microgrids DOI

Mohammed M. Mishref,

Makoto Tanaka

International Journal of Hydrogen Energy, Journal Year: 2023, Volume and Issue: 53, P. 1387 - 1395

Published: Dec. 9, 2023

Language: Английский

Citations

5
Pilot-scale SOE-MCFC hybrid system for Co2/H2 mixture production – First experiences in the “Tennessee” project DOI
J. Milewski, Arkadiusz Szczęśniak, Aliaksandr Martsinchyk

et al.

International Journal of Hydrogen Energy, Journal Year: 2023, Volume and Issue: 52, P. 1369 - 1380

Published: Oct. 25, 2023

Language: Английский

Citations

3
Integrating Experimental and Numerical Data for Improved Steam Reforming Simulation with Deep Learning DOI Open Access

Zofia Pizoń,

Shinji Kimijima,

Grzegorz Brus

et al.

Journal of Physics Conference Series, Journal Year: 2024, Volume and Issue: 2812(1), P. 012024 - 012024

Published: Aug. 1, 2024

Abstract In this paper, a data-driven methane steam reforming simulation is developed and used to predict the post-reaction mixture composition. Until today, remains predominant hydrogen production method, yet modeling its complex reactions significant challenge due intricate interplay of process variables. Here, we show an artificial neural network simulator that can effectively model these reactions, offering precise predictions based on parameters like temperature, inlet gas composition, flow, nickel catalyst mass. Our approach data curation integrates experimental, interpolated, theoretically calculated values refining by assessing relative importance each category. Various structures were tested before ultimately identifying optimal architecture with 5-6-8-6-4 structure. The underwent 6000 epochs training, leading demonstrates excellent agreement experimental observations, as evidenced mean squared error 0.000217 Pearson correlation coefficient 0.965. Moreover, all trajectories predicted are characterized smooth course within physical range values. Therefore, work overcomes common in chemical using networks also sets possible direction for future research field.

Language: Английский

Citations

0
Supercritical Water Gasification of Ethanol as Biomass Model Compound in Tandem with Steam Reforming: Kinetic Modeling of the Reforming Step and Techno-Economic Analysis of the Integrated Concept DOI Creative Commons
Athanasios A. Vadarlis, Bruno Lacerda de Oliveira Campos, Angeliki A. Lemonidou

et al.

Industrial & Engineering Chemistry Research, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 18, 2024

Language: Английский

Citations

0
An industrially-validated tube model for steam methane reformers used in direct reduced iron production DOI

J. H. Jeong,

Idalberto Herrera Moya, Sirisha Parvathaneni

et al.

International Journal of Hydrogen Energy, Journal Year: 2024, Volume and Issue: 91, P. 1232 - 1244

Published: Oct. 21, 2024

Language: Английский

Citations

0
Modeling of a Single-Tube Steam Methane Reformer: Choice Between Flue Gas Heating and Infrared Burner DOI

А. Б. Шигаров,

Д. И. Потемкин

Petroleum Chemistry, Journal Year: 2024, Volume and Issue: 64(11), P. 1286 - 1299

Published: Dec. 1, 2024

Language: Английский

Citations

0