Szczegóły publikacji
Opis bibliograficzny
A numerical analysis of the temperature field evolution during an optimization of the catalyst distribution in a steam reforming reactor / Marcin PAJĄK, Shinji Kimijima, Janusz S. SZMYD // W: ECOS 2021 [Dokument elektroniczny] : 34th International conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems : June 28 –July 2, 2021, Giardini Naxos, Sicily. — Wersja do Windows. — Dane tekstowe. — [Italy : s. n.], [2021]. — S. 1–11. — Wymagania systemowe: Adobe Reader. — Tryb dostępu: https://1drv.ms/f/s!Apzxe9IRmS0Wh_pS-U5F8zDS7c-tAA [2021-09-06]. — Bibliogr. s. 10–11, Abstr. — Dostęp po zalogowaniu
Autorzy (3)
- AGHPająk Marcin
- Kimijima Shinji
- AGHSzmyd Janusz
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 135988 |
|---|---|
| Data dodania do BaDAP | 2021-09-14 |
| Rok publikacji | 2021 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
Abstract
The steam reforming reaction is the most widespread method used for the hydrogen production. Both, for the industrial and small-scale applications. The reforming reaction has a strong endothermic character, meaning that it requires a constant heat supply to proceed. Due to the process’ character, a non-uniform temperature field is forming inside the reactor. The temperature gradients have an adverse influence on the reactor’s lifetime. The catalytic material is degrading rapidly as a consequence of occurring thermal stresses. The presented study addresses the given problem and proposes an optimization of the catalyst distribution as a solution. The catalytic material’s density and morphology are altered. Secondly, the catalyst is locally substituted with a non-reactive metallic foam to suppress the reaction and allow for reheating of the gaseous reactants. For the needs of the presented research an in-house numerical code simulating the reforming reaction is developed. The kinetics included in the code are derived basing on experimental analyses conducted by our team. The optimization procedure is prepared to limit the occurring temperature gradients, with no significant reduction in the overall process’ effectiveness.
