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Development of a Dashboard for Simulation Workflow Visualization and Optimization of an Ammonia Synthesis Reactor in the HySTrAm Project (Horizon EU).

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Název: Development of a Dashboard for Simulation Workflow Visualization and Optimization of an Ammonia Synthesis Reactor in the HySTrAm Project (Horizon EU).
Autoři: Douvi, Eleni, Douvi, Dimitra, Tsahalis, Jason, Tsahalis, Haralabos-Theodoros
Zdroj: Computation; Feb2026, Vol. 14 Issue 2, p38, 21p
Témata: HABER-Bosch process, DASHBOARDS (Management information systems), FLOW charts, CHEMICAL reactors, HYDROGEN storage, MATHEMATICAL optimization, CATALYST poisoning
Korporace: EUROPEAN Union
Abstrakt: Although hydrogen plays a crucial role in the EU's strategy to reduce greenhouse gas emissions, its storage and transport are technically challenging. If ammonia is produced efficiently, it can be a promising hydrogen carrier, especially in decentralized and flexible conditions. The Horizon EU HySTrAm project addresses this problem by developing a small-scale, containerized demonstration plant consisting of (1) a short-term hydrogen storage container using novel ultraporous materials optimized through machine learning, and (2) an ammonia synthesis reactor based on an improved low-pressure Haber–Bosch process. This paper presents an initial version of a Python (v3.9)-based dashboard designed to visualize and optimize the simulation workflow of the ammonia synthesis process. Designed as a baseline for a future online, automated tool, the dashboard allows the comparison of three reactor configurations already defined through simulations and aligned with the upcoming experimental campaign: single tube, two reactors in parallel swing mode and two reactors in series. Pressures at the inlet/outlet, temperatures across the reactor, operation recipe and ammonia production over time are displayed dynamically to evaluate the performance of the reactor. Future versions will include optimization features, such as the identification of optimal operating modes, the reduction of production time, an increase of productivity, and catalyst degradation estimation. [ABSTRACT FROM AUTHOR]
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Databáze: Biomedical Index
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Abstrakt:Although hydrogen plays a crucial role in the EU's strategy to reduce greenhouse gas emissions, its storage and transport are technically challenging. If ammonia is produced efficiently, it can be a promising hydrogen carrier, especially in decentralized and flexible conditions. The Horizon EU HySTrAm project addresses this problem by developing a small-scale, containerized demonstration plant consisting of (1) a short-term hydrogen storage container using novel ultraporous materials optimized through machine learning, and (2) an ammonia synthesis reactor based on an improved low-pressure Haber–Bosch process. This paper presents an initial version of a Python (v3.9)-based dashboard designed to visualize and optimize the simulation workflow of the ammonia synthesis process. Designed as a baseline for a future online, automated tool, the dashboard allows the comparison of three reactor configurations already defined through simulations and aligned with the upcoming experimental campaign: single tube, two reactors in parallel swing mode and two reactors in series. Pressures at the inlet/outlet, temperatures across the reactor, operation recipe and ammonia production over time are displayed dynamically to evaluate the performance of the reactor. Future versions will include optimization features, such as the identification of optimal operating modes, the reduction of production time, an increase of productivity, and catalyst degradation estimation. [ABSTRACT FROM AUTHOR]
ISSN:20793197
DOI:10.3390/computation14020038