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14. Influence of impurities on the use of Fe-based powder as sustainable fuel.

Author

Choisez, Laurine, Van Ende, Marie-Aline, Bruyr, Zakarie, Contino, Francesco, and Jacques, Pascal J.

Subjects
CLEAN energy, SUSTAINABILITY, FLUIDIZED bed reactors, METAL-base fuel, ENERGY development, FLAME temperature
Abstract

Sustainable energy production, inherently transient and non-uniformly distributed around the world, requires the rapid development of sustainable energy storage technologies. Recently, pure iron powder was proposed as a high-energy density carrier. While promising, challenges are faced, such as nanoparticle emissions, micro-explosions or cavitation. In this work, a screening of the impact of the most common impurities in iron sources on these mechanisms was conducted through purely thermodynamic simulations. Two idealized models were considered to obtain a range of plausible flame temperatures and emitted gases when considering a purely diffusive regime in standard conditions and stoichiometric air–fuel mixture. The flame temperature and iron evaporation are increasing with the specific energy. A strong evaporation of C, S, Mo, Cu and P is also expected. Most impurities are predicted to decrease cavitation, except for Mn and MnO. The regeneration process by hydrogen-based direct reduction in fluidized bed reactors is also discussed. MgO and CaO are the most promising additions in terms of reducing nanoparticles and porosities, as well as to improve the fluidization and reduction kinetics of the combusted products. The potential of Fe powder as sustainable fuel, already very promising, could be further improved by the addition of selectively chosen impurities. This article is part of the discussion meeting issue 'Sustainable metals: science and systems'. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Comprehensive Analyses on the Influential Factors in Supersonic Combustion Simulation Using Dynamic Adaptive Chemistry Method.

Author

Wu, Kun, Contino, Francesco, and Fan, Xuejun

Subjects
LARGE eddy simulation models, COMBUSTION kinetics, COMBUSTION, FACTOR analysis, REACTIVE flow, DYNAMIC simulation
Abstract

To overcome the major challenge of reactive flow simulation for chemical kinetics dominated flame dynamics in supersonic combustion, on-the-fly mechanism reduction for high fidelity simulation of scramjet becomes mandatory. For dynamic adaptive chemistry (DAC) methodology, there are three major factors controlling the accuracy and efficiency of the overall simulation, namely, the mechanism reduction method, error threshold value $${\varepsilon _{DAC}}$$ ε DAC , and search initiating species (SIS). In the present work, systematic investigations of the three influential factors were conducted for large eddy simulation of ethylene-fueled supersonic combustion within a unified DAC framework. The results show that all the four mechanism reduction methods, i.e., DRG, DRGEP, PFA, and DAC-L, are adequate for the combustor's global performance prediction regarding the wall pressure, stable combustion productions, and temperature. However, for intricate flame stabilization characteristics, the DRG, DRGEP, and DAC-L methods yield comparable prediction accuracy in radical distributions, whereas the PFA method leads to relatively large discrepancies compared to direct integration with the detailed mechanism. The DRGEP method obtains the best balance between numerical accuracy and computational efficiency among the four methods, while the PFA method is the most computationally demanding one. Regarding the mechanism reduction error threshold value, the relative errors in physical property predictions increase as the relaxation of the error threshold value. And the comparative study suggests that the $${\varepsilon _{DAC}}$$ ε DAC should not exceed $${10^{- 4}}$$ 10 − 4 for high fidelity simulations of supersonic combustion. Furthermore, the stable species combination, namely, fuel, O2, and N2 incurs larger relative errors in radical mass fraction prediction than the combination including fuel and intermediate species HO2 and CO. Nevertheless, the latter is less computationally efficient than the former as it requires 15% more CPU time to solve the stiff ODE system of the resultant skeletal mechanism. It should be noted that the computational overheads for mechanism reduction under various $${\varepsilon _{DAC}}$$ ε DAC values and SIS combinations are almost the same, and the overall computational efficiency is mainly determined by the CPU time for solving the stiff ODE system of the size-reduced skeletal mechanisms. [ABSTRACT FROM AUTHOR]

Published
2024
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