Computational Investigation of the Influence of Combustion Chamber Characteristics on a Heavy-Duty Ammonia Diesel Dual Fuel Engine

Autor: Youcef Sehili, Khaled Loubar, Lyes Tarabet, Mahfoudh Cerdoun, Clément Lacroix
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Energies, Vol 17, Iss 5, p 1231 (2024)
Druh dokumentu: article
ISSN: 17051231
1996-1073
DOI: 10.3390/en17051231
Popis: In response to increasingly stringent emissions regulations and the depletion of conventional fuel sources, integrating carbon-free fuels into the transport sector has become imperative. While hydrogen (H2) presents significant technical challenges, ammonia (NH3) could present a better alternative offering ease of transport, storage, and distribution, with both ecological and economic advantages. However, ammonia substitution leads to high emissions of unburned NH3, particularly at high loads. Combustion chamber retrofitting has proven to be an effective approach to remedy this problem. In order to overcome the problems associated with the difficult combustion of ammonia in engines, this study aims to investigate the effect of the piston bowl shape of an ammonia/diesel dual fuel engine on the combustion process. The primary objective is to determine the optimal configuration that offers superior engine performance under high load conditions and with high ammonia rates. In this study, a multi-objective optimization approach is used to control the creation of geometries and the swirl rate under the CONVERGETM 3.1 code. To maximize indicated thermal efficiency and demonstrate the influence of hydrogen enrichment on ammonia combustion in ammonia/diesel dual fuel engines, a synergistic approach incorporating hydrogen enrichment of the primary fuel was implemented. Notably, the optimum configuration, featuring an 85% energy contribution from ammonia, outperforms others in terms of combustion efficiency and pollutant reduction. It achieves over 43% reduction in unburned NH3 emissions and a substantial 31% improvement in indicated thermal efficiency.
Databáze: Directory of Open Access Journals
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