Determining Pilot Ignition Delay in Dual-Fuel Medium-Speed Marine Engines Using Methanol or Hydrogen
Parsa, Somayeh and Verhelst, Sebastian LU
(2025)
In Energies
18(12).
- Abstract
Dual-fuel engines are a way of transitioning the marine sector to carbon-neutral fuels like hydrogen and methanol. For the development of these engines, accurate simulation of the combustion process is needed, for which calculating the pilot’s ignition delay is essential. The present work investigates novel methodologies for calculating this. This involves the use of chemical kinetic schemes to compute the ignition delay for various operating conditions. Machine learning techniques are used to train models on these data sets. A neural network model is then implemented in a dual-fuel combustion model to calculate the ignition delay time and is compared using a lookup table or a correlation. The numerical results are compared with... (More)
Dual-fuel engines are a way of transitioning the marine sector to carbon-neutral fuels like hydrogen and methanol. For the development of these engines, accurate simulation of the combustion process is needed, for which calculating the pilot’s ignition delay is essential. The present work investigates novel methodologies for calculating this. This involves the use of chemical kinetic schemes to compute the ignition delay for various operating conditions. Machine learning techniques are used to train models on these data sets. A neural network model is then implemented in a dual-fuel combustion model to calculate the ignition delay time and is compared using a lookup table or a correlation. The numerical results are compared with experimental data from a dual-fuel medium-speed marine engine operating with hydrogen or methanol, from which the method with best accuracy and fastest calculation is selected.
(Less)
- author
- Parsa, Somayeh
and Verhelst, Sebastian
LU
- organization
- publishing date
- 2025-06
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ANN, chemical kinetics, dual fuel, hydrogen, ignition delay, lookup table, machine learning, methanol, multi-zone combustion model
- in
- Energies
- volume
- 18
- issue
- 12
- article number
- 3064
- publisher
- MDPI AG
- external identifiers
-
- scopus:105008985929
- ISSN
- 1996-1073
- DOI
- 10.3390/en18123064
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025 by the authors.
- id
- 8800bf9b-49b8-4f47-ba33-2296b9f6d0dc
- date added to LUP
- 2025-12-16 11:43:47
- date last changed
- 2025-12-16 11:44:29
@article{8800bf9b-49b8-4f47-ba33-2296b9f6d0dc,
abstract = {{<p>Dual-fuel engines are a way of transitioning the marine sector to carbon-neutral fuels like hydrogen and methanol. For the development of these engines, accurate simulation of the combustion process is needed, for which calculating the pilot’s ignition delay is essential. The present work investigates novel methodologies for calculating this. This involves the use of chemical kinetic schemes to compute the ignition delay for various operating conditions. Machine learning techniques are used to train models on these data sets. A neural network model is then implemented in a dual-fuel combustion model to calculate the ignition delay time and is compared using a lookup table or a correlation. The numerical results are compared with experimental data from a dual-fuel medium-speed marine engine operating with hydrogen or methanol, from which the method with best accuracy and fastest calculation is selected.</p>}},
author = {{Parsa, Somayeh and Verhelst, Sebastian}},
issn = {{1996-1073}},
keywords = {{ANN; chemical kinetics; dual fuel; hydrogen; ignition delay; lookup table; machine learning; methanol; multi-zone combustion model}},
language = {{eng}},
number = {{12}},
publisher = {{MDPI AG}},
series = {{Energies}},
title = {{Determining Pilot Ignition Delay in Dual-Fuel Medium-Speed Marine Engines Using Methanol or Hydrogen}},
url = {{http://dx.doi.org/10.3390/en18123064}},
doi = {{10.3390/en18123064}},
volume = {{18}},
year = {{2025}},
}