Development of optimised compact chemical kinetic mechanisms to support the transition to net zero
File(s)
Author(s)
Greenblatt, Daniel
Type
Thesis
Abstract
Attitudes towards energy sources and any pollutant emissions as a result of their use
are rapidly changing in a world seeking to reduce the rate of climate change. Renewable
electricity generation is beginning to displace the legacy fossil fuel combustion
based devices. However, due to intermittency issues with these renewable sources
in the power generation sector and the scale and diversity of the transportation sector,
combustion devices will linger in the mix, perhaps even indefinitely through
the use of renewable fuels. Therefore, it is paramount that ever more stringent
pollutant emission regulations are set and met and in order to achieve this, further
understanding and computational modelling capabilities of the fuels to be used is
required. In this work, chemical kinetic models are further developed and refined
and comprehensive validation used to assess their ability to predict both global
(burning velocities, ignition delay times) and detailed (speciation) properties. The
fuel components studied in this work include the primary reference fuels, iso-octane
and n-heptane, which represent the base level chemicals used to approximate real
fuels in both laboratory-based research and computational surrogates. Additionally,
with the advent of green hydrogen and its formation into green ammonia the study of
fuel alternatives, such as ammonia, and fuel enhancers, such as nitromethane, have
been included in this work. The chemical kinetic models are compact to allow for
their direct implementation in computing dynamic systems. All mechanisms provide
good to excellent agreement with experimental data for burning velocities and
ignition delay times, and an assessment of their ability to predict speciation results
with key sensitivities and uncertainties is outlined. Finally, these mechanisms have
been implemented to consider the key trends at conditions of practical relevance,
with a focus on the characteristic timescales within flames.
are rapidly changing in a world seeking to reduce the rate of climate change. Renewable
electricity generation is beginning to displace the legacy fossil fuel combustion
based devices. However, due to intermittency issues with these renewable sources
in the power generation sector and the scale and diversity of the transportation sector,
combustion devices will linger in the mix, perhaps even indefinitely through
the use of renewable fuels. Therefore, it is paramount that ever more stringent
pollutant emission regulations are set and met and in order to achieve this, further
understanding and computational modelling capabilities of the fuels to be used is
required. In this work, chemical kinetic models are further developed and refined
and comprehensive validation used to assess their ability to predict both global
(burning velocities, ignition delay times) and detailed (speciation) properties. The
fuel components studied in this work include the primary reference fuels, iso-octane
and n-heptane, which represent the base level chemicals used to approximate real
fuels in both laboratory-based research and computational surrogates. Additionally,
with the advent of green hydrogen and its formation into green ammonia the study of
fuel alternatives, such as ammonia, and fuel enhancers, such as nitromethane, have
been included in this work. The chemical kinetic models are compact to allow for
their direct implementation in computing dynamic systems. All mechanisms provide
good to excellent agreement with experimental data for burning velocities and
ignition delay times, and an assessment of their ability to predict speciation results
with key sensitivities and uncertainties is outlined. Finally, these mechanisms have
been implemented to consider the key trends at conditions of practical relevance,
with a focus on the characteristic timescales within flames.
Version
Open Access
Date Issued
2023-03
Date Awarded
2023-10
Copyright Statement
Creative Commons Attribution NonCommercial NoDerivatives Licence
Advisor
Lindstedt, Peter
Aleiferis, Pavlos
Publisher Department
Mechanical Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)