A chemical kinetic computational toolkit for computational modelling and estimation of fuel thermodynamic properties
Date
2023-03-27Author
Sánchez Martínez, Sergio Enrique
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Abstract
It is undeniable that, due to human activity, global warming is one of the most challenging
environmental issues of our time. It is well known that the main source of greenhouse gases
(GHG) is due to the burning of fossil fuels, particularly those used for electricity, heat, and
transportation purposes. These GHG emissions are mostly composed of carbon dioxide (CO2),
unburned hydrocarbons (UHC), nitrous oxides (NOx), soot, and industrial gases. Reducing
these emissions can be achieved by improving the efficiency of the combustion systems.
Therein lies the importance of the development of reliable chemical kinetic mechanisms.
Undoubtedly, as chemical kinetic mechanisms become more detailed so does our
understanding of the chemistry controlling fuel oxidation. For this reason, chemical kinetic
modelling is an essential tool to helping to increase the efficiency and reduce emissions from
combustion systems. However, the complexity and laboriousness of developing and modelling
real fuels make the process challenging. In this thesis chemical kinetic computational codes
have been developed to help automate the development of reliable chemical kinetic
mechanisms. These codes reduce considerably the time of simulation, the human error, and
allows the user to run multiple simulations at the same time. These can include different types
of reactors, such as shock tubes(STs), rapid compression machines(RCMs), jet-stirred reactors
(JSRs), and flow reactors (FRs), along with flame speed (FS) measurements. Moreover, the
user can validate a full database formed from hundreds to thousands of experimental points in
a short period of time, gathering, plotting, and printing out in a user-friendly way all of the
simulated data for sensible interpretation. These simulations can be performed in a server cluster or on a single supercomputer with high performance computing (HPC) with 100s to
1000s of cores, rather than in local machines with a limited number of expensive licenses.
These tools are developed using python language and using open-source libraries including
numpy, pandas, scipy, sundials, matplotlib, and Cantera. Cantera is widely used to solve
problems involving chemical kinetics, thermodynamics, and transport processes. These tools
are widely used in the data science and combustion modelling communities, and the current
suite of tools were designed with licencing and scalability of HPC clusters in mind.
These chemical computational tools are divided into three types; thermochemistry, kinetic and
post-processing codes to make the development of chemical kinetic mechanisms easier. In all
cases, the codes are designed to run automatically. The thermochemistry code, used for gas
phase fuels, calculates the thermodynamic properties including heat capacity, enthalpy and
entropy and generates a file with the thermochemistry data that is essential to run any kinetic
mechanism and validate it against kinetic properties such as ignition delay times (IDTs), and
speciation profiles (SPs). The kinetic code oversees the running of every simulation based on
the experimental conditions from either individual conditions or a large number of them. The
post-processing code allows the user to generate graphs of the experimental data compared
against one, or multiple simulation results, and produces a LaTeX document that converts into
a .pdf file with all results in a formal report format.
To validate the toolkit proposed in this work, a reliable chemical kinetic mechanism was
developed to describe the oxidation of C1 – C3 blends of gaseous hydrocarbons including
methane, ethane, ethylene, and propane for binary, ternary, and quaternary mixtures. This
mechanism was validated against the IDT of the next experimental conditions: T = 666 – 2615
K, p = 0.54 – 91.5 atm, and equivalence ratios (φ) = 0.5 – 2.0, from the University of Galway
(UG) and the physico-chemical fundamentals of combustion (PCFC) experimental database
which was collected in low-pressure/high pressure shock tubes (LP/HPST), and RCMs. Not
only this, but these codes have also been used widely within the context of C3 by other members
of the combustion chemistry centre (C3
) thus supporting the continued optimisation of gasoline
and diesel fuels, amongst others. The application of these mechanisms extends far beyond the
subset of C1 –C3 fuels presented here. Furthermore, the complete validation of the C
3
database
used to take a number of days, but with the application of these codes this time frame has been
reduced to a few hours using HPC servers. Finally, future work should aim to further develop
these tools in a number of ways; (i) in the further deployment on HPC clusters, and (ii) the
addition of further modules for other applications within the wider combustion landscape, such
as automatic rate rule development.