The combustion kinetics of three bio jet fuel compounds farnesane, p-menthane and p-cymene, derived from natural terpenoids, have been investigated experimentally by an atmospheric high temperature flow reactor coupled with molecular beam mass spectrometric detection (MBMS). Quantitative speciation data for their oxidation chemistry in combustion is presented to provide an insight into the combustion behavior and provide detailed validation data for kinetic modeling. The experimental results are compared and discussed to analyze distinct combustion phenomena such as fuel consumption pathways and soot precursor chemistry. The fuel selection focuses on biotechnologically producible terpenoid components, namely the isoalkane 2,6,10-trimethyl dodecane (farnesane), the cycloalkane 1-isopropyl-4-methylcyclohexane (p-menthane) and the branched aromatic compound 1-isopropyl-4-methylbenzene (p-cymene). Literature data on farnesane (recently approved with up to 10% blending in Jet A-1) is limited and even scarcer for the two potential synthetic fuel additive species, p-menthane and p-cymene. The comprehensive, systematic experimental speciation data set including the single fuel components for lean to rich stoichiometries (0.5 to 1.5) is available in the supplemental material to this contribution.
An automated data-centric infrastructure, Process Informatics Model (PrIMe), was applied to validation and optimization of a syngas combustion model. The Bound-to-Bound Data Collaboration (B2BDC) module of PrIMe was employed to discover the limits of parameter modifications based on uncertainty quantification (UQ) and consistency analysis of the model−data system and experimental data, including shock-tube ignition delay times and laminar flame speeds. Existing syngas reaction models are reviewed, and the selected kinetic data are described in detail. Empirical rules were developed and applied to evaluate the uncertainty bounds of the literature experimental data. The initial H 2 /CO reaction model, assembled from 73 reactions and 17 species, was subjected to a B2BDC analysis. For this purpose, a dataset was constructed that included a total of 167 experimental targets and 55 active model parameters. Consistency analysis of the composed dataset revealed disagreement between models and data. Further analysis suggested that removing 45 experimental targets, 8 of which were self-inconsistent, would lead to a consistent dataset. This dataset was subjected to a correlation analysis, which highlights possible directions for parameter modification and model improvement. Additionally, several methods of parameter optimization were applied, some of them unique to the B2BDC framework. The optimized models demonstrated improved agreement with experiments compared to the initially assembled model, and their predictions for experiments not included in the initial dataset (i.e., a blind prediction) were investigated. The results demonstrate benefits of applying the B2BDC methodology for developing predictive kinetic models.
This study initiates the gradual upgrade of the DLR reaction database. The upgrade plan has two main steps: an optimisation of the C 1-C 4 oxidation chemistry and a revision of the polyaromatic hydrocarbon (PAH) formation sub-mechanism based thereupon. The present paper reports the main principles applied to model improvements and results obtained for the acetylene (C 2 H 2) oxidation sub-mechanisms. The principle acetylene oxidation reactions have been revised as well as the detailed chemistry of important intermediates, i.e. methylene, ethynyl, vinylperoxy radical and also diacetylene, vinylacetylene and higher diacetylenes, important for PAH formation. The uncertainty intervals of the studied reactions were statistically evaluated, providing general bounds for the performed modifications to reaction rate coefficients. The first stage of the presented update was performed through revision of the thermochemical data and model optimisation on ignition delay data and laminar flame speed data, since they exhibit lower uncertainty in comparison to species profile data. The final model optimization was obtained through simulations of concentration profiles measured in shock tubes and laminar flames for improvement of the reaction paths and rate coefficients related to acetylene pyrolysis and PAH precursor formation. Approximately 500 data points were analysed. The updated reaction mechanism predicts all simulated experimental data, also not included in the optimisation loop data prom plug flow and jet-stirred reactors, either with good or satisfactory agreement. It was found that the vinylperoxy radical formation and consumption dictate the reaction progress at low temperatures. The performed study clearly determined that acetylene combustion proceeds through the strongly coupled reaction paths of fuel oxidation and PAH precursor formation; the same species are involved in these parallel processes. Therefore, the self-consistent reaction model for acetylene combustion could be obtained only by an optimisation performed on the experimental dataset encompassing both processes.
This manuscript describes a high-temperature flow reactor experiment coupled to the powerful molecular beam mass spectrometry (MBMS) technique. This flexible tool offers a detailed observation of chemical gas-phase kinetics in reacting flows under well-controlled conditions. The vast range of operating conditions available in a laminar flow reactor enables access to extraordinary combustion applications that are typically not achievable by flame experiments. These include rich conditions at high temperatures relevant for gasification processes, the peroxy chemistry governing the low temperature oxidation regime or investigations of complex technical fuels. The presented setup allows measurements of quantitative speciation data for reaction model validation of combustion, gasification and pyrolysis processes, while enabling a systematic general understanding of the reaction chemistry. Validation of kinetic reaction models is generally performed by investigating combustion processes of pure compounds. The flow reactor has been enhanced to be suitable for technical fuels (e.g. multi-component mixtures like Jet A-1) to allow for phenomenological analysis of occurring combustion intermediates like soot precursors or pollutants. The controlled and comparable boundary conditions provided by the experimental design allow for predictions of pollutant formation tendencies. Cold reactants are fed premixed into the reactor that are highly diluted (in around 99 vol% in Ar) in order to suppress self-sustaining combustion reactions. The laminar flowing reactant mixture passes through a known temperature field, while the gas composition is determined at the reactors exhaust as a function of the oven temperature. The flow reactor is operated at atmospheric pressures with temperatures up to 1,800 K. The measurements themselves are performed by decreasing the temperature monotonically at a rate of -200 K/h. With the sensitive MBMS technique, detailed speciation data is acquired and quantified for almost all chemical species in the reactive process, including radical species.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.