FG Thermodynamik / Thermische Verfahrenstechnik
Refine
Document Type
- Doctoral thesis (12)
- Scientific article (3)
Has Fulltext
- yes (15)
Is part of the Bibliography
- no (15)
Keywords
- Reaktionsmechanismus (4)
- CFD (3)
- NOx (3)
- Reaction mechanism (3)
- Stochastic reactor model (3)
- Verbrennung (3)
- Combustion (2)
- Detailed chemistry (2)
- Kinetic modeling (2)
- Kinetik (2)
Fundamental study on surrogates for commercially available fuels under engine-like conditions
(2025)
The increasing global energy demand, driven by technological advancements and population growth, has led to a significant rise in crude oil consumption. This trend is expected to continue until 2040 due to the lack of viable alternatives for sectors such as road freight, aviation, and petrochemicals. The combustion of fossil fuels, however, results in the emission of toxic and carcinogenic pollutants, including particulate matter (PM) and nitrogen oxides (NOx). This thesis aims to enhance the understanding of the formation and decomposition pathways of these pollutants under engine-like conditions using surrogate fuels.
The research was conducted at the Brandenburg University of Technology Cottbus-Senftenberg, funded by the EU FP7 Marie Skłodowska Curie action, Initial Training Network (ITN) project ECCO-MATE. The project involved collaboration with 11 key partners from academia and industry across Europe and Japan. The primary objective was to develop and implement novel combustion technologies for marine and automotive engines to improve efficiency and meet stringent emission standards.
Experimental studies were carried out using various analytical techniques, including gas chromatography, gas analysis, and luminescence techniques. These methods were optimized for engine-like conditions to investigate the formation of PM and NOx. The research utilized a range of experimental facilities, such as shock tubes and rapid compression machines, to measure ignition delay times and flame speciation. The study also involved the characterization of commercial fuels and the selection of surrogate fuels to represent their properties.
The findings indicate that the addition of diluents, such as nitrogen and carbon dioxide, can significantly reduce the formation of NOx and PM. The use of oxygenated fuels, like dimethyl ether (DME), was found to enhance combustion efficiency and reduce pollutant emissions. The research also highlighted the importance of understanding the chemical kinetics of fuel decomposition and the role of polycyclic aromatic hydrocarbons (PAHs) in soot formation.
Overall, this thesis provides valuable insights into the combustion behavior of surrogate fuels under engine-like conditions. The results contribute to the development of cleaner and more efficient combustion technologies for the automotive and marine sectors, aligning with global efforts to reduce the environmental impact of fossil fuel consumption.
Even if huge efforts are made to push alternative mobility concepts, such as electric cars and fuel-cell-powered cars, the significance and use of liquid fuels is anticipated to stay high during the 2030s. Biomethane and synthetic natural gas (SNG) might play a major role in this context, as they are raw material for chemical industry that is easy to be stored and distribute via existing infrastructure, and are a versatile energy carrier for power generation and mobile applications. Since biomethane and synthetic natural gas are suitable for power generation and for mobile applications, they can therefore replace natural gas without any infrastructure changes, thus playing a major role. In this paper, we aim to comprehend the direct production of synthetic natural gas from CO₂ and H₂ in a Sabatier process based on a thermodynamic analysis as well as a multi-step kinetic approach. For this purpose, we thoroughly discuss CO₂ methanation to control emissions in order to maximize the methane formation along with minimizing the CO formation and to understand the complex methanation process. We consider an equilibrium and kinetic modeling study on the NiO-SiO₂catalyst for methanation focusing on CO₂-derived SNG. The thermodynamic analysis of CO₂ hydrogenation is preformed to define the optimal process parameters followed by the kinetic simulations for catalyst development. The investigation presented in this paper can also be used for developing machine learning algorithms for methanation processes.
This thesis summarizes the author’s developments of combustion models and multi-objective optimization methods for gasoline and diesel engines. The combustion models belong to the family of zero-dimensional stochastic reactor models introduced in the 1990s to improve the prediction of emissions with detailed chemistry in partially stirred reactors.
The first part introduces the fundamentals of the physical and chemical models describing the combustion process. As a novelty, k−ε turbulence models were implemented in the stochastic reactor model to predict the turbulent time and length scales in gasoline and diesel engines. This development allowed an improvement of the models for convective heat transfer, fuel evaporation, gas exchange across the valves, turbulent flame propagation and crevice flow, which depend on the turbulent time and length scales.
In the second part, the multi-objective optimization platform for automatic training of the stochastic reactor model is presented. The optimization method considers multiple operating points to find a set of model parameters that predict performance and emissions over the entire engine map. The Non-domination Sorting Genetic Algorithm II is combined with the stochastic reactor model and response surface models to find the best Pareto front. Multi-criteria decision making is used to select the best designs from the Pareto front.
Finally, the third part of this thesis deals with the validation of the stochastic reactor model and the multi-objective optimization platform. For this purpose, experiments of two single-cylinder research engines with spark ignition, one passenger car engine with compression ignition and one heavy duty engine with compression ignition are used. For the spark ignition engines, a set of model parameters was found that predicts well the power and emissions over the whole engine map. The calculated turbulent kinetic energy, dissipation, and angular momentum follow the trends of the three-dimensional computational fluid dynamic simulations to a good approximation for various operating points. For the two compression ignition engines, the prediction of combustion progress and nitrogen oxide emissions are in good agreement with the experiments. Larger discrepancies were found for the prediction of carbon monoxide and unburned hydrocarbon. Optimization of the soot model parameters improves the prediction of soot mass for operating points throughout the engine map.
In this work, a reliable kinetic reaction mechanism was revised to accurately reproduce the detailed reaction paths of steam reforming of methane over a Ni/Al2O3 catalyst. A steadystate fixed-bed reactor experiment and a 1D reactor catalyst model were utilized for this task. The distinctive feature of this experiment is the possibility to measure the axially resolved temperature profile of the catalyst bed, which makes the reaction kinetics inside the reactor visible. This allows for understanding the actual influence of the reaction kinetics on the system; while pure gas concentration measurements at the catalytic reactor outlet show near-equilibrium conditions, the inhere presented temperature profile shows that it is insufficient to base a reaction mechanism development on close equilibrium data. The new experimental data allow for achieving much higher quality in the modeling efforts. Additionally, by carefully controlling the available active surface via dilution in the experiment, it was possible to slow down the catalyst conversion rate, which helped during the adjustment of the reaction kinetics. To assess the accuracy of the revised mechanism, a monolith experiment from the literature was simulated. The results show that the fitted reaction mechanism was able to accurately predict the experimental outcomes for various inlet mass flows, temperatures, and steam-to-carbon ratios.
Development of a hierarchically detailed chemical reaction mechanism from C₃ to C₅ hydrocarbons
(2022)
The oxidation of fuel molecules can be described by using a reaction mechanism, a tool that combines thermodynamic and transport properties with reaction rates to predict the behavior and sub-products at different temperatures, pressures and equivalence ratios. A detailed reaction mechanism helps to understand the fuel-specific pollutant formation process. The aim of this doctoral thesis is to generate a hierarchically-detailed chemical reaction mechanism from C3 to C5 hydrocarbons that can be used to understand the reaction decomposition pathways for different fuels at high temperature regime, e.g. propene, propane, butane isomers, butene isomers and pentene isomers. A new nomenclature based in the IUPAC rules, has been developed and implemented as part of this work. The naming follows the order of priority for choosing a principal characteristic group. These naming rules and some examples are explained here. As starting point for this investigation, the chemical model presented in Schenk et al. (2013) has been used. Thermodynamic data for sensitive species from C3 chemistry were revised and updated. Updates in reaction rates for n-butane (C4H10) and iso-butane (C4H10-Me2) are shown. The chemistry of the butene (C4H8) isomers have been revised and a correction taking into account the H-atom allyl abstraction is implemented. Laminar flame speeds and ignition delay times for the different isomers are presented and discussed together with experiments in similar conditions for burner-stabilized flame for the three butene and butane isomers.
The high-temperature chemistry for branched and linear C5H10 species is implemented in the model. 2-Methyl-2-butene (C5H10-D2Me2) is the most interesting isomer because 9 of its 10 C-H atoms are in allylic position and it is compared to n-Pentane as an example of a linear molecule. The validation of a burner-stabilized flame, ignition delay time, and laminar flame speed experiments for these fuels are presented and discussed. The compilation strategy was used and it aims to continuously increase the number and type of targets for mechanism validation.
Water injection is investigated for turbocharged spark-ignition engines to reduce knock probability and enable higher engine efficiency. The novel approach of this work is the development of a simulation-based optimization process combining the advantages of detailed chemistry, the stochastic reactor model and genetic optimization to assess water injection. The fast running quasi-dimensional stochastic reactor model with tabulated chemistry accounts for water effects on laminar flame speed and combustion chemistry. The stochastic reactor model is coupled with the Non-dominated Sorting Genetic Algorithm to find an optimum set of operating conditions for high engine efficiency. Subsequently, the feasibility of the simulation-based optimization process is tested for a three-dimensional computational fluid dynamic numerical test case. The newly proposed optimization method predicts a trade-off between fuel efficiency and low knock probability, which highlights the present target conflict for spark-ignition engine development. Overall, the optimization shows that water injection is beneficial to decrease fuel consumption and knock probability at the same time. The application of the fast running quasi-dimensional stochastic reactor model allows to run large optimization problems with low computational costs. The incorporation with the Non-dominated Sorting Genetic Algorithm shows a well-performing multi-objective optimization and an optimized set of engine operating parameters with water injection and high compression ratio is found.
In this thesis, a detailed chemical kinetic mechanism is developed to predict the oxidation of ammonia. The main aim is to cover the most important features of ammonia combustion - laminar flame speed, auto-ignition timing, emission formation, speciation in different reactors, and subsequently to study fuel/NOₓ interaction. Each elementary reaction in the mechanism is carefully reviewed based on several published literature, both experimental and theoretical rate parameters are selected accordingly. A wide range of published experimental data in multi-setup experiments are selected - in freely propagating and burner stabilized premixed flames and in shock tubes and jet-stirred and flow, reactor to assess the performance of the developed mechanism. The reaction mechanism also considers the formation of nitrogen oxides and the reduction of nitrogen oxides depending on the conditions of the surrounding gas phase. The experimental data from the literature are interpreted with the help of the kinetic model developed in this thesis.
A local algebraic simulation model was developed, to determine the characteristic length scales for dispersed phases. This model includes the Ishii- Zuber drag model, the lift, the wall lubrication force and the turbulent dispersion force as well. It is based on the Algebraic Interface Area Density (AIAD) model from the Helmholtz Zentrum Dresden Rossendorf (HZDR), which provides the morphology detection and the free surface drag model. The developed model is in agreement with the current state of knowledge based on an examination of the theory and of state of science models for interface momentum transfer.
This new simulation model was tested on three different experiments. Two experiments can be found in the literature, the Fabre 1987 and the Hewitt 1987 experiment. And the third simulation is based on a steam drum experiment. This steam drum experiment is designed with ERK Eckrohrkessel GmbH internals and was developed to examine the droplet mass flow out of the turbulent separation stage.
The implementation of all models and tests was performed using Ansys CFX. The first analysis was carried out to reproduce a wavy stratified flow to examine the effects of different simulation model set-ups according to the velocity and kinetic energy profiles, as well as the pressure drop gradient and the water level measured by Fabre 1987. The second analysis was a proof on concept for reproducing the vertical flow pattern by an experiment from Hewitt 1987. The third simulation analysed the water distribution in the steam drum and feeding pipes system as well as the droplet carryover into the gas phase in the turbulent separation region of the drum.
These simulations have shown, that the accuracy of the particle distribution model in interaction with the drag and non-drag forces is able to reproduce horizontal and vertical flow patterns. Higher deviations are recognised for the liquid volume fraction close above the interface. Generally, simulations can now be performed to optimise industrial steam drum designs.
Sophisticated engine knock modeling supports the optimization of the thermal efficiency of spark ignition engines. For this purpose the presented work introduces the resonance theory (Bradley and co-workers, 2002) for three-dimensional Reynolds-Averaged Navier-Stokes (RANS) and for the zero-dimensional Spark Ignition Stochastic Reactor Model (SI-SRM) simulations. Hereby, the auto-ignition in the unburnt gases is investigated directly instead of the resulting pressure fluctuations. Based on the detonation diagram auto-ignition events can be classified to be in acceptable deflagration regime or possibly turn to a harmful developing detonation.
Combustion is modeled using detailed chemistry and formulations for turbulent flame propagation. The use of detailed chemistry caters for the prediction of physical and chemical properties, such as the octane rating, C:H:O-ratio or dilution. For both models, the laminar flame speed is retrieved from surrogate specific look-up tables compiled using the reaction mechanism for Ethanol containing Toluene Reference Fuels by Seidel (2017). In the fresh gas zone, the scheme is used for auto-ignition prediction. For this purpose, the G-equation coupled with a Well-Stirred-Reactor model is applied in RANS. In analogy, in the SI-SRM the combustion is modeled using a two zone model with stochastic mixing between the particles.
RANS is used to develop the knock classification methodology and to analyze in detail location, size and shape of the auto-ignition kernels. RANS estimates the ensemble average of the process and therefore cannot reproduce a developing detonation. Hence, Large Eddy Simulation (LES) is used to verify the methodology. Studies using wide ranges of surrogates with different octane rating and cycle-to-cycle variations are carried out using the computationally efficient SI-SRM. Cyclic variations are predicted based on stochastic mixing, stochastic heat transfer to the wall, varying exhaust gas recirculation composition and imposed probability density functions for the inflammation time and the scaling of the mixing time retrieved from RANS.
The methodology is verified for spark timing and octane rating. It is shown that the surrogate formulation has an important impact on knock prediction.
RANS is suitable to predict the mean strength of auto-ignition in the unburnt gas if the thermodynamic and chemical state of the ignition kernel is analyzed instead of the pressure gradients. The probability of the transition to knocking combustion can be determined. Good agreement between RANS and SI-SRM are obtained. The combination of both tools gives insights of local effects using RANS and the distribution of auto-ignition in the whole pressure range of an operating point using SI-SRM with reasonable computationally cost for development purposes.
This thesis is a combined work of understanding the high temperature oxidation chemistry of cycloalkanes viz. methylcyclohexane based on previously developed cyclohexane and extending it to generate the larger n-propylcyclohexane chemical kinetic mechanism. The detailed kinetic reaction mechanism model for the oxidation of 1-hexene previously developed has been added to account for the ring opening of cyclohexane forming 1-hexene. As an update to the publication, preference of allylic H-abstractions from 1-hexene has been taken into account and retro-ene reaction producing propene has been added. The complete model is composed of 329 species and 2065 reactions with 3796 reversible elementary reactions. Further, these models have been validated against different experiments such as shock tubes, jet stirred reactors and laminar flames to cover full range of temperatures, pressures and equivalence ratios making the models comprehensive and was found to be adequate to satisfactorily reproduce the experimental data. The allylic radicals (C₆H₁₁-D1R3) preferred abstractions from 1-hexene improves the C₆H₁₁ profiles in the 1-hexene model. But it also influences the otherwise isomerization path of C₆H1₁₁-D1R6 to CYC₆H₁₁ (Cyclohexyl radical) which would further form cyclohexene (CYC₆H₁₀). It is observed that CYC₆H₁₀ profiles in 1-hexene flames and cyclohexane speciation are over-predicted. The major decomposition pathway of the cycloalkanes is through H-abstractions on the ring. The path which leads towards ring opening to form olefin is observed for cyclohexane and methylcyclohexane but is very low. The fulvene pathway influence on benzene profiles of 1-hexene is obvious but do not seem to affect the cycloalkanes. This infers there are other benzene formation pathways in cycloalkanes. Some possible pathways would be the dehydrogenation of dienes and dehydrogenation of cyclo-olefins.
