Completed
2023
PhD Candidate: Tim Franken
Supervisor:Prof. Dr.-Ing. Fabian Mauß
Abstract:
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.
2022
PhD Candidate: Larisa León de Syniawa
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
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.
2021
PhD Candidate: Krishna Prasad Shrestha
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
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.
2019
PhD Candidate: Corinna Netzer
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
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.
2018
PhD Candidate: Amruta Nawdiyal
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
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.
2017
PhD Candidate: Xiaoxiao Wang
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
In recent years, biodiesel is an alternative fuel to petroleum diesel that is renewable and creates less harmful emissions than conventional diesel. Biodiesel blends – usually B20 or below, have been the most commonly used biodiesel blends. In current study, the kinetic mechanism of n-decane/α-methylnaphthalene (AMN)/methyl-decanoate (MD) blend is developed and validated as the surrogate for biodiesel/diesel blends. The IDEA reference fuel (70% n-decane/30% AMN by liquid volume) was formulated in the past as a two-component diesel surrogate fuel. A comprehensive and compact oxidation model for the IDEA reference fuel is developed. One important fuel-fuel interaction pathway via reaction pathway of A2CH2 + HO2 is observed and detailed discussed. The IDEA blends are validated by comprehensive target experiments for n-decane, AMN, and the AMN/n-decane blends. Ignition delay times, flame speeds, and species composition in jet stirred reactor and counter flow flames are successfully simulated for a broad range of temperatures (500-2000 K) and pressures (1-50 bar). The simulations of the IDEA blend with current mod-el show acceptable agreement when compared with different experiments of ignition delay times for diesel fuels as well as flame speed experiments. With a chain of ten carbon atoms and a methyl-ester group attached, MD is considered as a one-component surrogate fuel for biodiesel. A comprehensive and compact kinetic model for MD is developed. The mechanism is critically tested by comparison of model predictions with experimental data over a wide temperature (500 to 1500 K) and pressure (1 to 20 bar) range and for different fuel/oxidizer ratios. The good maintenance of chemical information during the reduction has been confirmed by simulation results, as well as the sensitivity and flow analyses performed using the detailed and the skeletal model. The MD model is compared with available experimental ignition delay times of biodiesel fuels. The good agreement between the simulations and the experiments proves that this model is a reliable kinetic model for simulations, either used by itself or in combination with IDEA blend. To improve the mechanism analysis, this thesis introduces a new three-stage reactive flow analysis. The final skeletal n-decane/AMN/MD blend with skeletal base mechanism includes 295 species and 3500 reactions by using the CGR approach. Based on the above validations and comparisons, current blend is considered as one surrogate for biodiesel/diesel blends that is suitable for improving kinetic understanding and for application in engine simulations.
PhD Candidate: Lars Seidel
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
Within this thesis, a detailed multicomponent gasoline surrogate reaction scheme was developed and reduced to a four component scheme of skeletal size. The main target is to cover the most important features for typical spark ignited (SI) combustion - flame propagation, emission formation and the tendency to auto ignite and subsequently cause engine knock. To achieve this a variable mechanism concept was developed to include sub models for different fuels as needed. Using this approach a detailed mechanism describing the oxidation of n-heptane, iso-octane, toluene and ethanol was compiled and compared against various experiments published in literature. Furthermore, correlations were developed to suggest four component gasoline surrogates based on typical fuel data sheets. The correlation method is validated against measurements in Cooperative Fuel Research (CFR) engine from various groups and further compared against correlations between octane numbers (ON) and predicted 0D ignition delay times. These correlations are used to identify and discuss the impact of the uncertainty of two reactions on ignition delay time of a multicomponent fuel. To be able to reduce the detailed scheme in a time efficient way existing reduction concepts where improved and applied to different schemes and targets. Since various reduction techniques are available, an optimal sequence of those was worked out. Using this sequence of reduction steps two multicomponent schemes were compiled: one scheme for the prediction of laminar flame speeds and one for the prediction of major emissions and auto-ignition. To underline that the suggested reduction procedure is universal it was also applied to n-heptane as single fuel surrogate for diesel fuel and to a large two component fuel from another work group.
2016
PhD Candidate: Andreas Manz
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
Downsizing of modern gasoline engines with direct injection is a key concept for achieving future CO22 emission targets. However, high power densities and optimum efficiency are limited by an uncontrolled autoignition of the unburned air-fuel mixture, the so-called spark knock phenomena. By a combination of three-dimensional Computational Fluid Dynamics (3D-CFD) and experiments incorporating optical diagnostics, this work presents an integral approach for predicting combustion and autoignition in Spark Ignition (SI) engines. The turbulent premixed combustion and flame front propagation in 3D-CFD is modeled with the G-equation combustion model, i.e. a laminar flamelet approach, in combination with the level set method. Autoignition in the unburned gas zone is modeled with the Shell model based on reduced chemical reactions using optimized reaction rate coefficients for different octane numbers (ON) as well as engine relevant pressures, temperatures and EGR rates. The basic functionality and sensitivities of improved sub-models, e.g. laminar flame speed, are proven in simplified test cases followed by adequate engine test cases. It is shown that the G-equation combustion model performs well even on unstructured grids with polyhedral cells and coarse grid resolution. The validation of the knock model with respect to temporal and spatial knock onset is done with fiber optical spark plug measurements and statistical evaluation of individual knocking cycles with a frequency based pressure analysis. The results show a good correlation with the Shell autoignition relevant species in the simulation. The combined model approach with G-equation and Shell autoignition in an active formulation enables a realistic representation of thin flame fronts and hence the thermodynamic conditions prior to knocking by taking into account the ignition chemistry in unburned gas, temperature fluctuations and self-acceleration effects due to pre-reactions. By the modeling approach and simulation methodology presented in this work the overall predictive capability for the virtual development of future knockproof SI engines is improved.
2015
PhD Candidate: Michal Pasternak
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
The present work is concerned with the simulation of combustion, emission formation and fuel effects in Diesel engines. The simulation process is built around a zero-dimensional (0D) direct injection stochastic reactor model (DI-SRM), which is based on a probability density function (PDF) approach. An emphasis is put on the modelling of mixing time to improve the representation of turbulence-chemistry interactions in the 0D DI-SRM. The mixing time model describes the intensity of mixing in the gas-phase for scalars such as enthalpy and species mass fraction. On a crank angle basis, it governs the composition of the gas mixture that is described by PDF distributions for the scalars. The derivation of the mixing time is based on an extended heat release analysis that has been fully automated using a genetic algorithm. The predictive nature of simulations is achieved through the parametrisation of the mixing time model with known engine operating parameters such as speed, load and fuel injection strategy. It is shown that crank angle dependency of the mixing time improves the modelling of local inhomogeneity in the gas-phase for species mass fraction and temperature. In combination with an exact treatment of the non-linearity of reaction kinetics, it enables an accurate prediction of the rate of heat release, in-cylinder pressure and exhaust emissions, such as nitrogen oxides, unburned hydrocarbons and soot, from differently composed fuels. The method developed is particularly tailored for computationally efficient applications that focus on the details of reaction kinetics and the locality of combustion and emission formation in Diesel engines.
2014
PhD Candidate: Galin Nakov
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
The subject of this PhD thesis is 3D numerical simulations of combustion, soot and NOx emission formation for a diesel engine. For the soot simulation the detailed soot model by Prof. Dr. F. Mauss based on stationary flamelet library (Flamelet Library of Sources – FLOS) was applied. The model features pre-processing of the detailed chemistry, which allows considering local chemistry and turbulence effects at reasonable CPU costs. Under the assumption that soot chemistry is much slower than the turbulent length scales in the flow field, soot formation and oxidation rates can be stored in the soot library. Furthermore, a similarly constructed NOx model was developed, which was also based on the stationary flamelet library model. A major challenge of such approaches is the coupling to the CFD code. One of the main objectives of this work is to present a new coupling approach aiming to tackle this challenge. The approach proposed is based on a library of stationary flamelet temperature profiles. By means of this library the correct flamelet can be selected based on the conditions in the computational cell. Thereby the new approach ensures the consistency between flamelet library and CFD code regarding mixture fraction and temperature. A further optimization of the coupling between the FLOS model and the CFD code was achieved by considering the local concentration of acetylene. The FLOS soot model is independent on the combustion model used in the CFD software. Hence, the gas phase combustion is not influenced by the soot model and the soot model is not influenced by the gas phase chemistry. As the soot surface available for surface growth is unknown at the time when the FLOS is build, the consumption of acetylene is not included in the build of the library. Hence, a new approach – the acetylene feedback – was introduced to limit the soot surface growth rate, if the acetylene concentration becomes low. The FLOS model featuring the new approaches described above was coupled with the CFD code STAR-CD© and applied for emissions simulation in a diesel engine. The emphasis of the investigations is put on the effect of EGR rate and injection strategy on combustion as well as soot and NOx emissions. In this context a discussion is offered over the required quality of CFD setup and combustion simulation for obtaining reliable soot simulation results. The simulation results were compared to experimental and diagnostic data showing a very good agreement for the operating points investigated. This shows the potential of a predictive CFD package including soot and NOx model for improving the combustion chamber design and the operating strategy with respect to lower emissions.
PhD Candidate: Carlo Locci
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
The environmental emergency has led to the development of new combustion technologies. In this context, flameless combustion (FC in this manuscript) offers the prospect of a less polluting and more efficient technology. In FC, combustion is strongly diluted with recirculated burnt gases. Consequently the oxygen content is reduced and temperature peaks are smoothed, yielding reduced heat release. These conditions dramatically reduce the conditions of NO pollutant formation and increase the efficiency of the combustion process. Being FC a relatively new technology, it still needs optimization and R&D, which can be expensive and time consuming. Potentially, CFD can reduce both the financial costs as well as the R&D projects length. The context in which this thesis is inserted is exactly the numerical modeling of FC, by using Large Eddy Smulations for its better prediction of the turbulent ternary mixing (fuel - burnt gases -air), compared to RANS. This work has been divided into two main parts. In the first, combustion in FC has been investigated by means of a new tabulated combustion model initially written in the context of the EC-KIAI project and developed and adapted to FC in this thesis. The model uses diluted homogeneous reactors DHR to simulate FC and it was developed to account for under adiabatic enthalpy losses and the ternary mixing typical of FC. The model was firstly validated on a non-premixed flame academical configuration called Flame D and subsequently on a real FC combustor from the work of Verissimo et al. The results obtained for these configurations are quite correct although some discrepancies in CO prediction are observed. In the second part of the thesis, the NO pollutant modeling in FC is investigated. With this aim, the Diffusion Flame - NO relaxation approach DF-NORA was developed. It consists in tabulating the NO relaxation towards equilibrium of the NO source term in a flamelet structure. As done in the first part, the model was first validated on Flame D and then employed in a real FC configuration. Results are quite satisfactory in both config- urations. The encouraging results obtained in this work open the possibility of applying the proposed developments to real industrial configurations in the future.
PhD Candidate: Ngozi Ebenezer
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
In this work Adaptive Polynomial Tabulation (APT) is presented. It is a new approach to solve the initial value chemical rate equation system. In this approach zeroeth, first and second order polynomials are used in real-time to approximate the solution of the initial value chemical rate equation system. The sizes of the local regions encountered for the different orders of polynomial approximation are calculated in real-time. To improve accuracy the chemical state space is partitioned into hypercubes. During calculations the hypercubes accessed by the reactive mixture are divided into adaptive hypercubes depending on the accuracy of the local solution. Mixture initial conditions are stored in the adaptive hypercubes. Around each stored initial condition two concentric ellipsoids of accuracy (EOA) are defined. These include the ISAT and identical EOAs. The time evolution of mixture initial conditions which encounter an identical and ISAT EOA are approximated by zero and first order polynomials respectively. With a certain number of stored initial conditions within an adaptive hypercube, its second order polynomial coefficients are constructed from the stored initial conditions. The time evolution of additional mixture initial conditions that encounter this adaptive hypercube are approximated with second order polynomials. The APT model is simplified by the replacement of the entire set of species mass fractions with a progress variable based on the enthalpy of formation evaluated at 298 K. APT has 3 degrees of freedom which include the progress variable, total enthalpy and pressure. The APT model was tested with a zero dimensional Stochastic Reactor Model (SRM) for HCCI engine combustion. A skeletal n-heptane/toluene mechanism with 148 chemical species and 1281 reactions was used. In the tests, the HCCI engine simulations using APT were in very good agreement with the model calculations using the ODE solver. The cool flame and main ignition events were accurately captured. The major and minor species were also accurately captured by APT. In SRM-HCCI calculations without cyclic variations, a computational speed up factor greater than 1000 was obtained when APT was used for all the operating points considered without significant loss in accuracy. For the SRM-HCCI engine calculations with cyclic variations, APT demonstrated a computational speed up exceeding 12 without significant loss in accuracy.
2013
PhD Candidate: Linda Maria Beck
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
The virtual development of future Spark Ignition (SI) engine combustion processes in three-dimensional Computational Fluid Dynamics (3D-CFD) demands for the integration of detailed chemistry, enabling - additionally to the 3D-CFD modelling of flow and mixture formation - the prediction of fuel-dependent SI engine combustion in all of its complexity. This work presents an approach, which constitutes a coupled solution for flame propagation, auto-ignition, and emission formation modelling incorporating detailed chemistry, while exhibiting low computational costs.
For modelling the regular flame propagation, a laminar flamelet approach, the G-equation is used. Auto-ignition phenomena are addressed using an integrated flamelet approach, which bases on the tabulation of fuel-dependent reaction kinetics. By introducing a progress variable for the auto-ignition - the Ignition Progress Variable (IPV) - detailed chemistry is integrated in 3D-CFD. The modelling of emission formation bases on an interactively coupled flamelet approach, the Transient Interactive Flamelet (TIF) model.
The functionality of the combined approach to model the variety of SI engine combustion phenomena is proved first in terms of fundamentals and standalone sub-model functionality studies by introducing a simplified test case, which represents an adiabatic pressure vessel without moving meshes. Following the basic functionality studies, the sub-model functionalities are investigated and validated in adequate engine test cases. It is shown, that the approach allows to detect locally occurring auto-ignition phenomena in the combustion chamber, and to model their interaction with regular flame propagation. Moreover, the approach enables the prediction of emission formation on cell level.
2012
PhD Candidate: René Thygesen
Supervisor: Prof. Dr.-Ing. Fabian Mauß
PhD Candidate: Henrik Hoffmeyer
Supervisor: Prof. Dr.-Ing. Fabian Mauß
Abstract:
In spite of progress in the development of alternative powertrain systems and energy sources, the internal combustion and all its derivates still are and will be the main powertrain for automobiles. In SI-engines, several approaches compete with each other like the controlled auto ignition (CAI or HCCI), throttle-free load control using variable valvetrains, stratified mixture formation with lean engine operation or highly turbo charged downsizing concepts all combined with gasoline direct injection. The presented work makes a contribution for a deeper understanding of the combustion process of a turbo charged direct injection engine operating with external EGR as well as lean stratified mixture. Using detailed test bench investigations and introducing a new optical measurement tool, the combustion process is described in detail focusing on the occurrence of non-premixed combustion phenomena. The influence of engine parameters like global and local air-/fuel ratio, external EGR and fuel rail pressure as well as the influence of fuel parameters are discussed giving a characterization of the combustion process of stratified engine operation. Furthermore, the influences of non-inert exhaust gas components on engine knock tendency are investigated using external EGR with an EGR catalyst. Opposing the results to numerical analysis, combustion characteristics of turbo charged DISI-engines are presented.