@misc{FrankenNetzerPasternaketal., author = {Franken, Tim and Netzer, Corinna and Pasternak, Michal and Mauß, Fabian and Seidel, Lars and Matrisciano, Andrea and Borg, Anders and Lehtiniemi, Harry and Kulzer, Andr{\´e} Casal}, title = {Simulation of Spark-Ignited Engines with Water Injection using the Stochastic Reactor Model, 37th International Symposium on Combustion}, language = {en} } @misc{NetzerSeidelPasternaketal., author = {Netzer, Corinna and Seidel, Lars and Pasternak, Michal and Lehtiniemi, Harry and Perlman, Cathleen and Ravet, Fr{\´e}d{\´e}ric and Mauß, Fabian}, title = {Three-dimensional computational fluid dynamics engine knock prediction and evaluation based on detailed chemistry and detonation theory}, series = {International Journal of Engine Research}, volume = {19}, journal = {International Journal of Engine Research}, number = {1}, issn = {1468-0874}, doi = {10.1177/1468087417740271}, pages = {33 -- 44}, abstract = {Engine knock is an important phenomenon that needs consideration in the development of gasoline-fueled engines. In our days, this development is supported using numerical simulation tools to further understand and predict in-cylinder processes. In this work, a model tool chain which uses a detailed chemical reaction scheme is proposed to predict the auto-ignition behavior of fuels with different octane ratings and to evaluate the transition from harmless auto-ignitive deflagration to knocking combustion. In our method, the auto-ignition characteristics and the emissions are calculated using a gasoline surrogate reaction scheme containing pathways for oxidation of ethanol, toluene, n-heptane, iso-octane and their mixtures. The combustion is predicted using a combination of the G-equation based flame propagation model utilizing tabulated laminar flame speeds and well-stirred reactors in the burned and …}, language = {en} } @inproceedings{NetzerSeidelLehtiniemietal., author = {Netzer, Corinna and Seidel, Lars and Lehtiniemi, Harry and Ravet, Fr{\´e}d{\´e}ric and Mauß, Fabian}, title = {Impact of gasoline surrogates with different fuel sensitivity (RON-MON) on knock prediction}, series = {Proceedings of the 6th European Conference on Computational Mechanics (Solids, Structures and Coupled Problems) ECCM 6 and 7th European Conference on Computational Fluid Dynamics ECFD 7, Glasgow, Scotland, UK June 11 - 15, 2018}, booktitle = {Proceedings of the 6th European Conference on Computational Mechanics (Solids, Structures and Coupled Problems) ECCM 6 and 7th European Conference on Computational Fluid Dynamics ECFD 7, Glasgow, Scotland, UK June 11 - 15, 2018}, pages = {906 -- 917}, language = {en} } @misc{WernerMatriscianoNetzeretal., author = {Werner, Adina and Matrisciano, Andrea and Netzer, Corinna and Lehtiniemi, Harry and Borg, Anders and Seidel, Lars and Mauß, Fabian}, title = {Further Application of the Fast Tabulated CPV Approach}, doi = {10.13140/RG.2.2.18689.71529}, language = {en} } @misc{WernerNetzerLehtiniemietal., author = {Werner, Adina and Netzer, Corinna and Lehtiniemi, Harry and Borg, Anders and Matrisciano, Andrea and Seidel, Lars and Mauß, Fabian}, title = {A Computationally Efficient Combustion Progress Variable (CPV) Approach for Engine Applications}, doi = {10.13140/RG.2.2.15334.27209}, language = {en} } @misc{NetzerSeidelRavetetal., author = {Netzer, Corinna and Seidel, Lars and Ravet, Fr{\´e}d{\´e}ric and Mauß, Fabian}, title = {Impact of the surrogate formulation on 3D CFD engine knock prediction using detailed chemistry}, series = {Fuel}, volume = {Volume 254}, journal = {Fuel}, issn = {1873-7153}, doi = {10.1016/j.fuel.2019.115678}, pages = {13}, abstract = {For engine knock prediction, surrogate fuels are often composed of iso-octane and n-heptane since they are the components of the Primary Reference Fuel (PRF). By definition, a PRF has no octane sensitivity (S = RON-MON). However, for a commercial gasoline fuel holds RON > MON and therefor S > 0. More complex surrogates are Toluene Reference Fuels (TRF) and Ethanol containing Toluene Reference Fuels (ETRF). In this work, the impact of the surrogate formulation on the prediction of flame propagation and auto-ignition in the unburnt gases are investigated. The surrogates are composed such that the Research Octane Number is the same. The auto-ignition events ahead of the flame front are predicted using 3D CFD and a combustion model based on the ETRF mechanism by Seidel (2017). The strength of the auto-ignition is determined using the detonation diagram by Bradley and co-workers (2002, 2003). Applying the different surrogates, ignition kernels of different size and reactivity are predicted. The results indicate a dependency on the local temperature history and the low temperature chemistry of the fuel species. The comparison of homogenous constant volume reactor and transient simulations show that the analysis of ignition delay time and octane rating solely from homogenous simulations is not sufficient if the knock tendency of a surrogate in engine simulations needs to be characterized.}, language = {en} } @misc{NetzerSeidelRavetetal., author = {Netzer, Corinna and Seidel, Lars and Ravet, Fr{\´e}d{\´e}ric and Mauß, Fabian}, title = {Assessment of the validity of RANS knock prediction using the resonance theory}, series = {International Journal of Engine Research}, volume = {21}, journal = {International Journal of Engine Research}, number = {4}, issn = {2041-3149}, doi = {10.1177/1468087419846032}, pages = {610 -- 621}, abstract = {Following the resonance theory by Bradley and co-workers, engine knock is a consequence of an auto-ignition in the developing detonation regime. Their detonation diagram was developed using direct numerical simulations and was applied in the literature to engine knock assessment using large eddy simulations. In this work, it is analyzed if the detonation diagram can be applied for post-processing and evaluation of predicted auto-ignitions in Reynolds-averaged Navier-Stokes simulations even though the Reynolds-averaged Navier-Stokes approach cannot resolve the fine structures resolved in direct numerical simulations and large eddy simulations that lead to the prediction of a developing detonation. For this purpose, an engine operating point at the knock limit spark advance is simulated using Reynolds-averaged Navier-Stokes and large eddy simulations. The combustion is predicted using the G-equation and the well-stirred reactor model in the unburnt gases based on a detailed gasoline surrogate reaction scheme. All the predicted ignition kernels are evaluated using the resonance theory in a post-processing step. According to the different turbulence models, the predicted pressure rise rates and gradients differ. However, the predicted ignition kernel sizes and imposed gas velocities by the auto-ignition event are similar, which suggests that the auto-ignitions predicted by Reynolds-averaged Navier-Stokes simulations can be given a meaningful interpretation within the detonation diagram.}, language = {en} } @misc{NetzerPasternakSeideletal., author = {Netzer, Corinna and Pasternak, Michal and Seidel, Lars and Ravet, Fr{\´e}d{\´e}ric and Mauß, Fabian}, title = {Computationally efficient prediction of cycle-to-cycle variations in spark-ignition engines}, series = {International Journal of Engine Research}, volume = {21}, journal = {International Journal of Engine Research}, number = {4}, issn = {2041-3149}, doi = {10.1177/1468087419856493}, pages = {649 -- 663}, abstract = {Cycle-to-cycle variations are important to consider in the development of spark-ignition engines to further increase fuel conversion efficiency. Direct numerical simulation and large eddy simulation can predict the stochastics of flows and therefore cycle-to-cycle variations. However, the computational costs are too high for engineering purposes if detailed chemistry is applied. Detailed chemistry can predict the fuels' tendency to auto-ignite for different octane ratings as well as locally changing thermodynamic and chemical conditions which is a prerequisite for the analysis of knocking combustion. In this work, the joint use of unsteady Reynolds-averaged Navier-Stokes simulations for the analysis of the average engine cycle and the spark-ignition stochastic reactor model for the analysis of cycle-to-cycle variations is proposed. Thanks to the stochastic approach for the modeling of mixing and heat transfer, the spark-ignition stochastic reactor model can mimic the randomness of turbulent flows that is missing in the Reynolds-averaged Navier-Stokes modeling framework. The capability to predict cycle-to-cycle variations by the spark-ignition stochastic reactor model is extended by imposing two probability density functions. The probability density function for the scalar mixing time constant introduces a variation in the turbulent mixing time that is extracted from the unsteady Reynolds-averaged Navier-Stokes simulations and leads to variations in the overall mixing process. The probability density function for the inflammation time accounts for the delay or advancement of the early flame development. The combination of unsteady Reynolds-averaged Navier-Stokes and spark-ignition stochastic reactor model enables one to predict cycle-to-cycle variations using detailed chemistry in a fraction of computational time needed for a single large eddy simulation cycle.}, language = {en} } @misc{VaccaBargendeChiodietal., author = {Vacca, Antonino and Bargende, Michael and Chiodi, Marco and Netzer, Corinna and Gern, Maike Sophie and Kauf, Georg Malte and Kulzer, Andr{\´e} Casal and Franken, Tim}, title = {Analysis of Water Injection Strategies to Exploit the Thermodynamic Effects of Water in Gasoline Engines by Means of a 3D-CFD Virtual Test Bench}, publisher = {SAE International}, address = {Neapel}, doi = {10.4271/2019-24-0102}, abstract = {CO2 emission constraints taking effect from 2020 lead to further investigations of technologies to lower knock sensitivity of gasoline engines, main limiting factor to increase engine efficiency and thus reduce fuel consumption. Moreover the RDE cycle demands for higher power operation, where fuel enrichment is needed for component protection. To achieve high efficiency, the engine should be run at stoichiometric conditions in order to have better emission control and reduce fuel consumption. Among others, water injection is a promising technology to improve engine combustion efficiency, by mainly reducing knock sensitivity and to keep high conversion rates of the TWC over the whole engine map. The comprehension of multiple thermodynamic effects of water injection through 3D-CFD simulations and their exploitation to enhance the engine combustion efficiency is the main purpose of the analysis. As basis for the research a single cylinder engine derived from a 1l turbocharged 3-cylinders engine is used to evaluate indirect and direct water injection. The entire engine flow field is reproduced and analyzed with 3D-CFD simulations and numerical models are employed to separate the influence of chemical and thermodynamic properties. Measurements are performed with different injectors for indirect/direct water injection in the single-cylinder engine in order to assess water break-up, wall wetting, spray interaction and penetration. Several injection strategies, such as varying start of injection, injection pressure, and water to fuel ratio, are tested at the single-cylinder engine test bench. Detailed gas phase chemistry is employed to link flame front speed with water concentration and knocking occurrence. These results are correlated with the 3D-CFD simulation of mixture formation, in-cylinder flow and water distribution for two different operating points (part load and maximum power) in order to study water behavior, with focus on the evaporation process, in-cylinder pressure and temperature profile, as well as the combustion development, during multiple engine cycles.}, language = {en} } @misc{FrankenNetzerMaussetal., author = {Franken, Tim and Netzer, Corinna and Mauß, Fabian and Pasternak, Michal and Seidel, Lars and Borg, Anders and Lehtiniemi, Harry and Matrisciano, Andrea and Kulzer, Andr{\´e} Casal}, title = {Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry}, series = {International Journal of Engine Research}, volume = {20}, journal = {International Journal of Engine Research}, number = {10}, issn = {2041-3149}, doi = {10.1177/1468087419857602}, pages = {1089 -- 1100}, abstract = {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.}, language = {en} } @misc{NetzerLiSeideletal., author = {Netzer, Corinna and Li, Tian and Seidel, Lars and Mauß, Fabian and L{\o}v{\aa}s, Terese}, title = {Stochastic Reactor-Based Fuel Bed Model for Grate Furnaces}, series = {Energy \& Fuels}, volume = {34}, journal = {Energy \& Fuels}, number = {12}, issn = {1520-5029}, doi = {10.1021/acs.energyfuels.0c02868}, pages = {16599 -- 16612}, abstract = {Biomass devolatilization and incineration in grate-fired plants are characterized by heterogeneous fuel mixtures, often incompletely mixed, dynamical processes in the fuel bed and on the particle scale, as well as heterogeneous and homogeneous chemistry. This makes modeling using detailed kinetics favorable but computationally expensive. Therefore, a computationally efficient model based on zero-dimensional stochastic reactors and reduced chemistry schemes, consisting of 83 gas-phase species and 18 species for surface reactions, is developed. Each reactor is enabled to account for the three phases: the solid phase, pore gas surrounding the solid, and the bulk gas. The stochastic reactors are connected to build a reactor network that represents the fuel bed in grate-fired furnaces. The use of stochastic reactors allows us to account for incompletely mixed fuel feeds, distributions of local temperature and local equivalence ratio within each reactor and the fuel bed. This allows us to predict the released gases and emission precursors more accurately than if a homogeneous reactor network approach was employed. The model approach is demonstrated by predicting pyrolysis conditions and two fuel beds of grate-fired plants from the literature. The developed approach can predict global operating parameters, such as the fuel bed length, species release to the freeboard, and species distributions within the fuel bed to a high degree of accuracy when compared to experiments.}, language = {en} } @misc{MatriscianoNetzerWerneretal., author = {Matrisciano, Andrea and Netzer, Corinna and Werner, Adina and Borg, Anders and Seidel, Lars and Mauß, Fabian}, title = {A Computationally Efficient Progress Variable Approach for In-Cylinder Combustion and Emissions Simulations}, series = {SAE Technical Paper}, journal = {SAE Technical Paper}, issn = {0148-7191}, doi = {10.4271/2019-24-0011}, abstract = {The use of complex reaction schemes is accompanied by high computational cost in 3D CFD simulations but is particularly important to predict pollutant emissions in internal combustion engine simulations. One solution to tackle this problem is to solve the chemistry prior the CFD run and store the chemistry information in look-up tables. The approach presented combines pre-tabulated progress variable-based source terms for auto-ignition as well as soot and NOx source terms for emission predictions. The method is coupled to the 3D CFD code CONVERGE v2.4 via user-coding and tested over various speed and load passenger-car Diesel engine conditions. This work includes the comparison between the combustion progress variable (CPV) model and the online chemistry solver in CONVERGE 2.4. Both models are compared by means of combustion and emission parameters. A detailed n-decane/α-methyl-naphthalene mechanism, comprising 189 species, is used for both online and tabulated chemistry simulations. The two chemistry solvers show very good agreement between each other and equally predict trends derived experimentally by means of engine performance parameters as well as soot and NOx engine-out emissions. The CPV model shows a factor 8 speed-up in run-time compared to the online chemistry solver without compromising the accuracy of the solution.}, language = {en} }