TY - CHAP A1 - Mauß, Fabian A1 - Matrisciano, Andrea T1 - SRM in Engines: Performance and Emissions T2 - 3rd International Combustion Institute Summer School, June 19-23, Chania, Greece KW - Stochastic Reactor Models Y1 - 2016 UR - http://iciss2016.gr/site/wp-content/uploads/2016/05/ICISS_Mauss-Matrisciano_Abstract_Tutorial.pdf ER - TY - GEN A1 - Franken, Tim A1 - Klauer, Christian A1 - Kienberg, Martin A1 - Matrisciano, Andrea A1 - Mauß, Fabian T1 - Prediction of thermal stratification in an engine-like geometry using a zero-dimensional stochastic reactor model T2 - International Journal of Engine Research KW - Prediction of thermal stratification Y1 - 2019 UR - https://journals.sagepub.com/eprint/5AKgEhAVA8RDS2tQWdGK/full SN - 2041-3149 U6 - https://doi.org/10.1177/1468087418824217 SN - 1468-0874 ER - TY - CHAP A1 - Franken, Tim A1 - Netzer, Corinna A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Seidel, Lars A1 - Matrisciano, Andrea A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Kulzer, André Casal T1 - Assessment of Water Injection in a SI Engine using a Fast Running Detailed Chemistry Based Combustion Model T2 - Symposium of Combustion Control 2018, Aachen KW - Assessment of Water Injection Y1 - 2018 UR - https://www.researchgate.net/publication/326059620 UR - http://logesoft.com/loge-16/wp-content/uploads/2018/07/2018-06-19-SCC_-1.pdf CY - Aachen ER - TY - GEN A1 - Franken, Tim A1 - Matrisciano, Andrea A1 - Sari, Rafael A1 - Robles, Alvaro Fogue A1 - Monsalve-Serrano, Javier A1 - Pintor, Dario Lopez A1 - Pasternak, Michal A1 - Garcia, Antonio A1 - Mauß, Fabian T1 - Modeling of Reactivity Controlled Compression Ignition Combustion Using a Stochastic Reactor Model Coupled with Detailed Chemistry T2 - SAE technical papers : 15th International Conference on Engines & Vehicles N2 - Advanced combustion concepts such as reactivity controlled compression ignition (RCCI) have been proven to be capable of fundamentally improve the conventional Diesel combustion by mitigating or avoiding the soot-NOx trade-off, while delivering comparable or better thermal efficiency. To further facilitate the development of the RCCI technology, a robust and possibly computationally efficient simulation framework is needed. While many successful studies have been published using 3D-CFD coupled with detailed combustion chemistry solvers, the maturity level of the 0D/1D based software solution offerings is relatively limited. The close interaction between physical and chemical processes challenges the development of predictive numerical tools, particularly when spatial information is not available. The present work discusses a novel stochastic reactor model (SRM) based modeling framework capable of predicting the combustion process and the emission formation in a heavy-duty engine running under RCCI combustion mode. The combination of physical turbulence models, detailed emission formation sub-models and stateof-the-art chemical kinetic mechanisms enables the model to be computationally inexpensive compared to the 3D-CFD approaches. A chemical kinetic mechanism composed of 248 species and 1428 reactions was used to describe the oxidation of gasoline and diesel using a primary reference fuel (PRF)mixture and n-heptane, respectively. The model is compared to operating conditions from a single-cylinder research engine featuring different loads, speeds, EGR and gasoline fuel fractions. The model was found to be capable of reproducing the combustion phasing as well as the emission trends measured on the test bench, at some extent. The proposed modeling approach represents a promising basis towards establishing a comprehensive modeling framework capable of simulating transient operation as well as fuel property sweeps with acceptable accuracy. KW - Stochastic Reactor Models KW - RCCI KW - Chemical Kinetics KW - Low Temperature Combustion Y1 - 2021 UR - https://www.sae.org/publications/technical-papers/content/2021-24-0014/ U6 - https://doi.org/10.4271/2021-24-0014 SN - 0148-7191 SN - 2688-3627 ER - TY - GEN A1 - Franken, Tim A1 - Mauß, Fabian A1 - Seidel, Lars A1 - Gern, Maike Sophie A1 - Kauf, Malte A1 - Matrisciano, Andrea A1 - Kulzer, Andre Casal T1 - Gasoline engine performance simulation of water injection and low-pressure exhaust gas recirculation using tabulated chemistry T2 - International Journal of Engine Research N2 - This work presents the assessment of direct water injection in spark-ignition engines using single cylinder experiments and tabulated chemistry-based simulations. In addition, direct water injection is compared with cooled low-pressure exhaust gas recirculation at full load operation. The analysis of the two knock suppressing and exhaust gas cooling methods is performed using the quasi-dimensional stochastic reactor model with a novel dual fuel tabulated chemistry model. To evaluate the characteristics of the autoignition in the end gas, the detonation diagram developed by Bradley and coworkers is applied. The single cylinder experiments with direct water injection outline the decreasing carbon monoxide emissions with increasing water content, while the nitrogen oxide emissions indicate only a minor decrease. The simulation results show that the engine can be operated at l = 1 at full load using water–fuel ratios of up to 60% or cooled low-pressure exhaust gas recirculation rates of up to 30%. Both technologies enable the reduction of the knock probability and the decrease in the catalyst inlet temperature to protect the aftertreatment system components. The strongest exhaust temperature reduction is found with cooled low-pressure exhaust gas recirculation. With stoichiometric air–fuel ratio and water injection, the indicated efficiency is improved to 40% and the carbon monoxide emissions are reduced. The nitrogen oxide concentrations are increased compared to the fuel-rich base operating conditions and the nitrogen oxide emissions decrease with higher water content. With stoichiometric air–fuel ratio and exhaust gas recirculation, the indicated efficiency is improved to 43% and the carbon monoxide emissions are decreased. Increasing the exhaust gas recirculation rate to 30% drops the nitrogen oxide emissions below the concentrations of the fuel-rich base operating conditions. KW - Water Injection KW - Exhaust Gas Recirculation KW - Efficiency KW - Spark Ignition Engine KW - Stochastic Reactor Model KW - Emissions Y1 - 2020 UR - https://journals.sagepub.com/doi/abs/10.1177/1468087420933124 U6 - https://doi.org/10.1177/1468087420933124 SN - 2041-3149 SN - 1468-0874 VL - 21 IS - 10 SP - 1857 EP - 1877 ER - TY - GEN A1 - Franken, Tim A1 - Seidel, Lars A1 - Matrisciano, Andrea A1 - Mauß, Fabian A1 - Kulzer, Andre Casal A1 - Schuerg, Frank T1 - Analysis of the Water Addition Efficiency on Knock Suppression for Different Octane Ratings T2 - SAE World Congress N2 - Water injection can be applied to spark ignited gasoline engines to increase the Knock Limit Spark Advance and improve the thermal efficiency. The Knock Limit Spark Advance potential of 6 °CA to 11 °CA is shown by many research groups for EN228 gasoline fuel using experimental and simulation methods. The influence of water is multi-layered since it reduces the in-cylinder temperature by vaporization and higher heat capacity of the fresh gas, it changes the chemical equilibrium in the end gas and increases the ignition delay and decreases the laminar flame speed. The aim of this work is to extend the analysis of water addition to different octane ratings. The simulation method used for the analysis consists of a detailed reaction scheme for gasoline fuels, the Quasi-Dimensional Stochastic Reactor Model and the Detonation Diagram. The detailed reaction scheme is used to create the dual fuel laminar flame speed and combustion chemistry look-up tables. The Detonation Diagram is used as a novel approach in the Quasi-Dimensional Stochastic Reactor Model to evaluate the auto-ignition characteristic in the end gas and determine if it is a harmless deflagration or developing detonation. First, the Quasi-Dimensional Stochastic Reactor Model is trained for three engine operating points and a RON95 E10 fuel. Its performance is evaluated based on experimental results of a single cylinder research engine. Subsequently, different spark timings and water-fuel ratios are investigated for different Primary Reference Fuels. The results outline that water addition can effectively reduce the strength of auto-ignition in the end gas for different Primary Reference Fuels. Thereby, it can be stated that the reduction of the auto-ignition strength through water addition by 50 – 80 % water-fuel ratio for high octane number fuels corresponds to the spark timing delay of 6 °CA or an increase of research octane number by 10 points. KW - Gasoline KW - Knock KW - Water KW - Engines KW - Combustion KW - Simulation Y1 - 2020 U6 - https://doi.org/10.4271/2020-01-0551 SN - 2688-3627 SN - 0148-7191 ER - TY - GEN A1 - Franken, Tim A1 - Duggan, Alexander A1 - Tao, Feng A1 - Matrisciano, Andrea A1 - Lehtiniemi, Harry A1 - Borg, Anders A1 - Mauß, Fabian T1 - Multi-Objective Optimization of Fuel Consumption and NOx Emissions of a heavy-duty Diesel engine using a Stochastic Reactor Model T2 - SAE technical paper N2 - Highly fuel-efficient Diesel engines, combined with effective exhaust aftertreatment systems, enable an economic and low-emission operation of heavy-duty vehicles. The challenge of its development arises from the present engine complexity, which is expected to increase even more in the future. The approved method of test bench measurements is stretched to its limits, because of the high demand for large parameter variations. The introduction of a physics-based quasi-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of these Diesel engines. The stochastic reactor model mimics mixture and temperature inhomogeneities induced by turbulence, direct injection and heat transfer. Thus, it is possible to improve the prediction of NOx emissions compared to common mean-value models. To reduce the number of designs to be evaluated during … KW - Highly fuel-efficient Diesel engines Y1 - 2019 SN - 0096-5170 SN - 0148-7191 IS - 2019-01-1173 ER - TY - GEN A1 - Franken, Tim A1 - Netzer, Corinna A1 - Mauß, Fabian A1 - Pasternak, Michal A1 - Seidel, Lars A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Matrisciano, Andrea A1 - Kulzer, André Casal T1 - Multi-objective optimization of water injection in spark-ignition engines using the stochastic reactor model with tabulated chemistry T2 - International Journal of Engine Research N2 - 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. KW - Water Injection KW - Genetic Optimization KW - Spark Ignition Engine KW - Stochastic Reactor Model KW - Detailed Chemistry Y1 - 2019 UR - https://journals.sagepub.com/doi/full/10.1177/1468087419857602 U6 - https://doi.org/10.1177/1468087419857602 SN - 2041-3149 VL - 20 IS - 10 SP - 1089 EP - 1100 ER - TY - GEN A1 - Pasternak, Michal A1 - Mauß, Fabian A1 - Klauer, Christian A1 - Matrisciano, Andrea T1 - Diesel engine performance mapping using a parametrized mixing time model T2 - International Journal of Engine Research KW - Diesel engine performance Y1 - 2018 U6 - https://doi.org/10.1177/1468087417718115 SN - 2041-3149 SN - 1468-0874 VL - 19 IS - 2 SP - 202 EP - 213 ER - TY - GEN A1 - Franken, Tim A1 - Duggan, Alexander A1 - Feng, Tao A1 - Borg, Anders A1 - Lehtiniemi, Harry A1 - Matrisciano, Andrea A1 - Mauß, Fabian T1 - Multi-Objective Optimization of Fuel Consumption and NOx Emissions using a Stochastic Reactor Model, THIESEL 2018 Conference on Thermo- and Fluid Dynamic Processes in Direct Injection Engines KW - Multi-Objective Optimization Y1 - 2018 UR - https://www.researchgate.net/publication/328265385 ER -