TY - GEN A1 - Matrisciano, Andrea A1 - Franken, Tim A1 - Gonzalez Mestre, Laura Catalina A1 - Borg, Anders A1 - Mauß, Fabian T1 - Development of a Computationally Efficient Tabulated Chemistry Solver for Internal Combustion Engine Optimization Using Stochastic Reactor Models T2 - Applied Sciences N2 - The use of chemical kinetic mechanisms in computer aided engineering tools for internal combustion engine simulations is of high importance for studying and predicting pollutant formation of conventional and alternative fuels. However, usage of complex reaction schemes is accompanied by high computational cost in 0-D, 1-D and 3-D computational fluid dynamics frameworks. The present work aims to address this challenge and allow broader deployment of detailed chemistry-based simulations, such as in multi-objective engine optimization campaigns. A fast-running tabulated chemistry solver coupled to a 0-D probability density function-based approach for the modelling of compression and spark ignition engine combustion is proposed. A stochastic reactor engine model has been extended with a progress variable-based framework, allowing the use of pre-calculated auto-ignition tables instead of solving the chemical reactions on-the-fly. As a first validation step, the tabulated chemistry-based solver is assessed against the online chemistry solver under constant pressure reactor conditions. Secondly, performance and accuracy targets of the progress variable-based solver are verified using stochastic reactor models under compression and spark ignition engine conditions. Detailed multicomponent mechanisms comprising up to 475 species are employed in both the tabulated and online chemistry simulation campaigns. The proposed progress variable-based solver proved to be in good agreement with the detailed online chemistry one in terms of combustion performance as well as engine-out emission predictions (CO, CO2, NO and unburned hydrocarbons). Concerning computational performances, the newly proposed solver delivers remarkable speed-ups (up to four orders of magnitude) when compared to the online chemistry simulations. In turn, the new solver allows the stochastic reactor model to be computationally competitive with much lower order modeling approaches (i.e., Vibe-based models). It also makes the stochastic reactor model a feasible computer aided engineering framework of choice for multi-objective engine optimization campaigns. Y1 - 2020 U6 - https://doi.org/10.3390/app10248979 SN - 2076-3417 VL - 10 IS - 24 ER - TY - GEN A1 - Matrisciano, Andrea A1 - Netzer, Corinna A1 - Werner, Adina A1 - Borg, Anders A1 - Seidel, Lars A1 - Mauß, Fabian T1 - A Computationally Efficient Progress Variable Approach for In-Cylinder Combustion and Emissions Simulations T2 - SAE Technical Paper N2 - 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. Y1 - 2019 U6 - https://doi.org/10.4271/2019-24-0011 SN - 0148-7191 SN - 2688-3627 ER - TY - GEN A1 - Franken, Tim A1 - Duggan, Alexander A1 - Matrisciano, Andrea A1 - Lehtiniemi, Harry A1 - Borg, Anders A1 - Mauß, Fabian T1 - Multi-Objective Optimization of Fuel Consumption and NO x Emissions with Reliability Analysis Using a Stochastic Reactor Model T2 - SAE Technical Paper N2 - The introduction of a physics-based zero-dimensional stochastic reactor model combined with tabulated chemistry enables the simulation-supported development of future compression-ignited 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 the simulation-based multi-objective optimization, genetic algorithms are proven to be an effective tool. Based on an initial set of designs, the algorithm aims to evolve the designs to find the best parameters for the given constraints and objectives. The extension by response surface models improves the prediction of the best possible Pareto Front, while the time of optimization is kept low. This work presents a novel methodology to couple the stochastic reactor model and the Non-dominated Sorting Genetic Algorithm. First, the stochastic reactor model is calibrated for 10 low, medium and high load operating points at various engine speeds. Second, each operating point is optimized to find the lowest fuel consumption and specific NOx emissions. The optimization input parameters are the temperature at intake valve closure, the compression ratio, the start of injection, the injection pressure and exhaust gas recirculation rate. Additionally, it is ensured that the maximum peak cylinder pressure and turbine inlet temperature are not exceeded. This enables a safe operation of the engine and exhaust aftertreatment system under the optimized conditions. Subsequently, a reliability analysis is performed to estimate the effect of off-nominal conditions on the objectives and constraints. The novel multi-objective optimization methodology has proven to deliver reasonable results. The zero-dimensional stochastic reactor model with tabulated chemistry is a fast running physics-based model that allow to run large optimization problems in a short amount of time. The combination with the reliability analysis also strengthens the confidence in the simulation-based optimized engine operation parameters. Y1 - 2019 U6 - https://doi.org/10.4271/2019-01-1173 SN - 0148-7191 SN - 2688-3627 ER - TY - GEN A1 - Kurapati, Vinaykumar Reddy A1 - Borg, Anders A1 - Seidel, Lars A1 - Mauß, Fabian T1 - Fast CFD Diesel engine modelling using the 1-Dimentional SprayLet approach T2 - SAE Technical Paper N2 - In the SAE article 2023-24-0083: SprayLet: One-dimensional interactive cross-sectionally averaged spray model, we formulatet a one-dimensional Spray model in interaction with the surrounding gas phase. We could demonstrate, that the model predicted liquid and gaseous penetration length in good aggreement with ECN spray experiments. In this paper we use this model in engine CFD (CONVERGE CFD) and demonstrate a strong reduction in CPU time (50%). We can show a strong decrease in grid dependency, which allows a further reduction of CPU time (90%). We will present engine CFD simulations, comparing detailed spray with SpayLet simulations. This includes pressure traces, heat release, and emissions. Y1 - 2024 UR - https://www.sae.org/publications/technical-papers/content/2024-01-2684/ SN - 0148-7191 SN - 2688-3627 IS - 2024-01-2684 ER - TY - GEN A1 - Kurapati, Vinaykumar Reddy A1 - Borg, Anders A1 - Seidel, Lars A1 - Mauß, Fabian T1 - SprayLet: One-Dimensional Interactive Cross-Sectionally Averaged Spray Model T2 - SAE Technical Paper N2 - Spray modeling is among the main aspects of mixture formation and combustion in internal combustion engines. It plays a major role in pollutant formation and energy efficiency although adequate modeling is still under development. Strong grid dependence is observed in the droplet-based stochastic spray model commonly used. As an alternative, an interactive model called 'SprayLet' is being developed for spray simulations based on one-dimensional integrated equations for the gas and liquid phases, resulting from cross-sectionally averaging of multi-dimensional transport equations to improve statistical convergence. The formulated one-dimensional cross-section averaged system is solved independently of the CFD program to provide source terms for mass, momentum and heat transfer between the gas and liquid phases. The transport processes take place in a given spray cone where the nozzle exit is automatically resolved. In the 1D program, the conservation equations are for droplet diameter, droplet temperature, as well as for continuity and momentum of the liquid and the gaseous phase are solved. The source terms between the phases are conservatively embedded into the spray region of the CFD program. In CFD program, the transport equations are solved for gas phase only. The SprayLet model is validated using standard Sandia sprays by comparing penetration lengths and fuel mixture fractions with experimental data. Y1 - 2023 U6 - https://doi.org/10.4271/2023-24-0083 SN - 0148-7191 SN - 2688-3627 ER - TY - GEN A1 - Turquand d'Auzay, Charles A1 - Shapiro, Evgeniy A1 - Prouvier, Matthieu A1 - Winkler, Axel A1 - Seidel, Lars A1 - Borg, Anders A1 - Mauß, Fabian T1 - Evaluation of Fast Detailed Kinetics Calibration Methodology for 3D CFD Simulations of Spray Combustion T2 - SAE Technical Paper N2 - Meeting strict current and future emissions legislation necessitates development of computational tools capable of predicting the behaviour of combustion and emissions with an accuracy sufficient to make correct design decisions while keeping computational cost of the simulations amenable for large-scale design space exploration. While detailed kinetics modelling is increasingly seen as a necessity for accurate simulations, the computational cost can be often prohibitive, prompting interest in simplified approaches allowing fast simulation of reduced mechanisms at coarse grid resolutions appropriate for internal combustion engine simulations in design context. In this study we present a simplified Well-stirred Reactor (WSR) implementation coupled with 3D CFD Ricardo VECTIS solver. A detailed evaluation of benchmark ECN spray problem is presented demonstrating that a single point calibration of such a model using a bulk reaction multiplier approach can provide correct representation of the solution across a wide range of temperatures on grid sizes typically employed for RANS internal combustion engine simulations with tabulated kinetics or zonal combustion models. Y1 - 2022 U6 - https://doi.org/10.4271/2022-01-1042 SN - 0148-7191 SN - 0096-5170 IS - 2022-01-1042 ER -