TY - GEN A1 - Franken, Tim A1 - Mauss, Fabian A1 - Sharma, Saurabh A1 - Brueger, Arnim A1 - Lepka, Marco T1 - Optimization of oxyfuel biogas combustion in combined heat and power plants : a multi-criteria study T2 - 32. Deutscher Flammentag – Paderborn, Germany: 15th – 17th September 2025 N2 - This paper investigates the influence of oxygen addition on the combustion of biogas and biomethane in a combined heat and power plant using numerical methods. A multi-objective optimization platform was established, employing a stochastic engine model with detailed chemistry to predict oxyfuel combustion and emission formation. Additionally, a hybrid optimization algorithm, combining NSGA-II and metamodels, was utilized to conduct the optimization. The optimization results indicate that the lowest indicated specific fuel consumption was achieved with biomethane, while the lowest NOx emissions were attained with biogas. An increase in oxygen addition proved beneficial for reducing specific fuel consumption. However, higher oxygen addition rates resulted in increased NOx emissions. KW - Biogas KW - Optimization KW - Oxyfuel Y1 - 2025 ER - TY - GEN A1 - Franken, Tim A1 - Verma, Rakhi A1 - Sharma, Saurabh A1 - Gloesslein, Tobias A1 - Brueger, Arnim A1 - Mauss, Fabian T1 - Modeling of synthetic methane production using Gaussian processes regression T2 - CYPHER Workshop on "Digital Twins for the Decarbonization of hard-to-abate industries" N2 - The production of green gases using Power-to-gas in industry and the energy sector is essential for reducing the carbon footprint. In this process, green hydrogen and carbon dioxide are converted into synthetic methane using nickel catalysts. The carbon dioxide can be obtained from the environment or from point sources such as waste-to-energy plants, combined heat and power plants or industrial furnaces. A one-dimensional model of methane synthesis in the Sabatier reactor enables the simulation of transport processes in the porous medium and the reaction kinetics on the active surface of the nickel catalyst. Despite the low dimensionality, the reactor model is still computationally intensive, as it must solve the reaction mechanism of heterogeneous surface reactions and the mass and heat transport. The introduction of Gaussian processes regression can help to significantly reduce the computational effort for the prediction of species and temperature in the Sabatier reactor under different thermodynamic conditions. This allows for faster turnaround times, enables the application of advanced methods like optimization and more. The accuracy of a Gaussian processes regression is investigated in this work. KW - Gaussian Processes KW - Machine Learning KW - Reactor Y1 - 2024 UR - https://www.researchgate.net/publication/384441411_Modeling_of_synthetic_methane_production_using_Gaussian_processes_regression ER -