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<export-example>
  <doc>
    <id>36729</id>
    <completedYear/>
    <publishedYear>2025</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>image</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-11-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Optimization of oxyfuel biogas combustion in combined heat and power plants : a multi-criteria study</title>
    <abstract language="eng">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.&#13;
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.</abstract>
    <parentTitle language="deu">32. Deutscher Flammentag – Paderborn, Germany: 15th – 17th September 2025</parentTitle>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="ConferenceTitle">32. Deutscher Flammentag</enrichment>
    <enrichment key="ConferencePlace">Paderborn</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <author>
      <firstName>Tim</firstName>
      <lastName>Franken</lastName>
    </author>
    <submitter>
      <firstName>Tim</firstName>
      <lastName>Franken</lastName>
    </submitter>
    <author>
      <firstName>Fabian</firstName>
      <lastName>Mauss</lastName>
    </author>
    <author>
      <firstName>Saurabh</firstName>
      <lastName>Sharma</lastName>
    </author>
    <author>
      <firstName>Arnim</firstName>
      <lastName>Brueger</lastName>
    </author>
    <author>
      <firstName>Marco</firstName>
      <lastName>Lepka</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biogas</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Oxyfuel</value>
    </subject>
    <collection role="institutes" number="3207">FG Thermodynamik / Thermische Verfahrenstechnik</collection>
    <collection role="institutes" number="7004">Energie-Innovationszentrum / Energy Storage and Conversion Lab</collection>
  </doc>
  <doc>
    <id>36727</id>
    <completedYear/>
    <publishedYear>2024</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>image</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2025-11-18</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Modeling of synthetic methane production using Gaussian processes regression</title>
    <abstract language="eng">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.&#13;
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.&#13;
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.</abstract>
    <parentTitle language="deu">CYPHER Workshop on "Digital Twins for the Decarbonization of hard-to-abate industries"</parentTitle>
    <identifier type="url">https://www.researchgate.net/publication/384441411_Modeling_of_synthetic_methane_production_using_Gaussian_processes_regression</identifier>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="ConferenceTitle">CYPHER Workshop on "Digital Twins for the Decarbonization of hard-to-abate industries"</enrichment>
    <enrichment key="ConferencePlace">Thessaloniki, Greece</enrichment>
    <author>
      <firstName>Tim</firstName>
      <lastName>Franken</lastName>
    </author>
    <submitter>
      <firstName>Tim</firstName>
      <lastName>Franken</lastName>
    </submitter>
    <author>
      <firstName>Rakhi</firstName>
      <lastName>Verma</lastName>
    </author>
    <author>
      <firstName>Saurabh</firstName>
      <lastName>Sharma</lastName>
    </author>
    <author>
      <firstName>Tobias</firstName>
      <lastName>Gloesslein</lastName>
    </author>
    <author>
      <firstName>Arnim</firstName>
      <lastName>Brueger</lastName>
    </author>
    <author>
      <firstName>Fabian</firstName>
      <lastName>Mauss</lastName>
    </author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Gaussian Processes</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Machine Learning</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Reactor</value>
    </subject>
    <collection role="institutes" number="3207">FG Thermodynamik / Thermische Verfahrenstechnik</collection>
    <collection role="institutes" number="7004">Energie-Innovationszentrum / Energy Storage and Conversion Lab</collection>
  </doc>
</export-example>
