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  <doc>
    <id>30313</id>
    <completedYear/>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>image</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2023-02-06</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">BasMo - An interactive approach to modelling of trickle bed reactors</title>
    <abstract language="eng">The trickle bed reactor (TBR), in which gas and liquid flow downward through a packed bed to undergo chemical reactions, is a frequently used solution for industrial multiphase exothermic catalytic reactions (e.g., hydrogenation, oxidation, etc.) due to flexibility and simplicity of operation and large annual throughput (Tan et al., 2021). They have significant advantages with respect to other solutions, but they also show complex behaviour, with uncertainties in catalyst heterogeneity, packing, fluid flow, and transport parameters, resulting in its modelling being highly challenging (Azarpour et al., 2021).&#13;
In this contribution, the development of an interactive toolbox for the simulation of TBRs, based on the work of Schwidder &amp; Schnitzlein (2012) is introduced. The implementation uses a modular and flexible setup, mirroring the multiscale nature of the phenomena tacking place in the reactor, from large scale of the reactor to the medium and low scale of the particle bed, fluid flow, as well as fluid-solid and fluid-fluid interactions, including chemical reactions. The toolbox enables implementation of complex geometries of the catalyst particles, enabled by a novel representation of the surface mesh. Validation using experimental data shows that the model is able to reliably predict the performance of the catalytic TBR.</abstract>
    <parentTitle language="eng">Jahrestreffen der "Prozess-, Apparate- und Anlagentechnik", 21.–22. November 2022, Frankfurt am Main</parentTitle>
    <identifier type="url">https://dechema.de/PAAT2022_Themen/_/_1_Programm_PAAT_2022_ezl.pdf</identifier>
    <enrichment key="BTU">an der BTU erstellt / created at BTU</enrichment>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="opus.doi.autoCreate">false</enrichment>
    <enrichment key="opus.urn.autoCreate">false</enrichment>
    <enrichment key="Fprofil">1 Energiewende und Dekarbonisierung / Energy Transition and Decarbonisation</enrichment>
    <enrichment key="Fprofil">4 Künstliche Intelligenz und Sensorik / Artificial Intelligence and Sensor Technology</enrichment>
    <author>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </author>
    <submitter>
      <firstName>Bogdan</firstName>
      <lastName>Dorneanu</lastName>
    </submitter>
    <author>
      <firstName>Norbert</firstName>
      <lastName>Heinzelmann</lastName>
    </author>
    <author>
      <firstName>Klaus</firstName>
      <lastName>Schnitzlein</lastName>
    </author>
    <author>
      <firstName>Harvey</firstName>
      <lastName>Arellano-García</lastName>
    </author>
    <collection role="institutes" number="3603">FG Prozess- und Anlagentechnik</collection>
  </doc>
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