<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>2777</id>
    <completedYear>2022</completedYear>
    <publishedYear/>
    <thesisYearAccepted/>
    <language>deu</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume>254</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2022-03-03</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="deu">Numerical investigation of sugarcane bagasse gasification using Aspen Plus and response surface methodology</title>
    <parentTitle language="deu">Energy Conversion and Management</parentTitle>
    <identifier type="doi">10.1016/j.enconman.2021.115198</identifier>
    <identifier type="issn">0196-8904</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY-NC-ND - Namensnennung - Nicht kommerziell - Keine Bearbeitungen 4.0</licence>
    <author>Emmanuel Yeri Kombe</author>
    <author>Nickson Langat</author>
    <author>Paul Njogu</author>
    <author>Reiner Malessa</author>
    <author>Christian-Toralf Weber</author>
    <author>Francis Njoka</author>
    <author>Ulrich Krause</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Biomass gasification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Aspen Plus</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Optimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Gibbs free energy minimization</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Response surface methodology</value>
    </subject>
    <collection role="ddc" number="621">Angewandte Physik</collection>
    <collection role="institutes" number="">Fachbereich Technik</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
  <doc>
    <id>2958</id>
    <completedYear>2022</completedYear>
    <publishedYear>2022</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>11</pageLast>
    <pageNumber>11</pageNumber>
    <edition/>
    <issue/>
    <volume>361</volume>
    <type>article</type>
    <publisherName>Elsevier</publisherName>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>2023-10-11</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Process modeling and evaluation of optimal operating conditions for production of hydrogen-rich syngas from air gasification of rice husks using aspen plus and response surface methodology</title>
    <abstract language="eng">Biomass gasification is recognized as a viable avenue to accelerate the sustainable production of hydrogen. In this work, a numerical simulation model of air gasification of rice husks is developed using the Aspen Plus to investigate the feasibility of producing hydrogen-rich syngas. The model is experimentally validated with rice husk gasification results and other published studies. The influence of temperature and equivalence ratio on the syngas composition, H2 yield, LHVSyngas, H2/CO ratio, CGE, and PCG was studied. Furthermore, the synchronized effects of temperature and ER are studied using RSM to determine the operational point of maximizing H2 yield and PCG. The RSM analysis results show optimum performance at temperatures between 820 °C and 1090 °C and ER in the range of 0.06–0.10. The findings show that optimal operating conditions of the gasification system can be achieved at a more refined precision through simulations coupled with advanced optimization techniques.</abstract>
    <parentTitle language="eng">Bioresource Technology</parentTitle>
    <identifier type="url">https://linkinghub.elsevier.com/retrieve/pii/S096085242201063X</identifier>
    <identifier type="std-doi">https://doi.org/10.1016/j.biortech.2022.127734</identifier>
    <identifier type="issn">0960-8524</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0</licence>
    <author>Emmanuel Yeri Kombe</author>
    <author>Nickson Lang'at</author>
    <author>Paul Njogu</author>
    <author>Reiner Malessa</author>
    <author>Christian-Toralf Weber</author>
    <author>Francis Njoka</author>
    <author>Ulrich Krause</author>
    <collection role="open_access" number="">open_access</collection>
    <collection role="institutes" number="">Fachbereich Technik</collection>
    <collection role="Hochschulbibliografie" number="1">Hochschulbibliografie</collection>
    <thesisPublisher>Technische Hochschule Brandenburg</thesisPublisher>
  </doc>
</export-example>
