All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

An overview of slagging and fouling indicators and their applicability to biomass fuels

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F21%3APU140664" target="_blank" >RIV/00216305:26210/21:PU140664 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.sciencedirect.com/science/article/pii/S0378382021000837" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0378382021000837</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.fuproc.2021.106804" target="_blank" >10.1016/j.fuproc.2021.106804</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    An overview of slagging and fouling indicators and their applicability to biomass fuels

  • Original language description

    Slagging and fouling are common problems associated with biomass firing. The different nature of the mineral and phase composition of biomass ash makes the vast experience with coal firing insufficient for its translation to biomass fuels, especially when it comes to slagging and fouling behavior. Biomass tends to have lower ash content than coals; however, it is often rich in volatile alkalis. The mineral deposits found on boiler walls and superheater tubes are often comprised of alkali compounds. Numerous studies on ash melting and particle sticking behavior have been conducted. Laboratory observed ash fusion temperatures are commonly used to evaluate the slagging and fouling propensity of fuels. The tests are often time consuming, therefore several predictive indices have been developed to estimate the propensity based on the ash composition alone. Thermodynamic models as well as neural networks have also been applied to this end. However, for practical in the field purposes, the ash fusion tests and predictive indices are preferred because of their convenience. An overview of these indices is presented in this work. A sizeable dataset has been collected in order to statistically evaluate the applicability of the indices and of several AFT prediction formulas. General trends in ash composition on this extensive dataset have also been illustrated. Finally, a more convenient graphical solution is presented for preliminary slagging and fouling predictions.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20402 - Chemical process engineering

Result continuities

  • Project

    <a href="/en/project/EF16_019%2F0000753" target="_blank" >EF16_019/0000753: Research centre for low-carbon energy technologies</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    FUEL PROCESSING TECHNOLOGY

  • ISSN

    0378-3820

  • e-ISSN

    1873-7188

  • Volume of the periodical

    217

  • Issue of the periodical within the volume

    1

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    10

  • Pages from-to

    106804-106804

  • UT code for WoS article

    000647475600003

  • EID of the result in the Scopus database

    2-s2.0-85102335397