System disruptions
We are currently experiencing disruptions on the search portals due to high traffic. We are working to resolve the issue, you may temporarily encounter an error message.
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Utveckling och validering av modeller för att prediktera mögelväxt i byggnader
RISE Research Institutes of Sweden, Built Environment, Building and Real Estate.ORCID iD: 0000-0003-0200-6513
Lund University, Sweden.
Lund University, Sweden.
Thomas Svensson Ingenjörsstatistik, Sweden.
Show others and affiliations
2018 (Swedish)Report (Other academic)
Abstract [en]

In this project we have tested a mould model originally developed by Skanska (the m-model) and a method developed by RISE in Sweden (the GLC-method) on data from both laboratory and field measurements. The laboratory measurements had durations of a few months and were made in climate chambers at RISE; the field measurements were made in 12 buildings during 30 months. In both cases, temperature, relative humidity and mould growth was assessed on six different materials. The results were used to investigate if the m-model or the GLC-method could predict when there was mould growth. Both methods could differentiate between the (dry) cases without mould and the (moist) cases with mould. However, we could not find mould resistance parameters for the tested materials to be used with the m-model. This could be because the m-model cannot predict mould growth well enough, but it can also be because the types of measurements that we have made have relative large uncertainties in relative humidity. Isotheral calorimetry was also investigated as an interesting method to study how drying affects the activity of mould fungi.

Place, publisher, year, edition, pages
2018. , p. 48
Series
RISE Rapport ; 2018:167
Keywords [en]
mould, prediction, model, building materials, moisture, RH, critical moisture level
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-50999ISBN: 978-91-88695-51-2 (electronic)OAI: oai:DiVA.org:ri-50999DiVA, id: diva2:1507818
Available from: 2020-12-08 Created: 2020-12-08 Last updated: 2023-06-05Bibliographically approved

Open Access in DiVA

fulltext(1991 kB)184 downloads
File information
File name FULLTEXT01.pdfFile size 1991 kBChecksum SHA-512
2cac4e2fdef2c9c92ea12fb07844a9354c298f4606e389112dbeb22341105371db4e8c5ef1a2a1ae2bec4cc8e3d30bc59a17012333a3d8048336b45d5ed751a3
Type fulltextMimetype application/pdf

Authority records

Johansson, Pernilla

Search in DiVA

By author/editor
Johansson, Pernilla
By organisation
Building and Real Estate
Natural Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 185 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 203 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf