Effect of Extruded Mortar Joints on Mould Growth in Timber Frame Wall with Brick Veneer : Probabilistic and Machine Learning Modelling
(2025) 552. p.17-22- Abstract
- Extruded mortar joints, resulting from suboptimal workmanship in bricklaying, bridge air gaps within cavity external walls. This phenomenon establishes a connection between brick masonry claddings and adjacent layers (such as insulation or weather-resistive barriers), inadvertently intensifying water penetration due to wind-driven rain (WDR) loads. This study utilises a probabilistic analysis in conjunction with a metamodel to explore the influence of extruded mortar joints on mould growth. The metamodel, constructed using the Random Forests (RF) machine learning algorithm, serves as a tool for predicting maximum mould index (MMI). By utilising two distinct water penetration criteria—ASHRAE and Experimental Study-based (ES)—, this study... (More)
- Extruded mortar joints, resulting from suboptimal workmanship in bricklaying, bridge air gaps within cavity external walls. This phenomenon establishes a connection between brick masonry claddings and adjacent layers (such as insulation or weather-resistive barriers), inadvertently intensifying water penetration due to wind-driven rain (WDR) loads. This study utilises a probabilistic analysis in conjunction with a metamodel to explore the influence of extruded mortar joints on mould growth. The metamodel, constructed using the Random Forests (RF) machine learning algorithm, serves as a tool for predicting maximum mould index (MMI). By utilising two distinct water penetration criteria—ASHRAE and Experimental Study-based (ES)—, this study assesses their impact concerning extruded mortar joints within the climatic conditions of Gothenburg, Sweden. The investigation includes four orientations of the case study to discern the effects of different orientations on the analysis. The results revealed a congruence between the ASHRAE and ES criteria for orientations with high WDR loads. However, in walls facing orientations with low WDR loads, the ASHRAE criterion yielded a higher MMI than the ES criterion. In addition, the metamodel importance analysis demonstrated a correlation between the increase in the extruded mortar depth and elevated MMI. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/85f4f3ea-4433-439d-9724-e26907dc2b88
- author
- Bayat Pour, Mohsen
LU
; Kahangi Shahreza, Seyedmohammad
LU
and Abdul Hamid, Akram LU
- organization
- publishing date
- 2025
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Extruded mortar joint, Machine learning, Water penetration
- host publication
- 9th International Building Physics Conference (IBPC 2024), Multiphysics and Multiscale Building Physics
- volume
- 552
- pages
- 6 pages
- publisher
- Springer
- external identifiers
-
- scopus:85217194588
- ISBN
- 978-981-97-8305-2
- 978-981-97-8304-5
- DOI
- 10.1007/978-981-97-8305-2_2
- language
- English
- LU publication?
- yes
- id
- 85f4f3ea-4433-439d-9724-e26907dc2b88
- date added to LUP
- 2024-12-24 16:38:05
- date last changed
- 2025-07-10 14:59:55
@inproceedings{85f4f3ea-4433-439d-9724-e26907dc2b88, abstract = {{Extruded mortar joints, resulting from suboptimal workmanship in bricklaying, bridge air gaps within cavity external walls. This phenomenon establishes a connection between brick masonry claddings and adjacent layers (such as insulation or weather-resistive barriers), inadvertently intensifying water penetration due to wind-driven rain (WDR) loads. This study utilises a probabilistic analysis in conjunction with a metamodel to explore the influence of extruded mortar joints on mould growth. The metamodel, constructed using the Random Forests (RF) machine learning algorithm, serves as a tool for predicting maximum mould index (MMI). By utilising two distinct water penetration criteria—ASHRAE and Experimental Study-based (ES)—, this study assesses their impact concerning extruded mortar joints within the climatic conditions of Gothenburg, Sweden. The investigation includes four orientations of the case study to discern the effects of different orientations on the analysis. The results revealed a congruence between the ASHRAE and ES criteria for orientations with high WDR loads. However, in walls facing orientations with low WDR loads, the ASHRAE criterion yielded a higher MMI than the ES criterion. In addition, the metamodel importance analysis demonstrated a correlation between the increase in the extruded mortar depth and elevated MMI.}}, author = {{Bayat Pour, Mohsen and Kahangi Shahreza, Seyedmohammad and Abdul Hamid, Akram}}, booktitle = {{9th International Building Physics Conference (IBPC 2024), Multiphysics and Multiscale Building Physics}}, isbn = {{978-981-97-8305-2}}, keywords = {{Extruded mortar joint; Machine learning; Water penetration}}, language = {{eng}}, pages = {{17--22}}, publisher = {{Springer}}, title = {{Effect of Extruded Mortar Joints on Mould Growth in Timber Frame Wall with Brick Veneer : Probabilistic and Machine Learning Modelling}}, url = {{http://dx.doi.org/10.1007/978-981-97-8305-2_2}}, doi = {{10.1007/978-981-97-8305-2_2}}, volume = {{552}}, year = {{2025}}, }