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Effect of Extruded Mortar Joints on Mould Growth in Timber Frame Wall with Brick Veneer : Probabilistic and Machine Learning Modelling

Bayat Pour, Mohsen LU ; Kahangi Shahreza, Seyedmohammad LU orcid and Abdul Hamid, Akram LU orcid (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:
author
; and
organization
publishing date
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}},
}