Affiliation:
1. Department of Civil and Environmental Engineering, University of Alberta, Edmonton, AB T6G 1H9, Canada
Abstract
Partition walls play a crucial role in buildings, influencing their aesthetics, functionality, and integration with other architectural elements. However, the selection process for partition wall types is often challenging due to the multitude of options available, varying decision criteria, and inadequate decision-making practices in the Architecture, Engineering, and Construction (AEC) industry. To address these challenges and improve decision-making, a hybrid Decision Support System (DSS) named PartitionWall Pro is proposed. This tool combines both document-driven and model-driven approaches to assist in the selection and design of partition walls. The document-driven aspect utilizes a choosing-by-advantages (CBA) model to compare the advantages of different partition wall options, while the model-driven component employs computational design models to analyze the structural integrity of unreinforced masonry partition walls. Validation procedures ensure the reliability and accuracy of the DSS in practical applications. Through case studies involving a warehouse and a school, the study demonstrates how the DSS simplifies decision-making processes and encourages the adoption of cost-effective partition wall solutions. The results underline the potential of the DSS to enhance efficiency, foster stakeholder discussions, and improve communication in building design projects, thereby offering valuable insights for researchers and industry professionals alike, ultimately transforming partition wall design practice.
Funder
Natural Sciences and Engineering Research Council
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