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Research on anti leakage construction of building engineering exterior wall based on improved attribute recognition model

Authors :
Jinquan Qian
Yi Gu
Source :
Case Studies in Construction Materials, Vol 17, Iss , Pp e01410- (2022)
Publication Year :
2022
Publisher :
Elsevier, 2022.

Abstract

Due to the complexity of building shape, the diversification of building materials and the nonstandard construction technology, the seepage channel exists in the outer wall envelope of building engineering, which causes the leakage of the outer wall of the building project to become more and more serious. Therefore, the research on the construction of anti leakage of the exterior wall of the building project based on the improved attribute identification model is proposed. On the basis of the attribute recognition theory subsystem, this paper introduces the grey correlation degree method in the grey system to improve the attribute recognition theory subsystem, and uses the improved attribute recognition model to analyze the influencing factors of the leakage of the building envelope. Based on the porous medium model and numerical simulation method, this paper studies the internal flow of the medium in the external wall of construction engineering, and constructs the micro flow numerical model of fracture water. In this paper, the influence of wind pressure, height and local structure on crack flow is analyzed. The results show that the initial velocity of water is related to wind pressure, building height and the local structure of surrounding retaining structure. The water flowing into the fracture is deep at a small speed, and the velocity inside the fracture has nothing to do with the pressure distribution inside the fracture.

Details

Language :
English
ISSN :
22145095
Volume :
17
Issue :
e01410-
Database :
Directory of Open Access Journals
Journal :
Case Studies in Construction Materials
Publication Type :
Academic Journal
Accession number :
edsdoj.4d5786c111ab460ea42f1c04c3593201
Document Type :
article
Full Text :
https://doi.org/10.1016/j.cscm.2022.e01410