Research status and prospect of machine learning in construction 3D printing
被引:24
作者:
Geng, Songyuan
论文数: 0引用数: 0
h-index: 0
机构:
Shenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Guangdong Prov Key Lab Durabil Marine Civil Engn, Shenzhen 518060, Guangdong, Peoples R ChinaShenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Geng, Songyuan
[1
,2
]
Luo, Qiling
论文数: 0引用数: 0
h-index: 0
机构:
Shenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Guangdong Prov Key Lab Durabil Marine Civil Engn, Shenzhen 518060, Guangdong, Peoples R ChinaShenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Luo, Qiling
[1
,2
]
Liu, Kun
论文数: 0引用数: 0
h-index: 0
机构:
China Railway Tunnel Grp Three Co, Shenzhen 518052, Guangdong, Peoples R ChinaShenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Liu, Kun
[3
]
Li, Yunchao
论文数: 0引用数: 0
h-index: 0
机构:
China Railway Tunnel Grp Three Co, Shenzhen 518052, Guangdong, Peoples R ChinaShenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Li, Yunchao
[3
]
Hou, Yuchen
论文数: 0引用数: 0
h-index: 0
机构:
China Railway Tunnel Grp Three Co, Shenzhen 518052, Guangdong, Peoples R ChinaShenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Hou, Yuchen
[3
]
Long, Wujian
论文数: 0引用数: 0
h-index: 0
机构:
Shenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Guangdong Prov Key Lab Durabil Marine Civil Engn, Shenzhen 518060, Guangdong, Peoples R China
3688 Nanhai Ave, Shenzhen, Guangdong, Peoples R ChinaShenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
Long, Wujian
[1
,2
,4
]
机构:
[1] Shenzhen Univ, Coll Civil & Transportat Engn, Shenzhen 518060, Guangdong, Peoples R China
[2] Guangdong Prov Key Lab Durabil Marine Civil Engn, Shenzhen 518060, Guangdong, Peoples R China
[3] China Railway Tunnel Grp Three Co, Shenzhen 518052, Guangdong, Peoples R China
[4] 3688 Nanhai Ave, Shenzhen, Guangdong, Peoples R China
3D printing;
Artificial intelligence;
Machine learning;
Civil engineering;
NEURAL-NETWORK;
COMPRESSIVE STRENGTH;
BUILDING COMPONENTS;
SURFACE-ROUGHNESS;
ANOMALY DETECTION;
BOND STRENGTH;
CONCRETE;
DESIGN;
PREDICTION;
CLASSIFICATION;
D O I:
10.1016/j.cscm.2023.e01952
中图分类号:
TU [建筑科学];
学科分类号:
0813 ;
摘要:
3D printing brings new opportunities for the development of civil engineering. Machine learning (ML) is also widely used in various fields of 3D printing. To describe the main research issues and potential future applications of ML for construction 3D printing, it is essential to comprehensively overview the current research topics. This paper aims to review, summarize, analyze, and introduce the research progress of ML applications in construction 3D printing, followed by a discussion of the current challenges and future research scope. Firstly, the classification and working principle of 3D printing and ML technology were introduced. Secondly, in the aspects of the design of construction materials, control of printing process, and quality inspection of con-struction components, the application status of ML in construction 3D printing was discussed. Based on this, in terms of interlayer bond performance enhancement, real-time status monitoring, and anisotropic behavior control, the future potential and challenges of ML in construction 3D printing were summarized, to provide a reference for promoting the realization of high-efficiency, intelligence, and sustainability in the field of civil engineering.