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Using Machine Learning and Finite Element Modelling to Develop a Formula to Determine the Deflection of Horizontally Curved Steel I-beams
被引:1
|作者:
Ababu, Elvis M.
[1
]
Markou, George
[1
]
Bakas, Nikolaos
[2
]
机构:
[1] Univ Pretoria, Dept Civil Engn, Lynnwood Rd, Pretoria, South Africa
[2] RDC Informat, Dept RnD, Athens, Greece
来源:
ICAART: PROCEEDINGS OF THE 14TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE - VOL 3
|
2022年
关键词:
Curved Beams;
Machine Learning;
Steel;
Finite Element Method;
Design;
BEHAVIOR;
D O I:
10.5220/0010982400003116
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
The use of curved I-beams has been increasing throughout the years as the steel forming industry continues to advance. However, there are often design limitations on such structures due to the lack of recommendations and design code formulae for the estimation of the expected deflection of these structures. This is attributed to the lack of understanding of the behaviour of curved I-beams that exhibit extreme torsion and bending. Thus, currently, there are no formulae readily available for practising engineers to use to estimate the deflection of curved beams. Since the design of light steel structures is often governed by serviceability considerations, this paper aims to analyse the properties of curved steel I-beams and their impact on deflection as well as develop an accurate formula that will be able to predict the expected deflection of these beams. By using a combination of an experimentally validated finite element modelling approach and machine learning. Numerous formulae are developed and tested for the needs of this research work. The final proposed formula, which is the first of its kind, was found to have an average error of 4.11% in estimating the midspan deflection on the test dataset.
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页码:958 / 963
页数:6
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