Experimental investigation on monotonic bending behaviour of TSOBs bolted beam to hollow square section column connection with inner stiffener

Sun, Lele; Liang, Zeqi; Cai, Min; Liu, Xinyu; Wang, Peijun

doi:10.1016/j.jobe.2021.103765

Cited by 5 publications

(2 citation statements)

References 28 publications

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“…1), overcoming the installation challenges given by the lack of space to install a standard nut in the inner part of the steel tube. These connections are under investigation for the development of moment-resisting connections [9][10][11]. In the field of bolted connections in structural engineering, the use of traditional methods such as the component method [12] for the characterization of new bolting techniques continues to be highly researched [13][14][15].…”

Section: Application Backgroundmentioning

confidence: 99%

Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning

Cabrera

Ninić

Tizani

2023

Engineering with Computers

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The development of robust prediction tools based on machine learning (ML) techniques requires the availability of complete, consistent, accurate, and numerous datasets. The application of ML in structural engineering has been limited since, although real size experiments provide complete and accurate data, they are time-consuming and expensive. On the other hand, validated finite element (FE) models provide consistent and numerous synthetic data. Depending on the complexity of the problem, they might require large computational time and cost, and could be subjected to uncertainties and limitation in prediction capability given they are approximations of real-world problems. Hybrid approaches to combine experimental and synthetic datasets have emerged as an alternative to improve the reliability of ML model predictions. In this paper, we explore two hybrid methods to propose a robust approach for the prediction of the extended hollo-bolt (EHB) connection strength, stiffness, and column face displacement: (1) supervised ML methods with data fusion (DF) where learning is optimized with particle swarm optimization (PSO), and (2) artificial neural networks (ANN) based method with model fusion (MF). Based on the analysis of a dataset that combines 22 tensile experimental results with 2000 synthetic datapoints based on FE models, we concluded that using the first method (ML with DF and PSO) is the most suitable method for the prediction of the connection behavior. The ANN-based method with MF shows to be a promising method for the characterization of the EHB connection, however, more extensive experimental data is required for its implementation. Finally, a graphical user interface application was developed and shared in a public repository for the implementation of the proposed hybrid model.

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Section: Application Backgroundmentioning

confidence: 99%

Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning

Cabrera

Ninić

Tizani

2023

Engineering with Computers

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“…Liu et al tested the connection strength of tubular columns, added welding pads as reinforcement measures on the inner surface of tubular columns, revised the model of column wall bending strength prediction, and analyzed the influence of geometric shapes and material parameters on model failure 6 . Sun et al investigated the failure modes, bending moment-rotation relationships, characteristic values for structural behaviour, strain evolution of critical positions, and comparison with the reported behaviour of the unstrengthened joint, and the prediction models for the bending moment capacity of T-head Square-neck One-side Bolts with stiffeners are proposed 7 . Ye et al analyzed an experimental evaluation of the mechanical properties as well as flexural and local buckle strengths of steel square hollow section columns after heating and cooling processes 8 .…”

Section: Introductionmentioning

confidence: 99%

Application of telescopic box beam in heavy-duty wreckers

Liu

Zhang²,

Zhang³

et al. 2022

6th International Conference on Mechatronics and Intelligent Robotics (ICMIR2022)

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Heavy-duty wreckers generally use special operating devices such as lifting mechanisms and crane mechanisms to achieve the functions of supporting, lifting, and centering. The telescopic box beam is the most important working part of these mechanisms. Starting from the deflection differential equation, this paper derives the accurate recurrence formula of the out-of-plane instability critical force of the crane telescopic boom. Through the simulation analysis of ANSYS software, it is checked whether the strength of the telescopic box beam meets the design requirements.

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Mechanical performance of pre-engineered closed section beam-column connections in CFS frames: Experimental investigation

et al. 2022

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Experimental investigation on monotonic bending behaviour of TSOBs bolted beam to hollow square section column connection with inner stiffener

Cited by 5 publications

References 28 publications

Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning

Fusion of experimental and synthetic data for reliable prediction of steel connection behaviour using machine learning

Application of telescopic box beam in heavy-duty wreckers

Mechanical performance of pre-engineered closed section beam-column connections in CFS frames: Experimental investigation

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