Experimental and numerical analyses on stress concentration factors of concrete-filled welded integral K-joints in steel truss bridges

Jiang, Lei; Liu, Yongjian; Fam, Amir; Liu, Bin; Pu, Beichen; Zhao, Runze

doi:10.1016/j.tws.2022.110347

Cited by 10 publications

(6 citation statements)

References 29 publications

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“…In Ref. 16 , the maximum standard deviations in T-joint between formulae and experimental results under in-plane bending are greater than 0.2. Therefore, it can be seen that the fitting of the stress concentration coefficient has a certain degree of discreteness in the data.…”

Section: Suggestionsmentioning

confidence: 92%

“…22. Lei et al 23 and Lin et al 40 studied SCFs of the tubular joints with brace under axial tension, and Zheng et al 14 and Tong et al 16 found that When the brace of the T-joint was under tension, the SCFs in the joint were much higher than those under compression.…”

Section: Generalmentioning

confidence: 99%

“…Nevertheless, according to the Ref. 13,16 , the proposed formulae can capture the maximum SCF in the welded tubular joints, which plays the most important role in the prediction of fatigue life and the design of the welded tubular joints. The results calculated by the proposed formulae are conservative and the formulae are acceptable for predicting the SCFs and being applied to the fatigue design of SHS-CFSHS X-joints.…”

Section: Comparison Of Scfs Determined From Formulae and Testmentioning

confidence: 99%

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Experimental and numerical investigations on stress concentration factors of concrete filled steel tube X-joints

Diao,

He,

Wang

et al. 2024

Sci Rep

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An SHS-CFSHS X-joint is fabricated by welding two square hollow section (SHS) braces to a concrete-filled square hollow section (CFSHS) chord. In this paper, the stress concentration factors (SCFs) of SHS-CFSHS X-joints are investigated through experimental tests and finite element analysis (FEA), with the hot spot stress method serving as the analytical approach. Eight specimens are designed and manufactured, with FE models built in software ANSYS. These FE models are validated against the test results. The specimens are tested under brace axial tension to determine the SCFs of the X-joints. It shows that the concrete filled in the chord effectively reduces the SCFs of the X-joints. To further explore various load conditions and the influence of the parameters, FEA is carried out and a total of 64 FE models are built. Based on the FEA results, multiple regression analysis is used to obtain the SCF formulae of SHS-CFSHS X-joints under axial tension load and in-plane bending load in the brace, respectively. Comparison and analysis of the SCF results obtained from experimental tests, the proposed formulae, and FE simulations reveal that the formulae presented in this study are both conservative and suitable for predicting SCFs.

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Section: Suggestionsmentioning

confidence: 92%

Section: Generalmentioning

confidence: 99%

Section: Comparison Of Scfs Determined From Formulae and Testmentioning

confidence: 99%

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Experimental and numerical investigations on stress concentration factors of concrete filled steel tube X-joints

Diao,

He,

Wang

et al. 2024

Sci Rep

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“…Xu et al [11] proposed a novel anchor-rebarcolumn-foundation connection (SAC) tailored for CFST columns, and M. Ansari et al [12] undertook a numerical analysis of the performance of a rib stiffener steel beam connected to a circular CFST column under cyclic loading conditions. Additionally, Lei et al [13] introduced a novel fully welded concrete-filled integral K-joint with longitudinal preformed ribs to enhance fatigue performance, and Sun et al [14] delved into the local and post-local buckling behavior of welded square high-strength steel tubes with concreteinfilled restraints. Further contributions include Liu et al [15], who designed a T-shaped irregular CFST column by welding I-shaped and U-shaped steel components together and assessed their flexural stability under combined axial loads and moments.…”

Section: Introductionmentioning

confidence: 99%

Mechanical Behavior of Precast Circular Semi-Continuous CFST Columns under a Uniaxial Eccentric Load

Cao,

Zhu,

Qian

et al. 2024

Buildings

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For this study, we conducted a detailed examination and comprehensive comparative analysis of the structural responses and mechanical behavior of bolted sleeve connections in precast circular semi-continuous steel tubular concrete (PCSCFST) columns. The research involved fourteen specimens, and we considered the impacts of various parameters, including eccentricity, external steel sleeve thickness, bolt diameter, and slenderness ratio. The findings revealed that the external steel sleeve significantly enhances the protection of the connection area, enabling the bolts to effectively withstand eccentric loads. However, sleeves that are too thick may lead to premature bolt failure, reducing their ultimate load-bearing capacity. Using bolts to transfer loads to the concrete significantly strengthens the restraining effect of the steel sleeve. Nonetheless, increasing the bolt diameter beyond a certain threshold may diminish this beneficial impact, potentially leading to connection failure and a decrease in ultimate load-bearing capacity. A new ‘cooperative value q’ measures component collaboration at ultimate capacity, showing that shorter columns offer less effective coordination than longer ones. Through regression analysis, we formulated a prediction for axial ultimate bearing capacity, closely aligning with the experimental data (Npre-a/Nu average value of 1.003, variance 0.00248). Three N–M curves, including the Eurocode 4 method, offered conservative predictions, with Eurocode 4 closely matching the experimental results. A refined prediction method following Eurocode 4 was developed, yielding an average Ppre-U/Pu value of 0.971 and a variance of 0.0107.

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“…The significance of stress concentration analysis extends to many engineering disciplines such as automotive [11], aerospace [12], construction [13], biomechanics [14], etc. Significant effort has been made within the scope of manufacturing to identify the impact of pores or defects on the performance of printed parts [15].…”

Section: Introductionmentioning

confidence: 99%

A finite element-convolutional neural network model (FE-CNN) for stress field analysis around arbitrary inclusions

Rezasefat,

Hogan

2023

Mach. Learn.: Sci. Technol.

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This study presents a data-driven finite element-machine learning surrogate model for predicting the end-to-end full-field stress distribution and stress concentration around an arbitrary-shaped inclusion. This is important because the model’s capacity to handle large datasets, consider variations in size and shape, and accurately replicate stress fields makes it a valuable tool for studying how inclusion characteristics affect material performance. An automatized dataset generation method using finite element simulation is proposed, validated, and used for attaining a dataset with one thousand inclusion shapes motivated by experimental observations and their corresponding spatially-varying stress distributions. A U-Net-based convolutional neural network (CNN) is trained using the dataset, and its performance is evaluated through quantitative and qualitative comparisons. The dataset, consisting of these stress data arrays, is directly fed into the CNN model for training and evaluation. This approach bypasses the need for converting the stress data into image format, allowing for a more direct and efficient input representation for the CNN. The model was evaluated through a series of sensitivity analyses, focusing on the impact of dataset size and model resolution on accuracy and performance. The results demonstrated that increasing the dataset size significantly improved the model’s prediction accuracy, as indicated by the correlation values. Additionally, the investigation into the effect of model resolution revealed that higher resolutions led to better stress field predictions and reduced error. Overall, the surrogate model proved effective in accurately predicting the effective stress concentration in inclusions, showcasing its potential in practical applications requiring stress analysis such as structural engineering, material design, failure analysis, and multi-scale modeling.

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Experimental and numerical analyses on stress concentration factors of concrete-filled welded integral K-joints in steel truss bridges

Cited by 10 publications

References 29 publications

Experimental and numerical investigations on stress concentration factors of concrete filled steel tube X-joints

Experimental and numerical investigations on stress concentration factors of concrete filled steel tube X-joints

Mechanical Behavior of Precast Circular Semi-Continuous CFST Columns under a Uniaxial Eccentric Load

A finite element-convolutional neural network model (FE-CNN) for stress field analysis around arbitrary inclusions

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