Optimal probability function for ultimate resistance of offshore T/Y-connections enhanced with collar plates under compression, tension, and bending loads

This research introduces three theoretical probabilistic models to predict the ultimate resistance of T- and Y-nodes enhanced with collar plates in compressive, tensile, and bending loads. The study commenced with the creation and validation of a finite element (FE) model, incorporating 18 experimental results from the author and other researchers to ensure model accuracy. Following this, 630 FE simulations were carried out to evaluate the behavior of the retrofitted nodes. In the numerical simulations, welds connecting the reinforcement plate to the chord, as well as those between the brace and the reinforcement plate, were explicitly incorporated. Additionally, the contact behavior at the interface between the collar plate and the chord was modeled to accurately capture their interaction. The simulation data provided a strong basis for developing probabilistic models. 14 functions were fitted to the generated histograms. The appropriateness of the proposed distributions was verified through three statistical tests: Anderson-Darling, Chi-square, and Kolmogorov-Smirnov. Of the tested models, the Johnson SB was found to be the most accurate for modeling the resistance under compression. Also, for the enhanced connections under tensile and in-plane bending loads, the Generalized Extreme Value model was established. These findings demonstrate the potential of the proposed probabilistic framework to enhance the understanding and assessment of the behavior of strengthened T- and Y-shaped joints, within the scope and assumptions of the current study.

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Publication Details

Journal
Scientific Reports
Published
2025-10-21
DOI
https://doi.org/10.1038/s41598-025-20725-z
Citations
8
Primary Topic
Structural Load-Bearing Analysis
Type
article
Field-Weighted Citation Impact
7.63
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article

Optimal probability function for ultimate resistance of offshore T/Y-connections enhanced with collar plates under compression, tension, and bending loads

Hossein Nassiraei
8 citations
Scientific Reports
Structural Load-Bearing Analysis
7.63
article

Optimal probability function for ultimate resistance of offshore T/Y-connections enhanced with collar plates under compression, tension, and bending loads

Hossein Nassiraei
article en
8 citations

Abstract

This research introduces three theoretical probabilistic models to predict the ultimate resistance of T- and Y-nodes enhanced with collar plates in compressive, tensile, and bending loads. The study commenced with the creation and validation of a finite element (FE) model, incorporating 18 experimental results from the author and other researchers to ensure model accuracy. Following this, 630 FE simulations were carried out to evaluate the behavior of the retrofitted nodes. In the numerical simulations, welds connecting the reinforcement plate to the chord, as well as those between the brace and the reinforcement plate, were explicitly incorporated. Additionally, the contact behavior at the interface between the collar plate and the chord was modeled to accurately capture their interaction. The simulation data provided a strong basis for developing probabilistic models. 14 functions were fitted to the generated histograms. The appropriateness of the proposed distributions was verified through three statistical tests: Anderson-Darling, Chi-square, and Kolmogorov-Smirnov. Of the tested models, the Johnson SB was found to be the most accurate for modeling the resistance under compression. Also, for the enhanced connections under tensile and in-plane bending loads, the Generalized Extreme Value model was established. These findings demonstrate the potential of the proposed probabilistic framework to enhance the understanding and assessment of the behavior of strengthened T- and Y-shaped joints, within the scope and assumptions of the current study.

Scientific ReportsVol. 15(1)
University of Guilan (IR)
Openalex Percentile: Top 2%
Structural Load-Bearing Analysis
7.63
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