Post-fire load-reversed push-out performance of normal and lightweight concrete-filled steel tube columns: Experiments and predictions

Parsa-Sharif, Mohammad; Nematzadeh, Mahdi; Bahrami, Amirreza

doi:10.1016/j.istruc.2023.03.091

Cited by 8 publications

(1 citation statement)

References 26 publications

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“…The test results of ambient and post-fire bond strength of CFST columns [21][22][23][24][25][26] from the literature are shown in Figure 4 for comparison with Japanese, Chinese, and Eurocode values. It can be seen that bond strength in CFST columns has enhanced over the past decade.…”

Section: Figure 3 Typical Bond-slip Curve For Push-out Tests On Cfst ...mentioning

confidence: 99%

Bond Strength of Rectangular CFSST Columns after Exposed to Elevated Temperature

K.,

Santhi

2024

Civ Eng J

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This article investigates the bond- behavior of Rectangular Concrete-filled stainless-steel tubular (RCFSST) columns under post-fire conditions. The main objective of this research was to obtain τ-s relationship of RCFSST columns under the combined effects of high temperature and concrete age. A total of sixteen specimens, including four reference specimens, were tested with different parameters, namely: i) temperature (600 °C, 800 °C & 1000 °C) ii) different concrete ages (30 days, 60 days, 90 days & 180 days). Analyzing the τ-s curves of the test specimens, chemical adhesion and micro-locking were the principal forces contributing to bond strength at lower concrete ages under post-fire conditions. At a higher concrete age, RCFSST specimens displayed a longer curve after the inflection point, indicating the contribution of macro-locking forces in amplifying the bond-strength. Five distinct curve types were found from the experiments. Type 1 curves with three stages, i) initial linear, ii) non-linear, and ii) final linear stage, had a higher frequency among the other types. For 90-day cured specimens, a decline in bond strength was observed at higher temperatures, but for 180 days cured specimens, a significant rise was seen under post-fire conditions. A new set of τ-s relations for RCFSST columns with different concrete ages under post-fire was established. Doi: 10.28991/CEJ-2024-010-03-019 Full Text: PDF

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Section: Figure 3 Typical Bond-slip Curve For Push-out Tests On Cfst ...mentioning

confidence: 99%

Bond Strength of Rectangular CFSST Columns after Exposed to Elevated Temperature

K.,

Santhi

2024

Civ Eng J

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Machine learning and nonlinear finite element analysis of fiber‐reinforced polymer‐confined concrete‐steel double‐skin tubular columns under axial compression

Isleem,

Qiong,

Chukka

et al. 2024

Structural Concrete

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Fiber‐reinforced polymer (FRP)‐confined double‐skin tubular columns (DSTCs) are an innovative type of hybrid columns that consist of an outer tube made of FRP, an inner circular steel tube, and a concrete core sandwiched between them. Available literature focuses on hollow DSTCs with limited research on DSTCs made with inner steel tubes filled with concrete. Overall, DSTCs have many applications, highlighting the importance of studying the effects of concrete filling and strength on the composite system. To address this gap, finite element models (FEMs) and both traditional and innovative machine learning (ML) techniques were used to develop accurate models for predicting load‐bearing capacity and confined ultimate strain under axial loads. A comprehensive database of 60 experimental tests and 45 FEMs simulations of columns was analyzed, with five parameters selected as input variables for ML‐based models. New techniques like gradient boosting (GB), random forest (RF), convolutional neural networks, and long short‐term memory are compared with established algorithms like multiple linear regression, support vector regression (SVR), and empirical mode decomposition (EMD)‐SVR. Regression error characteristics curve, Shapley Additive Explanation analysis, and statistical metrics are used to assess the performance of these models using a database containing 105 FEMs test results that cover a range of input variables. While EMD‐SVR and GB perform well for confined ultimate strain, the suggested EMD‐SVR, GB, and RF models show superior predictive accuracy for confined ultimate load. To be more precise, for confined ultimate load prediction, EMD‐SVR, GB, and RF obtain values of 0.99, 0.989, and 0.960, respectively. The values for GB and EMD‐SVR at confined ultimate strain are 0.690 and 0.99, respectively. However, design engineers are limited by the “black‐box” nature of ML. In order to solve this, the study presents an open‐source GUI based on GB, which gives engineers the ability to precisely estimate confined ultimate load and strain under various test conditions, enabling them to make well‐informed decisions about mix proportion.

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Nonlinear finite element and machine learning modeling of tubed reinforced concrete columns under eccentric axial compression loading

Isleem,

Chukka,

Bahrami

et al. 2024

Alexandria Engineering Journal

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Post-fire load-reversed push-out performance of normal and lightweight concrete-filled steel tube columns: Experiments and predictions

Cited by 8 publications

References 26 publications

Bond Strength of Rectangular CFSST Columns after Exposed to Elevated Temperature

Bond Strength of Rectangular CFSST Columns after Exposed to Elevated Temperature

Machine learning and nonlinear finite element analysis of fiber‐reinforced polymer‐confined concrete‐steel double‐skin tubular columns under axial compression

Nonlinear finite element and machine learning modeling of tubed reinforced concrete columns under eccentric axial compression loading

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