Design procedure for the web-post buckling of steel cellular beams

Grilo, Lucas Figueiredo; Fakury, Ricardo Hallal; Silva, Ana Lydia Reis de Castro e; Veríssimo, Gustavo de Souza

doi:10.1016/j.jcsr.2018.06.020

Cited by 61 publications

(60 citation statements)

References 13 publications

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“…Tsavdaridis and D'Mello [4] tested closely spaced web openings of various shapes and found that all the tested cellular beams failed by WPB. More recently Grilo et al [5] tested nine cellular beams and the WPB failure dominates the failure of all beams. Erdal and Saka [6] tested 12 cellular beams and found that 6 beams failed by WPB and two beams failed by combined WPB and VB.…”

Section: Introductionmentioning

confidence: 99%

“…Panedpojaman et al [7] proposed further improvement of the effective length of the strut model that takes into consideration the effect of the strut's boundary conditions. Grilo et al [5] proposed a new formulation to determine the shear resistance in cellular beams for the web-post buckling based on resistance curved derived from the finite element analyses.…”

Section: Introductionmentioning

confidence: 99%

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Numerical and analytical analyses of high-strength steel cellular beams: A discerning approach

Shamass

Guarracino²

2020

Journal of Constructional Steel Research

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The behaviour of cellular beams made from normal and high strength steel with various geometries is investigated through a large number of finite element analyses and a simple mechanical model for the Web-Post Buckling (WPB) failure is developed and analysed in order to highlight the factors which influence its occurrence and development for both normal and High-Strength (HS) steels. The performed FE analyses and the proposed modelling, once calibrated, allow to shed some light on the characteristics of the phenomenon and to provide the basis of a reliable design method to predict shear buckling of web-post of cellular beams made both of mild and HS steel.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical and analytical analyses of high-strength steel cellular beams: A discerning approach

Shamass

Guarracino²

2020

Journal of Constructional Steel Research

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“…Durif et al [28] investigated behaviour of CBs with sinusoidal openings and compared with circular openings. There are some other studies available in the literature on bending and buckling behaviour of castellated beams such as Abidin and Izzuddin [29], Yuan et al [30], Sonck et al [31], Sorkhabi et al [32], Wang et al [33,34], Ellobody and Young [35], Tsavdaridis et al [36], Sonck and Belis [37,38], Wang et al [39], Najafi and Wang [40], Grilo et al [41], Zaher et al [42] etc.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Deflections in Cantilever and Fixed Castellated Beams with Hexagonal, Square and Circular Openings

Sayyad¹,

Shaikh²

2020

IJES

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“…In the field of structural engineering, the use of steel cellular beams has gained widespread attention thanks to their economic and aesthetic advantages [1,2]. Currently, as a result of their particular Appl.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, they are costly and require significant amounts of time [13]. Therefore, the development of a straightforward and rapid numerical tool to solve the bucking behavior problem of steel I-shaped cellular beams is imperative [1,12,14].…”

Section: Introductionmentioning

confidence: 99%

Development of Hybrid Machine Learning Models for Predicting the Critical Buckling Load of I-Shaped Cellular Beams

et al. 2019

Applied Sciences

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The principal purpose of this work is to develop three hybrid machine learning (ML) algorithms, namely ANFIS-RCSA, ANFIS-CA, and ANFIS-SFLA which are a combination of adaptive neuro-fuzzy inference system (ANFIS) with metaheuristic optimization techniques such as real-coded simulated annealing (RCSA), cultural algorithm (CA) and shuffled frog leaping algorithm (SFLA), respectively, to predict the critical buckling load of I-shaped cellular steel beams with circular openings. For this purpose, the existing database of buckling tests on I-shaped steel beams were extracted from the available literature and used to generate the datasets for modeling. Eight inputs, considered as independent variables, including the beam length, beam end-opening distance, opening diameter, inter-opening distance, section height, web thickness, flange width, and flange thickness, as well as one output of the critical buckling load of cellular steel beams considered as a dependent variable, were used in the datasets. Three quality assessment criteria, namely correlation coefficient (R), root mean squared error (RMSE) and mean absolute error (MAE) were employed for assessment of three developed hybrid ML models. The obtained results indicate that all three hybrid ML models have a strong ability to predict the buckling load of steel beams with circular openings, but ANFIS-SFLA (R = 0.960, RMSE = 0.040 and MAE = 0.017) exhibits the best effectiveness as compared with other hybrid models. In addition, sensitivity analysis was investigated and compared with linear statistical correlation between inputs and output to validate the importance of input variables in the models. The sensitivity results show that the most influenced variable affecting beam buckling capacity is the beam length, following by the flange width, the flange thickness, and the web thickness, respectively. This study shows that the hybrid ML techniques could help in establishing a robust numerical tool for beam buckling analysis. The proposed methodology is also promising to predict other types of failure, as well as other types of perforated beams.

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Design procedure for the web-post buckling of steel cellular beams

Cited by 61 publications

References 13 publications

Numerical and analytical analyses of high-strength steel cellular beams: A discerning approach

Numerical and analytical analyses of high-strength steel cellular beams: A discerning approach

Estimation of Deflections in Cantilever and Fixed Castellated Beams with Hexagonal, Square and Circular Openings

Development of Hybrid Machine Learning Models for Predicting the Critical Buckling Load of I-Shaped Cellular Beams

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