Uncertainty Assessment for the Buckling Analysis of Glass Columns with Random Parameters

Abstract

Load-bearing elements composed of glass, as known, are often susceptible to buckling collapse mechanisms. This intrinsic characteristic (and thus potential limitation for design) typically derives from the use of relatively small thicknesses to cover large spans and surfaces, thus resulting in a multitude of columns, beams, or plates that are characterized by high slenderness. In the literature, accordingly, several and design propositions support of the definition of efficient calculation models to capture the typical buckling response of glass elements variably shaped, sized, restrained and loaded. In this study, the attention is focused on the buckling analysis of glass columns and on the assessment of uncertainties due to input random parameters. With the support of finite element numerical models, a total of 800 glass columns are investigated, by accounting for stochastic variations in the geometry (size and thickness), modulus of elasticity and density of glass, maximum amplitude of the imposed initial imperfection, material type. Based on the Monte Carlo simulation method, the final result takes the form of 2400 simulations, where the postprocessing analysis is spent on the derivation of empirical formulations for the correlation of the relevant buckling capacity indicators. From the global out-of-plane bending analysis, the input random parameters are observed to affect severely both long and short columns with different flexural stiffness. Besides, a stable linear correlation is found for some influencing indicators. The attention is thus focused on the sensitivity analysis of critical buckling load, ultimate failure configuration, deflection at collapse, buckling reduction coefficient.

Analytical Fragility Curves for Seismic Design of Glass Systems Based on Cloud Analysis

“…Such a set of assumptions resulted in the generation of a statistical sample in which a total of 540 non-linear analyses were carried out, by combining seismic input variability with the structural uncertainties summarized in Table 5. Regarding the E g values in Table 5, in accordance with [69], the reference interval was calculated as:…”

Probabilistic and Semi-Probabilistic Analysis of Slender Columns Frequently Used in Structural Engineering

“…Furthermore, this study allowed a quantification of the modeling and calculation uncertainties [15]. In this context, it should be mentioned that there are already several studies in which uncertainties are analyzed on the structural behavior and design of slender columns, like for example [17].…”

Probabilistic Evaluation of Steel Column Damage under Blast Loading via Simulation Reliability Methods and Gene Expression Programming

“…The contemporary trend in structural design emphasizes reliability to build cost-effective and safe structures that are resilient to uncertainties. Consequently, the adoption of reliability methods in designing structures subjected to dynamic loads holds great significance [7][8][9][10][11][12][13]. This study aims to perform a probabilistic evaluation of steel columns under blast loads by employing various reliability methods, namely the Monte Carlo simulation (MCS) method; the point estimate method (PEM); and the MCS method combined with the Latin hypercube sampling (LHS) method, known as MCS-LHS.…”