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F. Giunta

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4 records found

Machine learning based optimization for interval uncertainty propagation

Journal article - A. Cicirello, F. Giunta

Two non-intrusive uncertainty propagation approaches are proposed for the performance analysis of engineering systems described by expensive-to-evaluate deterministic computer models with parameters defined as interval variables. These approaches employ a machine learning based optimization strategy, the so-called Bayesian optimization, for evaluating the upper and lower bounds of a generic response variable over the set of possible responses obtained when each interval variable varies independently over its range. The lack of knowledge caused by not evaluating the response function for all the possible combinations of the interval variables is accounted for by developing a probabilistic description of the response variable itself by using a Gaussian Process regression model. An iterative procedure is developed for selecting a small number of simulations to be evaluated for updating this statistical model by using well-established acquisition functions and to assess the response bounds. In both approaches, an initial training dataset is defined. While one approach builds iteratively two distinct training datasets for evaluating separately the upper and lower bounds of the response variable, the other one builds iteratively a single training dataset. Consequently, the two approaches will produce different bound estimates at each iteration. The upper and lower response bounds are expressed as point estimates obtained from the mean function of the posterior distribution. Moreover, a confidence interval on each estimate is provided for effectively communicating to engineers when these estimates are obtained at a combination of the interval variables for which no deterministic simulation has been run. Finally, two metrics are proposed to define conditions for assessing if the predicted bound estimates can be considered satisfactory. The applicability of these two approaches is illustrated with two numerical applications, one focusing on vibration and the other on vibro-acoustics.@en

Reliability analysis of randomly excited FE modelled structures with interval mass and stiffness via sensitivity analysis

Journal article - Alba Sofi, F. Giunta, Giuseppe Muscolino

The present study focuses on reliability analysis of linear discretized structures with uncertain mass and stiffness parameters subjected to stationary Gaussian multi-correlated random excitation. Under the assumption that available information on the uncertain parameters is poor ...

A sensitivity-based approach for reliability analysis of randomly excited structures with interval axial stiffness

Journal article - Alba Sofi, Giuseppe Muscolino, F. Giunta

Reliability assessment of linear discretized structures with interval parameters subjected to stationary Gaussian multicorrelated random excitation is addressed. The interval reliability function for the extreme value stress process is evaluated under the Poisson assumption of in ...

A sensitivity-based approach for reliability analysis of randomly excited structures with interval axial stiffness

Journal article - Alba Sofi, Giuseppe Muscolino, F. Giunta

Contributed

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Closed-form solution for the buckling analysis of Euler-Bernoulli columns and beam-columns with jump discontinuities

The influence of step-changes of geometrical and material properties, real joints, non-propagating open edge cracks, and real support conditions

Master thesis - M. James, A. Cicirello, F.P. van der Meer, M. Lukovic, F. Giunta

Structural elements under compression can fail due to instability. Such type of failure may present itself as flexural buckling, which is the sudden change of configuration of one state to another at a critical compressive load. Actual structure characteristics, such as cracks, real joints, sudden changes of flexural stiffness, bracing, and actual boundary conditions, make current analytical buckling methods inefficient. For this reason, most structures are evaluated using Finite Element (FE) software based on the Finite Element Method (FEM). However, such a numerical method may have a high computational cost when parametric studies need to be performed. The motivation for this thesis was to develop an analytical alternative for the buckling analysis of columns and beam-columns. The thesis analyses jointed Euler-Bernoulli columns and beam-columns with N discontinuities due to step-changes of flexural stiffness, and influence of open edge cracks, real joints, bracing, and actual support conditions. The approach considered utilizes the Heaviside function to obtain a single piecewise expression for the deflection, slope, moment, and shear of columns and beam-columns. The use of the Heaviside function, along with proposed closed-form expressions, reduce the number of unknown integration constants to only four. Main findings are listed as following: (i) Linear buckling analysis of a column only depends on solving the determinant of the 4x4 matrix of unknown coefficients, obtained by imposing four boundary conditions. (ii) Solving the four unknown constants of integration results in performing a geometrical non-linear static analysis of the beam-column, which perfectly agrees with results obtained through FE software. (iii) Closed-form expressions reduce the number of unknown constants of integrations to only four, regardless of the number of sections composing a column or beam-column. Concluding remarks and recommendations include: (i) Closed-form expressions accurately provide linear buckling loads for columns and geometrical non-linear expressions for beam-columns. (ii) Equations solved algebraically can be stored and used for future analysis, saving the computation time of rerunning the analysis for specific columns or beam-columns. Having the equations expressed algebraically allows for the ease of performing parametric analysis and exploring the performance of new designs. (iii) Computational cost (time needed for the computer to obtain the results) may depend on the mathematical software used for the calculations. Other software may result in having lower computational time for the same calculations.