924 publications from this institution
Built-up members of cold-formed steel (CFS) profiles were tested in 4-point bending. CFS profiles (generally thin-walled) deform considerably under load, and the deformed configuration is a result of the superposition of different buckling mode shapes. Local buckling propagates through the profile walls; during distortional buckling parts of the cross-section rotate around a web-flange juncture. Alongside the buckling effects, the overall deformation of the member is considerable. To study these slender and relatively long members, a sufficient number of measuring positions on the specimens is needed. Often, this is not feasible with the conventional measuring techniques. An optical measuring device was used to record the movement of a large number of points per specimen. The obtained results are placed in a 3D coordinate system and can be exported for further data processing. The goal of the measurement campaign was to calibrate a Finite Element model that will simulate the tests. The model will be used for the analysis of composed frame members of CFS profiles, whose design is not entirely covered by the European Standard [1]. After calibration, the FEA predicts the performance of these built-up members well.
This paper reviews stochastic system identification methods that have been used to estimate the modal parameters of vibrating structures in operational conditions. It is found that many classical input-output methods have an output-only counterpart. For instance, the Complex Mode Indication Function (CMIF) can be applied both to Frequency Response Functions and output power and cross spectra. The Polyreference Time Domain (PTD) method applied to impulse responses is similar to the Instrumental Variable (IV) method applied to output covariances. The Eigensystem Realization Algorithm (ERA) is equivalent to stochastic subspace identification.
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No abstract is provided for this article.
Circular cylindrical shell structures are sensitive to wind induced ovalling oscillation, which is an aeroelastic phenomenon. This paper presents a finite element model of a silo that is validated by means of experimental results obtained on a silo on which ovalling has been observed. Results obtained with a three-dimensional finite element model of the silo, including the connection between the silo and the supporting structure, show the best correspondence with measurement results. The boundary condition for the axial displacements strongly affects the eigenfrequencies and the mode shapes. Differences between results obtained with a model that exploits symmetry and a three-dimensional model are explained. The finite strip method allows us to reduce the silo model to two dimensions, so that it can be coupled to a two-dimensional wind flow in future fluid–structure interaction calculations that aim to predict the onset flow velocity.
No abstract is provided for this article.
No abstract is provided for this article.
Vibro-acoustic analysis at high frequencies is challenging due to a large sensitivity to spatial variations and short acoustical wavelengths, rendering deterministic methods expensive. At these frequencies, the wave field is usually assumed diffuse. A realization of a diffuse field can be obtained considering that the mode shapes of the system are Gaussian random fields, and that its squared eigenfrequency spacings distribution conforms to the Gaussian orthogonal ensemble (GOE) eigenvalue spacings distribution. These diffuse field properties were for example used to extend statistical energy analysis (SEA) towards energetic variance prediction. However, energetic methods such as SEA lack the propagation of phase information, which means that, e.g., time-domain reconstruction is not possible. In this contribution, instead of total energies, expressions for the ensemble average and the cross-frequency covariance of frequency response functions are presented. These expressions are obtained from the generalized definition of a diffuse field, treating the eigenfrequencies of a diffuse subsystem as a collection of points randomly located on the frequency axis, making the analysis amenable to random point process theory. These expressions are numerically validated by comparison with computationally costly detailed models where random wave scatterers are modeled explicitly.
In Operational Modal Analysis (OMA) of large structures, it is often necessary to measure the Degrees Of Freedom (DOFs) of interest in different setups, which are processed separately, resulting in different modal parameter estimates for each of the setups. Subsequently, the DOFs that are common to the different setups are used to combine the different parts of the mode shapes, while the eigenfrequencies and damping ratios are averaged. This strategy is named the PoSER approach. If the number of setups is large, this approach is tiresome, especially if some modes of interest are not well excited and hence might be difficult to extract from the data. Therefore, there is an increasing interest towards processing all setups at once, which results in so-called ‘global’ modal parameter estimates. In this article, two strategies for achieving this goal, named the PoGER and PreGER approaches, are presented, both in the time and in the frequency domain. The PoSER as well as the global strategies are then used for the extraction of the modal parameters from data measured on the steel Luiz I arch bridge in Porto, Portugal, using both the SSI-cov/ref and the pLSCF system identification methods. From the comparison of the obtained results, it is concluded that the PoGER strategy is the most robust global approach.
No abstract is provided for this article.
For the design of slender footbridges, the vibration serviceability under pedestrian excitation is often the governing criterion. In design stage, vibration levels are predicted using simplified load models that are extrapolated from single-person force models to represent the effect of a crowd. However, these load models disregard Human-Human Interaction (HHI) and Human-Structure Interaction (HSI). This contribution investigates the effect of human-human interaction on the resulting structural response. A social force model is applied to simulate the realistic pedestrian traffic. The time-varying position and velocity of each pedestrian in the crowd are transferred into the necessary inputs for detailed step-by-step simulations of the pedestrian-induced forces and the resulting pedestrian-induced vibrations. The results show that accounting for HHI results into a reduced global walking speed. Also, the inter-person variability of the step frequencies is lower than when HHI is disregarded. As an alternative to the computationally expensive social force model, the effect of HHI is translated into an equivalent distribution of step frequencies of the pedestrians in the crowd. The results show that this simplified model allows for a very good approximation of the HHI effects on the resulting crowd-induced loading and structural response.
Train induced vibrations are a major environmental concern both in Europe and China. Besides the effect of vibrations due to passenger and freight trains and subways at relatively low speed, the study of the vibrational impact of high speed trains is of high interest. In Belgium, for example, new high speed train lines connect Brussels with Paris and London, while extensions to Amsterdam and Cologne are presently under construction. In China, this problem will become equally important in the near future, as a high speed train connection is planned between Beijing and Shanghai. The partners in this research project are involved in the development of numerical models to predict traffic induced vibrations. The development, validation and practical use of these models rely on in situ vibration measurements. A preliminary measurement campaign was undertaken on a high speed train bridge, with sensors on the bridge as well as on the rails, to be able to get more insight in force transfer from train to construction.
