924 publications from this institution
In this paper, Smeulders' modification of Biot's saturated poroelastic theory is used to account for the presence of a small amount of air in the pores of an unsaturated medium. The influence of the gas phase on the compressibility of the generalized pore fluid is accounted for by a complex effective bulk modulus of the gas phase. This modification is introduced in a spectral element formulation, enabling to model transient wave propagation in layered dry, saturated and unsaturated poroelastic media. The extended application area of the method is illustrated by a numerical example.
A general procedure for determining beam and plate properties for beam- and platelike lattice structures is presented. In the literature several methods for the calculation of the equivalent stiffnesses of lattice structures exist. In this document an energy approach is used to derive explicit expressions for the equivalent stiffnesses of the most common types of plane trusses. Plane trusses can be combined to form threedimensional beamlike structures: based on the results of the plane trusses, the equivalent continuum properties of threedimensional beam elements, like the bending stiffnesses, the shear stiffnesses, the torsional stiffness, the position of the shear centre can be determined. Finally it is shown that platelike lattice structures can be modelled with Mindlin plate elements which incorporate bending as well as shear deformation. The approach is compared with an energy based method found in the literature. The accuracy of the continuum models is demonstrated by a number of representative examples.
No abstract is provided for this article.
Coupled Local Minimizers (CLM) is a new method applicable to global optimization problems. With the CLM method a cooperative search mechanism is set up using a population of local optimizers, each starting from a different point in the search space. The individual local optimizers are coupled during the search process by interaction and information exchange. The combination of a fast convergence, due to the derivative information used in the local algorithms, with the expected capability of finding the global minimum, resulting from the parallel strategy, offers an efficient global optimization algorithm. The principal idea of CLM is worked out in the paper and illustrated on a test function. Next, CLM is used for Finite Element Model (FEM) Updating using experimental modal data. As an example the damage pattern is identified of a reinforced concrete beam, on which a modal test has been carried out before and after it was damaged.
A probabilistic framework is developed for quantifying the combined effect of uncertain parameters in sound insulation measurements, such as test sample dimensions, room properties, and loudspeaker positions, on the sound insulation values. The joint probability distribution of the uncertain parameters is constructed from the available information by means of a maximum entropy approach. The resulting sound insulation predictions are fully compatible with the available information but otherwise maximally conservative, so that the robustness of the predictions is guaranteed. Fundamental insight in the inherent uncertainty of the measurement procedure for airborne sound insulation is obtained by combining the method with detailed numerical simulations of the measurement procedure for single and double walls. The resulting uncertainty levels are very large, especially in the lowest frequency bands, and agree with experimental results. Furthermore, the probability distribution of the band-averaged sound reduction index of modally sparse walls can be of bimodal form.
During social gatherings in large halls, multiple conversations taking place simultaneously can lead to very high noise levels. Increasing the amount of sound absorption in the hall can be very effective in this context: due to the Lombard effect, the noise level drops with 6 dB when doubling the equivalent absorption area, while only a 3 dB drop occurs for sources of constant sound power. However, the possibilities for the absorptive treatment of existing venues can be highly limited, especially when dealing with architectural heritage. Therefore, in the present study, sound absorbing chandeliers, consisting of dense arrangements of absorbing objects, have been designed, developed, tested, and applied in a hard-walled historic hall that hosts social gatherings of more than 800 people. Experiments in the hall during busy events have confirmed the effectiveness of the chandeliers, yet it was also found that, since the ceiling has become the main absorptive surface, they loose efficiency due to the resulting sound field directionality. Furthermore, the individual vocal effort was observed to stay constant when the background nose level was decreasing. Both effects have been thoroughly studied and analyzed, and a prediction methodology to account for these effects has been proposed.
In this study, the effects of high-amplitude initial conditions on the accuracy of modal parameters, identified from output-only vibration data, are investigated. The influence on the sample output correlation function, which is the basis of most time-domain operational modal analysis techniques, is analyzed first. Then, a numerical simulation is performed to quantify the effect of nonzero initial conditions on the relative accuracy of natural frequencies, damping ratios, and mode shapes. It is shown that, when all identification assumptions are satisfied, high-amplitude initial conditions can significantly reduce the estimation errors, especially for short data records. Finally, a full-scale application is presented where the modal parameters of a six-span high-speed railway bridge are determined from output-only data. The results obtained with two different data sets are compared: The first one consists of the bridge's response to ambient data only, whereas the second one also contains the free vibration recorded immediately after a train passage. Although for most modes the results are similar, it is possible to identify some additional bending and torsion modes from the free vibration data with good accuracy. Copyright © 2013 John Wiley & Sons, Ltd.
For slender and lightweight structures, the vibration serviceability under crowd- induced loading is often critical in design. Currently, designers rely on equivalent load models, upscaled from single-person force measurements. Furthermore, it is important to consider the mechanical interaction with the human body as this can significantly reduce the structural response. To account for these interaction effects, the contact force between the pedestrian and the structure can be modelled as the superposition of the force induced by the pedestrian on a rigid floor and the force resulting from the mechanical interaction between the structure and the human body. For the case of large crowds, however, this approach leads to models with a very high system order. In the present contribution, two equivalent reduced-order models are proposed to approximate the dynamic behaviour of the full-order coupled crowd-structure system. A numerical study is performed to evaluate the impact of the modelling assumptions on the structural response to pedestrian excitation. The results show that the full-order moving crowd model can be well approximated by a reduced-order model whereby the interaction with the pedestrians in the crowd is modelled using a single (equivalent) SDOF system.
This paper presents a novel approach for quantification of the estimation uncertainty on the results obtained from joint input-state estimation in structural dynamics.The uncertainty accounted for originates from measurement errors and unknown stochastic excitation, that is acting on the structure besides the forces that are to be identified.The uncertainty quantification approach is applied for a joint input-state estimation algorithm that is used for force identification and response estimation in structural dynamics.The approach can, however, be extended to other force and state estimation algorithms.The uncertainty on the estimated quantities can be used to design a sensor network and to determine the optimal noise statistics that are applied for joint input-state estimation.The uncertainty quantification approach is verified using numerical simulations.
