No abstract is provided for this article.
No abstract is provided for this article.
No abstract is provided for this article.
No abstract is provided for this article.
There are several ambient vibration system identification techniques available that were developed by different investigators or for different uses. Consequently, the question occurs to the comparison among those analysis techniques. The benchmark study of the paper is intended to compare system identification techniques for evaluating the dynamic characteristics of a building from ambient vibration data. The averaged normalised power spectral density method (also called peak picking method) and the stochastic subspace identification method based on the singular value decomposition are used in the study. A 15 storey reinforced concrete shear core building has been chosen as a case for verification. The results have shown that both techniques can identify the eigenfrequencies and the mode shapes. Damping ratios can only be determined by the stochastic subspace method. The stochastic subspace identification technique can detect frequencies that are possibly missed with the peak picking method and gives a more reasonable modal shape in most cases. However, the stochastic subspace technique is more time consuming. For real applications, it is suggested that the peak picking technique could be used on site to judge the overall dynamic characteristics of the structure. And then, the stochastic subspace identification technique could be applied afterwards to detail or to ensure the results.
This paper presents a new approach for damage detection in structures by applying a flexible combination based on an artificial neural network (ANN) and cuckoo search (CS) algorithm. ANN has become one of the most powerful tools employing computational intelligence techniques to tackle complex problems in numerous fields. However, due to the application of backpropagation algorithms based on gradient descent, a major drawback of ANN is the common problem of local minima that acts as a great hindrance to the search for the best solution. To overcome this disadvantage, we propose to combine ANN with evolutionary algorithms based on global search techniques. This paper employs CS to improve ANN training parameters (weight and bias) by minimizing the difference between real and desired outputs and then using these parameters to generate the network. Two numerical models, comprising a steel beam calibrated using experimental measurements and a large-scale truss bridge, are used to assess the robustness of the proposed approach. The results demonstrate that ANN combined with CS (ANN-CS) is accurate and requires a lower computational time than ANN, and evolutionary algorithm (EA) alone in terms of structural damage localization and quantification.
Coupled local minimizers (CLM) is a new method applicable to global optimization of functions with multiple local minima. In CLM a cooperative search mechanism is set up using a population of local optimizers, which are coupled during the search process by synchronization constraints. CLM is characterised by a relative fast convergence since the local optimizers are gradient-based. The combination of both, the coupled parallel strategy and the fast convergence, offers an efficient global optimization algorithm. In the paper the CLM method is described and is illustrated with a test function. Due to the simultaneous and coupled search of a whole population of optimizers, CLM is able to find the global minimum of the test function. Next, CLM is successfully applied to FE model updating using experimental modal data. In an example the damage pattern of a reinforced concrete beam is identified.
FOR AN INCREASING NUMBER OF CONCRETE STRUCTURES IT IS IMPORTANT TO MAKE A FORECAST OF CREEP AND SHRINKAGE EFFECTS. IN THE CASE OF PRESTRESSED CONCRETE STRUCTURES, MORE ESPECIALLY CANTILEVERED BRIDGES, A TIME-RELATED BEHAVIOUR CALCULATION IS INDISPENSABLE. STANDARDS SPECIFY THE INFLUENCE COEFFICIENT DEFINED FOR A CONSTANT STRESS. HOWEVER STRESS IN CONCRETE OFTEN VARIES WITH TIME; THE RESULTING DEFORMATION IS SUPERIMPOSED ON THE CREEP DEFORMATIONS CORRESPONDING TO THE STRESSES IMPOSED AT DIFFERENT MOMENTS. IN ORDER TO APPLY THE SUPERIMPOSITION PRINCIPLE IT IS NECESSARY TO USE NUMERICAL TECHNIQUES. THERE EXIST SEVERAL METHODS THAT SEEK TO AVOID NUMERICAL TECHNIQUES BY USING APPROXIMATIONS. THE LATTER ARE DISCUSSED AND COMPARED. PRACTICAL TABLES ARE APPENDED WHICH ILLUSTRATES THE AGE-ADJUSTED EFFECTIVE MODULUS METHOD THAT COMBINES SIMPLICITY AND ACCURACY. EXAMPLES ILLUSTRATE THE APPLICATION OF APPROXIMATE METHODS AND COMPARE THEIR RESULTS WITH THOSE OBTAINED WITH THE EXACT NUMERICAL METHOD.
Slender structures such as footbridges may be prone to human induced vibrations such that vibration mitigation devices as TMD's are adopted to increase the structural damping.Both the prediction of the structural response and the tuning of the TMD parameters rely on the modal parameters of the footbridge.These parameters are subjected to uncertainty in design stage, when only an estimation can be made for example using finite element models.After construction, the natural frequency and damping ratio can be measured but variations due to environmental effects such as temperature can result in parameter variations.Therefore it is important to take into account these uncertainties for the vibration serviceability assessment and the design of the TMD.The present paper proposes a robust TMD design which adopts a worst case approach to take into account uncertainties in design stage.The proposed approach is illustrated for the Phénix footbridge.Considering an uncertain natural frequency and damping value for the case study, a worst case approach is adopted to determine the optimal values of the TMD mass, stiffness and damping.A significant difference is found between the optimal TMD parameters of a nominal and robust tuned TMD.The mass and damping ratio of the robust TMD are found to be much higher than for the TMD tuned at nominal values of the natural frequency and damping ratio.This ensures that the comfort constraints are satisfied in all possible cases.
A finite element formulation for wave propagation in an unbounded problem domain necessitates the development of a transmitting boundary condition. Based on an analytical study of wave propagation in a saturated poroelastic medium, a frequency dependent absorbing boundary condition which is local in space can be obtained at the expense of spurious reflections for oblique incident waves. Reflection curves are presented for different kinds of incident waves and dimensionless frequencies for varying angles of incidence. Alternatively, the effective energy ratio allows to define a measure for the overall efficiency of the absorbing boundary condition. A numerical example reveals good wave absorbing capabilities of the transmitting boundary condition and encourages its implementation in a finite element formulation.
The design of transmitter masts is determined by the wind load. The mast should sustain the load without excessive stresses but moreover in order to prevent malfunctioning of the antennae, the rotation at the top has to be limited. Because the time dependent character of the wind, the response is inherent dynamic and susceptible to resonance effects. The dynamic magnification at resonance is largely dependent on the damping ratios of the lower vibration modes. Therefore a vibration experiment was performed on a steel transmitter mast in order to determine these damping ratios. A by-purpose was to derive the stiffness characteristics of the pile foundation from the experiment. Since it is very difficult, if not impossible, to measure the dynamic wind load, only response measurements were recorded. The stochastic subspace system identification method is suited to extract the modal parameters from such output-only data. Due to symmetry of the structure, closely spaced modes are likely to occur. This is confirmed by a Finite Element (FE) Analysis of the mast. Finally, the experimental results are compared with the FE-results.
When performing vibration tests on civil engineering structures, it is often unpractical and expensive to use artificial excitation (shakers, drop weights). Ambient excitation on the contrary is freely available (traffic, wind), but it causes other challenges. The ambient input remains unknown and the system identification algorithms have to deal with output-only measurements. For instance, realisation algorithms can be used: originally formulated for impulse responses they were easily extended to output covariances. More recently, data-driven stochastic subspace algorithms which avoid the computation of the output covariances were developed. The key element of these algorithms is the projection of the row space of the future outputs into the row space of the past outputs. Also typical for ambient testing of large structures is that not all degrees of freedom can be measured at once but that they are divided into several set-ups with overlapping reference sensors. These reference sensors are needed to obtain global mode shapes. In this paper, a novel approach of stochastic subspace identification is presented that incorporates the idea of the reference sensors already in the identification step: the row space of future outputs is projected into the row space of past reference outputs. The algorithm is validated with real vibration data from a steel mast excited by wind load. The price paid for the important gain concerning computational efficiency in the new approach is that the prediction errors for the non-reference channels are higher. The estimates of the eigenfrequencies and damping ratios do not suffer from this fact.
