A modified index for damage detection of structures using improved reduction system method

This paper presents the analysis of modal parameters (natural frequencies, damping ratios and mode shapes) of a simply supported beam with adhesively bonded double-strap joint by the finite-element based Modal Strain Energy (MSE) method using ANSYS 4.4A software. The results obtained by the MSE method are compared with closed form analytical solutions previously obtained by the first author for flexural vibration of the same system. Good agreement has been obtained between the two methods for both the natural frequencies and system loss factors. The effects of structural parameters and material properties of the adhesive on the modal properties of the joint system are also studied which are useful in the design of the joint system for passive vibration and noise control. In order to evaluate the MSE and analytical results, some experiments were conducted using aluminum double-strap joint with 3M ISD112 damping material. The experimental results agreed well with both analytical and MSE results indicating the validity of both analytical and MSE methods. Finally, a comparative study has been conducted using various commercially available damping materials to evaluate their relative merits for use in the design of these joints.

Purpose Aiming at the problems of high cost, high risk and traffic impact of in situ load testing of Bridges after fire, this paper proposes a fire bridge structural damage identification method based on a fire dynamics simulator (FDS)-Kriging model modification and a unit modal strain energy damage index, so as to effectively assess the damage of bridge structures after fire. Determine whether it can continue to be used and whether it affects driving safety. Design/methodology/approach Propose a fire bridge structural damage identification method to establish the FDS-Kriging model correction. Findings The finite element model of the fire bridge modified using FDS-Kriging approach can reflect the actual situation of the bridge structure more accurately, and the damage location and degree identified by the modal strain energy method are consistent with the actual bridge. Therefore, the effectiveness of the proposed method has been verified, and a new strategy for fire bridge damage identification has been provided. Research demonstrates that the finite element model of the fire-damaged bridge, modified using the FDS-Kriging method, can more accurately reflect the actual structural state. Moreover, the damage location and severity identified via the modal strain energy method align well with the actual bridge conditions. Thus, the effectiveness and engineering applicability of the proposed method are validated, offering a comprehensive new strategy and technical support for the integrated performance evaluation, damage identification and reliability analysis of fire-damaged bridges. Originality/value By determining the finite element correction interval and combining it with the Kriging model, the method realizes the fine correction of the finite element model of the fire bridge. Structural damage identification is carried out by using the unit modal strain energy damage index. This verifies the effectiveness and engineering applicability of the proposed method, which offers a novel approach and technical support for the comprehensive performance evaluation, damage identification and reliability analysis of fire-damaged bridges.

Damage identification of structures using incomplete mode shape and improved TLBO-PSO with self-controlled multi-stage strategy

The present dissertation describes the research work carried out towards: I. developing of analytical and numerical models for accurate and efficient analysis of laminates and sandwiches under different loading conditions (static analyses, impulsive loading and low velocity impacts); II. developing of techniques to improve structural performances of composites structures by tuning their energy absorption mechanism; A higher order theory (AD-ZZ) including zig-zag effects, transverse shear continuity, variable transverse displacement and layerwise representation is presented for analysis of laminates and sandwiches. This theory is cast in such a way that the unknowns in the model will involve only five variables like equivalent single layer models: the three displacement components and the two shear rotations of the normals on the reference surface. It is advantageous to formulate the theory in this way, as it provides the opportunity to refine its through-the-thickness representation by adding computational layers in the thickness direction without increasing the number of unknowns. After extensive evaluation of the accuracy obtained by the above mentioned theory for a variety of structures, the AD-ZZ model is enriched by adding a set of continuity functions in order to treat laminates and structures with in-plane discontinuities (e.g. bonded joints, two material wedge) under a unified approach without adding new unknowns. Speaking of techniques to improve structural performances, two approaches are presented: variable stiffness composites and stitching. The former tool works on the strain energy of the structure computing fibre distributions that minimize unwanted energy contributions and maximize the wanted ones. The latter prescribes the insertions of transverse reinforcements in sandwich structures. The homogenized mechanical properties of this structure, required by the AD-ZZ model to perform the analysis, are evaluated through virtual material tests using a 3D FE model. The results obtained applying these techniques demonstrate that both are effective in reducing transverse stresses at critical interfaces and, in certain cases, in improving bending stiffness. New C0 displacement-based and stress-based finite elements for analysis of laminated and sandwich plates based on the AD-ZZ model are developed. To achieve this goal, a new technique that converts derivatives of functional degrees of freedom contained in the AD-ZZ is presented. Both the elements satisfy all the requirements of computationally efficient finite element models for analysis of multilayered structures, namely 1) the number of degrees of freedom is independent from the number of layers; 2) no shear correction factors or penalty number are added in the formulation. Consistent shear fields are obtained for the present finite element formulations. Numerical results demonstrate that these new elements are robust, accurate and computationally efficient for analysis of multilayered structures. In order to study structures subjected to impact loading a new simulation procedure is developed. It is based on the AD-ZZ model and considers the crushing behaviour of soft-like media without performing each time a detailed 3D finite element analysis. Numerical results show that the response of composites undergoing low velocity impact is very accurately predicted with low computational effort. Overall, the present procedure holds great promise for analysis of laminated and sandwich structures undergoing low velocity impact

In this paper a new technique is presented to estimate the rotational degrees of freedom of a flexural structure, using only a limited number of sensors that measure the translational DoFs of the system. A set of flexural mode shapes in a limited number of nodes is obtained by modal testing, while a different set of approximated mode is calculated by a Finite Element Model (FEM) at all the nodes and degrees of freedom of the structure. The technique is based on the classical assumption that the response can be determined by a linear combination of the structure’s mode shapes. The structure’s mode shapes are approximated by using the local correspondence principle for mode shapes, i.e. by using an optimally selected set of finite element mode shapes as Ritz vectors for the true mode shapes. This allows to obtain the rotational response at unmeasured DoFs. The technique is validated by comparing predicted and experimental results.

In full-scale ambient vibration tests, many situations exist where it is required to obtain a detailed mode shape of a structure with a limited number of sensors. A common feasible strategy is to perform multiple setups with each one covering a different part of the structure while sharing some reference degrees of freedom (DOF) in common. Methods exist that assemble the mode shapes identified in individual setups to form a global one covering all measured DOF. This paper presents a fast Bayesian method for modal identification capable of incorporating the fast Fourier transform information in different setups consistent with probability logic. The method allows the global mode shape to be determined, taking into account the quality of data in different setups. A fast iterative algorithm is developed that allows practical implementation even for a large number of DOF. The method is illustrated with synthetic and field test data. Challenges of the mode shape assembly problem arising in field applications are investigated through a critical appraisal.

To obtain the best information for fault diagnosis, and achieve a large amount of information with a limited number of sensors while information redundancy can be avoided effectively, a new sensor placement method based on Fuzzy C-means was presented. Firstly, the structural modal analysis was conducted, and mode shapes were extracted. Then, according to the dynamic similarity of the mode shape values at important modes, the degrees of freedom (DOFs) were clustered using Fuzzy C-means clustering algorithm. The DOFs with much information were chosen from each cluster as candidate test points. The objective functions were established based on modal assurance criterion (MAC). Genetic algorithm was adopted to solve this objective optimization. The sensor's locations were optimized. Finally, MAC criterion, Fisher information criterion and singular value ratio of modal matrix were used to comprehensively evaluate different optimization results. Taking a locomotive pump body as an example, the simulation results show that the proposed method can effectively avoid measuring points aggregation and overcome information redundancy while complete information is obtained.

State-of-the-art data analysis tools have to deal with high-dimensional data. Fortunately, the inherent dimensionality of data is often much smaller, as it has an internal structure limiting its degrees of freedom. In most cases, this structure can be approximated using a graph, i.e, a set of nodes connected by edges. Based on this idea, graphs have been largely used in semi-supervised and unsupervised learning. The canonical assumption when incorporating a graph prior is to assume that the signal is smooth with respect to the graph, i.e, that connected pieces of data have similar values. Nevertheless, this hypothesis is insufficient to characterize more complex relations between the data and its structure, the graph. To this end, the field of Graph Signal Processing (GSP) extends the graph smoothness hypothesis to a more general assumption. Its key idea is to think of the signal as a sum of harmonic modes, which are obtained from the eigen-decomposition of the Laplacian, an operator representing the second order derivative. Thus, the essence of GSP resides in the Fourier transform defined by the projection on the Laplacian eigenvectors basis, which allows us to filter graph signals. However, GSP suffers from a counterintuitive irregularity. Contrarily to the classical Fourier basis, the graph Laplacian eigenvectors are not spreading uniformly on the vertex set and can be highly concentrated in a region of the graph. This non-uniformity results in a lack of any intuitive translation operator and consequently poses challenges to generalize some of the classical signal processing theory, e.g., stationarity, uncertainty principles, or sampling. In this thesis, we answer these difficulties by accepting that each node is unique and should be treated specially according to its surrounding structure. This is achieved using an operator called localization that shifts a kernel defined in the spectral domain around a specific node while adapting to the local graph structure. In the first part of the thesis, we focus on harmonic analysis in GSP. We start by making use of the norm of localized kernels to capture the spectral local features of the graph vertices. To illustrate the relevance of this analysis we then introduce structural clustering, an algorithm that groups nodes according to the role they play in the graph. Then, we bound the vertex-frequency concentration of graph filter banks atoms. Because of the irregular structure of graphs, we construct a local uncertainty principle that is, again, driven by the norm of a localized kernel. In the second part of the thesis, we tackle GSP problems from a machine learning perspective. We use the localization operator to extend the notion of stationarity to graph signals. It consists of a graph signal probabilistic framework allowing us to optimally solve inverse problems. Finally, we show how the graph total variation can be used in semi-supervised learning and prove its consistency with respect to the underlying graph manifold.

In this study, a two-stage damage detection procedure using a new approximation of modal strain energy (MSE) value is developed to boost the accuracy of structural damage localization in plate-type structures. The MSE is calculated using the center differential method for both intact and damaged states. The new formulas to approximate MSE are developed based on the nine-node isometric quadrilateral element that eliminates boundary conditions’ effect on damage detection results. The modal assurance criteria (MAC) is used as an indicator to choose the mode shapes with the best damage detection results. A global and a local MSE are proposed to enhance the accuracy of detecting the location of structural damage. An aluminum plate is used to verify the effectiveness of the proposed procedure with several damage scenarios. The results show that the new estimation of MSE value combined with MAC and the two-step MSE procedure can improve the accuracy of identifying the damage location compared to the original MSE procedure.KeywordsDamage detectionModal assurance criteriaModal strain energyPlate-type structureStructural health monitoring

Fluid-Structure Coupling Effects on the Dynamic Response of Pump-Turbine Guide Vanes

Protein adsorption at oil-water interfaces interfacial structure and function of proteins in emulsions

An easy and fast approach based on the pole assignment method is given in order to design the optimal observer for high-order structural systems. It is shown that the optimal observer is not only the one which is characterised by an optimal gain; the optimal locations of the sensors and their types, the optimal locations of the control forces and their optimal design are also important factors in the design of the optimal observer used to control flexible structures. It has been found that the suitable sensor type and its location differ from one structure to another, depending on the natural frequencies and mode shapes of the structure. Two numerical examples are given to illustrate the application of this method.

ModalPINN: An extension of physics-informed Neural Networks with enforced truncated Fourier decomposition for periodic flow reconstruction using a limited number of imperfect sensors

The current trend toward construction of high rise building with the use of lightweight, high strength material and advance construction methods have led to making comparatively light and flexible structures, which have relatively low natural damping. Results make structures more prone to environmental excitation such as earthquake loads. An asymmetry in a building which may arise due to unsymmetrical distribution of stiffness, mass, damping and strength characteristics. The responses of asymmetric structure under earthquake are characterized by translation and rotational degree of freedom. This paper includes an experimental investigation of multi-storied asymmetric building subjected to harmonic loading with and without MTMD. Experimentation of multi-storied structural model is done on shake table and observation was recorded. The displacements and time history of frame model were recorded and compare with the frames having multiple tuned mass dampers, to study the effectiveness of MTMD for leading toward response

Structures are designed in such a way that they behave in a nonlinear manner when subject to strong ground motions. Energy concepts have been widely used to evaluate the structural performance for the last few decades. Energy based design can be expressed as the balance of energy input and the energy dissipation capacity of the structure. New research is needed for multi degree of freedom systems (MDOFs)-real structures- within the framework of the energy based design methodology. In this paper, energy parameters are evaluated for low-, medium- and high-rise steel special concentrically braced frames (SCBFs) in terms of total energy input and hysteretic energy. Nonlinear dynamic time history analyses are carried out to assess the variation of energy terms along the height of the frames. A seismic energy demand spectrum is developed and hysteretic energy distributions within the frames are presented.