Vibration-based methods are promising for damage identification; however, their capabilities for damage identification under temperature variations are usually limited. In the paper, a vibration-based nondestructive global damage identification method based on a genetic algorithm (GA) is proposed to identify structural damage location and severity under the influence of temperature variation and noise. The proposed method is verified by a number of damage scenarios of a three-span continuous beam and a two-span steel grid and shows good robustness under random noise levels. First, considering that the material properties of a structure and boundary conditions of a system are generally temperature-dependent, the relation between temperature and elastic and geometric stiffness matrices is introduced, and damage parameters along with temperature are defined as variables of the numeric model. Second, a GA is introduced where a new objective function with different weight coefficients, combined with frequencies and mode shape, is proposed and developed. Third, damage identification of a three-span continuous beam and a two-span steel grid under temperature variation is carried out numerically, considering changes of material properties and boundary conditions, and damage existence, location, and severity are accurately identified. Finally, it is shown that the proposed method is very robust even when the data are polluted with artificial noise.

Piezoelectric lead zirconate titanate (PZT) is being gradually applied into practice as a new intelligent material for structural health monitoring. In order to study the damage detection properties of PZT on concrete slabs, simply supported reinforced concrete slabs with piezoelectric patches attached to their surfaces were chosen as the research objects and the Electromechanical Impedance method (EMI) was adopted for research. Five kinds of damage condition were designed to test the impedance values at different frequency bands. Consistent rules are found by calculation and analysis. Both the root mean square deviation (RMSD) and the correlation coefficient deviation (CCD) damage indices are capable of detecting the structural damage. The newly proposed damage index R_y/R_x can also predict the changes well. The numerical and experimental studies verify that the Electromechanical Impedance method can accurately predict changes in the amount of damage in reinforced concrete slabs. The damage index changes regularly with the distance of damages to the sensor. This relationship can be used to determine the damage location. The newly proposed damage index R_y/R_x is accurate in determining the damage location.

This paper develops a novel hybrid approach that integrates metamodeling, machine learning algorithms, and a variance decomposition technique to support global uncertainty and sensitivity (US) analysis under uncertainty. It consists of three main steps: (1) metamodel construction; (2) metamodel validation; and (3) global US analysis. A multi-input and multioutput metamodel, with least-squares support vector machine (LSSVM) and particle swarm optimization (PSO) algorithms incorporated, is built in order to simulate system behaviors of tunnel-induced building damage. Three indicators—mean absolute percentage error (MAPE), variance of absolute percentage error (VAPE), and mean square percentage error (MSPE)—are proposed to test the prediction performance of the metamodel. The extended Fourier amplitude sensitivity test (EFAST) is used to perform global US analysis on the basis of the well-trained metamodel. The novelty of the developed approach lies in its capability of learning from given data to identify relationships between model inputs and outputs to provide an access for conducting global US analysis. The collected data from the construction of the Wuhan Metro system (WMS) in China are used in a case study to demonstrate the effectiveness and applicability of the developed approach. Results indicate that the developed approach is capable of (1) predicting and assessing the magnitude of tunnel-induced building damage in terms of the cumulative distribution function (CDF) of model outputs, and (2) identifying the most significant and insignificant factors for possible dimension reduction to improve the understanding of the model behavior. This research contributes to (1) the body of knowledge by proposing a more appropriate research methodology that can cope with aleatory and epistemic uncertainty and support global US analysis based on given data, and (2) the state of practice by providing a data-driven metamodel technique to simulate system behaviors of tunnel-induced building damage with high reliability and reduce dependency on domain experts.

A method for the shape finding of a specific type of self-anchored suspension bridge whose main cable is three-dimensionally curved is proposed in this study. The method, referred to as the coordinate iteration method (CIM), is developed from the force equilibrium features of the rational arch axis for suspension cables modeled by truss-cable elements. By establishing the linear iterative equations in terms of unknown coordinates and updating the relation matrices iteratively, a trial profile of the three-dimensional cable-only system easily and stably converges to the target system. The CIM is then extended to the shape finding of the total bridge system with the aid of a specific numerical model proposed in this study referred to as the indiscrimination coordinate rod model (ICRM). This model is used to simulate the core deformation effects of the total bridge. The detailed procedure undertaken to establish a finite-element model of the equilibrium system for the finished dead load state based on CIM and ICRM is also presented. The precision and efficiency of the method are demonstrated through actual numerical examples.

Piezoelectric sensor diagnosis and validity assessment as a prior component of structural health monitoring system are necessary in the practical application of electromechanical impedance technique. This article proposed an innovative sensor self-diagnosis process based on extracting the characterization of the real admittance (inverse of impedance) signature within a high-frequency range, which covered both diagnosis on damaged sensor after its installation and discrimination of sensor and structural damages during structural health monitoring process. Theoretical analysis was derived from the impedance model of piezoelectric-bonding layer-structure dynamic interaction system. Experimental investigations on piezoelectric sensor-bonded steel beam involved with structural damages of mass addition and notch damage were conducted to verify the process. It was found that the real admittance was reliable and critical in sensor diagnosis, and sensor faults of debonding, scratch, and breakage can be identified and differentiated from structural damage. Validity assessment of the diagnosed damaged sensor was addressed through resonant frequency shift method. The results showed that the validity of damaged sensor for structural health monitoring was inordinately depreciated by sensor damage. This article is expected to be useful for structural health monitoring application especially when damaged piezoelectric sensors existed.

In this paper, an improved particle swarm optimization (IPSO) method, which is based on standard particle swarm optimization (PSO) and a changing range genetic algorithm (GA), is proposed, and it is applied in the form-finding analysis of a suspension bridge installation. The new method has been integrated into the successive iteration method of the form-finding analysis, and it transfers the usual iterative process of form-finding analysis into a single objective optimization problem. The computation formulation and computer code of the IPSO have been developed and implemented, and benchmark examples are studied to test the performance of the IPSO method through numerical experiments. The results show that IPSO can be used as a viable solution methodology for the form-finding analysis in various initial, boundary, and complicated load conditions to overcome the limitations of the conventional Newton-Raphson (N-R) iterative method. Furthermore, compared with GA, PSO, and GA-PSO, IPSO has greater a...