Damage Identification of Semi-Rigid Joints in Frame Structures Based on Additional Virtual Mass Method.

In civil engineering, the joints of structures are complex, and their damage is generally hard to be detected. Due to the insensitivity of structural modal information to local joint damage, this paper presents a method based on additional virtual mass for damage identification of a semi-rigid joint in a frame structure. Firstly, the modeling of a semi-rigid is described. Secondly, the frequency response of the virtual structure is constructed, and the natural frequency of the constructed virtual structure is extracted by the ERA method. By adding multiple values of virtual masses at different positions, the natural frequency information sensitive to joint damage for damage identification is effectively increased. Based on the above theory, qualitative identification of joint damage is proposed to detect the potential damage, and identification of both damage location and its extent is presented, using natural frequency. Improved Orthogonal Matching Pursuit (IOMP) algorithm is employed to improve the accuracy of the natural frequency-based method for damage identification. At last, numerical simulation of a three-story frame is performed to discuss and to verify the effectiveness of the proposed method.

Bridge Damage Identification Using Vehicle Bump Based on Additional Virtual Masses.

Structural damage identification plays an important role in providing effective evidence for the health monitoring of bridges in service. Due to the limitations of measurement points and lack of valid structural response data, the accurate identification of structural damage, especially for large-scale structures, remains difficult. Based on additional virtual mass, this paper presents a damage identification method for bridges using a vehicle bump as the excitation. First, general equations of virtual modifications, including virtual mass, stiffness, and damping, are derived. A theoretical method for damage identification, which is based on additional virtual mass, is formulated. The vehicle bump is analyzed, and the bump-induced excitation is estimated via a detailed analysis in four periods: separation, free-fall, contact, and coupled vibrations. The precise estimation of bump-induced excitation is then applied to a bridge. This allows the additional virtual mass method to be used, which requires knowledge of the excitations and acceleration responses in order to construct the frequency responses of a virtual structure with an additional virtual mass. Via this method, a virtual mass with substantially more weight than a typical vehicle is added to the bridge, which provides a sufficient amount of modal information for accurate damage identification while avoiding the bridge overloading problem. A numerical example of a two-span continuous beam is used to verify the proposed method, where the damage can be identified even with 15% Gaussian random noise pollution using a 1-degree of freedom (DOF) car model and 4-DOF model.

Optimal Placement of Virtual Masses for Structural Damage Identification.

Adding virtual masses to a structure is an efficient way to generate a large number of natural frequencies for damage identification. The influence of a virtual mass can be expressed by Virtual Distortion Method (VDM) using the response measured by a sensor at the involved point. The proper placement of the virtual masses can improve the accuracy of damage identification, therefore the problem of their optimal placement is studied in this paper. Firstly, the damage sensitivity matrix of the structure with added virtual masses is built. The Volumetric Maximum Criterion of the sensitivity matrix is established to ensure the mutual independence of measurement points for the optimization of mass placement. Secondly, a method of sensitivity analysis and error analysis is proposed to determine the values of the virtual masses, and then an improved version of the Particle Swarm Optimization (PSO) algorithm is proposed for placement optimization of the virtual masses. Finally, the optimized placement is used to identify the damage of structures. The effectiveness of the proposed method is verified by a numerical simulation of a simply supported beam structure and a truss structure.

Experimental Study for Damage Identification of Storage Tanks by Adding Virtual Masses.

This research proposes a damage identification approach for storage tanks that is based on adding virtual masses. First, the frequency response function of a structure with additional virtual masses is deduced based on the Virtual Distortion Method (VDM). Subsequently, a Finite Element (FE) model of a storage tank is established to verify the proposed method; the relation between the added virtual masses and the sensitivity of the virtual structure is analyzed to determine the optimal mass and the corresponding frequency with the highest sensitivity with respect to potential damages. Thereupon, the damage can be localized and quantified by comparing the damage factors of substructures. Finally, an experimental study is conducted on a storage tank. The results confirm that the proposed method is feasible and practical, and that it can be applied for damage identification of storage tanks.

High hepatitis B virus (HBV) DNA viral load as the most important risk factor for HBV reactivation in patients positive for HBV surface antigen undergoing autologous hematopoietic cell transplantation.

The risk factors for hepatitis due to hepatitis B virus (HBV) reactivation in patients positive for hepatitis B surface antigen (HBsAg) treated with autologous hematopoietic cell transplantation (HCT) are unknown. We evaluated 137 consecutive patients (23 positive for HBsAg, 37 positive for hepatitis B surface antibody, and 77 negative for HBV) who underwent HCT. Serial serum ALT were measured before transplant and after transplant at 1 to 4 weekly intervals for the first year and then at 2 to 12 weekly intervals thereafter. Before HCT, basic core promoter (T(1762)/A(1764)) and precore (A(1896)) HBV variants were determined in HBsAg-positive and HBV DNA-positive (by polymerase chain reaction assay) patients by direct sequencing and serum HBV DNA quantitation using the Digene Hybrid Capture II assay. Cox proportional hazards analysis was used to assess the association between pretransplantation HBV virologic and host factors and occurrence of hepatitis due to HBV reactivation. After HCT, hepatitis due to HBV reactivation was more common in HBsAg-positive patients than in HBsAg-negative patients (hazard ratio, 33.3; 95% confidence interval [CI], 7.35-142.86; P <.0001). HBsAg-positive patients with detectable serum HBV DNA before HCT (on Digene assay) had a significantly higher risk of hepatitis due to HBV reactivation than HBsAg-positive patients with no detectable serum HBV DNA (adjusted hazard ratio, 9.35; 95% CI, 1.65-52.6; P =.012). Thus, we found that hepatitis due to HBV reactivation is common in HBsAg-positive patients undergoing autologous HCT. A high HBV DNA level (>10(5) copies/mL) was the most important risk factor for HBV reactivation, and its lowering by administration of nucleoside analogues before transplantation should be considered.