Parameter Identification of Multispan Rigid Frames Using a Stiffness Separation Method.

Identifying the parameters of multispan rigid frames is challenging because of their complex structures and large computational workloads. This paper presents a stiffness separation method for the static response parameter identification of multispan rigid frames. The stiffness separation method segments the global stiffness matrix of the overall structure into the stiffness matrices of its substructures, which are to be computed, thereby reducing the computational workload and improving the efficiency of parameter identification. Loads can be applied individually to each separate substructure, thereby guaranteeing obvious local static responses. The veracity and efficacy of the proposed methodology are substantiated by applying it to three- and eight-span continuous rigid frame structures. The findings indicate that the proposed approach significantly enhances the efficiency of parameter identification for multispan rigid frames.

Estimation of vehicle-induced bridge dynamic responses using fiber Bragg grating strain gages.

Strain gage sensors have been used to evaluate the local behavior of structures; however, there are limited studies for its application in bridge dynamic feature identification. In this study, fiber Bragg grating strain gages were installed on the lower chord members of a bridge, and dynamic features were identified successfully using strain gage readings when vehicles passed over the bridge. The results were also verified using a finite element model. The innovation presented in this article is the use of fiber Bragg grating strain gage readings to identify the dynamic features of a long-span, steel-girder bridge. To clarify the effect of truck dynamic load, the load spectrum of the truck is characterized. This article introduces a new method for identifying the dynamic parameters of bridges.

Monitoring Bridge Dynamic Responses Using Fiber Bragg Grating Tiltmeters.

In bridge health monitoring, tiltmeters have been used for measuring rotation and curvature; however, their application in dynamic parameter identification has been lacking. This study installed fiber Bragg grating (FBG) tiltmeters on the bearings of a bridge and monitored the dynamic rotational angle. The dynamic features, including natural frequencies and mode shapes, have been identified successfully. The innovation presented in this paper is the first-time use of FBG tiltmeter readings to identify the natural frequencies of a long-span steel girder bridge. The identified results have been verified using a bridge finite element model. This paper introduces a new method for the dynamic monitoring of a bridge using FBG tiltmeters. Limitations and future research directions are also discussed in the conclusion.