Failure Patterns and Ultimate Load-Carrying Capacity Evolution of a Prestressed Concrete Cable-Stayed Bridge: Case Study

An approach to analyzing the evolution of the failure patterns and ultimate load-carrying capacity of prestressed concrete (P.C.) cable-stayed bridges based on a mixture of inspection and structural health monitoring (SHM) techniques is proposed. Firstly, a finite element model (FEM) of a bridge structure was established based on the design blueprint and was updated using periodic inspection or SHM data. The relationship between girder section axial force and bending moment bearing capacity was analysed with the consideration of damage and performance deterioration. Then, using vehicle loading patterns, which can be obtained from SHM data or bridge design codes, vehicle loads are applied to the updated FEM to determine the internal forces in bridge components. Finally, the locations where loads exceed the bearing capacity of components are set as plastic hinges to model the nonlinear behaviour of the structure. This procedure is repeated with the load increasing continuously up to the ultimate load-carrying capacity of the bridge. The corresponding FEM at this point gives the failure mode of the bridge. A P.C. cable-stayed bridge with a 260-m main span was employed to validate the proposed approach for 4 representative states (healthy, damaged, strengthened, and re-damaged states). The results presented in this paper confirm the feasibility of the proposed approach, and indicate that durability damage (such as girder cracking and steel bar corrosion), variations in the cable forces, girder shape (i.e., girder deflection) and structural configuration (i.e., boundary condition variations) have significant effects on the failure mode and ultimate load-carrying capacity of the P.C. cable-stayed bridge.

[1]  José J. Oliveira Pedro,et al.  Nonlinear analysis of composite steel–concrete cable-stayed bridges , 2010 .

[2]  M. Z. Cohn,et al.  MULTIOBJECTIVE OPTIMIZATION OF PRESTRESSED CONCRETE STRUCTURES , 1993 .

[3]  S. N. Sivanandam,et al.  Introduction to genetic algorithms , 2007 .

[4]  Goldberg,et al.  Genetic algorithms , 1993, Robust Control Systems with Genetic Algorithms.

[5]  R. Jankowski Pounding force response spectrum under earthquake excitation , 2006 .

[6]  V. Torczon,et al.  A GLOBALLY CONVERGENT AUGMENTED LAGRANGIAN ALGORITHM FOR OPTIMIZATION WITH GENERAL CONSTRAINTS AND SIMPLE BOUNDS , 2002 .

[7]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[8]  Man-Chung Tang BUCKLING OF CABLE-STAYED GIRDER BRIDGES , 1976 .

[9]  Jun Zhao,et al.  Sensitivity Study for Vibrational Parameters Used in Damage Detection , 1999 .

[10]  A. Griffiths Introduction to Genetic Analysis , 1976 .

[11]  S. P. Seif,et al.  NONLINEAR ANALYSIS AND COLLAPSE LOAD OF P/C CABLE-STAYED BRIDGES , 1990 .

[12]  Hong Hao,et al.  Evaluation of Bridge Load Carrying Capacity Using Updated Finite Element Model and Nonlinear Analysis , 2012 .

[13]  Nicholas I. M. Gould,et al.  A globally convergent Lagrangian barrier algorithm for optimization with general inequality constraints and simple bounds , 1997, Math. Comput..

[14]  Wei-Xin Ren ULTIMATE BEHAVIOR OF LONG-SPAN CABLE-STAYED BRIDGES , 1999 .

[15]  Robert K. Brayton,et al.  A new algorithm for statistical circuit design based on quasi-newton methods and function splitting , 1979 .

[16]  Seung-Eock Kim,et al.  Analysis of the overall collapse mechanism of cable-stayed bridges with different cable layouts , 2007 .