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Health Assessment of Engineered Structures : Bridges, Buildings and Other Infrastructures.
Health Assessment of Engineered Structures has become one of the most active research areas and has attracted multi-disciplinary interest. Since available financial recourses are very limited, extending the lifespan of existing bridges, buildings and other infrastructures has become a major challeng...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Singapore :
World Scientific Publishing Company,
2013.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Preface; Contents; Chapter 1. Structural Health Monitoring for Civil Infrastructure E.J. Cross, K. Worden and C.R. Farrar; 1. Introduction: SHM Ideology; 1.1. The aims of SHM; 1.2. Potential benefits of SHM; 1.3. Disambiguation: what SHM is not; 2. SHM in Practice; 2.1. Instrumentation for SHM; 2.2. Assessment of structural condition from measurements; 2.2.1. Feature Extraction; 2.2.2. Pattern Recognition for inference on structural condition from features; 2.3. Validation of SHM systems; 2.4. Fundamental axioms of SHM; 3. Civil Infrastructure and SHM; 4. Benchmarks; 4.1. The I-40 Bridge.
- 4.2. The Steelquake Structure4.3. The Z24 Bridge; 5. Case Study: Z24 Bridge; 6. Continuing Challenges in SHM; Acknowledgments; References; Chapter 2. Enhanced Damage Locating Vector Method for Structural Health Monitoring S.T. Quek, V.A. Tran, and N.N.K. Lee; 1. The DLV Method Introduction; 1.1. General concept; 1.2. Normalized cumulative energy (NCE); 2. Identifying Actual Damage Elements; 2.1. Intersection scheme; 3. Formulation of Flexibility Matrix at Sensor Location; 3.1. Forming flexibility matrix using static responses; 3.1.1. Static responses with load of known magnitude.
- 3.1.2. Static responses with load of unknown magnitude3.2. Forming flexibility matrix using dynamic responses; 3.2.1. Dynamic responses with known excitation; 3.2.2. Dynamic responses with unknown excitation; 4. Lost Data Reconstruction for Wireless Sensors; 4.1. Lost data reconstruction algorithm; 5. Numerical and Experimental Examples; 5.1. Numerical example: 2-D warehouse frame structure; 5.2. Experimental example: 3-D modular truss structure; 6. Concluding Remarks; References; Chapter 3. Dynamics-based Damage Identification Pizhong Qiao and Wei Fan; 1. Introduction.
- 2. Damage Identification Algorithms2.1 Literature review; 2.2 Two-dimensional Gapped Smoothing Method (GSM); 2.3 Strain Energy-based Damage Index Method (DIM); 2.4 Uniform Load Surface (ULS); 2.5 Generalized Fractal Dimension (GFD); 3. Comparative Study; 3.1 Geometry of the composite plate; 3.2 Numerical analysis; 3.3 Damage identification based on numerical data; 3.4 Experimental program; 3.5 Damage identification based on experimental data; 4. Summary and Conclusions; Acknowledgements; References.
- Chapter 4. Simulation Based Methods for Model Updating in Structural Condition Assessment H.A. Nasrellah, B. Radhika, V.S. Sundar, and C.S. Manohar1. Introduction; 2. Statically loaded structures: MCMC based methods; 3. Dynamically loaded structures: sequential Monte Carlo approach; 3.1 Hidden state estimation; 3.2 Combined state and force identification; 3.3 Combined state and parameter estimation; 3.3.1 Method of augmented states and global iterations; 3.3.2 Method of maximum likelihood; 3.3.3 Bank of filter approach; 3.3.4 Combined MCMC and Bayesian filters.