Mechanical Engineering in Uncertainties from Classical Approaches to Some Recent Developments

Detalles Bibliográficos
Autor principal: Gogu, Christian
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated, 2021.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Cover
  • Half-Title Page
  • Title Page
  • Copyright Page
  • Contents
  • Foreword
  • Preface
  • Part 1: Modeling, Propagation and Quantification of Uncertainties
  • Chapter 1: Uncertainty Modeling
  • 1.1. Introduction
  • 1.2. The usefulness of separating epistemic uncertainty from aleatory uncertainty
  • 1.3. Probability theory
  • 1.3.1. Theoretical context
  • 1.3.2. Probabilistic approach for modeling aleatory uncertainties
  • 1.3.3. Probabilistic approach for modeling epistemic uncertainties
  • 1.4. Probability box theory (p-boxes)
  • 1.5. Interval analysis
  • 1.6. Fuzzy set theory
  • 1.7. Possibility theory
  • 1.7.1. Theoretical context
  • 1.7.2. Comparison between probability theory and possibility theory
  • 1.7.3. Rules for combining possibility distributions
  • 1.8. Evidence theory
  • 1.8.1. Theoretical context
  • 1.8.2. Rules for combining belief mass functions
  • 1.9. Evaluation of epistemic uncertainty modeling
  • 1.10. References
  • Chapter 2: Microstructure Modeling and Characterization
  • 2.1. Introduction
  • 2.2. Probabilistic characterization of microstructures
  • 2.2.1. Random sets
  • 2.2.2. Covariance
  • 2.2.3. Granulometry
  • 2.2.4. Minkowski functionals
  • 2.2.5. Stereology
  • 2.2.6. Linear erosion
  • 2.2.7. Representative volume element
  • 2.3. Point processes
  • 2.3.1. Homogeneous Poisson point processes
  • 2.3.2. Inhomogeneous Poisson point processes
  • 2.4. Boolean models
  • 2.4.1. Definition and Choquet capacity
  • 2.4.2. Properties
  • 2.4.3. Covariance
  • 2.4.4. Other characteristics
  • 2.4.4.1. Three-point function
  • 2.4.4.2. Contact distribution
  • 2.4.4.3. Specific surface area
  • 2.4.4.4. Linear erosion curves for convex primary grains
  • 2.5. RSA models
  • 2.6. Random tessellations
  • 2.6.1. Voronoi tessellation
  • 2.6.2. Johnson-Mehl tessellation
  • 2.6.3. Laguerre tessellation
  • 2.6.4. Random Poisson tessellation
  • 2.6.5. The dead-leaves model
  • 2.6.6. Generalized random partition models
  • 2.7. Gaussian fields
  • 2.8. Conclusion
  • 2.9. Acknowledgments
  • 2.10. References
  • Chapter 3: Uncertainty Propagation at the Scale of Aging Civil Engineering Structures
  • 3.1. Introduction
  • 3.2. Problem positioning
  • 3.2.1. Probabilistic formulation
  • 3.2.2. Thermo-hydro-mechanical-leakage transfer function
  • 3.2.3. Resulting probabilistic THM-F problem
  • 3.3. Random field-based modeling of material properties
  • 3.3.1. Random fields
  • 3.3.2. Generation methods for discretized random fields
  • 3.3.2.1. Discrete approximations
  • 3.3.2.2. Functional approximations
  • 3.3.3. Random fields and autocorrelations
  • 3.3.4. Application: contribution to modeling the cracking of reinforced concrete works by self-correlated r.f.
  • 3.3.4.1. Context presentation
  • 3.3.4.2. Effect of autocorrelated r.f.
  • 3.4. Modeling uncertainty propagation using response surface methods
  • 3.4.1. Probabilistic coupling strategies

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