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Probabilistic Structural Simulation and Design Reliability

30 Chapters
View Course Samples Online
01
Course overview
scope, concepts, and technical context of probabilistic structural simulation and design reliability.
technicalprobabilistic
02
Uncertainty taxonomy in structural engineering
aleatory and epistemic sources, random variables, and stochastic fields.
Uncertaintytaxonomy
03
Probability theory foundations for structural reliability
random variables, distributions, moments, and joint probability.
Probabilityfoundations
04
Structural reliability fundamentals
limit state functions, failure probability, and reliability index.
Structuralreliability
05
First Order Reliability Method (FORM)
linearization, Hasofer-Lind index, and sensitivity factors.
ReliabilityFORM
06
Second Order Reliability Method (SORM)
curvature corrections and accuracy improvements over FORM.
ReliabilitySORM
07
Monte Carlo simulation for structural reliability
direct sampling, variance reduction, and convergence assessment.
simulationstructural
08
Importance sampling and subset simulation
efficient estimation of small failure probabilities.
Importancesampling
09
Response surface methods and surrogate models for reliability analysis
polynomial, Kriging, and polynomial chaos.
Responsesurrogate
10
Stochastic finite element method
discretization of random fields and spectral representation.
Stochasticdiscretization
11
Perturbation and Neumann expansion approaches for stochastic structural analysis.
Perturbation and Neumann expansion approaches for stochastic structural analysis.
Perturbationexpansion
12
Polynomial chaos expansion
construction, coefficients, and application to structural response variability.
Polynomialexpansion
13
Reliability-based design optimization (RBDO)
problem formulation, constraints, and solution strategies.
Reliability-basedoptimization
14
System reliability analysis
series, parallel, and mixed systems, and bounds on failure probability.
reliabilityanalysis
15
Time-dependent reliability and stochastic process modeling for deteriorating structures.
Time-dependent reliability and stochastic process modeling for deteriorating structures.
Time-dependentreliability
16
Reliability sensitivity analysis
gradient computation, importance measures, and parameter ranking.
Reliabilitysensitivity
17
Bayesian methods in structural reliability
updating, model calibration, and posterior prediction.
Bayesianstructural
18
Probabilistic fatigue and fracture mechanics
random loading, crack growth variability, and life prediction.
Probabilisticfracture
19
Seismic reliability analysis of structures
ground motion uncertainty and fragility curves.
reliabilityanalysis
20
Wind and wave load reliability for offshore and tall structures
stochastic load modeling and response.
reliabilityoffshore
21
Reliability of composite and advanced materials
random material properties and failure criteria.
Reliabilitycomposite
22
Structural health monitoring and reliability updating
damage detection, Bayesian inference, and prognosis.
Structuralmonitoring
23
Robust design and tolerance optimization under uncertainty
Taguchi methods and six sigma in structures.
toleranceoptimization
24
Code-based reliability calibration
partial safety factors and target reliability levels.
Code-basedreliability
25
Verification and validation of probabilistic structural models
benchmarking and experimental comparison.
Verificationvalidation
26
Software tools for probabilistic structural simulation
commercial and open-source frameworks.
Softwareprobabilistic
27
Case study
reliability assessment of a bridge under traffic and environmental loads.
reliabilityassessment
28
Case study
probabilistic design of an aerospace structural component.
probabilisticaerospace
29
Case study
reliability-based design of a wind turbine support structure.
reliability-basedstructure
30
Emerging trends and future directions in probabilistic structural simulation and design reliability.
Emerging trends and future directions in probabilistic structural simulation and design reliability.
Emergingdirections