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AS 5104:2017

[Current]

General principles on reliability for structures

Adopts ISO 2394:2015 is to provide a risk and reliability-informed foundation for decision making concerning design and assessment of structures in the context of specific projects.
Published: 07/09/2017
Pages: 112
Table of contents
Cited references
Content history
Table of contents
Header
About this publication
Preface
Foreword
Introduction
1 Scope
2 Terms and definitions
2.1 General terms
2.2 Terms related to design and assessment
2.3 Terms related to actions, action effects, and environmental influences
2.4 Terms related to structural response, resistance, material properties, and geometrical quantities
3 Symbols
3.1 General
3.2 Latin upper case letters
3.3 Latin lower case letters
3.4 Greek letters
3.5 Subscripts
4 Fundamentals
4.1 General
4.2 Aims and requirements to structures
4.2.1 Fundamental requirements to structures
4.2.2 Target performance level
4.3 Conceptual basis
4.3.1 Decisions concerning structures
4.3.2 Structural performance modelling
4.3.3 Uncertainty and treatment of knowledge
4.4 Approaches
4.4.1 General
4.4.2 Risk-informed and reliability-based approaches
4.4.2.1 Risk-informed decisions concerning design and assessment
4.4.2.2 Reliability-based design and assessment
4.4.3 Semi-probabilistic approaches
4.5 Documentation
5 Performance modelling
5.1 General
5.1.1 Structural performance and limit state concept
5.1.2 Performance and performance indicators
5.1.3 Basic performance requirement and design situations
5.1.4 Levels of verification
5.2 Performance model
5.2.1 General
5.2.2 Time-dependent aspects
5.2.3 System aspects
5.3 Limit states
5.3.1 Ultimate limit state
5.3.2 Serviceability limit states
5.3.3 Condition limit states
5.3.4 Limit state function
6 Uncertainty representation and modelling
6.1 General
6.1.1 Types of uncertainty
6.1.2 Treatment of uncertainty
6.1.3 Interpretation of probability
6.1.4 Probabilistic models
6.1.5 Population/outcome space
6.1.6 Hierarchical modelling of uncertainty
6.2 Models for structural analysis
6.2.1 General
6.2.2 Actions and environmental influences
6.2.2.1 General
6.2.2.2 Classifications
6.2.2.3 Action model
6.2.3 Geometrical properties
6.2.4 Material properties
6.2.4.1 General
6.2.4.2 Characterization
6.2.4.3 Material model
6.2.5 Responses and resistances
6.2.5.1 Classification
6.2.5.2 Models for static response
6.2.5.3 Models for dynamic response
6.2.5.4 Models for degradation and damage accumulation
6.3 Models for consequences
6.4 Model uncertainty
6.5 Experimental models
6.6 Updating of probabilistic models
7 Risk-informed decision making
7.1 General
7.2 System identification
7.3 System modelling
7.4 Risk quantification
7.5 Decision optimization and risk acceptance
8 Reliability-based decision making
8.1 General
8.2 Decisions based on updated probability measures
8.3 Systems reliability versus component reliability
8.4 Target failure probabilities
8.5 Calculation of the probability of failure
8.5.1 General
8.5.2 Time-invariant reliability problems
8.5.3 Transformation of time-variant into time-invariant problems
8.5.4 Out-crossing approach
8.6 Implementation of probability-based design
9 Semi-probabilistic method
9.1 General
9.2 Basic principles
9.3 Representative and characteristic values
9.3.1 Actions
9.3.2 Resistances
9.4 Safety formats
9.4.1 General
9.4.2 Partial factor method
9.4.2.1 Actions
9.4.2.2 Resistances
9.4.3 The design value method
9.5 Verification in case of cumulative damage
Annex A
A.1 Objectives
A.2 Definitions
A.2.1 General definitions related to quality management, quality assurance, and quality control
A.2.2 Definitions relating to Annex A
A.2.2.1
A.2.2.2
A.2.2.3
A.2.2.4
A.2.2.5
A.2.2.6
A.2.2.7
A.3 Quality management
A.4 Quality assurance
A.5 Quality control
A.5.1 General
A.5.2 Control procedure
A.5.3 Control criteria and acceptance rules
A.5.4 Control process
A.5.5 Filtering effects of quality control
A.6 Quality level differentiation
Annex B
B.1 Introduction
B.2 Main phases of structural integrity management process
B.3 Data collection
B.4 Evaluation and structural assessment
B.4.1 Data evaluation
B.4.2 Structural assessment
B.4.3 Updating information
B.5 Inspection strategy
B.6 Inspection programme
Annex C
C.1 Overview
C.2 General considerations
C.3 Consideration of differences between reality and testing conditions
C.4 Planning
C.5 Direct evaluation of the test results
C.5.1 General
C.5.2 Partial factor design
C.5.3 Evaluation using full probabilistic methods
C.6 Evaluation on the basis of an analysis model
Annex D
D.1 Introduction
D.2 Uncertainty representation of geotechnical design parameters
D.2.1 Estimation of geotechnical design parameters
D.2.2 Sources of uncertainties
D.2.3 Inherent variability
D.2.4 Measurement error
D.2.5 Transformation of uncertainty
D.2.6 Total uncertainty
D.2.7 Scale of fluctuation
D.3 Statistical characterization of multivariate geotechnical data
D.3.1 General
D.4 Statistical characterization of model factors
D.4.1 General
D.5 Implementation issues in geotechnical reliability-based design
D.5.1 General
D.5.2 Goal and challenges
D.5.3 Reliability-based design method
D.5.4 Semi-probabilistic method
D.5.5 Characteristic value
D.5.6 Quantile-based design
D.5.7 System reliability
Annex E
E.1 Introduction
E.2 Probabilistic models for calibration
E.3 Code calibration as optimization problem
E.4 Reliability-based code optimization
E.4.1 Design equations and limit state functions
E.4.2 Procedure
E.4.2.1 Steps
E.4.2.2 Step1: Definition of the scope of the code
E.4.2.3 Step 2: Definition of the code objective
E.4.2.4 Step 3: Definition of the code format
E.4.2.5 Step 4: Identification of typical failure modes and probabilistic models
E.4.2.6 Step 5: Definition of a measure of closeness
E.4.2.7 Step 6: Determination of the optimal partial factors for the chosen code format
E.4.2.8 Step 7: Examination and determination of partial factors
E.5 Examples for calibration of partial factors44 A software tool is available for code calibration in accordance with the procedure described here; CodeCal developed by JCSS, see also www.jcss.byg.dtu.
E.5.1 Problem setting
E.5.2 Case 1: One variable load and partial factors in both load and resistance terms
E.5.3 Case 2: Two variable loads and partial factors in both load and resistance terms
E.6 Calibration of design values in design-value methods
E.6.1 Design values according to FORM
E.6.2 Sensitivity factors according to FORM
E.7 Partial factor design for fatigue based on S-N lines
E.7.1 S-N lines
E.7.2 Verification procedure in partial factor design
Annex F
F.1 Introduction
F.2 Classification of structures according to consequences
F.3 Guideline for selection of appropriate design strategies and robustness provisions
F.3.1 General
F.3.2 Event control
F.3.3 Specific Load Resistance (SLR)
F.3.4 Alternative Load Paths (ALP)
F.3.5 Consequence reducing measures
F.4 Risk-based approach to robustness assessments
F.4.1 General
F.4.2 Risk assessment for structural systems
F.4.3 Representation of hazards
F.4.4 Direct and indirect consequences
F.4.5 Further characteristics of risks and structural robustness
F.4.6 Alternative measures relating to robustness
Annex G
G.1 Introduction
G.2 Relationship between the MLSC principle and present best practice
G.3 How to calculate the expected value of the benefits as basis for optimization
G.3.1 General
G.3.2 Case of private ownership
G.3.3 Case of public ownership
G.4 How to calculate the limiting value of the lifesaving costs based on the LQI
G.4.1 General
G.4.2 Assessment of the marginal lifesaving costs based on the LQI
G.5 How to utilize the principles in practice
G.5.1 Maximum acceptable target failure probabilities
G.5.2 Target reliabilities based on economic optimization
Bibliography
Cited references in this standard
Content history
[Current]
[Superseded]
DR AS 5104:2017
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