NorMoor JIP, Structural Reliability Analysis for Mooring Lines in Ultimate and Accidental Limit State

2017 ◽  
Author(s):  
Torfinn Hørte ◽  
Siril Okkenhaug ◽  
Øivind Paulshus
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Mooring Lines ◽  
Structural Reliability Analysis

First-Order Reliability Method for Structural Reliability Analysis in the Presence of Random and Interval Variables

2015 ◽  
Vol 1 (4) ◽  
Author(s):  
Umberto Alibrandi ◽  
C. G. Koh
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Computational Cost ◽  
Computational Effort ◽  
Stochastic Dynamic ◽  
First Order Reliability Method ◽  
First Order ◽  
Structural Reliability Analysis ◽  
Reliability Method

This paper presents a novel procedure based on first-order reliability method (FORM) for structural reliability analysis in the presence of random parameters and interval uncertain parameters. In the proposed formulation, the hybrid problem is reduced to standard reliability problems, where the limit state functions are defined only in terms of the random variables. Monte Carlo simulation (MCS) for hybrid reliability analysis (HRA) is presented, and it is shown that it requires a tremendous computational effort; FORM for HRA is more efficient but still demanding. The computational cost is significantly reduced through a simplified procedure, which gives good approximations of the design points, by requiring only three classical FORMs and one interval analysis (IA), developed herein through an optimization procedure. FORM for HRA and its simplified formulation achieve a much improved efficiency than MCS by several orders of magnitude, and it can thus be applied to real-world engineering problems. Representative examples of stochastic dynamic analysis and performance-based engineering are presented.

On the Application of Structural Reliability Analysis

2017 ◽  
Author(s):  
Torfinn Hørte ◽  
Gudfinnur Sigurdsson
Keyword(s):  
Reliability Analysis ◽  
Structural Engineering ◽  
Structural Reliability ◽  
Limit State ◽  
Design Analysis ◽  
Ultimate Limit State ◽  
Hull Girder ◽  
Structural Reliability Analysis ◽  
Code Calibration ◽  
Calculated Probability

Structural Reliability Analysis (SRA) is a useful tool in structural engineering. Uncertainty in input parameters and model uncertainties in the analysis predictions are explicitly modelled by random variables. With this methodology, the uncertainties involved are handled in a consistent and transparent way. Compared to a deterministic analysis, SRA provides improved insight in how the various uncertainties involved influence the results. The main results from SRA is the calculated probability of structural failure, but other useful results such as uncertainty importance factors and design points being the most likely combination of all variables at failure represent helpful information. The present paper illustrates some the features using SRA for two different types of application. The first application is the use of SRA as a tool for code calibration and the second shows the application of SRA to a problem where common practice is likely to be rather conservative and therefore leading to unacceptable results, but where the degree of conservatism is not known. Two examples are chosen to illustrate code calibration; i.e. hull girder ultimate limit state (ULS) for tankers and ULS for mooring design in the ULS for floating offshore vessels. Code calibration involves both SRA and design analysis following the code. It is shown how the design analysis can be modified in order to better reflect a chosen target reliability level across a selected set of test cases representative for what the code should cover. Fatigue of subsea wellhead systems is selected as an example of a special case when application of existing rules may lead to unsatisfactory results which are likely to be rather conservative. It is shown how results can be presented in terms of the accumulated probability of fatigue failure as a function of time. This may be a more suitable basis for decision making than a calculated fatigue life from a standard analysis. It is also illustrated how importance factors from the SRA can be used as guidance on how to prioritize effort in order to improve prediction of the fatigue damage. The present paper is not intended to be detailed in all input and analysis methodology, but draw the attention towards the possibilities and benefits of applying SRA in structural engineering, where the examples are used to illustrate this potential.

scholarly journals Structural Reliability Analysis of Limit State Functions With Multiple Design Points Using Evolutionary Strategies

2009 ◽  
Vol 10 (2) ◽  
pp. 87-97 ◽  
Author(s):  
Federico Barranco-Cicilia ◽  
◽  
Edison Castro-Prates de Lima ◽  
Luís Volnei Sudati-Sagrilo ◽  
◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Evolutionary Strategies ◽  
Structural Reliability Analysis ◽  
State Functions

scholarly journals Structural Reliability Analysis of Ship Hulls Accounting for Collision or Grounding Damage

2020 ◽  
Author(s):  
Branka Bužančić Primorac ◽  
Joško Parunov ◽  
C. Guedes Soares
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Random Variables ◽  
Bending Moment ◽  
State Equation ◽  
Limit States ◽  
Moment Capacity ◽  
Ship Hulls ◽  
Structural Reliability Analysis

AbstractClassical structural reliability analysis of intact ship hulls is extended to the case of ships with collision or grounding damages. Still water load distribution and residual bending moment capacity are included as random variables in the limit state equation. The probability density functions of these random variables are defined based on random damage parameters given by the Marine Environment Protection Committee of the International Maritime Organization, while the proposed reliability formulation is consistent with international recommendations and thus may be valuable in the development of rules for accidental limit states. The methodology is applied on an example of an Aframax oil tanker. The proposed approach captures in a rational way complex interaction of different pertinent variables influencing safety of damaged ship structure.

Bayesian Approach for Structural Reliability Analysis and Optimization Using the Kriging Dimension Reduction Method

2010 ◽  
Vol 132 (5) ◽  
Author(s):  
Jooho Choi ◽  
Dawn An ◽  
Junho Won
Keyword(s):  
Dimension Reduction ◽  
Reliability Analysis ◽  
Bayesian Approach ◽  
Structural Reliability ◽  
Reduction Method ◽  
Epistemic Uncertainty ◽  
Limit State ◽  
State Function ◽  
Dimension Reduction Method ◽  
Structural Reliability Analysis

An efficient method for a structural reliability analysis is proposed under the Bayesian framework, which can deal with the epistemic uncertainty arising from a limited amount of data. Until recently, conventional reliability analyses dealt mostly with the aleatory uncertainty, which is related to the inherent physical randomness and its statistical properties are completely known. In reality, however, epistemic uncertainties are prevalent, which makes the existing methods less useful. In the Bayesian approach, the probability itself is treated as a random variable of a beta distribution conditional on the provided data, which is determined by conducting a double loop of reliability analyses. The Kriging dimension reduction method is employed to promote efficient implementation of the reliability analysis, which can construct the PDF of the limit state function with favorable accuracy using a small number of analyses. Mathematical examples are used to demonstrate the proposed method. An engineering design problem is also addressed, which is to find an optimum design of a pigtail spring in a vehicle suspension, taking material uncertainty due to limited test data into account.

A modified downhill simplex algorithm interpolation response surface method for structural reliability analysis

2019 ◽  
Vol 37 (4) ◽  
pp. 1423-1450
Author(s):  
Hailiang Su ◽  
Fengchong Lan ◽  
Yuyan He ◽  
Jiqing Chen
Keyword(s):  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Limit State ◽  
Simplex Algorithm ◽  
Content Type ◽  
Structural Reliability Analysis ◽  
Surface Method ◽  
Downhill Simplex

Purpose Because of the high computational efficiency, response surface method (RSM) has been widely used in structural reliability analysis. However, for a highly nonlinear limit state function (LSF), the approximate accuracy of the failure probability mainly depends on the design point, and the result is that the response surface function composed of initial experimental points rarely fits the LSF exactly. The inaccurate design points usually cause some errors in the traditional RSM. The purpose of this paper is to present a hybrid method combining adaptive moving experimental points strategy and RSM, describing a new response surface using downhill simplex algorithm (DSA-RSM). Design/methodology/approach In DSA-RSM, the operation mechanism principle of the basic DSA, in which local descending vectors are automatically generated, was studied. Then, the search strategy of the basic DSA was changed and the RSM approximate model was reconstructed by combining the direct search advantage of DSA with the reliability mechanism of response surface analysis. Findings The computational power of the proposed method is demonstrated by solving four structural reliability problems, including the actual engineering problem of a car collision. Compared to specific structural reliability analysis methods, the approach of modified DSA interpolation response surface for structural reliability has a good convergent capability and computational accuracy. Originality/value This paper proposes a new RSM technology based on proxy model to complete the reliability analysis. The originality of this paper is to present an improved RSM that adjusts the position of the experimental points judiciously by using the DSA principle to make the fitted response surface closer to the actual limit state surface.

UHB Model Uncertainty for Structural Reliability Analysis of Pipeline OOS Design

2018 ◽  
Author(s):  
M. Liu ◽  
C. Cross
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Universal Design ◽  
Limit State ◽  
Load Factor ◽  
Design Curve ◽  
Design Load ◽  
Structural Reliability Analysis ◽  
Load Factors ◽  
Curve Method

Design load factor structural reliability analysis is critical for pipeline postlay OOS design to mitigate global UHB for a trenched and buried subsea pipeline configuration operating at elevated temperature and pressure. During the detailed engineering phase it is necessary to evaluate and define any measure available to be finalised for UHB mitigation such as deep trenching selection, enhanced blanket or spot rockdumping. In order account for inherent uncertainties in the design variables, a pre-emptive SRA is normally performed for the probabilistic UHB design load factors prior to pipeline installation according to the typical trench imperfection statistics and some specified survey accuracy. As per the current practice the semi-analytical universal design curve method is used in the limit state for design load factor predictions. The SRA results will be updated once the OOS survey data become available. A rockdump schedule can then be established by FEA incorporating appropriate safety or load factors to address uncertainties in the design parameters and as-built pipeline OOS survey measurement accuracy. This paper examines the UHB model uncertainties in the load factor and backfill cover assessment with a view to improving the SRA OOS analysis. Sources of uncertainties and variability in the UHB design are discussed first. Some disparity and inconsistency arising between the SRA and FEA models for the limit state are considered. Alternative UHB models are investigated by taking Timoshenko shear stiffness and associated deformation with pipe-soil interactions into consideration. A comparison is made with the conventional universal design curve method, the improved model and FE modelling to demonstrate the findings and conclusions. Of these, the pipe-soil interaction and its representation in the SRA limit state assessment are identified as a significant factor.

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