Fatigue Reliability Assessment of Coupled Spar-Mooring System

2011 ◽  
Author(s):  
Mohammed Jameel ◽  
Suhail Ahmad
Keyword(s):  
Limit State ◽  
Reliability Assessment ◽  
Coupled Analysis ◽  
State Function ◽  
Mooring System ◽  
Limit State Function ◽  
Mooring Lines ◽  
Reliability Indices ◽  
Current Limit ◽  
Reliability Method

Spar platform is a compliant floating structure used for exploration of oil and gas from deep sea. To ensure safe operations, reliability against mooring line failure is a major concern in design. Furthermore, the mooring lines have high investment costs and are normally not accessible for in-service inspection. The common approach for solving the dynamics of Spar system is to employ a decoupled quasi-static approach which ignores the platform and mooring lines interaction. Coupled analysis, used presently, considers the mooring lines and platform in an integrated single model. Hence, it effectively captures the damping effect due to Spar and mooring lines coupling. Finite element code ABAQUS is used to obtain the response of Spar-mooring system under long crested random sea with current. Limit state function is derived based on failure due to fatigue for probabilistic reliability assessment. Random variables, participating actively in the limit state function are identified and statistically modeled. The most probable points or the design points are found to be an effective parameter for estimating partial factors of safety for load and resistance variables. First Order Reliability Method (FORM) is used to calculate probability of failure and reliability indices. The results are later checked against Monte carlo simulation. Reliabilities of segmental length of mooring and of full length are determined as they may significantly differ if the mooring properties change along the length. Reliability indices of annual and life time sea states are calculated.

Probabilistic Analysis and Risk Assessment of Deep Water Composite Production Riser Against Fatigue Limit State

2015 ◽  
Author(s):  
Manander Singh ◽  
Suhail Ahmad
Keyword(s):  
Risk Assessment ◽  
Deep Water ◽  
Probabilistic Analysis ◽  
Limit State ◽  
Reliability Assessment ◽  
Random Variables ◽  
State Function ◽  
Limit State Function ◽  
Wide Range ◽  
Reliability Method

Deep water composite risers are subjected to randomly fluctuating loads, induced by wind and waves in the presence of fluctuating axial tension which may be critical in deep sea conditions. Therefore, risers experience the extreme bending and randomly fluctuating stresses throughout their service life. Cumulative fatigue damage is a critical assessment of riser life in the presence of large dynamic stresses. Probabilistic analysis and risk assessment of composite risers for cumulative fatigue is a vital design requirement for its satisfactory service and survival for stipulated period. Without addressing the reliability assessment, composite risers may not be recommended for deep water oil and gas exploration and production. Hence, the reliability assessment is a critical issue that is to be addressed for the safety of the deep water composite riser. It is studied for the entire system for all possible sea states occurring in the exploration region. Unlike conventional risers, the wall structure of a composite riser is more complicated. Therefore, multiple failure mechanisms are used jointly to assess the safety of the composite riser. Fatigue reliability is a challenging task due to complex nature of dynamic response and associated uncertainties caused by the material and external loads. The present study is focused on reliability assessment using stochastic finite element analysis. Response time histories for random sea plus current have been obtained. Requisite numbers of sea states are considered for the simulation of a wide range of off-shore environment and estimation of accumulated damage. By using the S-N data, damage fractions are calculated then summed linearly using Miner-Palmgren rule. The total damage has been obtained by summing the accumulated damages over all the sea states under consideration. Non-linear limit state function is derived based upon the above given approach to calculate the fatigue life. Important uncertainties associated with random variables are considered while deriving the limit state function. Numerical methods, such as Monte Carlo simulation and Advanced First Order Reliability Method, are used for the calculation of the reliability. The sensitivities of various random variables on overall probability of failure have been studied and design points have been located on failure surface. Probabilities of failure for important parameters are investigated.

Second-Order Reliability Method With First-Order Efficiency

2010 ◽  
Author(s):  
Xiaoping Du ◽  
Junfu Zhang
Keyword(s):  
Limit State ◽  
Saddlepoint Approximation ◽  
Quadratic Function ◽  
Second Order ◽  
State Function ◽  
Limit State Function ◽  
First Order ◽  
Reliability Method ◽  
Order Of Magnitude ◽  
Univariate Function

The widely used First Order Reliability Method (FORM) is efficient, but may not be accurate for nonlinear limit-state functions. The Second Order Reliability Method (SORM) is more accurate but less efficient. To maintain both high accuracy and efficiency, we propose a new second order reliability analysis method with first order efficiency. The method first performs the FORM and identifies the Most Probable Point (MPP). Then the associated limit-state function is decomposed into additive univariate functions at the MPP. Each univariate function is further approximated as a quadratic function, which is created with the gradient information at the MPP and one more point near the MPP. The cumulant generating function of the approximated limit-state function is then available so that saddlepoint approximation can be easily applied for computing the probability of failure. The accuracy of the new method is comparable to that of the SORM, and its efficiency is in the same order of magnitude as the FORM.

scholarly journals Predictable Behavior of GFRP-Reinforced Bridge Decks: Formulation of a Strain-Based Capacity Model

2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Young Hoon Kim ◽  
Yeesock Kim ◽  
Yeonho Park
Keyword(s):  
Failure Modes ◽  
Limit State ◽  
State Function ◽  
Limit State Function ◽  
Analysis Framework ◽  
Multiple Failure Modes ◽  
Reliability Indices ◽  
Capacity Model ◽  
Exposure Temperature ◽  
Over Time

This paper proposes a reliability analysis framework for glass fiber-reinforced polymer- (GFRP-) reinforced concrete systems with uncertain capacities and demands over time. Unfortunately, there has been limited discussion or research done related to the potential change of failure modes over time. Therefore, a rational approach is needed to integrate multiple failure modes in a single analysis framework, considering uncertainties of time-variant demands and capacities. To account for multiple failure modes, this study proposes the limit state function to estimate the safety margin, based on strain values of GFRP-reinforcing bars. A proposed limit state function can capture the likelihood of both shear and flexural failure modes, simultaneously. In this study, seven typical bridge deck configurations (e.g., varied deck thickness, girder spacing, and bar size) were exposed to various ambient temperatures. Simulation results show that reliability indices of 100-year exposure exhibit significant variance, ranging from 2.35 to 0.93, with exposure temperatures ranging from 13 to 33°C. Exposure temperature and time are the dominant factors influencing the reliability indices, so are the ones that need to be changed. As exposure time and/or exposure temperature increase, the flexural capacity model plays an important role to determine the reliability indices. When flexural and shear failure modes are equally dominant, reliability indices can capture risks of both failures, using the proposed strain-based approach.

scholarly journals Hybrid Reliability Analysis for Spacecraft Docking Lock with Random and Interval Uncertainty

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jianguo Zhang ◽  
Jiwei Qiu ◽  
Pidong Wang
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Random Variables ◽  
Simple Problem ◽  
State Function ◽  
Limit State Function ◽  
Interval Variables ◽  
Reliability Method ◽  
Hybrid Reliability

This paper presents a novel procedure based on first-order reliability method (FORM) for structural reliability analysis with hybrid variables, that is, random and interval variables. This method can significantly improve the computational efficiency for the abovementioned hybrid reliability analysis (HRA), while generally providing sufficient precision. In the proposed procedure, the hybrid problem is reduced to standard reliability problem with the polar coordinates, where an n-dimensional limit-state function is defined only in terms of two random variables. Firstly, the linear Taylor series is used to approximate the limit-state function around the design point. Subsequently, with the approximation of the n-dimensional limit-state function, the new bidimensional limit state is established by the polar coordinate transformation. And the probability density functions (PDFs) of the two variables can be obtained by the PDFs of random variables and bounds of interval variables. Then, the interval of failure probability is efficiently calculated by the integral method. At last, one simple problem with explicit expressions and one engineering application of spacecraft docking lock are employed to demonstrate the effectiveness of the proposed methods.

Time-Dependent Reliability Analysis by a Sampling Approach to Extreme Values of Stochastic Processes

2012 ◽  
Author(s):  
Zhen Hu ◽  
Xiaoping Du
Keyword(s):  
Stochastic Processes ◽  
Reliability Analysis ◽  
Extreme Values ◽  
Limit State ◽  
Time Dependent ◽  
State Function ◽  
Limit State Function ◽  
Reliability Method ◽  
Time Invariant ◽  
State Functions

Maintaining high accuracy and efficiency is a challenging issue in time-dependent reliability analysis. In this work, an accurate and efficient method is proposed for limit-state functions with the following features: The limit-state function is implicit with respect to time, and its input contains stochastic processes; the stochastic processes include only general strength and stress variables, or the limit-state function is monotonic to these stochastic processes. The new method employs random sampling approaches to estimate the distributions of the extreme values of the stochastic processes. The extreme values are then used to replace the corresponding stochastic processes, and consequently the time-dependent reliability analysis is converted into its time-invariant counterpart. The commonly used time-invariant reliability method, the First Order Reliability Method, is then applied for the time-variant reliability analysis. The results show that the proposed method significantly improves the accuracy and efficiency of time-dependent reliability analysis.

Inversion analysis to determine design parameters for reliability assessment in pavement structures

2014 ◽  
Vol 41 (10) ◽  
pp. 845-855 ◽  
Author(s):  
Sungho Mun
Keyword(s):  
Reliability Index ◽  
Limit State ◽  
Reliability Assessment ◽  
Pavement Performance ◽  
Design Parameters ◽  
State Function ◽  
Limit State Function ◽  
Performance Function ◽  
Pavement Structures ◽  
Inversion Analysis

Reliability assessment has been used to evaluate the performance of pavement structures. However, probabilistic inversion analysis of pavement structure design has not yet been tested to determine the design parameters of the pavement performance function, given a specified reliability index. In this study, a limit state function numerical calculation and the inversion technique of the Nelder–Mead simplex algorithm were used to determine the design parameters for the pavement performance function. The method of moments was used to develop the forward limit state function, which was then compared to Monte Carlo simulations; the comparison indicated good agreement between the two methods. Additionally, several cases were studied to determine the design parameters of the pavement performance function for the reliability index specified in this study. The case studies indicated that the structure number significantly affected the pavement performance function.

Reliability Analysis of Pressure Vessels in Lubricant Process Unit for Risk Based Inspection

2008 ◽  
Author(s):  
Chi-Hui Chien ◽  
Chun-Hung Chen
Keyword(s):  
Reliability Analysis ◽  
Pressure Vessel ◽  
Safety Concern ◽  
Limit State ◽  
Reliability Assessment ◽  
Pressure Vessels ◽  
State Function ◽  
Process Unit ◽  
Limit State Function ◽  
Failure Probabilities

As a safety concern to a pressurized system, to monitor the corrosion rate of each pressure vessel in order to make the repair decision at the right time based on the required thickness to withstand the maximum allowable working pressure (MAWP), is important to the plant owner. A plant inspector will normally assess the risk by evaluating the probability of failure of each pressure vessel during service hours with inspection and maintenance planning. Therefore, a scheme of reliability assessment to the pressure vessels should be established. The objective of this study is to discuss the failure probabilities of the pressure vessels in a lubricant unit in order to provide the input information for Risk Based Inspection (RBI) assessments. The reliability assessment of a pressure vessel involves the estimation of the failure pressure and evaluation of the limit state function. Based on the formula for calculating required thickness of a pressure vessel component, and due to the presence of non-linearity in the limit state function and the non-normal distributed variables, the first order second moment method (FOSM) was adopted for carrying out the reliability analysis. The uncertainties of the random variables in the limit state function were modeled by using normal and non-normal probabilistic distributions. As the heat exchanger is an important pressure vessel to a pressurized system, the failure probabilities together with the ranking categories of the heat exchangers in a lubricant unit are chosen as a case study to be discussed and presented in this paper.

scholarly journals High Dimension Model Representation-Based Response Surface for Reliability Analysis of Tunnel

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Hongbo Zhao
Keyword(s):  
Reliability Analysis ◽  
Response Surface ◽  
Reliability Index ◽  
Limit State ◽  
State Function ◽  
Limit State Function ◽  
Implicit Function ◽  
Surface Method ◽  
Reliability Method ◽  
Rock Tunnel

Uncertainty is an important prosperity to rock tunnel. Reliability analysis is widely used to deal with the uncertainty. But it is difficult to be adopted in rock tunnel using the traditional reliability method because the limit state function is an implicit function. High dimension model representation (HDMR) can approximate the high dimensional, nonlinear, and implicit function using the low dimensional function. In this study, the HDMR method was adapted to approximate the limit state function through combining with response surface method (RSM). A new reliability analysis approach of HDMR-based response surface method, combined with the first-order reliability method (FORM), is developed to calculate the reliability index of tunnel, and implementation of the method is explained briefly. A circular tunnel with analytical solution and horseshoe tunnel with numerical solution are used to demonstrate the proposed method. The obtained reliability index is in excellent agreement with Low and Tang’s (2007) method and traditional RSM. It shows that HDMR-based response surface can approximate well the limit state function, and the proposed method is an efficient and effective approach for reliability analysis in tunnel engineering. It is very useful for reliability analysis of practical large-scale rock engineering.

A Second-Order Reliability Method With First-Order Efficiency

2010 ◽  
Vol 132 (10) ◽  
Author(s):  
Junfu Zhang ◽  
Xiaoping Du
Keyword(s):  
Limit State ◽  
Saddlepoint Approximation ◽  
Quadratic Function ◽  
Second Order ◽  
State Function ◽  
Limit State Function ◽  
First Order ◽  
Reliability Method ◽  
Order Of Magnitude ◽  
Univariate Function

The first-order reliability method (FORM) is efficient but may not be accurate for nonlinear limit-state functions. The second-order reliability method (SORM) is more accurate but less efficient. To maintain both high accuracy and efficiency, we propose a new second-order reliability analysis method with first-order efficiency. The method first performs the FORM to identify the most probable point (MPP). Then, the associated limit-state function is decomposed into additive univariate functions at the MPP. Each univariate function is further approximated by a quadratic function. The cumulant generating function of the approximated limit-state function is then available so that saddlepoint approximation can be easily applied in computing the probability of failure. The accuracy of the new method is comparable to that of the SORM, and its efficiency is in the same order of magnitude as the FORM.

Reliability Analysis for Multidisciplinary Systems Involving Stationary Stochastic Processes

2015 ◽  
Author(s):  
Zhifu Zhu ◽  
Zhen Hu ◽  
Xiaoping Du
Keyword(s):  
Stochastic Processes ◽  
Reliability Analysis ◽  
Limit State ◽  
Time Dependent ◽  
State Function ◽  
Limit State Function ◽  
Current Time ◽  
Reliability Method ◽  
Stationary Stochastic Processes ◽  
Multidisciplinary System

The response of a component in a multidisciplinary system is affected by not only the discipline to which it belongs, but also by other disciplines of the system. If any components are subject to time-dependent uncertainties, responses of all the components and the system are also time dependent. Thus, time-dependent multidisciplinary reliability analysis is required. To extend the current time-dependent reliability analysis for a single component, this work develops a time-dependent multidisciplinary reliability method for components in a multidisciplinary system under stationary stochastic processes. The method modifies the First and Second Order Reliability Methods (FORM and SORM) so that the Multidisciplinary Analysis (MDA) is incorporated while approximating the limit-state function of the component under consideration. Then Monte Carlo simulation is used to calculate the reliability without calling the original limit-state function. Two examples are used to demonstrate and evaluate the proposed method.

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