Reliability Based Structural Risk Assessments and Associated Economic Gains

2021 ◽  
Author(s):  
Mohamed Atia ◽  
Ahmed Abdelkhalek ◽  
Anjan Sarkar ◽  
Matt Keys ◽  
Mahesh Patel ◽  
...  
Keyword(s):  
Risk Evaluation ◽  
Structural Reliability ◽  
Joint Probability ◽  
Cost Savings ◽  
Offshore Structures ◽  
Probability Of Failure ◽  
Mitigation Measures ◽  
Risk Matrix ◽  
Structural Risk ◽  
Corporate Risk

Abstract Managing a large fleet of offshore structures is a dynamic process that aims at minimising risks to personnel, environment, and businesses, as well as minimising the associated Operations Expenditure. Through the collaborative efforts of ADNOC Offshore and Kent, formerly Atkins Oil & Gas, (Atkins, 2020), revised structural evaluation and integrity approaches have yielded significant cost savings. The considerable savings were associated with the elimination of the requirement for installing many new offshore structures and through reducing the subsea inspection associated efforts. The approach for evaluating the offshore assets’ structural performance was developed based on adopting target probability of failure figures subject to each asset's consequence of failure. Accordingly, structural reliability analyses were conducted specific to each structure, where the analysis considered structure specific environmental hazard curves and failure surfaces. Through mapping the evaluated structural probability of failure and ADNOC's corporate risk matrix's HSE Likelihood, each structure was precisely placed on the risk matrix. Furthermore, the inspection intervals and Topsides, Splash Zone, Subsea Levels I, II and III were mapped to each risk evaluation on the risk matrix. The optimisation approach of adopting a structure specific reliability analysis and mapping with ADNOC's corporate risk matrix yielded considerable cost benefits while providing a more accurate representation of each asset's risk. As a result of the implementation of the developed process, approximately 41% of the assets got lower risk evaluation compared to the legacy approach and presented extra structural capacities that can be utilised for future expansions and eliminating the requirement for installation of new assets. As the process expanded to include asset inspections, the subsea inspection requirements reduced by approximately 43% reflecting a considerable decrease in operating costs. A major contribution of the risk improvement is attributed to the consideration of the storm prevailing approach directions, the joint probability of wave and current magnitudes and directions, as well as the relative alignment of each structure. The developed approaches provide a framework that allows continuous update of the risk assessment and enables executives and management to make risk-based-decision supported by a consistent measure of structural risk. This has been translated into the generation of the Structural Passports (Summary reports) clearly demonstrating the assets current risk and recommendations for mitigation measures, if deemed required.

Wellhead Fatigue Analysis Method: Benefits of a Structural Reliability Analysis Approach

2012 ◽  
Author(s):  
Torfinn Hørte ◽  
Lorents Reinås ◽  
Jan Mathisen
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Offshore Structures ◽  
Probability Of Failure ◽  
Fatigue Analysis ◽  
Life Extension ◽  
Inspection Planning ◽  
Structural Reliability Analysis ◽  
Extreme Load ◽  
Input Parameters

Structural Reliability Analysis (SRA) methods have been applied to marine and offshore structures for decades. SRA has proven useful in life extension exercises and inspection planning of existing offshore structures. It is also a useful tool in code development, where the reliability level provided by the code is calibrated to a target failure probability obtained by SRA. This applies both to extreme load situations and also to a structural system under the influence of a time dependent degradation process such as fatigue. The current analysis methods suggested for service life estimation of subsea wells are deterministic, and these analyses are associated with high sensitivity to variations in input parameters. Thus sensitivity screening is often recommended for certain input parameters, and the worst case is then typically used as a basis for the analysis. The associated level of conservatism embedded in results from a deterministic analysis is not quantified, and it is therefore difficult to know and to justify if unnecessary conservatism can be removed from the calculations. By applying SRA to a wellhead fatigue analysis, the input parameters are accounted for with their associated uncertainty given by probability distributions. Analysis results can be generated by use of Monte-Carlo simulations or FORM/SORM (first/second order reliability methods), accounting for the full scatter of system relations and input variations. The level of conservatism can then be quantified and evaluated versus an acceptable probability of failure. This article presents results from a SRA of a fictitious but still realistic well model, including the main assumptions that were made, and discusses how SRA can be applied to a wellhead fatigue analysis. Global load analyses and local stress calculations were carried out prior to the SRA, and a response surface technique was used to interpolate on these results. This analysis has been limited to two hotspots located in each of the two main load bearing members of the wellhead system. The SRA provides a probability of failure estimate that may be used to give better decision support in the event of life extension of existing subsea wells. In addition, a relative uncertainty ranking of input variables provides insight into the problem and knowledge about where risk reducing efforts should be made to reduce the uncertainty. It should be noted that most attention has been given to the method development, and that more comprehensive analysis work and assessment of specific input is needed in a real case.

scholarly journals Development of Risk-Reliability Based Underwater Inspection for Fixed Offshore Platforms in Indonesia

2018 ◽  
Vol 147 ◽  
pp. 05002
Author(s):  
Ricky L. Tawekal ◽  
Faisal D. Purnawarman ◽  
Yati Muliati
Keyword(s):  
Structural Reliability ◽  
Structural Integrity ◽  
Damage Mechanism ◽  
Offshore Structures ◽  
Probability Of Failure ◽  
American Petroleum Institute ◽  
Offshore Platform ◽  
Risk Level ◽  
Offshore Platforms ◽  
Fixed Offshore Platform

In RBUI method, platform with higher risk level will need inspection done more intensively than those with lower risk level. However, the probability of failure (PoF) evaluation in RBUI method is usually carried out in semi quantitative way by comparing failure parameters associated with the same damage mechanism between a group of platforms located in the same area. Therefore, RBUI will not be effective for platforms spread in distant areas where failure parameter associated with the same damage mechanism may not be the same. The existing standard, American Petroleum Institute, Recommended Practice for Structural Integrity Management of Fixed Offshore Structures (API RP-2SIM), is limited on the general instructions in determining the risk value of a platform, yet it does not provide a detail instruction on how determining the Probability of Failure (PoF) of platform. In this paper, the PoF is determined quantitatively by calculating structural reliability index based on structural collapse failure mode, thus the method in determining the inspection schedule is called Risk-Reliability Based Underwater Inspection (RReBUI). Models of 3-legs jacket fixed offshore platform in Java Sea and 4-legs jacket fixed offshore platform in Natuna Sea are used to study the implementation of RReBUI.

Progressive Collapse Approach Compared to the Traditional Temperature Screening on Structural Assessment of Offshore Structures Against Fire

2016 ◽  
Author(s):  
Paula T. Nascimento ◽  
Marco A. P. Rosas ◽  
Leonardo Brandão ◽  
Fernando Castanheira
Keyword(s):  
Traditional Approach ◽  
Progressive Collapse ◽  
Screening Method ◽  
Substantial Reduction ◽  
Cost Savings ◽  
Offshore Structures ◽  
Significant Cost ◽  
Fire Scenarios

The present study compares the progressive collapse approach with the traditional temperature screening method on determination of PFP requirements at topside offshore structures. The advantage to evaluate the consequences of fire scenarios on the global integrity and stability of topside modules can be revealed by a substantial reduction of the required amount of PFP, and consequently significant cost savings for operators, when compared to the traditional approach. In the case study presented in this paper, there is a reduction of 79% in PFP allocation.

Reliability Based Assessment of Deck Elevations for Offshore Jacket Platforms

2004 ◽  
Vol 126 (4) ◽  
pp. 331-336 ◽  
Author(s):  
Ernesto Heredia-Zavoni ◽  
Dante Campos ◽  
Gallegher Ramı´rez
Keyword(s):  
Reliability Index ◽  
Structural Reliability ◽  
Failure Modes ◽  
Probability Of Failure ◽  
Upper And Lower Bounds ◽  
Series System ◽  
Wave Loading ◽  
System Components ◽  
Storm Wave ◽  
Wave Heights

Structural reliability analyses of fixed marine platforms subjected to storm wave loading are performed to assess deck elevations. Platforms are modeled as a series system consisting of the deck and jacket bays. The structural reliability analyses are carried out assuming dominant failure modes for the system components. Upper and lower bounds of the probability of failure are computed. The variation of the reliability index per bay component as a function of wave height, with a focus on those wave heights that generate forces on the deck, is analyzed. A comparison is given for the deck probability of failure and the lower bound probability of failure of the jacket in order to assess how the deck or the jacket controls the probability of failure of the system. Results are also given for reliability analyses considering different deck elevations. Finally, an analysis of the total probabilities of failure, unconditioned on wave heights, is given.

Efficient Reliability Assessment With the Conditional Probability Method

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Rami Mansour ◽  
Mårten Olsson
Keyword(s):  
Conditional Probability ◽  
Structural Reliability ◽  
A Priori ◽  
Reliability Assessment ◽  
Probability Of Failure ◽  
Assessment Method ◽  
Probability Method ◽  
Probability Of Survival ◽  
Design Variables ◽  
Reliability Method

Reliability assessment is an important procedure in engineering design in which the probability of failure or equivalently the probability of survival is computed based on appropriate design criteria and model behavior. In this paper, a new approximate and efficient reliability assessment method is proposed: the conditional probability method (CPM). Focus is set on computational efficiency and the proposed method is applied to classical load-strength structural reliability problems. The core of the approach is in the computation of the probability of failure starting from the conditional probability of failure given the load. The number of function evaluations to compute the probability of failure is a priori known to be 3n + 2 in CPM, where n is the number of stochastic design variables excluding the strength. The necessary number of function evaluations for the reliability assessment, which may correspond to expensive computations, is therefore substantially lower in CPM than in the existing structural reliability methods such as the widely used first-order reliability method (FORM).

Adjusting Environmental Contours for Specified Expected Number of Unwanted Events

2020 ◽  
Author(s):  
Erik Vanem
Keyword(s):  
Reliability Analysis ◽  
Return Period ◽  
Environmental Conditions ◽  
Structural Reliability ◽  
Probability Of Failure ◽  
Expected Number ◽  
Probability Of Exceedance ◽  
Underlying Distribution ◽  
Extreme Loads ◽  
Time Period

Abstract Environmental contours are applied in probabilistic structural reliability analysis to identify extreme environmental conditions that may give rise to extreme loads and responses. Typically, they are constructed to correspond to a certain return period and a probability of exceedance with regards to the environmental conditions that can again be related to the probability of failure of a structure. Thus, they describe events with a certain probability of being exceeded one or more times during a certain time period, which can be found from a certain percentile of the underlying distribution. In this paper, various ways of adjusting such environmental contours to account for the expected number of exceedances within a certain time period are discussed. Depending on how such criteria are defined, one may get more lenient or more stringent criteria compared to the classical return period.

An efficient particle swarm optimization-joint probability distribution optimization method for structural reliability analysis

2020 ◽  
pp. 095440622094155
Author(s):  
Hossein Mansourinejad ◽  
Kamran Daneshjou
Keyword(s):  
Particle Swarm Optimization ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Particle Swarm ◽  
Joint Probability ◽  
Joint Probability Distribution ◽  
Engineering Structures ◽  
Swarm Optimization ◽  
Highly Nonlinear ◽  
Conventional Methods

The performance function of many engineering structures and mechanisms is usually complex, highly nonlinear, and described in the implicit form. The reliability analysis of these structures using common methods requires high cost and time. In this paper, a new approach for reliability analysis of engineering structures and mechanisms by using the particle swarm optimization algorithm is presented. The advantages of this method in comparison with the conventional methods are its simplicity and accuracy. In addition, the limitations of the common previously presented methods are eliminated by the proposed method. This approach is based on a new redefinition of most probable point in the reliability analysis. To evaluate the performance and validity of the proposed method, some examples in the reliability analysis of various functions are employed. Finally, the superiority of the proposed method in performance and accuracy is demonstrated and compared to the conventional methods and it can be used for reliability analysis of complicated engineering structures.

scholarly journals The UAVs threat to airport security: risk analysis and mitigation

2019 ◽  
Vol 9 (2) ◽  
pp. 63 ◽  
Author(s):  
John Pyrgies
Keyword(s):  
Risk Management ◽  
Risk Analysis ◽  
Mitigation Measures ◽  
Airport Security ◽  
Negative Consequences ◽  
Security Risk ◽  
Risk Matrix ◽  
Safety Risk ◽  
Risk Management Process ◽  
Different Sources

Purpose: This research studies the UAV incidents in the vicinity of worldwide airports in order to deliver a quantitative and qualitative analysis of this phaenomenon, to analyse the risks associated to this threat and propose mitigation measures that brings this risk to an ‘acceptable’ level.Methodology: A population of 139 ‘serious UAV incidents in the vicinity of worldwide airports’ has been constituted on the basis of the FAA and NASA databases and articles published on the Web by online media. This phaenomenon has then been analysed quantitatively using descriptive statistics techniques and qualitatively by analysing in-depth some representative incidents. A risk analysis has then been performed based on the FAA Safety Risk Management 5-steps process to identify the hazards i.e. the root causes of those UAV incidents, determine their outcome i.e. negative consequences that jeopardize airports objectives and assign them a severity level and likelihood i.e. frequency level. Analysed risks have then been assessed based on FAA ARP Risk Matrix. Mitigation measures (prevention, deterrence, denial, detection, neutralisation) have been identified following a ‘Defence-in-Depth’ approach.Findings: The findings of the study are that those UAV incidents are more numerous than anticipated and happen higher and further from the airports than expected: they happen not only in CTRs but also in TMAs. This has an impact on the mitigation measures that shall not only be deployed at airports side but also be on-boarded in manned aircrafts.Originality: To our knowledge, no study has combined different sources to constitute such a population focused on ‘serious’ UAVs incidents around airports worldwide, has applied the official FAA Safety Risk Management process to assess this risk and followed a structured ‘Defence-in-Depth’ approach typically used in Cybersecurity to mitigate this risk.Keywords: Airport security and safety, Unmanned Aerial Vehicles (UAVs) threat, Risk analysis and mitigation, Counter-UAVs technologies.

Reduction Factors for Estimating the Probability of Failure of Mechanical Damage Due to External Interference

2008 ◽  
Author(s):  
Andrew Cosham ◽  
Jane Haswell ◽  
Neil Jackson
Keyword(s):  
Structural Reliability ◽  
Historical Data ◽  
Mechanical Damage ◽  
Probability Of Failure ◽  
Risk Assessments ◽  
External Interference ◽  
Failure Data ◽  
Major Accident ◽  
The Uk ◽  
Reduction Factors

Quantified risk assessments (QRAs) are widely used in the UK to assess the significance of the risk posed by major accident hazard pipelines on the population and infrastructure in the vicinity of the pipeline. A QRA requires the calculation of the frequency of failures and the consequences of failures. One of the main causes of failures in onshore pipelines is mechanical damage due to external interference, such as a dent, a gouge, or a dent and gouge. In the published literature, two methods have been used to calculate the probability of failure due to external interference: • historical failure data and • limit state functions combined with historical data (i.e. structural reliability-based methods). Structural reliability-based methods are mathematically complicated, compared to using historical failure data, but have several advantages, e.g. extrapolation beyond the limited historical data, and the identification of trends that may not be apparent in the historical data. In view of this complexity, proposed supplements to the UK pipeline design codes IGE/TD/1 (natural gas) and PD 8010 (all substances) — on the application of QRAs to proposed developments in the vicinity of major accident hazard pipelines — include simple ‘reduction factors’ for use in ‘screening’ risk assessments. These ‘reduction factors’ are based on a comprehensive parametric study using a structural reliability-based model to calculate the probability of failure due to mechanical damage, defined as: gouges, and dents and gouges. The two ‘reduction factors’ are expressed in terms of the design factor and wall thickness of the pipeline. It is shown that, through appropriate normalisation, the effects of diameter, grade and toughness are secondary. Reasonably accurate, but conservative, estimates of the probability of failure can be obtained using these ‘reduction factors’. The proposed methodology is considerably simpler than a structural reliability-based analysis. The development and verification of these ‘reduction factors’ is described in this paper.

Co-Occurrence Probability Analysis of Sea Ice at Yingkou and Huludao Observation Stations of China

2017 ◽  
Author(s):  
Shanshan Tao ◽  
Zhifeng Wang ◽  
Ri Zhang ◽  
Sheng Dong
Keyword(s):  
Sea Ice ◽  
Probability Distributions ◽  
Joint Probability ◽  
Offshore Structures ◽  
Early Spring ◽  
Probability Analysis ◽  
Ice Thickness ◽  
Occurrence Probability ◽  
Sea Ice Thickness ◽  
Ice Conditions

Co-occurrence probability analysis of sea ice between adjacent areas is very helpful for the hazard prevention and protection strategy making of coastal and offshore engineering. Yingkou and Huludao with similar latitudes are located on the opposite sides of Liaodong Bay of China. Their sea ice conditions are both apparent in winter and early spring, so it is useful to study on the co-occurrence situations of sea ice conditions between these two areas. Based on the annual maximum sea ice thickness of Yingkou and Huludao observation stations, the co-occurrence probability analysis of sea ice thickness is conducted. The joint probability distributions of sea ice thickness between these adjacent areas are constructed by using univariate maximum entropy distributions and four bivariate copulas. Both marginal curve fittings are very well, and the model determined by Gumbel-Hougaard copula describes the bivariate sea ice thickness data best. Then different cases of co-occurrence probabilities of sea ice thickness between Yingkou and Huludao are presented, and they can provide references to the hazard protection of the coastal and offshore structures between these two areas.

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