Lazy-Wave Buoyancy Length Reduction Based on Fatigue Reliability Analysis

Author(s):  
Vinícius Ribeiro Machado da Silva ◽  
Luis V. S. Sagrilo ◽  
Mario Alfredo Vignoles

When the profit scenario of an industry changes, the continuity of some projects can be at risk. The current downturn of the oil and gas industry force managers to take hard decisions about the continuity of projects, resulting in delays, postponements or even the cancellation of forecasted projects. In order to keep with these projects, the rush for cost reduction is a reality and the industry is pushing the involved parties to be aligned with this objective. The Brazilian Pre-Salt region, characterized by ultra-deep waters, is an example of this scenario. Subsea structures represented by flexible risers, which are responsible for the flow assurance of oil, gas and water, are forecasted to have a demand about 4.000 km in the next years. Usually, in these type of applications, lazy-wave configurations are adopted, increasing the costs of the solution with the necessity of the buoyancy modules acquisition. The smaller the buoyancy length is the cheaper the project become, reducing the necessary amount of buoys and the time spent for its installation. These type of solutions can probably carry with it a high level of conservatism, imposed by the use of standardized safety factors, and can potentially be optimized with the adoption of probabilistic approaches within the chain of analysis. The objective of this paper is to assess the possibility of buoyancy length reduction of lazy-wave configurations by using structural reliability methods of analysis. The focus stays on the evaluation of the fatigue of the armour wires located at the bend stiffener region, one of the most critical failure mode for the design of flexible pipes in offshore Brazilian installations. As already discussed in Ref. [1], many variables can influence on such kind of analysis. Based on this previous study, the first six random variables, identified to be the most important ones, are taken to carry out the analysis. The fatigue reliability approach considers four 6” flexible riser configurations: an original lazy-wave, a lazy-wave with less 30% of buoyance length, another one with less 50% of buoyance length and a free-hanging configuration. Failure probabilities and safety factor calibration curves are shown for each presented configuration and compared among themselves. The results indicate the possibility of defining a lazy-wave configuration with smaller buoyancy lengths, reaching 75% of reduction without changing the preconized high safety class at last year of its operational time. Safety factor curves shows to have similar behavior no matter the configuration considered. Structural reliability analysis comes as a potential method to help engineers to have a better understanding on the driving random variables of the problem, giving a support for the actual cost reduction scenario and for better decision-makings based on quantified risk.

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Vinícius Ribeiro Machado da Silva ◽  
Luis V. S. Sagrilo ◽  
Mario Alfredo Vignoles

The current downturn of the oil and gas industry force managers to take hard decisions about the continuity of projects, resulting in delays, postponements, or even their cancellation. In order to keep with them, the rush for cost reduction is a reality and the industry is pushing the involved parties to be aligned with this objective. The Brazilian presalt region, characterized by ultra-deep waters, faces this scenario where flexible risers in lazy-wave configurations are usually adopted as a solution to safe transfer fluids from sea bed until the floating unit. The smaller the buoyancy length, the cheaper the project becomes, reducing the necessary amount of buoys and the time spent for its installation. This paper investigates the possibility of buoyancy length reduction of lazy-wave configurations by using structural reliability methods on fatigue failure mode. The application of the fatigue reliability approach considers four 6 in flexible riser configurations: an original lazy-wave, a lazy-wave with less 30% of buoyancy length, another one with less 50% of buoyancy length and a free-hanging. Failure probabilities and safety factor calibration curves are shown for each configuration and compared among themselves. The results indicate the possibility of defining a lazy-wave configuration with smaller buoyancy lengths, reaching 75% of reduction without changing the preconized high safety class. Structural reliability analysis is available to help engineers understand the driving random variables of the problem, supporting the actual scenario of cost reduction for better decision-making based on quantified risk.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jinsheng Wang ◽  
Muhannad Aldosary ◽  
Song Cen ◽  
Chenfeng Li

Purpose Normal transformation is often required in structural reliability analysis to convert the non-normal random variables into independent standard normal variables. The existing normal transformation techniques, for example, Rosenblatt transformation and Nataf transformation, usually require the joint probability density function (PDF) and/or marginal PDFs of non-normal random variables. In practical problems, however, the joint PDF and marginal PDFs are often unknown due to the lack of data while the statistical information is much easier to be expressed in terms of statistical moments and correlation coefficients. This study aims to address this issue, by presenting an alternative normal transformation method that does not require PDFs of the input random variables. Design/methodology/approach The new approach, namely, the Hermite polynomial normal transformation, expresses the normal transformation function in terms of Hermite polynomials and it works with both uncorrelated and correlated random variables. Its application in structural reliability analysis using different methods is thoroughly investigated via a number of carefully designed comparison studies. Findings Comprehensive comparisons are conducted to examine the performance of the proposed Hermite polynomial normal transformation scheme. The results show that the presented approach has comparable accuracy to previous methods and can be obtained in closed-form. Moreover, the new scheme only requires the first four statistical moments and/or the correlation coefficients between random variables, which greatly widen the applicability of normal transformations in practical problems. Originality/value This study interprets the classical polynomial normal transformation method in terms of Hermite polynomials, namely, Hermite polynomial normal transformation, to convert uncorrelated/correlated random variables into standard normal random variables. The new scheme only requires the first four statistical moments to operate, making it particularly suitable for problems that are constraint by limited data. Besides, the extension to correlated cases can easily be achieved with the introducing of the Hermite polynomials. Compared to existing methods, the new scheme is cheap to compute and delivers comparable accuracy.


2013 ◽  
Vol 838-841 ◽  
pp. 360-363 ◽  
Author(s):  
Li Rong Sha ◽  
Yue Yang

In order to predict the failure probability of a complicated structure, the structural responses usually need to be predicted by a numerical procedure, such as FEM method. The response surface method could be used to reduce the computational effort required for reliability analysis. However the conventional response surface method is still time consuming when the number of random variables is large. In this paper, a Fourier orthogonal neural network (FONN)-based response surface method is proposed. In this method, the relationship between the random variables and structural responses is established using FONN models. Then the FONN model is connected to the first order and second moment method (FORM) to predict the failure probability. Numerical example result shows that the proposed approach is efficient and accurate, and is applicable to structural reliability analysis.


Author(s):  
A.A. Solovyova ◽  
◽  
S.A. Solovyov ◽  

Abstract. The reliability of load-bearing structural elements is one of the indicators of structural safety. The article presents methods for steel trusses bars reliability analysis according to the buckling criterion using p-boxes. A p-box consists of two boundary probability distribution functions that form the area of possible distribution functions. Such model used for modeling random variables in conditions of incomplete statistical data by quantity or quality. An algorithm for summing p-boxes of random load models is demonstrated on the example of a probabilistic estimate of the force in the truss bar. The result of reliability analysis using p-boxes is presented in interval form. The use of p-boxes makes it possible to obtain a more cautious assessment of reliability in case of incomplete statistical data. To increase the informativity of the reliability analysis result, it is necessary to obtain more statistical data about random variables in design mathematical models of limit state, which will allow forming p-boxes with narrower boundary distribution functions.


Author(s):  
Sherif Hassanien ◽  
Len Leblanc ◽  
Javier Cuervo ◽  
Karmun Cheng

Reliability engineering science is a mature discipline that has been used extensively in industries such as aviation, nuclear energy, automobiles, and structures. The application of reliability principles (especially structural reliability) in oil and gas transmission pipelines is still an active area of development. The advent of high resolution in-line inspections tools (ILI) facilitates a formal application/utilization of reliability methods in pipeline integrity in order to safely manage deformation, metal loss, and crack threats. At the same time, the massive amount of ILI data, their associated uncertainties, and the availability/accuracy of failure prediction models present a challenge for operators to effectively implement the use of reliability analysis to check the safety of integrity programs within available timeframes. On the other hand, approximate reliability techniques may affect the analysis in terms of both accuracy and precision. In this paper, a Pipeline Integrity Reliability Analysis (PIRA) approach is presented where the sophistication of the reliability analysis is staged into three levels: PIRA levels I, II and III. The three PIRA levels correspond to different representations of integrity uncertainties, uses of available validated/calibrated data, uses of statistical models for operating pressure and resistance random variables, implementation of reliability methods, and consideration of failure modes. Moreover, PIRA levels allow for improved integration of reliability analysis with the existing timelines/stages of traditional integrity programs, such that integrity data are updated as the integrity program progresses. The proposed integrity reliability approach allows for the delivery of safety checks leveraging all types of information available at any given point in time. In addition, the approach provides a full understanding of the strengths and weaknesses of each PIRA level. Pipeline corrosion case studies are provided herein to illustrate how the PIRA Levels can be applied to integrity programs.


2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Jianguo Zhang ◽  
Jiwei Qiu ◽  
Pidong Wang

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.


2011 ◽  
Vol 422 ◽  
pp. 705-715 ◽  
Author(s):  
Patuan Alfon ◽  
Johny W. Soedarsono ◽  
Dedi Priadi ◽  
S Sulistijono

Reliability of equipment of the oil and gas industry is vital, whereas on pipeline transmission system, decreasing the integrity of the pipeline is generally caused by corrosion. Failure that occurs due to corrosion deterioration influenced by the environment within a certain time, and has exceeded the nominal thickness of the pipe so there is a failure. This study used the reliability analysis approach based on modeling corrosion degradation ratio that is determined by the amount of the corrosion rate externally and internally. Using the Weibull probabilistic distribution method, results that the reliability of pipeline will decrease with increasing lifetime. It was identified that internal corrosion has a major contribution to the remaining life of pipeline. From the calculation results obtained by external corrosion has the greatest reliability over 60 years, followed by internal corrosion less than 30 years and the least is by cumulative corrosion which is less than 20 years. From the value of reliability, it can be known probability of failure (POF) which is the anti reliability.


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