Probabilistic Modeling of Failure

Failure of a system or a component of a system is and has been a major concern to systems’ operators and owners. Failure could be traced back to different causes and may take different forms and shapes. It may result from software malfunction, hardware degraded performance, human error, sabotage, environmental as well as other external factors. There are various techniques found in the literature that can assist in the analysis of failure. These techniques comprise deterministic and probabilistic techniques. Deterministic techniques ignore the variability and uncertainties of the variables in the analysis which may lead to unsatisfactory and inaccurate results. While probabilistic techniques produce accurate and an all-inclusive result because they incorporate the variabilities and uncertainties in the analysis. The focus of this chapter is to present commonly used probabilistic failure analysis techniques and their mathematical derivations. Examples to enhance the understanding of the concept of failure analysis are also presented

Probabilistic Modeling of Failure: Nonlinear Approximation

The failure of systems to meet the specified requirements may have adverse effects on their integrity and reliability. The systems could be mechanical, electrical, structural, telecommunications, or electronic that are designed and built to satisfy certain technical specifications and operational requirements. Failure does not necessarily mean the occurrence of a disaster or damage to the system, but also the degraded performance of such systems is considered a failure. One of the essential indicators of the performance and reliability of a system is the probability of failure which is computed by probabilistic methods. One of these methods is the first-order reliability method (FORM). Using FORM to estimate the probability of failure of systems having a nonlinear or a higher-order performance function may provide inaccurate results that may lead to misleading conclusions. To resolve this issue, the second-order reliability method (SORM) is recommended to estimate the probability of failure. This chapter presents commonly used probabilistic approximation methods to estimate the probability of failure for nonlinear performance functions. Illustrative examples to demonstrate the application of these methods are provided at the end of the chapter

The interaction between lysyl-lysine and arginine in the neonatal Yucatan miniature pig small intestine

Using an in situ intestinal perfusion model in sow-fed neonatal piglets, our objectives were to determine whether the lysyl-lysine enhanced arginine absorption led to a functional benefit of greater mucosal protein synthesis, and whether it was mediated through the mTOR pathway. Three segments of piglet’s small intestine were isolated, and were continuously perfused with: arginine, arginine + lysyl-lysine, or arginine + L-lysine. At 90 min, buffers containing the same amino acids plus phenylalanine were initiated for 30 min to measure mucosal protein synthesis. Six additional piglets underwent the identical protocol, but one hour before the intestinal perfusion, rapamycin was delivered intravenously. Co-perfusing arginine with lysyl-lysine resulted in greater arginine uptake, and higher mucosal protein synthesis. Moreover, both protein synthesis and the phosphorylation of mTOR were inhibited by rapamycin. Thus, lysyl-lysine led to a greater mucosal protein synthesis, which was likely mediated through enhanced arginine absorption

Ultrasonic guided waves applications for locating and quantifying pipelines defects

On-line Health Monitoring of industrial structures in particular the oil and gas transporting system such as pipelines is of great importance to the reliability and survivability of the plant. In this research the propagation of Ultrasonic Guided Waves as a tool to condition monitoring of the pipes was investigated. Also, under this research the Kirchhoff flaw approximation model was modified to provide an estimation of the size and location of flaws that may exist along the pipe. The modified model and the dispersion curves generated by the Ultrasonic Waves using PCDISP software can provide assessment of the location and extent of the flaw. Several simulation trials were performed using Matlab to validate the feasibility and applicability of the modified model and the results indicate that this model can accurately estimate the size and location of the flaws that exist in the pipe

Probabilistic methods for assessing the performance of offshore pipelines condition monitoring systems

Oil and gas condition monitoring systems play a major role in maintaining the operability, integrity, and reliability of oil and gas infrastructure. A leak detection monitoring system (LDS) constitutes an important member of these systems. The main function of this system is to detect the occurrence and location of hydrocarbon leakages in a timely manner before the leaked products can cause a devastating effect on production, health, safety, and the environment. To ensure the continuity of operation and the safety of personnel as well as the environment, this system should be assessed on a regular basis. Traditionally, a deterministic approach is adopted to assess such systems. A deterministic assessment does not consider uncertainties or random variabilities that are inherent in the performance parameters. Thus, it produces results that may not characterize the actual situation of the system or its circumstances. To tackle this issue, it is proposed to use a probabilistic approach to assess the performance since it allows the incorporation of any uncertainties or random variabilities that may exist in the assessment. Hence, a quantifiable probability of failure can be estimated. Once the probability and consequences of failure become known, risk can be easily estimated. A complete assessment of risk cannot by obtained without incorporating the probability of failure of the pipeline itself. The major research activities include, formulation of the LDS probability of detection and false detection for a single point along the oil and gas transport component; development of a probabilistic performance assessment scheme for the entire LDS along the oil and gas transport component using a limit-state approach; application of probabilistic methods to determine the probability of failure and the remaining life of the oil and gas transport component and development of a risk-based assessment methodology to determine the risk associated with the simultaneous failure of the LDS and the oil and gas transport component (i.e., pipelines). These major research components establish the foundation for an overall evaluation scheme that can be used to provide an up-to-date assessment of the oil and gas transport components and the LDS. The outcome of the assessment can serve as a basis for a well-informed decision-making process that enables the decision makers to determine the best strategy for assessing and maintaining the integrity of the evaluated systems

Probability of detection and false detection for subsea leak detection systems: model and analysis

Ensuring the integrity of subsea process components is one of the primary business objectives of the oil and gas industry. Leak detection system (LDS) is one type of system used to safeguard reliability of a pipeline. Different types of LDS use different technologies for detecting and locating leaks in pipelines. One technology, which is gaining wide acceptance by the industry, is the fiber opticbased LDS. This technology has great potential for subsea pipeline applications. It is the most suited for underwater applications due to the ease of installation and reliable sensing capabilities. Having pipelines underwater in the deep sea presents a great challenge and a potential threat to the environment and operation. Thus, there is a need to have a reliable and effective system to provide the assurances that the monitored subsea pipeline is safe and functioning as per operating conditions. Two important performance parameters that are of concern to operators are the probability of detection and probability of false alarm. This paper presents a probabilistic formulation of the probability of detection and probability of false detection for a fiber optic-based LDS.Peer reviewed: YesNRC publication: Ye

Risk assessment of offshore crude oil pipeline failure

Failure of Leak Detection System (LDS) to detect pipeline leakages or ruptures may result in drastic consequences that could lead to excessive financial losses. To minimize the occurrence of such failure, the functionality of the LDS and the integrity of the pipeline should be assessed on a priority basis. This paper presents an integrated risk-based assessment scheme to predict the failure and the failure consequences of offshore crude oil pipelines. To estimate risk, two important quantities have to be determined, the joint probability of failure of the pipeline and its LDS and the consequences of failure. Consequences incorporate the financial losses associated with environmental damage, oil spill cleanup and lost production. The assessment provides an estimate of the risk in monetary value and determines whether the estimated risk exceeds a predefined target risk. Moreover, the critical year for the asset can be determined. In essence, the outcome of the assessment facilitates an informed decision-making about the future of the asset.Peer reviewed: YesNRC publication: Ye