Modeling of pipeline corrosion degradation mechanism with a Lévy Process based on ILI (In-Line) inspections

International audienceIn pipelines, one of the primary testing procedures used to identify the e↵ects and evolution of corrosion over time is through In-Line Inspections (ILI). ILI inspections provide detailed information regarding the inner and outer pipeline condition based on the remaining wall thickness. Based on this information, di↵erent approaches have been proposed to predict the degradation extent of the defects detected. However, these predictions are subject of uncertainties due to the inspection tool and the degradation process that poses some challenges for assessing an entire pipeline within the timespan between two inspections. To address this problem, ILI data was used to formulate a degradation model for steel-pipe degradation based on a Mixed Lévy Process. The model combines a Gamma and Compound Poisson Processes aimed for a better description of the degradation reported by the ILI data. The model seeks to estimate corrosion lifetime distribution and the mean time to failure (MTTF) more accurately. The model was tested on an actual segment of an oil pipeline, and the results have been used to support a preventive maintenance program

Risk-based evaluation of pitting corrosion in process facilities

Pitting is one of the most challenging forms of corrosion to study and model due to complex pit behavior. Pitting can occur in different engineering alloys and can lead to catastrophic consequences. Pits are usually latent or difficult-to-detect and resulting degradation often causes in-service failure of process equipment. Therefore, the ability to predict pit behavior is key to design and maintenance of assets. In particular, pitting corrosion is a significant challenge in marine environments and offshore operations due to remoteness of operations and hidden damage under insulations. Thus, the ability to assess risk and estimate remaining life of assets affected by pitting corrosion is necessary for timely maintenance and safe operation of assets. This thesis proposes a methodology to assess and dynamically update the risk of pressurized components affected by pitting corrosion. To take into consideration the time-dependent growth of pits, the application of non-homogenous Markov process is proposed to model the maximum pit depth. The integration of the developed maximum pit model into a pressureresistance model is proposed to predict the failure probability of affected components. An economic consequence analysis model is developed to estimate both business and accidental losses due to failure of the affected component. Then, risk is estimated by integrating models developed for probability of failure and associated consequences. The application of Bayesian analysis is proposed to update estimated risk as new inspection data gets available and also as economic condition of the process evolves. This work also proposes a risk management strategy including corrosion prevention, control and monitoring measures to make effective decision related to pitting corrosion. The application of the proposed methods is demonstrated using different case studies

A Framework for Remaining Useful Life Prediction of Steam Turbines Applicable to Various Data Types

학위논문 (박사)-- 서울대학교 대학원 : 공과대학 기계항공공학부, 2018. 8. 윤병동.최근 발전사간 경쟁이 치열해짐에 따라 발전 산업에서는 운전 비용을 절감하고 핵심 설비의 수명을 연장하는데 많은 노력을 기울이고 있다. 한편 운전 시간이 설계 수명에 근접함에 따라 증기터빈과 같은 핵심 설비의 열화가 가속되고 크고 작은 고장이 많이 발생하고 있다. 가속화된 열화나 예기치 못한 손상으로 발전소가 정지되면 막대한 경제적 손실과 국가적인 재해를 야기할 수 있다. 이에 따라 안정적인 설비의 운전을 가능케 하는 다양한 기술들이 개발되고 있으며 최근 들어 더욱 많은 각광을 받고 있는 시스템 건전성 관리 기술은 효과적으로 시스템의 상태를 감지, 진단, 그리고 예지하여 관리자가 유지 보수에 있어 필요한 결정을 내릴 수 있도록 도와준다. 특히 최적 유지정비 관점에서 적합한 방법론을 통해 예측된 잔존유효수명은 설비 수명에 정확한 정보를 기반으로 효과적인 유지 정비를 가능하게 한다. 증기 터빈은 발전소 수명을 결정하는 핵심 설비이기 때문에 발전소의 최적 운영을 위해 활용 가능한 정보를 최대한 활용하여 운전 중인 증기터빈의 잔존유효수명을 정확하게 예측하는 방법론의 개발이 매우 중요하다. 이에 본 박사학위 논문에서는 (1) 증기 터빈에 대한 고장모드영향분석과 연계한 잔존유효수명 예측 프레임워크, 그리고 이를 바탕으로 한 (2) 손상 성장 모델 (데이터 기반 방법론), (3) 크리프-피로 손상 상호작용을 고려한 모드 의존 손상 모델 (모델 기반 방법론) 등의 연구를 제안한다. 첫 번째 연구에서는 고장모드영향분석에 기반하여 증기터빈의 잔존유효수명을 예측하는 프레임워크를 제안한다. 프레임워크는 측정된 데이터에 기반한 방법론과 손상 모델에 기반한 방법론으로 구성된다. 오프라인이나 온라인과 같이 다른 목적으로 잔존유효수명을 예측할 때 불확실도를 평가하고 감소시킬 수 있도록 불확실도를 정량화하는 절차를 포함하였다. 두 번째 연구에서는 데이터 기반 방법론을 이용해 증기터빈의 잔존유효수명을 평가할 수 있는 손상 성장 모델의 개발을 목적으로 한다. 잔존유효수명은 손상 인자로부터 손상 성장 모델을 연계하여 예측한다. 현장에서 측정된 경도값으로부터 손상인자의 확률분포를 추정하고 손상의 성장을 평가할 때 불확실도를 고려하기 위해 베이지안 방법을 사용하였다. 제안된 손상 성장 모델을 통해 기저부하나 첨두부하에 사용되는 증기터빈의 종류에 상관없이 정확한 잔존유효수명 예측이 가능하다는 것을 검증하였다. 마지막 연구에서는 모델 기반 방법론을 이용해 크리프와 피로 상호작용이 고려된 모드 기반 손상모델을 제안하였다. 손상기구에 따른 재료 데이터를 통계적 기법으로 분석하고 실 증기터빈의 형상 정보와 운전정보를 이용해 기저부하와 첨두부하 터빈을 대상으로 크리프 및 피로 손상율을 계산하였다. 각각 계산된 손상율 결과와 크리프-피로 상호작용 모델을 통해 운전모드 또는 손상모드에 따른 증기터빈에서의 크리프와 피로 상호작용 효과를 분석하였다. Abstract i List of Tables viii List of Figures x Nomenclatures xiv Chapter 1 Introduction 1 1.1 Motivation 1 1.2 Research Scope and Overview 4 1.3 Dissertation Layout 7 Chapter 2 Literature Review 8 2.1 Life Prediction Methodologies of Steam Turbine 8 2.1.1 Destructive Method 11 2.1.2 Non-destructive Method 11 2.1.3 Analytical Method 13 2.1.4 Summary and Discussion 13 2.2 Data-driven and Model-based Life Prediction 15 2.2.1 Data-driven Approach 21 2.2.2 Model-based Approach 21 2.3 Empirical Model-based Life Prediction 15 2.3.1 On-site Data Measurement 18 2.3.2 Bayesian Inference 19 2.3.3 Summary and Discussion 20 2.4 Damage Model-based Life Prediction 21 2.4.1 Creep or Fatigue Damage Model Analysis 22 2.4.2 Creep-Fatigue Damage Summation Model analysis 23 2.4.3 Summary and Discussion 27 Chapter 3 A Practical RUL Prediction Framework of Steam Turbine with FMEA Analysis 28 3.1 Overview of Steam Turbines 28 3.2 FMEA for Steam Turbines 31 3.3 A Framework for RUL Prediction of Steam Turbine 34 3.4 Summay and Discussion 38 Chapter 4 A Bayesian Approach for RUL Prediction of Steam Turbines with Damage Growth Model 39 4.1 Characteristics of On-site Measurement Data 40 4.2 Measured Data based Damage Indices 46 4.3 Damage Growth Model using Sporadically Measured and Heterogeneous On-site Data 51 4.3.1 Proposed Damage Growth Model 51 4.3.2 Bayesian Updating Scheme of the Damage Growth Model 58 4.3.3 Damage Growth Model Updating 60 4.4 Predicting the Remaining Useful Life(RUL) of Steam Turbines 68 4.4.1 Damage Threshold 68 4.4.2 Validation of the Proposed Damage Growth Model 72 4.4.3 RUL Prediction 74 4.5 Summary and Discussion 78 Chapter 5 Mode-Dependent Damage Assessment for Steam Turbines with Creep-Fatigue Interaction Model 80 5.1 Dominant Damage Mechanisms of Steam Turbine 82 5.2 Typical Opeation Data of Steam Turbine 83 5.3 Dominant Damage Model of Steam Turbine 86 5.3.1 Creep Damage Model 86 5.3.2 Fatigue Damage Model 88 5.3.3 Creep-Fatigue Damage Model 90 5.4 Statiatical Damage Calculation for Steam Turbine 91 5.4.1 Statistical Characterization of Creep-Fatigue Damage Data 91 5.4.2 Creep Damage Calculation with Steady State Stress 94 5.4.3 Fatigue Damage Calculation with Transient Strain 95 5.5 Mode-Dependent Multiple Damage Interaction Model 100 5.5.1 Estimation of Damage Interaction Parameters 100 5.5.2 Validation of Mode-Dependent Model 101 5.5.3 Effect of Mode-dependence Effects on Multiple Damage 104 5.5.4 Case Study : Risk Assessment 108 5.6 Summary and Discussion 111 Chapter 6 Conclusions 113 6.1 Contributions and Impacts 113 6.2 Suggestions for Future Research 116 References 119 국문 초록 142Docto

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen