99,254 research outputs found

    Optimal Inspection and Maintenance Planning for Deteriorating Structural Components through Dynamic Bayesian Networks and Markov Decision Processes

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    Civil and maritime engineering systems, among others, from bridges to offshore platforms and wind turbines, must be efficiently managed as they are exposed to deterioration mechanisms throughout their operational life, such as fatigue or corrosion. Identifying optimal inspection and maintenance policies demands the solution of a complex sequential decision-making problem under uncertainty, with the main objective of efficiently controlling the risk associated with structural failures. Addressing this complexity, risk-based inspection planning methodologies, supported often by dynamic Bayesian networks, evaluate a set of pre-defined heuristic decision rules to reasonably simplify the decision problem. However, the resulting policies may be compromised by the limited space considered in the definition of the decision rules. Avoiding this limitation, Partially Observable Markov Decision Processes (POMDPs) provide a principled mathematical methodology for stochastic optimal control under uncertain action outcomes and observations, in which the optimal actions are prescribed as a function of the entire, dynamically updated, state probability distribution. In this paper, we combine dynamic Bayesian networks with POMDPs in a joint framework for optimal inspection and maintenance planning, and we provide the formulation for developing both infinite and finite horizon POMDPs in a structural reliability context. The proposed methodology is implemented and tested for the case of a structural component subject to fatigue deterioration, demonstrating the capability of state-of-the-art point-based POMDP solvers for solving the underlying planning optimization problem. Within the numerical experiments, POMDP and heuristic-based policies are thoroughly compared, and results showcase that POMDPs achieve substantially lower costs as compared to their counterparts, even for traditional problem settings

    Monitoring of Critical Metallic Assets in Oil and Gas Industry Using Ultrasonic Guided Waves

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    This chapter presents advancements in structural health monitoring (SHM) using ultrasonic guided waves (UGW) technology for metallic structures to support their integrity and maintenance management. The focus is on pipelines and storage tanks, which are critical assets in the Oil and Gas industry, whose operational conditions can greatly accelerate damage mechanisms. Conventional routine inspections are both costly and time consuming and affect the plant reliability and availability. These operational and economic disadvantages have led to development of SHM systems which can be permanently installed on these critical structures to provide information about developing damage and optimise maintenance planning and ensure structural integrity. These technology advancements enable inspection without interruption to operations, and generate diagnosis and prognosis data for condition-based maintenance, hence increasing safety and operational efficiency. The fundamentals, architecture and development of such SHM systems for pipes and above ground storage tanks are described here

    Life-cycle of fatigue sensitive structures under uncertainty

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    Fatigue is the one of the main contributors to problems related to structural safety of civil and marine structures. Life-cycle management (LCM) techniques considering various uncertainties can be used to predict the safe service life of fatigue sensitive structures, plan for their future inspections and support the decision making process regarding maintenance and repair actions. This paper provides a brief overview of the LCM of fatigue sensitive civil and marine structures under uncertainty. Probabilistic performance prediction, inspection scheduling and maintenance optimization for such structures are discussed

    Condition monitoring benefit for offshore wind turbines

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    As more offshore wind parks are commissioned, the focus will inevitably shift from a planning, construction and warranty focus to an operation, maintenance and investment payback focus. In this latter case, both short-term risks associated with wind turbine component assemblies, and longterm risks related to structural integrity of the support structure, are highly important. This research focuses on the role of condition monitoring to lower costs associated with short-term reliability and long-term asset integrity. This enables comparative estimates of life cycle costs and reduction in uncertainty, both of which are of value to investors

    A multi-objective framework for the optimisation of life-cycle costs of wind turbines

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    Classes of decision analysis

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    The ultimate task of an engineer consists of developing a consistent decision procedure for the planning, design, construction and use and management of a project. Moreover, the utility over the entire lifetime of the project should be maximized, considering requirements with respect to safety of individuals and the environment as specified in regulations. Due to the fact that the information with respect to design parameters is usually incomplete or uncertain, decisions are made under uncertainty. In order to cope with this, Bayesian statistical decision theory can be used to incorporate objective as well as subjective information (e.g. engineering judgement). In this factsheet, the decision tree is presented and answers are given for questions on how new data can be combined with prior probabilities that have been assigned, and whether it is beneficial or not to collect more information before the final decision is made. Decision making based on prior analysis and posterior analysis is briefly explained. Pre-posterior analysis is considered in more detail and the Value of Information (VoI) is defined

    The safety case and the lessons learned for the reliability and maintainability case

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    This paper examine the safety case and the lessons learned for the reliability and maintainability case

    Risk based bridge data collection and asset management and the role of structural health monitoring

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    Report on visit to four North American airlines

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    The object of the visits was to discuss the current state-of-the-art with the Engineering Departments of several North American airlines which were known to be leading the field in the application of certain advanced techniques. In the limited time available it was decided to confine the talks mainly to those topics on which the chosen operators were known to have had unique experience. This note is presented in chronological sequence and is only intended to be a record of the information gathered; no derivations, or comparisons with other operators, are made. United Air Lines were visited first and reliability programmes are detailed, although the application of critical path techniques to aircraft and engine overhaul is summarised. Continental Air Lines are noted for their use of the continuous maintenance philosophy, and this is reported next. The third visit was to Air Canada where talks ranged from the applications of operations research and electronic data processing (EDP) techniques to aircraft evaluation procedures. Finally the PanAm aircraft system reliability programme is reviewed, together with a note on their general LDP engineering and maintenance activities. A bibliography is given, although it should be appreciated that some of the items listed contain information which may be commercially secure
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