Michael Havbro Faber

Inspections and maintenance are essential activities required to ensure the integrity of sub-surface production wells. These activities are critical to the integrity management of the production wells and are important to ensure loss oil and gas production is reduced over the service life at a reduced risk - risk associated with progressive loss of integrity and well cross-section

Modeling of fatigue crack growth plays a key role in risk informed inspection and maintenance planning for fatigue sensitive structural details. Probabilistic models must be available for observable fatigue performances such as crack length and depth, as a function of time. To this end, probabilistic fracture mechanical models are generally formulated and calibrated to provide the

In pipelines, pressure vessels and various other steel structures, the remaining thickness of a corroding ligament can be measured directly and repeatedly over time. Statistical analysis of these measurements is a common approach for estimating the rate of corrosion growth, where the uncertainties associated with the inspection activity are taken into account. An additional source

All engineering structures degrade or become damaged in service to some extent. Information collection activities, such as inspection or structural health monitoring can reduce uncertainty in probabilistic models of structural condition. By linking the information that they provide to the improved integrity management strategies that they facilitate, their expected value can be quantified. This value of information can be obtained using Bayesian decision analysis. In this work an extended value of information model is presented that accounts for the risk associated with exposure to a hazardous environment. By evaluating this risk on the same scale as the risk of structural failure, the relationship between the expected quality of information and the number of staff-hours in a hazardous environment (such as an offshore oil and gas platform) is investigated. An example case study identifies the requirements regarding the precision, bias, and reliability of information from autonomous or remote inspection methods, for them to be considered as an optimal risk management strategy.

Resilient and sustainable traffic infrastructure systems such as bridges play a crucial role in societal economic growth. During the last decades, substantial research has been undertaken for the optimal management of risks associated with extreme events, and the concept of resilience was introduced. The knowledge on the system characteristics affecting resilience is increasing and so is the capability to model and analyze systems. The first step in systems modelling and analysis is to define the system which has not been addressed methodically in the literature. In this contribution, we provide a framework for systems identification in the context of resilience informed management of historic bridges. The proposed approach rests on the indicator-based systems modelling framework of the Joint Committee on Structural Safety (JCSS). With this basis we identify ten resilience indicators which provide information concerning the resilience performances of historic bridges. Finally, we apply the suggested approach through an example.

This paper presents a novel decision analytical framework for systems modeling in the context of the risk-informed integrity management of offshore facilities. Our focus concerns the development of system models representing environmental loads associated with storm events. Appreciating that system models in general serve to facilitate the optimal ranking of decision alternatives, we formulate the problem of systems modeling as an optimization problem to be solved jointly with the ranking of integrity management decision alternatives. Taking offset in recent developments in structure learning and Bayesian regression techniques, a generic approach for the modeling of environmental loads is established, which accommodates for a joint utilization of phenomenological understanding and knowledge contained in databases of observations. In this manner, we provide a framework and corresponding techniques supporting the combination of bottom-up and top-down modeling. Moreover, since phenomenological understanding and analysis of databases may lead to the identification of several competing system models, we include these in the formulation of the optimization problem. The proposed framework and utilized techniques are illustrated in an example. The example considers systems modeling and decision optimization in the context of a possible evacuation of an offshore facility in the face of an emerging storm event.

A novel framework for resilience modeling of wind turbine parks is proposed in support of optimization of decisions on asset integrity management. The concept of resilience originating from natural and social sciences is adapted here to facilitate the joint optimization of decision alternatives related to design, with decision alternatives addressing organizational performance. The generic probabilistic systems representation framework by the Joint Committee on Structural Safety (JCSS) (2008) is utilized to establish a scenario-based modeling of how different types of disturbances may lead to damages and failures of systems and sub-systems of wind turbine parks, together with associated direct and indirect consequences. Special emphasis is directed on the consistent probabilistic representation of the uncertainties and the stochastic and causal dependencies within the wind turbine park system. The framework facilitates the identification of optimal asset integrity management decision alternatives that fulfill given requirements to resilience. The potentials associated with the use of the framework are highlighted by an example considering a wind turbine park with ten identical wind turbines, with each modelled as a system of mechanical, electrical, and structural sub-systems. The resilience performance characteristics of the wind turbine park, such as the expected value of generated service life benefits, the expected value of production down time, and the probability of resilience failure are modelled and quantified such as to support the ranking of decision alternatives relating to the design of the wind turbine sub-systems, the level of organizational preparedness, the percentage of the generated service life benefits to be kept to ensure sufficient economic capacity to deal with future disturbances, and the stock-keeping of essential spare parts.

(2019). 9th IFED forum event on ‘resilient infrastructures – integration of risk and sustainability’. Sustainable and Resilient Infrastructure. Ahead of Print.

Substantial increase in research on sustainability and resilience is changing the traditional disciplinary boundaries of risk assessment and management. To understand the implications of this change and define future strategic directions for risk education, we conduct a comprehensive exploratory study of the knowledge domains encompassing risk, sustainability and resilience between 1990 and 2017. Combining quantitative bibliometric techniques such as term co-occurrence and bibliographic coupling, we show the historical evolution of the knowledge domains of risk, sustainability and resilience on a to-date unprecedented scale, based on 442,171 scientific records. Based on a comprehensive background study involving more than 100 cluster network maps, in the present paper, we illustrate the different disciplinary contributions, important authors, geographic distribution of the research, and the organizations producing the research as well as the extent to which they are integrated into the knowledge domain of risk. A complementary qualitative analysis provides context to the concepts and trends identified in the bibliometric analysis, together with an outlined vision for future education in risk, sustainability and resilience science.

The main objective of the present paper is to suggest guidelines for the improvement of how robustness is treated in future generations of the Eurocodes, namely concerning the design philosophy and the design requirements. It is now widely recognised that robustness has a governing role in attaining sustainable and resilient infrastructures. Without surprise, robustness was identified by the European Commission as one of the key additions to the existing Eurocodes under the presently ongoing revisions. This should be seen as a stimulus to develop updated (or new), rational, accurate, and practical design methodologies and requirements for robustness, extending and enhancing current coverage of robustness in the Eurocodes. This paper starts by reviewing how robustness is treated in the Eurocodes, pin-pointing the limitations of the existing design framework. Subsequently, a performance-based design framework for robustness is proposed that allows designers to determine if a given structure is sufficiently robust. Different levels of sophistication are proposed to cater for different levels of classes of structures. Therefore, the suggested approach enables the best available knowledge and the latest technologies to be applied in a way that is acceptable for practitioners, promoting competitiveness, cost-effectiveness and sustainability in design and innovation.