Search

This paper uncovers a novel component for exchange rate predictability based on the price difference between sovereign credit default swaps denominated in different currencies. This new forecasting variable – the credit-implied risk premium – captures the expected currency depreciation conditional on a severe but rare credit event. Using data for 16 Eurozone countries, we find that the credit-implied risk premium positively forecasts the dollar-euro exchange rate return at various horizons. Moreover, a currency strategy that exploits the informative content of our predictor generates substantial out-of-sample economic value against the na¨ıve random walk benchmark.

Arctic pipelines (PL) are located north of the 60th parallel. The main factors that characterize features of such pipelines are the climatic conditions in their areas of installation. Arctic pipeline routes pass through tundra with dwarf vegetation, marshes, and large areas with permafrost lenses, in watery and swampy areas with unique geological and hydrological conditions. The absolute difference of temperatures ranges from –56 degrees Centigrade in winter to 34 Centigrade in summer; and strong winds with speed over 40 m/s. Under these conditions, reliability and safety assessment of pipelines is associated with many principal difficulties, one of which is the need to take into account the simultaneous action (a combination) of many natural and technological loads on the pipeline infrastructure, which are random by nature and can be adequately described only by stochastic processes. Currently, reliability assessment of such systems is not performed due to lack of valid calculation methods. In this paper a description is given of the first stage of assessing reliability of a pipeline subject to a combination of loads described as random Markov processes. This method, developed by S. A. Timashev in [1], a. k.a. assessment of reliability in the space of loads, assumes the ability of constructing admissible areas in this load space with respect to different limit states. The method is applied to a segment of an above ground arctic oil pipeline with surface corrosion type defects, subjected to a combination (simultaneous action) of four loads: 1) dead weight of the pipe with insulation and oil being pumped, 2) operating pressure, 3) wind load, and 4) exposure to a uniform wall thickness thinning. The pipeline is considered as a continuous multi-bay thin wall cylindrical beam. The pipeline design is performed according to the (conditional) limit state which is reached when the equivalent stresses in pipe wall reach the yield stress of pipe material. The main purpose of the presented work is reliability assessment of PL in the space of load (impacts). At this the dead load of the pipeline structure is considered to be deterministic. The influence of the wind load, uniform corrosion, and operating pressure (OP) are considered to be variables. For them the permissible region is constructed using the above limit state. Арктические трубопроводы находятся к северу от 60?й параллели. Основными факторами, характеризующими особенности таких трубопроводов, являются климатические условия в местах их прокладки. Арктические трассы трубопроводов проходят через тундру с карликовой растительностью, болота и большие территории с вечной мерзлотой, обводненную и заболоченную местность с уникальными геологическими и гидрологическими условиями. Разница температур составляет от –56 зимой до +34 °C в летний период; скорость ветра свыше 40 м/с. В таких условиях оценка надежности и безопасности трубопроводов связана с множеством проблем, одной из которых является необходимость учитывать одновременное воздействие на трубопроводы многих природных и технологических нагрузок, которые носят случайный характер и могут быть адекватно описаны только с помощью случайных процессов. В настоящее время оценка надежности таких систем не выполняется из-за отсутствия научно обоснованных методов расчета. В данной статье описывается первый этап оценки надежности трубопровода при условии описания сочетания нагрузок как случайного процесса Маркова. Этот метод, разработанный С. А. Тимашевым [1], называется методом оценки надежности в пространстве нагрузок и предполагает возможность построения допустимых областей в пространстве нагрузки с учетом различных предельных состояний. Метод применен к сегменту наземного арктического нефтепровода с коррозией поверхности, подверженному комбинации (одновременному действию) четырех нагрузок: 1) собственный вес трубы с изоляцией и перекачиваемой нефти, 2) рабочее давление, 3) ветровая нагрузка и 4) утоньшение стенки. Трубопровод рассматривается как непрерывная многосекционная тонкостенная цилиндрическая балка. Проектирование трубопровода осуществляется по предельному состоянию, которое достигается, когда эквивалентные напряжения в стенке трубы достигают предела текучести материала трубы. Основной целью данной работы является оценка надежности трубопровода в пространстве нагрузок (воздействий). Здесь постоянные нагрузки на трубопровод считаются неизменными. Влияние ветровой нагрузки, равномерной коррозии и рабочее давление считаются переменными. Для них построена допустимая область с учетом описанного выше предельного состояния.

The safety of Generations II and III nuclear power plants relies on the availability of AC power, which is required for decay heat removal. This AC power (designated offsite power) is provided by sources outside the power plant via a grid that is susceptible to both random and induced failures. When offsite power is lost, alternative emergency sources on-site are started to drive the plant's safety systems. If, however, a situation arises where these sources are also unavailable or unable to provide the required power for the entire period the offsite sources are unavailable, a complete loss of power to the safety buses ensues. This phenomenon is known as Station Blackout (SBO), and its severity depends on its duration as well as, the plant's initial status. Consequently, the time-dependent non-recovery probability of AC power is a key parameter in the risk assessment and management of nuclear power plants. In this work, an easy-to-use and generally applicable reliability framework is proposed to model power recovery in station blackout sequences. It employs a load flow technique integrated into an efficient event-driven Monte-Carlo simulation algorithm. The resulting framework quantifies the probability of power recovery as a function of both time and power level, including other relevant indices. It, therefore, serves the purpose of a rational decision support tool in the mitigation of station blackout accidents. The proposed framework is used to analyse station blackouts emanating from grid and switchyard failures at the Maanshan nuclear power plant in Taiwan.

Studying failure scenarios allows one to gain insights into their cause and consequence, providing information for effective mitigation, contingency planning and improving system resilience. A new efficient algorithm is here proposed to solve applications where an expensive-to-evaluate computer model is involved. The algorithms allows to generate the conditional samples for the Subset simulation by representing each random variable by an arbitrary number of hidden variables. The resulting algorithm is very simple yet powerful and it does not required the use of the Markov Chain Monte Carlo method. The proposed algorithm has been implemented in a open source general purpose software, OpenCossan allowing the solution of large scale problems of industrial interest by taking advantages of High Performance Computing facilities. The applicability and flexibility of the proposed approach is shown by solving a number of different problems.

In many engineering applications, the assessment of reliability has to be done within a limited amount of information, which does not allow to use exact values for the distributional hyperparameters. This is achieved defining probability boxes and assessing the reliability computing the failure probability bounds. Probability boxes are often obtained from known probability distribution functions represented by interval hyper-parameters. In the applications, not only it is of interest estimating the failure probability bounds, but it is also required to identify the extreme realizations leading to the estimated bounds. In this paper, we propose a strategy, based on the Kolmogorov-Smirnov test, to identify the parental distribution function that best fit the distribution of extreme realizations, obtained from the minmax propagation. From the results obtained comparing the strategy with a direct search, it has emerged that the proposed method is generally applicable and efficient.

In the automotive industry a significant part of research is dedicated to design and produce better products. The unavoidable presence of uncertainties in manufacturing processes and structural parameters leads to the necessity to develop stochastic models able to correctly represent physical behaviours. This paper presents numerical and experimental investigations on the effects of the fitting process on the stress/strain map of assembled automotive rim-disk systems. Different strategies of geometrical decomposition are used to condense large volumes of data by retaining essential information for the whole design process including not only manufacturing pre-stresses and operational loads but also dimensional tolerances of mating parts by means of a probabilistic model. Efficient approaches are used to identify the relative importance of input factors on the output uncertainties. A real test case of a wheel assembly is presented and discussed.

In order to investigate the possible association between mast cells (MCs) and the fibrous plaque of La Peyronie's disease, the number of MCs in normal penile tissue and in the fibrous plaque was determined.The control group consisted of 5 total and 3 partial penectomies with no fibrotic lesions, while the study group consisted of 23 excisional biopsies from cases of La Peyronie's disease dating back to at least 2 years earlier and with no signs of activity. The biopsies included tissues from the tunica albuginea (TA), the areolar tissue (Br) between the tunica and the erectile tissue (CC) and from the latter. The number of MCs was counted with the aid of an image analysis program following staining the antibody antitryptase.In the cases of La Peyronie's disease the number of MCs/mm(2) was significantly higher in the TA and Br but lower in the CC. The MCs were related to fibroblasts and vasculonervous channels in the TA, and were concentrated around the fibrous plaques and granulation tissue between the TA and BR and between the latter and the CC.Our data indicate that MCs have a role in the genesis of the fibrous plaque in the TA and in the persistent inflammation in the Br. Medical treatment aimed at repressing MC activation and proliferation locally might be useful in La Peyronie's disease.

The development process of complex technical products of the last years shows an increasing amount of sensors, electronic control units, data logging and monitoring systems within consumer goods (e.g. automobiles, washing machines) and industrial goods (e.g. machine tools, manufacturing sys-tems). In many cases, the main goal of data logging is monitoring, controlling and optimisation of the product functionalities within the usage phase. A further aim is the fulfilment of the process capability of manufacturing processes. Therefore, the layout of the concept of operating data logging and monitoring systems—especially operating data (mainly type, volume, and format) as well as hardware (like sensors and storage)-is designed by the development engineer within the product concept development phase. This paper discusses challenges, requirements and approaches for future conceptual design of operating data logging concepts of technical products related to reliability engineering. Base of operations is the state of art. Based on that, the concept for operating data logging within a monitoring system is shown. The concept draft is subdivided in three parts which are divided as follows: part one deals with data analytics, part two contains data requirements, and part three focuses on hardware requirements. The presented research study was worked out on the international research platform “Computational Reliability Engineering in Product Development and Manufacturing (CRE) – 2017” and contains contributions of universities, institutes and original equipment manufacturers of industrial nations: Germany, United Kingdom, Japan, Turkey and France.

It is essential to conduct a reliability analysis of systems with multiple types of components, and deal with the uncertainties within the components failure time distribution. Moreover, finding the most "critical" component in the system at a certain time facilitates a risk management. In this paper, we introduce the survival signature into a real world hydro power plant system and solve the epistemic uncertainties in the component's failure time distribution. By implementing a relative importance index for each component, we can derive the reliability trend of the system depending on a component failure. The results show that the survival signature used on reliability analysis can help us deal with real world systems with more than one component type as well as to get bounds on system responses concerning epistemic uncertainties.

Remarkable advances in engineering and system controls in recent times and the consequent development of state-of-the-art technologies are clearly resulting in economic, environmental and safety benefits to the society. Latest disasters, however, put human error in the glare of the media spotlight. The February 2016 train collision in southern Bavaria, Germany, which took 11 lives and left more than 90 people injured, is one of several examples where human errors appear to have played a significant role in a major accident. In this emblematic case, the railway system had multiple safety barriers in place, such as an automatic braking system if a train crosses a stop signal, but the track controller had reportedly disabled it. When he realised the error and tried to warn the drivers, it was too late (BBC, 2016).

In recent years, the system signature has been recognized as an important tool to quantify the reliability of systems consist of independent and identically distributed (iid) or exchangeable components with respect the random failure times. System signature separates the system structure from the component probabilistic failure distribution. However, when it is adopted to solve a complex system with more than one component type, it requires the computation of the probabilities of all possible different ordering statistics of each component failure lifetime distributions, which is often an intractable procedure.

The harnessing of nuclear energy as means to provide an alternative source of energy has helped provide numerous benefits in today's world such as cheap electricity and reduced carbon emissions. However, the use of such technology comes with its risks as history would point us to the Chernobyl nuclear reactor disaster, Three-mile Island Accident, and the most recent Fukushima-Daiichi catastrophe. With the current issue of global warming, the increased in demand for electricity world-wide, and the strong consideration by many countries in adopting nuclear power, this brings an even greater need to look into probabilistic safety assessment methods to quantify the risks associated with nuclear power plants. This conference paper seeks to apply the probabilistic concepts of statistical dependence of events and logical gate theory to transform a Fault-Tree model into a credal network to perform probabilistic safety assessment. The so called Fault-tree to Credal network conversion technique adopts probabilistic intervals to represent the imprecise state of the components of complex systems as well as allowing perform prediction and diagnostic analyses, differently from the Fault-Tree analysis. The imprecision is referred here as the epistemic uncertainty due to the lack of information or inconsistent data. In the scope of risk assessments, this model allows for the study of the dependability of the elements in the system and analyse the outcomes of different possible scenarios with its associated uncertainty. The Fault-tree to credal network conversion method is applied to produce a probability model for safety assessment of the reactor core system within the Three-Mile Island nuclear reactor as it is the critical system associated with loss of coolant accidents. This case study allows to show the capabilities of Fault-tree to credal network conversion.

Rapid technological development, wireless communication, and monitoring, growing environmental awareness, alternative fuels, and harsher regulations are continuously pressuring maritime transportation and shipbuilding. The maritime sector is exploring ways to reduce cost and emissions but at the same time to increase safety and energy efficiency. Autonomous shipping is an emerging topic, where technical, economic, safety, and environmental aspects are still not mature enough to significantly increase the percentage of autonomous vessels in the global fleet. The reduced crew onboard brings savings and a lower risk of human-induced errors that can lead to human casualties and environmental disasters. However, autonomous vessels monitored from the shore require a high-quality and reliable communication system. The technologies needed for autonomous navigation already exist and it is necessary to find the optimal way to combine their safety, reliability, feasibility, and cost- effectiveness. Short-sea shipping is an ideal candidate for developing and testing new technologies due to shorter routes, low energy demand, and frequent port calls. The Croatian part of the Adriatic coastline with numerous islands and developed tourism activity is extremely sensitive to congestion and marine pollution. This paper presents the analysis of Croatian maritime accident reports to assess whether the accident would have happened if the ship had been autonomous, and once the accident had happened - would its consequences have been different.

Maintenance of structures and infrastructures is of increasing importance in order to reach acceptable level of safety despite the unavoidable uncertainty, and the economic efforts have to be reasonable. These two goals represent competing objectives in an overall optimization of very complex system and structure, which involve significant uncertainties. In fact, all civil engineering structures and engineering systems are subjected to degradation by fatigue cracks and corrosion due to varying loads. When the cracks propagate or corrosion grows, the structural system accumulates damage thereby leading to serviceability loss and eventual collapse. These failures can be prevented by appropriate maintenance scheduling and repair, even in the presence of uncertainties of various nature and scale, leading to a reduction in fluctuations and changes of structural and environmental parameters and conditions in the models describing the processes involved in fatigue cracks and corrosion growth. Degradation models used to predict the future state of components often involve simplifications and assumptions to compensate a lack of data, imprecision and vagueness, which cannot be ignored. To overcome these issues, the imprecise probabilities framework and markovian approach are proposed for performing reliability analysis, decision-making, and risk-based design and maintenance. It is shown how these approaches can improve the current practise based on models: B31G, Modified B31G, DNV-101 and Shell-92 failure pressure models. The reliability assessment is performed by taking into account the simultaneous action of many natural and technological loads. These loads are random by nature and can be adequately described only by stochastic processes; which are not performed due to lack of valid calculation methods. This methodology has been applied to study the reliability of arctic pipeline infrastructure. Finally, a robust and efficient probabilistic framework for optimal inspection and maintenance schedule selection for corroded pipelines and fatigue cracks in bridges is presented. Optimal solution is obtained through only one reliability assessment removing huge computational cost of the reliability-base optimization approach and making the analysis of industrial size problem feasible.

This thesis applies agency theory to design risk regulatory policies in the implementation of sustainable sea defences. The aim is to investigate methods to reduce the probability of an accident inflicted on the society by resolving a downstream and an upstream moral hazard problem existing in engineering problems with an emphasis on the construction of sustainable sea defences. The risk regulation aims at reducing the probability of damage cost associated with flooding by enhancing an operator's safety operational procedures. It is defined by three policies; a safety design, a transfer payment, and a fine. In the downstream moral hazard between an operator and a regulator, a risk neutral operator under full liability will implement a sea defence which is optimal from the regulator's point of view when a fine is set equal to damage cost without a cost for the regulator. However, if the operator has limited assets to cover the damage cost, a cap on the operator's fine is placed to take into account that an operator may default if damage costs are too high. Limiting the responsibility of the operator in case of an accident decreases the strength of the incentive mechanism leading to the implementation of a sea defence below the socially optimum. This second best height of the sea defence involves an informational cost to the society in the form of a liability rent to guarantee the participation of the operator in the engineering project. The more we make the operator liable for the damage cost, the higher the liability rent. The society faces a trade off between liability rent and residual risk. The higher the residual risk, the lower the liability rent. Unlike the limited liability case, an operator with averse attitude to uncertain payoffs will implement a sea defence higher than a risk neutral operator in order to reduce the weight on the upper extreme values of the tail of the fine. This is because the marginal fine decreases under risk aversion. Similarly to the limited liability case, the implementation of a second best height of the sea defence is not free for the society. The society will have to compensate the operator for participating in the project in the presence of uncertain payoffs. This compensation takes the form of a risk premium and is subject to the risk coefficient and the variance of the damage cost distribution. Due to the lack of regulatory quality and independence, a pro-industry regulator and a government may have conflicting interest about the fine cap to impose to the operator. While the regulator prefers a higher fine cap to induce a higher liability rent, the government seeks to impose a lower fine cap. The government faces a trade off problem between how much discretion should be given up and how much expert information should be used from the regulator. In the case when the government observes that any of the fine cap choices available to the regulator is higher than its ex-ante choice of the fine cap, no discretion will be granted because the cost to the society outweighs the benefits of using the regulator's expertise. Nevertheless, when the government observes that some of the fine cap choices available to the regulator are lower than its ex-ante choice of the fine cap some level of discretion can be granted. The limit on the fine caps that the regulator can announce is determined by how much the regulator is biased towards the interests of the nuclear industry. When the regulator's range of fine caps is optimally restricted, the objectives of the regulator and the operator will be aligned by encouraging the regulator to choose a fine cap that will not exceed the optimal fine cap of the government.