Probabilistic fatigue design of reinforced-concrete wind turbine foundations

Probabilistic fatigue design of wind turbines is a new approach to optimize the design by reducing in a reliability- and cost-optimal way the amount of materials used for the construction, ultimately reducing the cost of energy. This paper presents such a probabilistic framework for reliability assessment of onshore wind turbine foundations with aim to optimize the design. This framework includes stochastic modelling of fatigue strength based on a large database of test results, stochastic modelling of the fatigue load (wind), modelling of the related epistemic and aleatory uncertainties, along with a case study showing how optimization could be exercised using the reliability-based framework.Current work is carried out under the project INFRASTAR (infrastar.eu), which has received funding from the European Unions Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 676139. The grant is gratefully acknowledged

Uncertainty Modeling and Fatigue Reliability Assessment of Offshore Wind Turbine Concrete Structures

In this paper, the propagation of uncertainties related to structural, environmental and fatigue damage model parameters is evaluated by performing Monte Carlo fatigue simulations of a concrete foundation for offshore wind turbines. Concrete fatigue damage models are formulated based on the S-N approach, where the resistance model uncertainty is calibrated against experimental fatigue tests. Results indicate that the resistance model uncertainty governs the concrete FLS assessment. This underlines the importance of improving estimates of model uncertainty by conducting experimental fatigue tests at lower stress cycle amplitudes and at different mean stress levels.This is the postprint version of the article published in the International Journal of Offshore and Polar Engineering (ISSN 1053-5381), Vol. 29, No. 2, June 2019, pp. 165–171; https://doi.org/10.17736/ijope.2019.il5

Role of oral foci in systemic diseases: An update

Background: A current research disagreement middles about a theorized connection between chronic oral infections and the progress of adverse systemic health conditions. However, the gap between general and dental medicine is quickly closing, due to significant findings supporting the association between dental infections and systemic conditions such as cardiovascular diseases, type 2 diabetes mellitus, respiratory diseases, stroke, adverse pregnancy outcomes, osteoporosis, renal diseases, and gastrointestinal diseases. Relentless efforts have brought light on numerous advances in illuminating their etiopathological links. However, the majority of data about possible role or interlink between the infection and systemic disease is available in the form of case report or summary. As case reports are not the acceptable to many indexed scientific magazines, many these findings undergo unnoticed to researchers. The currently minimal accessible data provide only an indication of the actuality. Aim: This article highlights the Role of oral foci in systemic diseases. Conclusion: There is need of sincere work efforts on genetic relatedness of organisms, rather than their phenotypes, sophisticated sampling, detection, and analytical techniques to create the associations. To give insight to recent apprises of different systemic diseases as a consequence of primary oral infections and the pathogenesis link. The odontogenic bacteremia is likely to cause systemic and end organ infections, but such infections can easily resist by body defenses. It is important that role of good oral health and the risks associated with poor oral health should told to the individuals. Clinical significance: Dentists and medical practitioners should work together to provide comprehensive health care, thereby reducing the morbidity and mortality associated with oral infections

Probabilistic design of wind turbine concrete components subject to fatigue

Wind turbines contribute significantly to the production of renewable energy. In order to minimize the Levelized Cost of Energy (LCOE) the cost of the wind turbine incl. tower and the foundation should be as low as possible but at the same time have a sufficient reliability. In this paper, focus is on wind turbine components which may be made of concrete such as tower and foundation. In traditional deterministic design based on design standards, partial safety factors are applied to obtain the design values. Improved design with a consistent reliability level for all components can be obtained by use of probabilistic design methods with explicit consideration of uncertainties connected to loads, strengths and numerical models / calculation methods. Wind turbines are basically designed based on IEC 61400-1:2019 which indicates a target reliability level that can be used for probabilistic design. In this paper, probabilistic fatigue models for concrete are presented based on the fatigue models in fib Model Code 2010, but extended within a stochastic modelling using a large dataset of fatigue tests. Generic uncertainty models for the fatigue load are applied. It is illustrated how reliability analyses can be performed within a probabilistic design framework

Comparative investigation of uncertainty analysis with different methodologies on fatigue data of rebars

Stochastic modeling of uncertainties for fatigue strength parameters is vital step as basis for reliability analyses. In this paper, the Maximum Likelihood Method (MLM) is used for fitting the statistical parameters in a regression model for the fatigue strength. Furthermore, application of the Bootstrap method is investigated. The results indicate that the latter methodology does not work well in the considered case study because of runout tests within the test data. Moreover, use of Bayesian inference with Markov Chain Monto Carlo implementation is studied. These results indicate reduction in the uncertainty and thus better parameter estimations