Overtopping events may cause different failure modes depending on overtopped flow characteristics. Most of the studies about overtopping hazard analysis link the damages caused by the overtopping event to its mean overtopping discharge (q), which provides no information about overtopped flow characteristics or its spatial distribution. In this paper it is presented a non intrusive measurement system based on video imagery techniques and optical level sensors (OLS), which aim is to obtain overtopped highly aerated flows´ principal characteristics: velocity, volume, and density, in order to deep in the knowledge of this phenomenon, and minimizing the damages that it may cause to port´s infrastructures and exploitation
Floating structures elements are part of complex systems in which climatic agents, those derived from human interaction during use and exploitation and freedom constraints are applied. Such complexity requires different analysis techniques for its comprehension This paper presents a methodology to define and optimize operationality thresholds of floating structures using a global scaled simulator in which all agents and system's responses are modeled during a complete operational process.Keywords: operationality thresholds, floating structures, simulator, floating gate, physical modeling
INTRODUCTION AND MOTIVATIONFloating structures are widely used in port and ocean engineering. They are also present in any activity related to marine structures, dock's or lock's gates, barges, floating cranes, floating terminals or vertical caisson for breakwater construction are just some examples. Even though these uses for floating bodies can be very different, most of the difficulties related to their use and exploitation are closely related. They are all part of a very complex system in which the agents are those called climatic (wind, waves and currents) but are also exposed to those derived from the use they were designed for. In addition to this, the reactions of floating bodies to such demands are frequently constrained by mooring lines, fenders or even the sea bed. All these interrelations make very difficult the comprehension and prediction of the response of such systems. One of the main reasons to study such structures is the need to establish a threshold for one, or more, agents under which the operation of the floating facility is safe and profitable. It is very common to define operativity thresholds after an iterative process of analytical and then numerical analysis (Terencio,2011) and once this has been accomplished, those threshold are revised during normal operation of the floating structure. Such revision usually represents a higher level of operationality and therefore an increase in the operator's profits. Works as the one described in (DELTARES,2008) come closer to the optimal threshold by means of a physical model in which most of the agents and operation conditions are modeled. But there was still room for an improvement (Cabrerizo, 2007) Therefore the principal aim of this study is to develop the methods and tools to achieve a deep knowledge of those floating systems and obtain capabilities to optimize their operationality thresholds by modeling not only climatic agents, but also those derived from the use and exploitation during a complete operation in a single test. A secondary objective has been to design and implement a global scaled simulator (1:22) in which all factors and agents are present; this includes climatic agents, those derived from operational design, operator's immediate decisions and every aspect related to human interaction.
El sistema portuario español es sumamente complejo y admite el estudio desde numerosos puntos de vista En este artículo se estudian los puertos según su actividad y sus características externas para la clasificación en agrupaciones. Para ello se han utilizado indicadores que reflejan la actividad portuaria y se han aplicado sobre las 28 Autoridades Portuarias españolas. Con estos indicadores se ha aplicado una metodología específica para a través del análisis de conglomerados (cluster) para averiguar cuáles son los agrupamientos que se producen. El análisis cluster se complementa con otros análisis estadísticos: análisis multivariante y componentes principales, para conocer qué indicadores son los más relevantes en las agrupaciones y cómo se comportan. Los resultados finales obtenidos muestran que este tipo de estudios estadísticos son apropiados para realizarse en el entorno portuario y que los agrupamientos reflejan correctamente la realidad portuaria.
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