A methodology proposal to obtain operational parameter forecasts and operational risk assessment in container terminals

Las terminales de contenedores son sistemas complejos en los que un elevado número de actores económicos interactúan para ofrecer servicios de alta calidad bajo una estricta planificación y objetivos económicos. Las conocidas como "terminales de nueva generación" están diseñadas para prestar servicio a los mega-buques, que requieren tasas de productividad que alcanzan los 300 movimientos/ hora. Estas terminales han de satisfacer altos estándares dado que la competitividad entre terminales es elevada. Asegurar la fiabilidad de las planificaciones del atraque es clave para atraer clientes, así como reducir al mínimo el tiempo que el buque permanece en el puerto. La planificación de las operaciones es más compleja que antaño, y las tolerancias para posibles errores, menores. En este contexto, las interrupciones operativas deben reducirse al mínimo. Las principales causas de dichas perturbaciones operacionales, y por lo tanto de incertidumbre, se identifican y caracterizan en esta investigación. Existen una serie de factores que al interactuar con la infraestructura y/o las operaciones desencadenan modos de fallo o parada operativa. Los primeros pueden derivar no solo en retrasos en el servicio sino que además puede tener efectos colaterales sobre la reputación de la terminal, o incluso gasto de tiempo de gestión, todo lo cual supone un impacto para la terminal. En el futuro inmediato, la monitorización de las variables operativas presenta gran potencial de cara a mejorar cualitativamente la gestión de las operaciones y los modelos de planificación de las terminales, cuyo nivel de automatización va en aumento. La combinación del criterio experto con instrumentos que proporcionen datos a corto y largo plazo es fundamental para el desarrollo de herramientas que ayuden en la toma de decisiones, ya que de este modo estarán adaptadas a las auténticas condiciones climáticas y operativas que existen en cada emplazamiento. Para el corto plazo se propone una metodología con la que obtener predicciones de parámetros operativos en terminales de contenedores. Adicionalmente se ha desarrollado un caso de estudio en el que se aplica el modelo propuesto para obtener predicciones de la productividad del buque. Este trabajo se ha basado íntegramente en datos proporcionados por una terminal semi-automatizada española. Por otro lado, se analiza cómo gestionar, evaluar y mitigar el efecto de las interrupciones operativas a largo plazo a través de la evaluación del riesgo, una forma interesante de evaluar el effecto que eventos inciertos pero probables pueden generar sobre la productividad a largo plazo de la terminal. Además se propone una definición de riesgo operativo junto con una discusión de los términos que representan con mayor fidelidad la naturaleza de las actividades y finalmente, se proporcionan directrices para gestionar los resultados obtenidos. Container terminals are complex systems where a large number of factors and stakeholders interact to provide high-quality services under rigid planning schedules and economic objectives. The socalled next generation terminals are conceived to serve the new mega-vessels, which are demanding productivity rates up to 300 moves/hour. These terminals need to satisfy high standards because competition among terminals is fierce. Ensuring reliability in berth scheduling is key to attract clients, as well as to reduce at a minimum the time that vessels stay the port. Because of the aforementioned, operations planning is becoming more complex, and the tolerances for errors are smaller. In this context, operational disturbances must be reduced at a minimum. The main sources of operational disruptions and thus, of uncertainty, are identified and characterized in this study. External drivers interact with the infrastructure and/or the activities resulting in failure or stoppage modes. The later may derive not only in operational delays but in collateral and reputation damage or loss of time (especially management times), all what implies an impact for the terminal. In the near future, the monitoring of operational variables has great potential to make a qualitative improvement in the operations management and planning models of terminals that use increasing levels of automation. The combination of expert criteria with instruments that provide short- and long-run data is fundamental for the development of tools to guide decision-making, since they will be adapted to the real climatic and operational conditions that exist on site. For the short-term a method to obtain operational parameter forecasts in container terminals. To this end, a case study is presented, in which forecasts of vessel performance are obtained. This research has been entirely been based on data gathered from a semi-automated container terminal from Spain. In the other hand it is analyzed how to manage, evaluate and mitigate disruptions in the long-term by means of the risk assessment, an interesting approach to evaluate the effect of uncertain but likely events on the long-term throughput of the terminal. In addition, a definition for operational risk evaluation in port facilities is proposed along with a discussion of the terms that better represent the nature of the activities involved and finally, guidelines to manage the results obtained are provided.

Design Parameter Analysis of Point Absorber WEC via an Evolutionary-Algorithm-Based Dimensioning Tool

Wave energy conversion has an essential difference from other renewable energies since the dependence between the devices design and the energy resource is stronger. Dimensioning is therefore considered a key stage when a design project of Wave Energy Converters (WEC) is undertaken. Location, WEC concept, Power Take-Off (PTO) type, control strategy and hydrodynamic resonance considerations are some of the critical aspects to take into account to achieve a good performance. The paper proposes an automatic dimensioning methodology to be accomplished at the initial design project stages and the following elements are described to carry out the study: an optimization design algorithm, its objective functions and restrictions, a PTO model, as well as a procedure to evaluate the WEC energy production. After that, a parametric analysis is included considering different combinations of the key parameters previously introduced. A variety of study cases are analysed from the point of view of energy production for different design-parameters and all of them are compared with a reference case. Finally, a discussion is presented based on the results obtained, and some recommendations to face the WEC design stage are given.

The Malthusian parameter of ascents: What prevents the exponential increase of one’s ancestors?

The reason that the indefinite exponential increase in the number of one’s ancestors does not take place is found in the law of sibling interference, which can be expressed by the following simple equation:\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} \begin{equation*}\begin{matrix}{\mathit{N}}_{{\mathit{n}}} \enskip & \\ {\mathit{{\blacksquare}}} \enskip & \\ {\mathit{ASZ}} \enskip & \end{matrix} {\mathrm{\hspace{.167em}{\times}\hspace{.167em}2\hspace{.167em}=\hspace{.167em}}}{\mathit{N_{n+1},}}\end{equation*}\end{document} where Nn is the number of ancestors in the nth generation, ASZ is the average sibling size of these ancestors, and Nn+1 is the number of ancestors in the next older generation (n + 1). Accordingly, the exponential increase in the number of one’s ancestors is an initial anomaly that occurs while ASZ remains at 1. Once ASZ begins to exceed 1, the rate of increase in the number of ancestors is progressively curtailed, falling further and further behind the exponential increase rate. Eventually, ASZ reaches 2, and at that point, the number of ancestors stops increasing for two generations. These two generations, named AN SA and AN SA + 1, are the most critical in the ancestry, for one’s ancestors at that point come to represent all the progeny-produced adults of the entire ancestral population. Thereafter, the fate of one’s ancestors becomes the fate of the entire population. If the population to which one belongs is a successful, slowly expanding one, the number of ancestors would slowly decline as you move toward the remote past. This is because ABZ would exceed 2. Only when ABZ is less than 2 would the number of ancestors increase beyond the AN SA and AN SA + 1 generations. Since the above is an indication of a failing population on the way to extinction, there had to be the previous AN SA involving a far greater number of individuals for such a population. Simulations indicated that for a member of a continuously successful population, the AN SA ancestors might have numbered as many as 5.2 million, the AN SA generation being the 28th generation in the past. However, because of the law of increasingly irrelevant remote ancestors, only a very small fraction of the AN SA ancestors would have left genetic traces in the genome of each descendant of today.

Proposal of a New Parameter for the Weathering Characterization of Carbonate Flysch-Like Rock Masses: The Potential Degradation Index (PDI)

The susceptibility of clay bearing rocks to weathering (erosion and/or differential degradation) is known to influence the stability of heterogeneous slopes. However, not all of these rocks show the same behaviour, as there are considerable differences in the speed and type of weathering observed. As such, it is very important to establish relationships between behaviour quantified in a laboratory environment with that observed in the field. The slake durability test is the laboratory test most commonly used to evaluate the relationship between slaking behaviour and rock durability. However, it has a number of disadvantages; it does not account for changes in shape and size in fragments retained in the 2 mm sieve, nor does its most commonly used index (Id2) accurately reflect weathering behaviour observed in the field. The main aim of this paper is to propose a simple methodology for characterizing the weathering behaviour of carbonate lithologies that outcrop in heterogeneous rock masses (such as Flysch slopes), for use by practitioners. To this end, the Potential Degradation Index (PDI) is proposed. This is calculated using the fragment size distribution curves taken from material retained in the drum after each cycle of the slake durability test. The number of slaking cycles has also been increased to five. Through laboratory testing of 117 samples of carbonate rocks, extracted from strata in selected slopes, 6 different rock types were established based on their slaking behaviour, and corresponding to the different weathering behaviours observed in the field.

Bulk sediment parameter of surface sediment samples (Table 3)

Comparison of rates of accumulation of organic carbon in surface marine sediments from the central North Pacific, the continental margins off northwest Africa, northwest and southwest America, the Argentine Basin, and the western Baltic Sea with primary production rates suggests that the fraction of primary produced organic carbon preserved in the sediments is universally related to the bulk sedimentation rate. Accordingly, less than 0.01% of the primary production becomes fossilized in slowly accumulating pelagic sediments [(2 to 6 mm (1000 y)**-1] of the Central Pacific, 0.1 to 2% in moderately rapidly accumulating [2 to 13 cm (1000 y)**-1] hemipelagic sediments off northwest Africa, northwest America (Oregon) and southeast America (Argentina), and 11 to 18% in rapidly accumulating [66 to 140 cm (1000 y)**-1] hemipelagic sediments off southwest America (Peru) and in the Baltic Sea. The emiprical expression: %Org-C = (0.0030*R*S**0.30)/(ps(1-Theta)) implies that the sedimentary organic carbon content (% Org-C) doubles with each 10-fold increase in sedimentation rate (S), assuming that other factors remain constant; i.e., primary production (R), porosity and sediment density (ps). This expression also predicts the sedimentary organic carbon content from the primary production rate, sedimentation rate, dry density of solids, and their porosity; it may be used to estimate paleoproductivity as well. Applying this relationship to a sediment core from the continental rise off northwest Africa (Spanish Sahara) suggests that productivity there during interglacial oxygen isotope stages 1 and 5 was about the same as today but was higher by a factor of 2 to 3 during glacial stages 2, 3, and 6.

Statistical grain size parameter of surface samples from Kiel Bay

Geological observations, using "free-diving" techniques (Figure I) were made in September, 1960 and March 1961 along two continuous profiles in the outer Kiel Harbor, Germany and at several other spot locations in the Western Baltic Sea. A distinct terrace, cut in Pleistocene glacial till, was found that was covered with varying amounts and types of recent deposits. Hand samples were taken of the sea-floor sediments and grainsize distribution determined for both the sediment as a whole and for its heavy mineral fraction. From the Laboratory and Field observations it was possible to recognize two distinct types of sand; Type I, Sand resulting from transportation over a long period of time and distance and Type 11, Sand resulting from little transportation and found today near to xvhere it was formed. Several criterea related to the agent of movement could be used to classify the nature of the sediment; (1) undisturbed (the sediment Cover of the Pleistocene Terrace is essentially undisturbed), (2) mixed by organisms, (3) transported by water movements (sediment found with ripple marks, etc., and (4) "Scoured" (the movement of individual particles of sediment from around larger boulders causes a slow downward movement or "Creeping" which is due to both the force of gravity and bottom currents. These observations and laboratory studies are discussed concerning their relationship to the formation of residual sediments, the direction of sand transportation, and the intensive erosion on the outer edge of the wave-cut platform found in this part of the Baltic Sea.