PEECE II mesocosm experiment: Dynamics of extracellular enzyme activities in seawater under changed atmospheric pCO2, 2011

As part of the PeECE II mesocosm project, we investigated the effects of pCO2 levels on the initial step of heterotrophic carbon cycling in the surface ocean. The activities of microbial extracellular enzymes hydrolyzing 4 polysaccharides were measured during the development of a natural phytoplankton bloom under pCO2 conditions representing glacial (190 µatm) and future (750 µatm) atmospheric pCO2. We observed that (1) chondroitin hydrolysis was variable throughout the pre-, early- and late-bloom phases, (2) fucoidanase activity was measurable only in the glacial mesocosm as the bloom developed, (3) laminarinase activity was low and constant, and (4) xylanase activity declined as the bloom progressed. Concurrent measurements of microbial community composition, using denaturing-gradient gel electrophoresis (DGGE), showed that the 2 mesocosms diverged temporally, and from one another, especially in the late-bloom phase. Enzyme activities correlated with bloom phase and pCO2, suggesting functional as well as compositional changes in microbial communities in the different pCO2 environments. These changes, however, may be a response to temporal changes in the development of phytoplankton communities that differed with the pCO2 environment. We hypothesize that the phytoplankton communities produced dissolved organic carbon (DOC) differing in composition, a hypothesis supported by changing amino acid composition of the DOC, and that enzyme activities responded to changes in substrates. Enzyme activities observed under different pCO2 conditions likely reflect both genetic and population-level responses to changes occurring among multiple components of the microbial loop.

Effects of ocean acidification on population dynamics and community structure of crustose coralline algae

Calcification and growth of crustose coralline algae (CCA) are affected by elevated seawater pCO2 and associated changes in carbonate chemistry. However, the effects of ocean acidification (OA) on population and community-level responses of CCA have barely been investigated. We explored changes in community structure and population dynamics (size structure and reproduction) of CCA in response to OA. Recruited from an experimental flow-through system, CCA settled onto the walls of plastic aquaria and developed under exposure to one of three pCO2 treatments (control [present day, 389±6 ppm CO2], medium [753±11 ppm], and high [1267±19 ppm]). Elevated pCO2 reduced total CCA abundance and affected community structure, in particular the density of the dominant species Pneophyllum sp. and Porolithon onkodes. Meanwhile, the relative abundance of P. onkodes declined from 24% under control CO2 to 8.3% in high CO2 (65% change), while the relative abundance of Pneophyllum sp. remained constant. Population size structure of P. onkodes differed significantly across treatments, with fewer larger individuals under high CO2. In contrast, the population size structure and number of reproductive structures (conceptacles) per crust of Pneophyllum sp. was similar across treatments. The difference in the magnitude of the response of species abundance and population size structure between species may have the potential to induce species composition changes in the future. These results demonstrate that the impacts of OA on key coral reef builders go beyond declines in calcification and growth, and suggest important changes to aspects of population dynamics and community ecology.

Impact of CO2 enrichment on organic matter dynamics during nutrient induced coastal phytoplankton blooms

A mesocosm experiment was conducted to investigate the impact of rising fCO2 on the build-up and decline of organic matter during coastal phytoplankton blooms. Five mesocosms (~38 m³ each) were deployed in the Baltic Sea during spring (2009) and enriched with CO2 to yield a gradient of 355-862 µatm. Mesocosms were nutrient fertilized initially to induce phytoplankton bloom development. Changes in particulate and dissolved organic matter concentrations, including dissolved high-molecular weight (>1 kDa) combined carbohydrates, dissolved free and combined amino acids as well as transparent exopolymer particles (TEP), were monitored over 21 days together with bacterial abundance, and hydrolytic extracellular enzyme activities. Overall, organic matter followed well-known bloom dynamics in all CO2 treatments alike. At high fCO2, higher dPOC:dPON during bloom rise, and higher TEP concentrations during bloom peak, suggested preferential accumulation of carbon-rich components. TEP concentration at bloom peak was significantly related to subsequent sedimentation of particulate organic matter. Bacterial abundance increased during the bloom and was highest at high fCO2. We conclude that increasing fCO2 supports production and exudation of carbon-rich components, enhancing particle aggregation and settling, but also providing substrate and attachment sites for bacteria. More labile organic carbon and higher bacterial abundance can increase rates of oxygen consumption and may intensify the already high risk of oxygen depletion in coastal seas in the future.

Dynamics of halocarbons in coastal surface waters during short term mesocosm experiments

The aim of the present study was to evaluate the influence of different light quality, especially ultraviolet radiation (UVR), on the dynamics of volatile halogenated organic compounds (VHOCs) at the sea surface. Short term experiments were conducted with floating gas-tight mesocosms of different optical qualities. Six halocarbons (CH3I, CHCl3, CH2Br2, CH2ClI, CHBr3 and CH2I2), known to be produced by phytoplankton, together with a variety of biological and environmental variables were measured in the coastal southern Baltic Sea and in the Raunefjord (North Sea). These experiments showed that ambient levels of UVR have no significant influence on VHOC dynamics in the natural systems. We attribute it to the low radiation doses that phytoplankton cells receive in a normal turbulent surface mixed layer. The VHOC concentrations were influenced by their production and removal processes, but they were not correlated with biological or environmental parameters investigated. Diatoms were most likely the dominant biogenic source of VHOCs in the Baltic Sea experiment, whereas in the Raunefjord experiment macroalgae probably contributed strongly to the production of VHOCs. The variable stable carbon isotope signatures (d13C values) of bromoform (CHBr3) also indicate that different autotrophic organisms were responsible for CHBr3 production in the two coastal environments. In the Raunefjord, despite strong daily variations in CHBr3 concentration, the carbon isotopic ratio was fairly stable with a mean value of -26 per mil. During the declining spring phytoplankton bloom in the Baltic Sea, the d13C values of CHBr3 were enriched in 13C and showed noticeable diurnal changes (-12 per mil ± 4). These results show that isotope signature analysis is a useful tool to study both the origin and dynamics of VHOCs in natural systems.

Temporal biomass dynamics of an Arctic plankton bloom

Ocean acidification and carbonation, driven by anthropogenic emissions of carbon dioxide (CO2), have been shown to affect a variety of marine organisms and are likely to change ecosystem functioning. High latitudes, especially the Arctic, will be the first to encounter profound changes in carbonate chemistry speciation at a large scale, namely the under-saturation of surface waters with respect to aragonite, a calcium carbonate polymorph produced by several organisms in this region. During a CO2 perturbation study in 2010, in the framework of the EU-funded project EPOCA, the temporal dynamics of a plankton bloom was followed in nine mesocosms, manipulated for CO2 levels ranging initially from about 185 to 1420 ?atm. Dissolved inorganic nutrients were added halfway through the experiment. Autotrophic biomass, as identified by chlorophyll a standing stocks (Chl a), peaked three times in all mesocosms. However, while absolute Chl a concentrations were similar in all mesocosms during the first phase of the experiment, higher autotrophic biomass was measured at high in comparison to low CO2 during the second phase, right after dissolved inorganic nutrient addition. This trend then reversed in the third phase. There were several statistically significant CO2 effects on a variety of parameters measured in certain phases, such as nutrient utilization, standing stocks of particulate organic matter, and phytoplankton species composition. Interestingly, CO2 effects developed slowly but steadily, becoming more and more statistically significant with time. The observed CO2 related shifts in nutrient flow into different phytoplankton groups (mainly diatoms, dinoflagellates, prasinophytes and haptophytes) could have consequences for future organic matter flow to higher trophic levels and export production, with consequences for ecosystem productivity and atmospheric CO2.

Liquid lead and Lithium. A Comprehensive molecular dynamics study

Pb17Li is today a reference breeder material in diverse fusion R&D programs worldwide. One of the main issues in these programs is the problem of liquid metals breeder blanket behavior. Structural material of the blanket should meet high requirements because of extreme operating conditions. Therefore the knowledge of eutectic properties like optimal composition, physical and thermodynamic behavior or diffusion coefficients of Tritium are extremely necessary for current designs. In particular, the knowledge of the function linking the tritium concentration dissolved in liquid materials with the tritium partial pressure at a liquid/gas interface in equilibrium, CT=f(PT), is of basic importance because it directly impacts all functional properties of a blanket determining: tritium inventory, tritium permeation rate and tritium extraction efficiency. Nowadays, understanding the structure and behavior of this compound is a real goal in fusion engineering and materials science. Simulations of liquids can provide much information to the community; not only supplementing experimental data, but providing new tests of theories and ideas, making specific predictions that require experimental tests, and ultimately helping to lead to the deeper understanding and better predictive behavior.

Análisis experimental y computacional de modelos termofluidomecánicos para el diseño de ingeniería con metales líquidos

Es importante disponer de una herramienta con la cual diseñar dispositivos de uso industrial y comercial que trabajen con metales líquidos (fuentes de neutrones de alta intensidad, núcleos de sistemas de transmutación nuclear, reactores de fisión de nueva generación, instalaciones de irradiación de materiales o reactores de fusión nuclear). Los códigos CFD (Computational Fluid Dynamics) son una de esas herramientas, y la manera de llevar a cabo su validación es la simulación de experimentos existentes. La turbulencia y la presencia de dos o más fases, son los dos principales problemas a los que tiene que hacer frente un código CFD. La mayoría de los modelos de turbulencia presentes en los códigos CFD se basan en considerar la proporcionalidad directa entre el transporte de cantidad de movimiento turbulento y el transporte turbulento de calor. Precisamente, el coeficiente de difusión del calor turbulento, se asume que sea proporcional a la viscosidad turbulenta a través de una constante empírica, llamada número de Prandtl turbulento. El valor de este número, en los códigos comerciales está entre 0,9 y 0,85 dependiendo del modelo de turbulencia, lo cual significa que en los códigos se asume que el transporte turbulento tanto de cantidad de movimiento como de calor, son prácticamente equivalentes. Esta asunción no es cierta en los flujos de metales líquidos, donde se demuestra que la transmisión de calor por turbulencia es pequeña frente a la transmisión de calor molecular. La solución pasa por aumentar el número de Prandtl turbulento, o abandonar la analogía de Reynolds, en el tratamiento de la turbulencia. Por otro lado, en los metales líquidos la capa límite térmica es más ancha que la de velocidad, y las funciones de pared incluidas en los códigos no satisfacen adecuadamente los flujos turbulentos de los fluidos con bajo número de Prantdl (los metales líquidos). Sí serían adecuados, si el mallado es tal, que la celda más cercana a la pared, está dentro de la subcapa laminar, en la cual la propiedad dominante es la conductividad molecular. En la simulación de flujo multifase los códigos se encuentran con una serie de dificultades, que en el caso de que las densidades de los fluidos que intervienen sean muy diferentes entre sí (como ocurre con los metales líquidos y los gases), serán aún mayores. La modelización de la interfase gas metal líquido, así como el encontrar una correlación válida para los coeficientes de resistencia y sustentación para el movimiento de las burbujas en el seno del metal líquido, son dos de los principales retos en la simulación de este tipo de flujos. Las dificultades no se limitan sólo a la simulación mediante CFD, las medidas experimentales de velocidad de las burbujas y del metal líquido también son complicadas. Hay parámetros que no se pueden definir bien: la trayectoria y la forma de las burbujas entre ellos. En el campo de aplicación industrial de los metales líquidos, los altos valores de los coeficientes de expansión volumétrica y de conductividad térmica hacen que estos fluidos sean muy atractivos en la refrigeración por convección libre en dispositivos de alta densidad de potencia. Tomando como base uno de los diseños de ADS (Accelerator Driven System), y teniendo en cuenta la dificultad que conlleva el uso de múltiples modelos físicos, los cálculos realizados muestran cómo, en caso de fallo eléctrico, la operación de la instalación puede continuar de forma segura. Para la validación de los códigos CFD en su uso como herramienta de diseño, uno de los fenómenos donde cuantitativamente más dificultades encuentran los códigos es en los que aparecen en la modelización de las superficies libres. Un buen ajuste de los modelos multifase y de turbulencia es imprescindible en este tipo de simulaciones. Efectivamente, en la instalación de irradiación de materiales IFMIF, la formación de ondas en la superficie libre del flujo de Litio, es un fenómeno que hay que tratar de evitar, y además se requiere predecir las temperaturas, para ver si hay peligro de ebullición del metal líquido. La simulación llevada a cabo se enfoca al análisis termohidráulico. Variando la velocidad de inyección de Litio desde 10 hasta 20 m/s, se comprueba que las temperaturas máximas quedan alejadas del punto de ebullición del Litio, debido al aumento de presión producido por la fuerza centrífuga. Una de las cuestiones más críticas que se presentan en las fuentes de neutrones sería la refrigeración de la ventana metálica sobre la que incide el haz de protones. La simulación de experimentos como MEGAPIE y TS-1, permite la “visualización” de recirculación en el flujo, de los puntos de estancamiento, de los puntos calientes, etc, y da una fotografía de las zonas críticas del diseño.

Experimental analysis of the breakage of a liquid bridge under microgravity conditions

The experimental results obtained in experiment “STACO” made on board the Spacelab D-2 are re-visited, with image-analysis tools not then available. The configuration consisted of a liquid bridge between two solid supporting discs. An expected breakage occurred during the experiment. The recorded images are analysed and the measured behaviour compared with the results of a three dimensional model of the liquid dynamics, obtaining a much better fit than with linear models

Computational Fluid Dynamics Expert System using Artificial Neural Networks

The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

A molecular dynamics study of swift heavy ion irradiation of amorphous silica: the role of thermal effects

Irradiation with swift heavy ions (SHI), roughly defined as those having atomic masses larger than 15 and energies exceeding 1 MeV/amu, may lead to significant modification of the irradiated material in a nanometric region around the (straight) ion trajectory (latent tracks). In the case of amorphous silica, SHI irradiation originates nano-tracks of higher density than the virgin material (densification). As a result, the refractive index is increased with respect to that of the surroundings. Moreover, track overlapping leads to continuous amorphous layers that present a significant contrast with respect to the pristine substrate. We have recently demonstrated that SHI irradiation produces a large number of point defects, easily detectable by a number of experimental techniques (work presented in the parallel conference ICDIM). The mechanisms of energy transfer from SHI to the target material have their origin in the high electronic excitation induced in the solid. A number of phenomenological approaches have been employed to describe these mechanisms: coulomb explosion, thermal spike, non-radiative exciton decay, bond weakening. However, a detailed microscopic description is missing due to the difficulty of modeling the time evolution of the electronic excitation. In this work we have employed molecular dynamics (MD) calculations to determine whether the irradiation effects are related to the thermal phenomena described by MD (in the ps domain) or to electronic phenomena (sub-ps domain), e.g., exciton localization. We have carried out simulations of up to 100 ps with large boxes (30x30x8 nm3) using a home-modified version of MDCASK that allows us to define a central hot cylinder (ion track) from which heat flows to the surrounding cold bath (unirradiated sample). We observed that once the cylinder has cooled down, the Si and O coordination numbers are 4 and 2, respectively, as in virgin silica. On the other hand, the density of the (cold) cylinder increases with respect to that of silica and, furthermore, the silica network ring size decreases. Both effects are in agreement with the observed densification. In conclusion, purely thermal effects do not explain the generation of point defects upon irradiation, but they do account for the silica densification.

Comparison of turbulence models for the computational fluid dynamics simulation of wind turbine wakes in the atmospheric boundary layer

An elliptic computational fluid dynamics wake model based on the actuator disk concept is used to simulate a wind turbine, approximated by a disk upon which a distribution of forces, defined as axial momentum sources, is applied on an incoming non-uniform shear flow. The rotor is supposed to be uniformly loaded with the exerted forces estimated as a function of the incident wind speed, thrust coefficient and rotor diameter. The model is assessed in terms of wind speed deficit and added turbulence intensity for different turbulence models and is validated from experimental measurements of the Sexbierum wind turbine experiment.

Collective Organization of Complex Networks: Emergent Scales, Vulnerability, and Targeting of Desired Dynamics

Cuando una colectividad de sistemas dinámicos acoplados mediante una estructura irregular de interacciones evoluciona, se observan dinámicas de gran complejidad y fenómenos emergentes imposibles de predecir a partir de las propiedades de los sistemas individuales. El objetivo principal de esta tesis es precisamente avanzar en nuestra comprensión de la relación existente entre la topología de interacciones y las dinámicas colectivas que una red compleja es capaz de mantener. Siendo este un tema amplio que se puede abordar desde distintos puntos de vista, en esta tesis se han estudiado tres problemas importantes dentro del mismo que están relacionados entre sí. Por un lado, en numerosos sistemas naturales y artificiales que se pueden describir mediante una red compleja la topología no es estática, sino que depende de la dinámica que se desarrolla en la red: un ejemplo son las redes de neuronas del cerebro. En estas redes adaptativas la propia topología emerge como consecuencia de una autoorganización del sistema. Para conocer mejor cómo pueden emerger espontáneamente las propiedades comúnmente observadas en redes reales, hemos estudiado el comportamiento de sistemas que evolucionan según reglas adaptativas locales con base empírica. Nuestros resultados numéricos y analíticos muestran que la autoorganización del sistema da lugar a dos de las propiedades más universales de las redes complejas: a escala mesoscópica, la aparición de una estructura de comunidades, y, a escala macroscópica, la existencia de una ley de potencias en la distribución de las interacciones en la red. El hecho de que estas propiedades aparecen en dos modelos con leyes de evolución cuantitativamente distintas que siguen unos mismos principios adaptativos sugiere que estamos ante un fenómeno que puede ser muy general, y estar en el origen de estas propiedades en sistemas reales. En segundo lugar, proponemos una medida que permite clasificar los elementos de una red compleja en función de su relevancia para el mantenimiento de dinámicas colectivas. En concreto, estudiamos la vulnerabilidad de los distintos elementos de una red frente a perturbaciones o grandes fluctuaciones, entendida como una medida del impacto que estos acontecimientos externos tienen en la interrupción de una dinámica colectiva. Los resultados que se obtienen indican que la vulnerabilidad dinámica es sobre todo dependiente de propiedades locales, por tanto nuestras conclusiones abarcan diferentes topologías, y muestran la existencia de una dependencia no trivial entre la vulnerabilidad y la conectividad de los elementos de una red. Finalmente, proponemos una estrategia de imposición de una dinámica objetivo genérica en una red dada e investigamos su validez en redes con diversas topologías que mantienen regímenes dinámicos turbulentos. Se obtiene como resultado que las redes heterogéneas (y la amplia mayora de las redes reales estudiadas lo son) son las más adecuadas para nuestra estrategia de targeting de dinámicas deseadas, siendo la estrategia muy efectiva incluso en caso de disponer de un conocimiento muy imperfecto de la topología de la red. Aparte de la relevancia teórica para la comprensión de fenómenos colectivos en sistemas complejos, los métodos y resultados propuestos podrán dar lugar a aplicaciones en sistemas experimentales y tecnológicos, como por ejemplo los sistemas neuronales in vitro, el sistema nervioso central (en el estudio de actividades síncronas de carácter patológico), las redes eléctricas o los sistemas de comunicaciones. ABSTRACT The time evolution of an ensemble of dynamical systems coupled through an irregular interaction scheme gives rise to dynamics of great of complexity and emergent phenomena that cannot be predicted from the properties of the individual systems. The main objective of this thesis is precisely to increase our understanding of the interplay between the interaction topology and the collective dynamics that a complex network can support. This is a very broad subject, so in this thesis we will limit ourselves to the study of three relevant problems that have strong connections among them. First, it is a well-known fact that in many natural and manmade systems that can be represented as complex networks the topology is not static; rather, it depends on the dynamics taking place on the network (as it happens, for instance, in the neuronal networks in the brain). In these adaptive networks the topology itself emerges from the self-organization in the system. To better understand how the properties that are commonly observed in real networks spontaneously emerge, we have studied the behavior of systems that evolve according to local adaptive rules that are empirically motivated. Our numerical and analytical results show that self-organization brings about two of the most universally found properties in complex networks: at the mesoscopic scale, the appearance of a community structure, and, at the macroscopic scale, the existence of a power law in the weight distribution of the network interactions. The fact that these properties show up in two models with quantitatively different mechanisms that follow the same general adaptive principles suggests that our results may be generalized to other systems as well, and they may be behind the origin of these properties in some real systems. We also propose a new measure that provides a ranking of the elements in a network in terms of their relevance for the maintenance of collective dynamics. Specifically, we study the vulnerability of the elements under perturbations or large fluctuations, interpreted as a measure of the impact these external events have on the disruption of collective motion. Our results suggest that the dynamic vulnerability measure depends largely on local properties (our conclusions thus being valid for different topologies) and they show a non-trivial dependence of the vulnerability on the connectivity of the network elements. Finally, we propose a strategy for the imposition of generic goal dynamics on a given network, and we explore its performance in networks with different topologies that support turbulent dynamical regimes. It turns out that heterogeneous networks (and most real networks that have been studied belong in this category) are the most suitable for our strategy for the targeting of desired dynamics, the strategy being very effective even when the knowledge on the network topology is far from accurate. Aside from their theoretical relevance for the understanding of collective phenomena in complex systems, the methods and results here discussed might lead to applications in experimental and technological systems, such as in vitro neuronal systems, the central nervous system (where pathological synchronous activity sometimes occurs), communication systems or power grids.

Experimental investigation of dynamic pressure loads during dam break

The objectives of this work are to revisit the experimental measurements on dam break flow over a dry horizontal bed and to provide a detailed insight into the dynamics of the dam break wave impacting a vertical wall downstream the dam, with emphasis on the pressure loads. The measured data are statistically analyzed and critically discussed. As a result, an extensive set of data for validation of computational tools is provided.