Thermobaric control of gravitational potential energy generation by diapycnal mixing in the deep ocean

Sources and sinks of gravitational potential energy (GPE) play a rate-limiting role in the large scale ocean circulation. A key source is turbulent diapycnal mixing, whereby irre- versible mixing across isoneutral surfaces is enhanced by turbulent straining of these surfaces. This has motivated international observational efforts to map diapycnal mixing in the global ocean. However, in order to accurately relate the GPE supplied to the large scale circulation by diapycnal mixing to the mixing energy source, it is first necessary to determine the ratio, ξ , of the GPE generation rate to the available potential energy dissipation rate associated with turbulent mixing. Here, the link between GPE and hydro- static pressure is used to derive the GPE budget for a com- pressible ocean with a nonlinear equation of state. The role of diapycnal mixing is isolated and from this a global cli- matological distribution of ξ is calculated. It is shown that, for a given source of mixing energy, typically three times as much GPE is generated if the mixing takes place in bottom waters rather than in the pycnocline. This is due to GPE destruction by cabbelling in the pycnocline, as opposed to thermobaric enhancement of GPE generation by diapycnal mixing in the deep ocean.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

Challenges in quantifying wind generation's contribution to securing peak demand

Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

The novel ruthenium-gamma-linolenic complex [Ru(2)(aGLA)(4)Cl] inhibits C6 rat glioma cell proliferation and induces changes in mitochondrial membrane potential, increased reactive oxygen species generation and apoptosis in vitro

The present study reports the synthesis of a novel compound with the formula [Ru(2)(aGLA)(4)Cl] according to elemental analyses data, referred to as Ru(2)GLA. The electronic spectra of Ru(2)GLA is typical of a mixed valent diruthenium(II,III) carboxylate. Ru(2)GLA was synthesized with the aim of combining and possibly improving the anti-tumour properties of the two active components ruthenium and gamma-linolenic acid (GLA). The properties of Ru(2)GLA were tested in C6 rat glioma cells by analysing cell number, viability, lipid droplet formation, apoptosis, cell cycle distribution, mitochondrial membrane potential and reactive oxygen species. Ru(2)GLA inhibited cell proliferation in a time and concentration dependent manner. Nile Red staining suggested that Ru(2)GLA enters the cells and ICP-AES elemental analysis found all increase in ruthenium from <0.02 to 425 mg/Kg in treated cells. The sub-G1 apoptotic cell population was increased by Ru(2)GLA (22 +/- 5.2%) when analysed by FACS and this was confirmed by Hoechst staining of nuclei. Mitochondrial membrane potential was decreased in the presence of Ru(2)GLA (44 +/- 2.3%). In contrast, the cells which maintained a high mitochondrial membrane potential had an increase (18 +/- 1.5%) in reactive oxygen species generation. Both decreased mitochondrial membrane potential and increased reactive oxygen species generation may be involved in triggering apoptosis in Ru(2)GLA exposed cells. The EC(50) for Ru(2)GLA decreased with increasing time of exposure from 285 mu M at 24h, 211 mu M at 48 h to 81 mu M at 72 h. In conclusion, Ru(2)GLA is a novel drug with anti proliferative properties in C6 glioma cells and is a potential candidate for novel therapies in gliomas. Copyright (C) 2009 John Wiley & Sons, Ltd.

Generation of Vortices and Observation of Quantum Turbulence in an Oscillating Bose-Einstein Condensate

We report on the experimental observation of vortex formation and production of tangled vortex distribution in an atomic BEC of (87)Rb atoms submitted to an external oscillatory perturbation. The oscillatory perturbations start by exciting quadrupolar and scissors modes of the condensate. Then regular vortices are observed finally evolving to a vortex tangle configuration. The vortex tangle is a signature of the presence of a turbulent regime in the cloud. We also show that this turbulent cloud has suppression of the aspect ratio inversion typically observed in quantum degenerate bosonic gases during free expansion.

Meteomap: Generation Of Meteorological Variables For Distributed Physically-Based Hydrological Modeling

Distributed energy and water balance models require time-series surfaces of the meteorological variables involved in hydrological processes. Most of the hydrological GIS-based models apply simple interpolation techniques to extrapolate the point scale values registered at weather stations at a watershed scale. In mountainous areas, where the monitoring network ineffectively covers the complex terrain heterogeneity, simple geostatistical methods for spatial interpolation are not always representative enough, and algorithms that explicitly or implicitly account for the features creating strong local gradients in the meteorological variables must be applied. Originally developed as a meteorological pre-processing tool for a complete hydrological model (WiMMed), MeteoMap has become an independent software. The individual interpolation algorithms used to approximate the spatial distribution of each meteorological variable were carefully selected taking into account both, the specific variable being mapped, and the common lack of input data from Mediterranean mountainous areas. They include corrections with height for both rainfall and temperature (Herrero et al., 2007), and topographic corrections for solar radiation (Aguilar et al., 2010). MeteoMap is a GIS-based freeware upon registration. Input data include weather station records and topographic data and the output consists of tables and maps of the meteorological variables at hourly, daily, predefined rainfall event duration or annual scales. It offers its own pre and post-processing tools, including video outlook, map printing and the possibility of exporting the maps to images or ASCII ArcGIS formats. This study presents the friendly user interface of the software and shows some case studies with applications to hydrological modeling.

The best are never normal : exploring the distribution of firm performance

Competitive Strategy literature predicts three different mechanisms of performance generation, thus distinguishing between firms that have competitive advantage, firms that have competitive disadvantage or firms that have neither. Nonetheless, previous works in the field have fitted a single normal distribution to model firm performance. Here, we develop a new approach that distinguishes among performance generating mechanisms and allows the identification of firms with competitive advantage or disadvantage. Theorizing on the positive feedback loops by which firms with competitive advantage have facilitated access to acquire new resources, we proposed a distribution we believe data on firm performance should follow. We illustrate our model by assessing its fit to data on firm performance, addressing its theoretical implications and comparing it to previous works.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Time-series-based maximization of distributed wind power generation integration

Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of MPG.

Strategic capacitor placement in distribution systems by minimisation of harmonics amplification because of resonance

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Primary power distribution systems planning taking into account reliability, operation and expansion costs

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Phosphate distribution in the sediments along a cascade of reservoirs - (Paranapanema River, SE, Brazil)

Total phosphorus concentrations in the sediment of a cascade of 8 reservoirs located in the Paranapanema River (SE, Brazil) were analysed during two consecutive seasonal periods (2000 and 200 1). The reservoirs of Jurumirim, Chavantes, Salto Grande, Canoas 11, Canoas 1, Capivara, Taquarucu and Rosana were built during the last five decades with the purpose of hydroelectric generation. The sampling points were distributed along a 700 km of river stretch in 19 stations distributed in the river-reservoirs zones and main tributaries as well as in 5 stations representing the adjacent wetlands. The nutrient concentration was determined in samples from surface layers of sediment. Temporal and spatial changes were observed for both years. Three different areas could be identified along the river, considering not only Tot-P variations but also others physical and chemical characteristics such as organic matter concentration, nitrogen concentration of sediment and 02, pH, conductivity and Eh measured in the bottom layer of the water column. Higher values of Tot-P were found in the middle and lower region of the Paranapanema basin (maximum value of 1.96 mg g(-1) in Tibagi River in October/2001). Agricultural practices and cattle raising are the main external sources of nutrient in these regions. Superficial or sub-superficial watershed drainage and tributaries entrances are important nutrient contributors, leading to an increasing accumulation of nutrient in the sediment. This process seems to be especially important in the middle region of the Paranapanema Valley, were the values of Tot-P were higher comparing to the other areas.

Aquatic macrophyte distribution in relation to water and sediment conditions in the Itaipu Reservoir, Brazil

Aquatic macrophyte community distribution along the eastern shoreline of the Itaipu Reservoir (one of the South America's largest impoundments) is described in relation to limnological and sedimentological factors. The central body of the reservoir is mesotrophic, while the arms (flooded influent river valleys) along the eastern shore may be oligo-mesotrophic to eutrophic, depending on time of year and sub-catchment characteristics. Macrophyte community composition and species cover were surveyed at 30 sites in four arms, in relation to sediment total P and organic matter; underwater light regime; and water total P and Kjeldahl N concentration, alkalinity, conductivity, depth and pH. Seventeen euhydrophyte and six emergent macrophyte species were recorded. Large stands of Egeria najas dominated the euhydrophyte vegetation, together with free-floating weed species (Pistia stratiotes Linn., Salvinia auriculata Aublet and Eichhornia crassipes (Mart.) Solms.). Canonical Correspondence Analysis of the data showed that two sets of variables were important predictors of aquatic macrophyte community structure. Floating macrophyte assemblage was closely related to concentration of nutrients in both water and sediment, while light penetration was the strongest predictor of submerged species occurrence. Although a large number of potential nuisance species were present, dense growths were restricted to shallower areas of the Itaipu Reservoir, causing localised problems. The possibility of increasing interference by these plants with fisheries, recreational use, transport and hydroelectricity generation suggests a need for continued monitoring of weed distribution and abundance, and investigation of appropriate management measures.

How to not inflate population estimates? Spatial density distribution of white-lipped peccaries in a continuous Atlantic forest

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)