Quinstant Dark Energy Predictions for Structure Formation

We explore the predictions of a class of dark energy models, quinstant dark energy, concerning the structure formation in the Universe, both in the linear and non-linear regimes. Quinstant dark energy is considered to be formed by quintessence and a negative cosmological constant. We conclude that these models give good predictions for structure formation in the linear regime, but fail to do so in the non-linear one, for redshifts larger than one.Comment: 9 pages, 14 figures, "Accepted for publication in Astrophysics & Space Science

Methodology for ranking controllable parameters to enhance operation of a steam generator with a combined Artificial Neural Network and Design of Experiments approach

The operation of complex systems can drift away from the initial design conditions, due to environmental conditions, equipment wear or specific restrictions. Steam generators are complex equipment and their proper operation relies on the identification of their most relevant parameters. An approach to rank the operational parameters of a subcritical steam generator of an actual 360 MW power plant is presented. An Artificial Neural Network - ANN delivers a model to estimate the steam generator efficiency, electric power generation and flue gas outlet temperature as a function of seven input parameters. The ANN is trained with a two-year long database, with training errors of 0.2015 and 0.2741 (mean absolute and square error) and validation errors of 0.32% and 2.350 (mean percent and square error). That ANN model is explored by means of a combination of situations proposed by a Design of Experiment - DoE approach. All seven controlled parameters showed to be relevant to express both steam generator efficiency and electric power generation, while primary air flow rate and speed of the dynamic classifier can be neglected to calculate flue gas temperature as they are not statistically significant. DoE also shows the prominence of the primary air pressure in respect to the steam generator efficiency, electric power generation and the coal mass flow rate for the calculation of the flue gas outlet temperature. The ANN and DoE combined methodology shows to be promising to enhance complex system efficiency and helpful whenever a biased behavior must be brought back to stable operation

Ultrafine particles in four European urban environments: Results from a new continuous long-term monitoring network

To gain a better understanding on the spatiotemporal variation of ultrafine particles (UFPs) in urban environments, this study reports on the first results of a long-term UFP monitoring network, set up in Amsterdam (NL), Antwerp (BE), Leicester (UK) and London (UK). Total number concentrations and size distributions were assessed during 1e2 years at four fixed urban background sites, supplemented with mobile trailer measurements for co-location monitoring and additional short-term monitoring sites. Intra- and interurban spatiotemporal UFP variation, associations with commonly-monitored pollutants (PM, NOx and BC) and impacts of wind fields were evaluated. Although comparable size distributions were observed between the four cities, source-related differences were demonstrated within specific particle size classes. Total and size-resolved particle number concentrations showed clear traffic-related temporal variation, confirming road traffic as the major UFP contributor in urban environments. New particle formation events were observed in all cities. Correlations with typical traffic-related pollutants (BC and NOx) were obtained for all monitoring stations, except for Amsterdam, which might be attributable to UFP emissions from Schiphol airport. The temporal variation in particle number concentration correlated fairly weakly between the four cities (rs = 0.28 0.50, COD = 0.28 0.37), yet improved significantly inside individual cities (rs = 0.59-0.77). Nevertheless, considerable differences were still obtained in terms of particle numbers (20-38% for total particle numbers and up to 49% for size-resolved particle numbers), confirming the importance of local source contributions and the need for careful consideration when allocating UFP monitoring stations in heterogeneous urban environments