Predictivity Strength of the Spatial Variability of Phenanthrene Sorption Across Two Sandy Loam Fields

Sorption is commonly agreed to be the major process underlying the transport and fate of polycyclic aromatic hydrocarbons (PAHs) in soils. However, there is still a scarcity of studies focusing on spatial variability at the field scale in particular. In order to investigate the variation in the field of phenanthrene sorption, bulk topsoil samples were taken in a 15 × 15-m grid from the plough layer in two sandy loam fields with different texture and organic carbon (OC) contents (140 samples in total). Batch experiments were performed using the adsorption method. Values for the partition coefficient K d (L kg−1) and the organic carbon partition coefficient K OC (L kg−1) agreed with the most frequently used models for PAH partitioning, as OC revealed a higher affinity for sorption. More complex models using different OC compartments, such as non-complexed organic carbon (NCOC) and complexed organic carbon (COC) separately, performed better than single K OC models, particularly for a subset including samples with Dexter n < 10 and OC <0.04 kg kg−1. The selected threshold revealed that K OC-based models proved to be applicable for more organic fields, while two-component models proved to be more accurate for the prediction of K d and retardation factor (R) for less organic soils. Moreover, OC did not fully reflect the changes in phenanthrene retardation in the field with lower OC content (Faardrup). Bulk density and available water content influenced the phenanthrene transport mechanism phenomenon.

Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling

The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Avaliação do comportamento de uma ponte metálica centenária sujeita à ação de tráfego ferroviário ligeiro

A presente dissertação tem como objetivo principal a análise numérica do comportamento dinâmico de uma ponte ferroviária, sob ação de tráfego ligeiro ferroviário. Neste contexto são apresentados alguns fundamentos teóricos a ter em conta nestes domínios, visando uma melhor compreensão dos fenómenos existentes no comportamento dinâmico de pontes ferroviárias quando sujeitas ao tráfego. O caso de estudo teve como foco a ponte Luiz I, uma ponte metálica situada sobre o rio Douro, que liga as cidades do Porto e Vila Nova de Gaia, sob ação de tráfego ligeiro ferroviário no seu tabuleiro superior para a condição anterior aos trabalhos de reabilitação e reforço realizados entre 2004 e 2005. Para o efeito foi desenvolvido um modelo numérico de elementos finitos da ponte realizado com recurso ao programa ANSYS, assim como um modelo numérico do veículo do Metro de Lisboa. Com base nestes modelos foram obtidos os parâmetros modais, nomeadamente as frequências naturais e os modos de vibração de toda a estrutura e do veículo. O estudo do comportamento dinâmico da ponte foi realizado por intermédio de uma metodologia de cargas móveis e de interação veículo-estrutura, através da ferramenta computacional Train-Bridge Interaction (TBI). As análises dinâmicas foram efetuadas para a passagem dos veículos de passageiros das redes de Metros do Porto e Lisboa. Nestas análises é estudada a resposta da estrutura em função da variabilidade ao nível da secção transversal, dependência do tramo, influência do veículo, da sua velocidade de circulação e impacto das frequências de vibração estimadas pelo modelo numérico.