Uma ferramenta para cálculo da máxima intensidade da ilha de calor noturna

O objetivo deste artigo é verificar a influência da geometria urbana na intensidade de ilhas de calor noturnas com uso de uma ferramenta computacional desenvolvida como extensão de um SIG. O método deste trabalho está dividido em três principais etapas: desenvolvimento da ferramenta, calibração do modelo e simulação de cenários hipotéticos com diferentes geometrias urbanas. Um modelo simplificado que relaciona as intensidades máximas de ilha de calor urbana (ICUmáx) com a geometria urbana foi incorporado à subrotina de cálculo e, posteriormente, adaptado para fornecer resultados mais aproximados à realidade de duas cidades brasileiras, as quais serviram de base para a calibração do modelo. A comparação entre dados reais e simulados mostraram uma diferença no aumento da ICUmáx em função da relação H/W e da faixa de comprimento de rugosidade (Z0). Com a ferramenta já calibrada, foi realizada uma simulação de diferentes cenários urbanos, demonstrando que o modelo simplificado original subestima valores de ICUmáx para as configurações de cânions urbanos de Z0 < 2,0 e superestima valores de ICUmáx para as configurações de cânions urbanos de Z0 ≥ 2,0. Além disso, este estudo traz como contribuição à verificação de que cânions urbanos com maiores áreas de fachadas e com alturas de edificações mais heterogêneas resultam em ICUmáx menores em relação aos cânions mais homogêneos e com maiores áreas médias ocupadas pelas edificações, para um mesmo valor de relação H/W. Essa diferença pode ser explicada pelos diferentes efeitos na turbulência dos ventos e nas áreas sombreadas provocados pela geometria urbana.

Strategic planning of electricity systems: Integrating renewable energies

Tese de Doutoramento - Programa Doutoral em Engenharia Industrial e Sistemas (PDEIS)

Search for dark matter in events with heavy quarks and missing transverse momentum in pp collisions with the ATLAS detector

This article reports on a search for dark matter pair production in association with bottom or top quarks in 20.3fb−1 of pp collisions collected at s√=8 TeV by the ATLAS detector at the LHC. Events with large missing transverse momentum are selected when produced in association with high-momentum jets of which one or more are identified as jets containing b-quarks. Final states with top quarks are selected by requiring a high jet multiplicity and in some cases a single lepton. The data are found to be consistent with the Standard Model expectations and limits are set on the mass scale of effective field theories that describe scalar and tensor interactions between dark matter and Standard Model particles. Limits on the dark-matter--nucleon cross-section for spin-independent and spin-dependent interactions are also provided. These limits are particularly strong for low-mass dark matter. Using a simplified model, constraints are set on the mass of dark matter and of a coloured mediator suitable to explain a possible signal of annihilating dark matter.

Innovation in “low-tech” industries: Portuguese footwear industry

ICEIM – International Conference in Entrepreneurship and Innovation Management, Roma, 17-18 de setembro de 2015.

ATLAS Run 1 searches for direct pair production of third-generation squarks at the Large Hadron Collider

This paper reviews and extends searches for the direct pair production of the scalar supersymmetric partners of the top and bottom quarks in proton--proton collisions collected by the ATLAS collaboration during the LHC Run 1. Most of the analyses use 20 fb−1 of collisions at a centre-of-mass energy of s√=8 TeV, although in some case an additional 4.7 fb−1 of collision data at s√=7 TeV are used. New analyses are introduced to improve the sensitivity to specific regions of the model parameter space. Since no evidence of third-generation squarks is found, exclusion limits are derived by combining several analyses and are presented in both a simplified model framework, assuming simple decay chains, as well as within the context of more elaborate phenomenological supersymmetric models.

Field oriented control of an axial flux permanent magnet synchronous motor for traction solutions

Electric Vehicles (EVs) are increasingly used nowadays, and different powertrain solutions can be adopted. This paper describes the control system of an axial flux Permanent Magnet Synchronous Motor (PMSM) for EVs powertrain. It is described the implemented Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique. Also, the mathematical model of the PMSM is presented. Both, simulation and experimental, results with different types of mechanical load are presented. The experimental results were obtained using a laboratory test bench. The obtained results are discussed.

Learning joint representations for order and timing of perceptual-motor sequences: a dynamic neural field approach

Many of our everyday tasks require the control of the serial order and the timing of component actions. Using the dynamic neural field (DNF) framework, we address the learning of representations that support the performance of precisely time action sequences. In continuation of previous modeling work and robotics implementations, we ask specifically the question how feedback about executed actions might be used by the learning system to fine tune a joint memory representation of the ordinal and the temporal structure which has been initially acquired by observation. The perceptual memory is represented by a self-stabilized, multi-bump activity pattern of neurons encoding instances of a sensory event (e.g., color, position or pitch) which guides sequence learning. The strength of the population representation of each event is a function of elapsed time since sequence onset. We propose and test in simulations a simple learning rule that detects a mismatch between the expected and realized timing of events and adapts the activation strengths in order to compensate for the movement time needed to achieve the desired effect. The simulation results show that the effector-specific memory representation can be robustly recalled. We discuss the impact of the fast, activation-based learning that the DNF framework provides for robotics applications.