PV system modeling by five parameters and in Situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Solid-State bipolar Marx modulator modeling

A mathematical model that simulates the operation of a solid-state bipolar Marx modulator topology, including the influence of parasitic capacitances is presented and discussed as a tool to analyze the circuit behavior and to assist the design engineer to select the semiconductor components and to enhance the operating performance. Simulations show good agreement with experimental results, considering a four stage circuit assembled with 1200 V isolated gate bipolar transistors and diodes, operating at 1000 V dc input voltage and 1-kHz frequency, giving 4 kV and 10-mu s output pulses into several resistive loads. Results show that parasitic capacitances between Marx cells to ground can significantly load the solid-state switches, adding new operating circuit conditions.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

Probing wrong-sign Yukawa couplings at the LHC and a future linear collider

We consider the two-Higgs-doublet model as a framework in which to evaluate the viability of scenarios in which the sign of the coupling of the observed Higgs boson to down-type fermions (in particular, b-quark pairs) is opposite to that of the Standard Model (SM), while at the same time all other tree-level couplings are close to the SM values. We show that, whereas such a scenario is consistent with current LHC observations, both future running at the LHC and a future e(+)e(-) linear collider could determine the sign of the Higgs coupling to b-quark pairs. Discrimination is possible for two reasons. First, the interference between the b-quark and the t-quark loop contributions to the ggh coupling changes sign. Second, the charged-Higgs loop contribution to the gamma gamma h coupling is large and fairly constant up to the largest charged-Higgs mass allowed by tree-level unitarity bounds when the b-quark Yukawa coupling has the opposite sign from that of the SM (the change in sign of the interference terms between the b-quark loop and the W and t loops having negligible impact).

Machine learning Vasicek model calibration with Gaussian processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.

Extraction of volatile oil from aromatic plants with supercritical carbon dioxide: experiments and modeling

An overview of the studies carried out in our laboratories on supercritical fluid extraction (SFE) of volatile oils from seven aromatic plants: pennyroyal (Mentha pulegium L.), fennel seeds (Foeniculum vulgare Mill.), coriander (Coriandrum sativum L.), savory (Satureja fruticosa Beguinot), winter savory (Satureja montana L.), cotton lavender (Santolina chamaecyparisus) and thyme (Thymus vulgaris), is presented. A flow apparatus with a 1 L extractor and two 0.27 L separators was built to perform studies at temperatures ranging from 298 to 353 K and pressures up to 30.0 MPa. The best compromise between yield and composition compared with hydrodistillation (HD) was achieved selecting the optimum experimental conditions of extraction and fractionation. The major differences between HD and SFE oils is the presence of a small percentage of cuticular waxes and the relative amount of thymoquinone, an oxygenated monoterpene with important biological properties, which is present in the oils from thyme and winter savory. On the other hand, the modeling of our data on supercritical extraction of volatile oil from pennyroyal is discussed using Sovova's models. These models have been applied successfully to the other volatile oil extractions. Furthermore, other experimental studies involving supercritical CO2 carried out in our laboratories are also mentioned.

Modeling of a solid-state bipolar blumlein generator for N stages

This paper models an n-stage stacked Blumlein generator for bipolar pulses for various load conditions. Calculation of the voltage amplitudes in time domain at the load and between stages is described for an n-stage generator. For this, the reflection and transmission coefficients are mathematically modeled where impedance discontinuity occurs (i.e., at the junctions between two transmission lines). The mathematical model developed is assessed by comparing simulation results to experimental data from a two-stage Blumlein solid-state prototype.

Transformador diferencial de variação linear: condicionamento de sinal e desmodulação síncrona

Dissertação para obtenção do grau de Mestre em Engenharia Eletrotécnica Ramo de Automação e eletrónica Industrial

Numerical 3D modeling of heat transfer in human tissues for microwave radiometry monitoring of Brown fat metabolismo

Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.

Influência da variabilidade dos materiais compósitos na resposta dinâmica de estruturas laminadas

Trabalho Final de Mestrado para a obtenção do grau de Mestre em Engenharia Mecânica

Distributed controllers modeling through Petri nets with multi-asynchronous-channels

This paper proposes the concept of multi-asynchronous-channel for Petri nets. Petri nets extended with multi-asynchronous-channels and time-domains support the specification of distributed controllers, where each controller has a synchronous execution but the global system is asynchronous (globally-asynchronous locally-synchronous systems). Each multi-asynchronous-channel specify the interaction between two or more distributed controllers. These channels, together with the time-domain concept, ensure the creation of network-independent models to support implementations using heterogeneous communication networks. The created models support not only the systems documentation but also their validation and implementation through simulation tools, verification tools, and automatic code generators. An application example illustrates the use of a Petri net class extended with the proposed channels. © 2015 IEEE.

Verificação da segurança sísmica de um edifício existente em betão armado

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Estruturas

Projeto de fundações e estrutura de um edifício em Lisboa

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização em Estruturas