Vehicle-to-anything application (v2anything app) for electric vehicles

This paper presents a mobile information system denominated as Vehicle-to-Anything Application (V2Anything App), and explains its conceptual aspects. This application is aimed at giving relevant information to Full Electric Vehicle (FEV) drivers, by supporting the integration of several sources of data in a mobile application, thus contributing to the deployment of the electric mobility process. The V2Anything App provides recommendations to the drivers about the FEV range autonomy, location of battery charging stations, information of the electricity market, and also a route planner taking into account public transportations and car or bike sharing systems. The main contributions of this application are related with the creation of an Information and Communication Technology (ICT) platform, recommender systems, data integration systems, driver profile, and personalized range prediction. Thus, it is possible to deliver relevant information to the FEV drivers related with the electric mobility process, electricity market, public transportation, and the FEV performance.

Modelo para calcular a contribuição da fibra na resistência à punção de lajes em concreto reforçado com fibra de aço

Neste artigo, formulações analíticas são desenvolvidas para calcular a resistência à punção de lajes lisas de concreto reforçado com fibras de aço (CRFA) e que também são reforçadas à flexão por barras de aço (reforço convencional). A partir de análises estatísticas sobre um banco de dados que reúne resultados experimentais de caracterização do comportamento pós-fissuração do CRFA, equações são estabelecidas para avaliar parâmetros da resistência residual à tração na flexão (fRi) a partir de informações fundamentais que caracterizam a fibra de aço. O parâmetro de resistência fRi, proposto pelo ModelCode10 foi usado para definir a lei tensão-abertura da fissura (σ-w) que simula o mecanismo de reforço da fibra em um material cimentício. A segunda parte do artigo descreve uma formulação analítica baseada nos conceitos propostos por Muttoni e Ruiz, onde a lei σ-w é convenientemente integrada para simular a contribuição da fibra de aço na resistência à punção de lajes em CRFA. A partir de um banco de dados, composto de 154 ensaios de punção, o bom desempenho da proposta apresentada é demonstrado. O desempenho do modelo também é evidenciado comparando-se os seus resultados a outros modelos.

Implementation of integral viscoelastic constitutive models in OpenFOAM® computational library

This work reports the implementation and verification of a new so lver in OpenFOAM® open source computational library, able to cope with integral viscoelastic models based on the integral upper-convected Maxwell model. The code is verified through the comparison of its predictions with analytical solutions and numerical results obtained with the differential upper-convected Maxwell model

Weld lines in extrusion: Understanding the role of the flow conditions

This work reports the implemen tation and verification of a new so lver in OpenFOAM® open source computational library, able to cope w ith integral viscoelastic models based on the integral upper-convected Maxwell model. The code is verified through the comparison of its predictions with anal ytical solutions and numerical results obtained with the differential upper-convected Maxwell model

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Moda ética: a consciencialização através da comunicação

Dissertação de mestrado em Design e Comunicação de Moda

High strain rate constitutive modeling forhistorical structures subjected to blast loading

Doctoral Thesis Civil Engineering

Aging and Alzheimer's disease: Searching for novel molecular cues

Tese de Doutoramento em Ciências da Saúde

Methodology for real-time adaptation of tunnels support using the observational method

The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.

Sistema de predição de avarias em máquinas de unidades fabris globalmente dispersas

Tese de Doutoramento Ramo Engenharia Industrial e de Sistemas

Evaluation of the DPMFoam solver

[Extrat] Multiphase flows are relevant in several industrial processes, thus the availability of accurate numerical modeling tools, able to support the design of products and processes, is of much significance. OpenFOAM version 2.3.x comprises a multiphase flow solver able to couple Eulerian and Lagrangian phases using the discrete particles method (DPM), the DPMFoam. In this work the DPMFoam solver is assessed by comparing its predictions with analytical results and experimental and simulated data available in the literature. They are results from Goldschmidt’s [1] and Hoomans’s [2] theses and the analytical Ergun equation. The goal was to define accuracy and performance of DPMFoam in general scientific or commercial applications. Obtained results demonstrate a good agreement with the reference simulation data and is within reasonable deviations from the experimental values. (...)

Impact performance prediction of injection-molded talc-filled polypropylene through thermomechanical environment assessment

Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

Simultaneous measurements of the tt¯, W+W−, and Z/γ∗→ττ production cross-sections in pp collisions at s√=7 TeV with the ATLAS detector

Simultaneous measurements of the tt¯, W+W−, and Z/γ∗→ττ production cross-sections using an integrated luminosity of 4.6 fb−1 of pp collisions at s√=7 TeV collected by the ATLAS detector at the LHC are presented. Events are selected with two high transverse momentum leptons consisting of an oppositely charged electron and muon pair. The three processes are separated using the distributions of the missing transverse momentum of events with zero and greater than zero jet multiplicities. Measurements of the fiducial cross-section are presented along with results that quantify for the first time the underlying correlations in the predicted and measured cross-sections due to proton parton distribution functions. These results indicate that the correlated NLO predictions for tt¯ and Z/γ∗→ττ significantly underestimate the data, while those at NNLO generally describe the data well. The full cross-sections are measured to be σ(tt¯)=181.2±2.8+9.7−9.5±3.3±3.3 pb, σ(W+W−)=53.3±2.7+7.3−8.0±1.0±0.5 pb, and σ(Z/γ∗→ττ)=1174±24+72−87±21±9 pb, where the cited uncertainties are due to statistics, systematic effects, luminosity and the LHC beam energy measurement, respectively.

Measurement of the forward-backward asymmetry of electron and muon pair-production in pp collisions at s√ = 7 TeV with the ATLAS detector

This paper presents measurements from the ATLAS experiment of the forward-backward asymmetry in the reaction pp→Z/γ∗→l+l−, with l being electrons or muons, and the extraction of the effective weak mixing angle. The results are based on the full set of data collected in 2011 in pp collisions at the LHC at s√ = 7 TeV, corresponding to an integrated luminosity of 4.8 fb−1. The measured asymmetry values are found to be in agreement with the corresponding Standard Model predictions. The combination of the muon and electron channels yields a value of the effective weak mixing angle of 0.2308±0.0005(stat.)±0.0006(syst.)±0.0009(PDF), where the first uncertainty corresponds to data statistics, the second to systematic effects and the third to knowledge of the parton density functions. This result agrees with the current world average from the Particle Data Group fit.

Search for heavy lepton resonances decaying to a Z boson and a lepton in pp collisions at s√=8 TeV with the ATLAS detector

A search for heavy leptons decaying to a Z boson and an electron or a muon is presented. The search is based on pp collision data taken at s√=8 TeV by the ATLAS experiment at the CERN Large Hadron Collider, corresponding to an integrated luminosity of 20.3 fb−1. Three high-transverse-momentum electrons or muons are selected, with two of them required to be consistent with originating from a Z boson decay. No significant excess above Standard Model background predictions is observed, and 95% confidence level limits on the production cross section of high-mass trilepton resonances are derived. The results are interpreted in the context of vector-like lepton and type-III seesaw models. For the vector-like lepton model, most heavy lepton mass values in the range 114-176 GeV are excluded. For the type-III seesaw model, most mass values in the range 100-468 GeV are excluded.