Diagnostic techniques for EHD and MHD interaction

The impact of plasma technologies is growing both in the academic and in the industrial fields. Nowadays, a great interest is focused in plasma applications in aeronautics and astronautics domains. Plasma actuators based on the Magneto-Hydro-Dynamic (MHD) and Electro- Hydro-Dynamic (EHD) interactions are potentially able to suitably modify the fluid-dynamics characteristics around a flying body without utilizing moving parts. This could lead to the control of an aircraft with negligible response time, more reliability and improvements of the performance. In order to study the aforementioned interactions, a series of experiments and a wide number of diagnostic techniques have been utilized. The EHD interaction, realized by means of a Dielectric Barrier Discharge (DBD) actuator, and its impact on the boundary layer have been evaluated by means of two different experiments. In the first one a three phase multi-electrode flat panel actuator is used. Different external flow velocities (from 1 to 20m/s) and different values of the supplied voltage and frequency have been considered. Moreover a change of the phase sequence has been done to verify the influence of the electric field existing between successive phases. Measurements of the induced speed had shown the effect of the supply voltage and the frequency, and the phase order in the momentum transfer phenomenon. Gains in velocity, inside the boundary layer, of about 5m/s have been obtained. Spectroscopic measurements allowed to determine the rotational and the vibrational temperature of the plasma which lie in the range of 320 ÷ 440°K and of 3000 ÷ 3900°K respectively. A deviation from thermodynamic equilibrium had been found. The second EHD experiment is realized on a single electrode pair DBD actuator driven by nano-pulses superimposed to a DC or an AC bias. This new supply system separates the plasma formation mechanism from the acceleration action on the fluid, leading to an higher degree of the control of the process. Both the voltage and the frequency of the nano-pulses and the amplitude and the waveform of the bias have been varied during the experiment. Plasma jets and vortex behavior had been observed by means of fast Schlieren imaging. This allowed a deeper understanding of the EHD interaction process. A velocity increase in the boundary layer of about 2m/s had been measured. Thrust measurements have been performed by means of a scales and compared with experimental data reported in the literature. For similar voltage amplitudes thrust larger than those of the literature, had been observed. Surface charge measurements led to realize a modified DBD actuator able to obtain similar performances when compared with that of other experiments. However in this case a DC bias replacing the AC bias had been used. MHD interaction experiments had been carried out in a hypersonic wind tunnel in argon with a flow of Mach 6. Before the MHD experiments a thermal, fluid-dynamic and plasma characterization of the hypersonic argon plasma flow have been done. The electron temperature and the electron number density had been determined by means of emission spectroscopy and microwave absorption measurements. A deviation from thermodynamic equilibrium had been observed. The electron number density showed to be frozen at the stagnation region condition in the expansion through the nozzle. MHD experiments have been performed using two axial symmetric test bodies. Similar magnetic configurations were used. Permanent magnets inserted into the test body allowed to generate inside the plasma azimuthal currents around the conical shape of the body. These Faraday currents are responsible of the MHD body force which acts against the flow. The MHD interaction process has been observed by means of fast imaging, pressure and electrical measurements. Images showed bright rings due to the Faraday currents heating and exciting the plasma particles. Pressure measurements showed increases of the pressure in the regions where the MHD interaction is large. The pressure is 10 to 15% larger than when the MHD interaction process is silent. Finally by means of electrostatic probes mounted flush on the test body lateral surface Hall fields of about 500V/m had been measured. These results have been used for the validation of a numerical MHD code.

How serious is the omission of bilateral tariff rates in gravity?

In this paper, using the worldwide dataset of bilateral tariff rates, we explore how serious the omission of bilateral tariff rates in gravity is. Our findings are as follow. Firstly, the omission of bilateral tariff rates seems not to be so serious in terms of omitted-variable biases because the coefficients for the usual gravity variables do not change before or after their inclusion. Secondly, while the widely-used dummy variable of regional trade agreement could not play an alternative role in place of tariff rates, the inclusion of time-invariant pair fixed effects in addition to the time-variant importer fixed effects and exporter fixed effects accounts for the omission of tariff rates. The inclusion of those fixed effects makes the coefficient for bilateral tariff rates insignificant.

Impact of diagonal cumulation rule on FTA utilization : evidence from bilateral and multilateral FTAs between Japan and Thailand

In this paper, we empirically investigate the effect of diagonal cumulation on free trade agreement (FTA) utilization by exploring Thai exports to Japan under two kinds of FTA schemes. While the one scheme adopts bilateral cumulation, the other scheme does diagonal cumulation. Comparing trade under these two kinds of FTAs, we can examine the effect of diagonal cumulation without relying on not only the variation in cumulation rules across country pairs but also the variation across years. In short, our estimates do not suffer from biases from time-variant elements and country pair-specific elements. As a result, our estimates show around 4% trade creation effect of diagonal cumulation, which is much smaller than the estimates in the previous studies (around 15%).

Efeito da corrosão do chapeamento do fundo do casco sobre a confiabilidade estrutural de navios.

A engenharia é a ciência que transforma os conhecimentos das disciplinas básicas aplicadas a fatos reais. Nosso mundo está rodeado por essas realizações da engenharia, e é necessário que as pessoas se sintam confortáveis e seguras nas mesmas. Assim, a segurança se torna um fator importante que deve ser considerado em qualquer projeto. Na engenharia naval, um apropriado nível de segurança e, em consequência, um correto desenho estrutural é baseado, atualmente, em estudos determinísticos com o objetivo de obter estruturas capazes de suportar o pior cenário possível de solicitações durante um período de tempo determinado. A maior parte das solicitações na estrutura de um navio se deve à ação da natureza (ventos, ondas, correnteza e tempestades), ou, ainda, aos erros cometidos por humanos (explosões internas, explosões externas e colisões). Devido à aleatoriedade destes eventos, a confiabilidade estrutural de um navio deveria ser considerada como um problema estocástico sob condições ambientais bem caracterizadas. A metodologia probabilística, baseada em estatística e incertezas, oferece uma melhor perspectiva dos fenômenos reais que acontecem na estrutura dos navios. Esta pesquisa tem como objetivo apresentar resultados de confiabilidade estrutural em projetos e planejamento da manutenção para a chapa do fundo dos cascos dos navios, as quais são submetidas a esforços variáveis pela ação das ondas do mar e da corrosão. Foram estudados modelos estatísticos para a avaliação da estrutura da viga-navio e para o detalhe estrutural da chapa do fundo. Na avaliação da estrutura da viga-navio, o modelo desenvolvido consiste em determinar as probabilidades de ocorrência das solicitações na estrutura, considerando a deterioração por corrosão, com base numa investigação estatística da variação dos esforços em função das ondas e a deterioração em função de uma taxa de corrosão padrão recomendada pela DET NORSKE VERITAS (DNV). A abordagem para avaliação da confiabilidade dependente do tempo é desenvolvida com base nas curvas de resistências e solicitações (R-S) determinadas pela utilização do método de Monte Carlo. Uma variação estatística de longo prazo das adversidades é determinada pelo estudo estatístico de ondas em longo prazo e ajustada por uma distribuição com base numa vida de projeto conhecida. Constam no trabalho resultados da variação da confiabilidade ao longo do tempo de um navio petroleiro. O caso de estudo foi simplificado para facilitar a obtenção de dados, com o objetivo de corroborar a metodologia desenvolvida.

A fresh look at decision making in international investment choices: Firm international coherence and home-host country relatedness

Understanding how decisions for international investments are made and how this affects the overall pattern of investments and firm’s performance is of particular importance both in strategy and international business research. This dissertation introduced first home-host country relatedness (HHCR) as the degree to which countries are efficiently combined within the investment portfolios of firms. It theorized and demonstrated that HHCR will vary with the motivation for investments along at least two key dimensions: the nature of foreign investments and the connectedness of potential host countries to the rest of the world. Drawing on cognitive psychology and decision-making research, it developed a theory of strategic decision making proposing that strategic solutions are chosen close to a convenient anchor. Building on research on memory imprinting, it also proposed that managers tend to rely on older knowledge representation. In the context of international investment decisions, managers use their home countries as an anchor and are more likely to choose as a site for foreign investments host countries that are ‘close’ to the home country. These decisions are also likely to rely more strongly on closeness to time invariant country factors of historic and geographic nature rather than time-variant institutions. Empirical tests using comprehensive investments data by all public multinational companies (MNC) worldwide, or over 15,000 MNCs with over half a million subsidiaries, support the claims. Finally, the dissertation introduced the concept of International Coherence (IC) defined as the degree to which an MNE’s network comprises countries that are related. It was hypothesized that maintaining a high level of coherence is important for firm performance and will enhance it. Also, the presence of international coherence mitigates some of the negative effects of unrelated product diversification. Empirical tests using data on foreign investments of over 20,000 public firms, while also developing a home-host country relatedness index for up to 24,300 home-host pairs, provided support for the theory advanced.

A Study of How Economic Attitudes Are Shaped by Environmental Shocks and Life Experiences

Social attitudes, attitudes toward financial risk and attitudes toward deferred gratification are thought to influence many important economic decisions over the life-course. In economic theory, these attitudes are key components in diverse models of behavior, including collective action, saving and investment decisions and occupational choice. The relevance of these attitudes have been confirmed empirically. Yet, the factors that influence them are not well understood. This research evaluates how these attitudes are affected by large disruptive events, namely, a natural disaster and a civil conflict, and also by an individual-specific life event, namely, having children.

By implementing rigorous empirical strategies drawing on rich longitudinal datasets, this research project advances our understanding of how life experiences shape these attitudes. Moreover, compelling evidence is provided that the observed changes in attitudes are likely to reflect changes in preferences given that they are not driven just by changes in financial circumstances. Therefore the findings of this research project also contribute to the discussion of whether preferences are really fixed, a usual assumption in economics.

In the first chapter, I study how altruistic and trusting attitudes are affected by exposure to the 2004 Indian Ocean tsunami as long as ten years after the disaster occurred. Establishing a causal relationship between natural disasters and attitudes presents several challenges as endogenous exposure and sample selection can confound the analysis. I take on these challenges by exploiting plausibly exogenous variation in exposure to the tsunami and by relying on a longitudinal dataset representative of the pre-tsunami population in two districts of Aceh, Indonesia. The sample is drawn from the Study of the Tsunami Aftermath and Recovery (STAR), a survey with data collected both before and after the disaster and especially designed to identify the impact of the tsunami. The altruistic and trusting attitudes of the respondents are measured by their behavior in the dictator and trust games. I find that witnessing closely the damage caused by the tsunami but without suffering severe economic damage oneself increases altruistic and trusting behavior, particularly towards individuals from tsunami affected communities. Having suffered severe economic damage has no impact on altruistic behavior but may have increased trusting behavior. These effects do not seem to be caused by the consequences of the tsunami on people’s financial situation. Instead they are consistent with how experiences of loss and solidarity may have shaped social attitudes by affecting empathy and perceptions of who is deserving of aid and trust.

In the second chapter, co-authored with Ryan Brown, Duncan Thomas and Andrea Velasquez, we investigate how attitudes toward financial risk are affected by elevated levels of insecurity and uncertainty brought on by the Mexican Drug War. To conduct our analysis, we pair the Mexican Family Life Survey (MxFLS), a rich longitudinal dataset ideally suited for our purposes, with a dataset on homicide rates at the month and municipality-level. The homicide rates capture well the overall crime environment created by the drug war. The MxFLS elicits risk attitudes by asking respondents to choose between hypothetical gambles with different payoffs. Our strategy to identify a causal effect has two key components. First, we implement an individual fixed effects strategy which allows us to control for all time-invariant heterogeneity. The remaining time variant heterogeneity is unlikely to be correlated with changes in the local crime environment given the well-documented political origins of the Mexican Drug War. We also show supporting evidence in this regard. The second component of our identification strategy is to use an intent-to-treat approach to shield our estimates from endogenous migration. Our findings indicate that exposure to greater local-area violent crime results in increased risk aversion. This effect is not driven by changes in financial circumstances, but may be explained instead by heightened fear of victimization. Nonetheless, we find that having greater economic resources mitigate the impact. This may be due to individuals with greater economic resources being able to avoid crime by affording better transportation or security at work.

The third chapter, co-authored with Duncan Thomas, evaluates whether attitudes toward deferred gratification change after having children. For this study we also exploit the MxFLS, which elicits attitudes toward deferred gratification (commonly known as time discounting) by asking individuals to choose between hypothetical payments at different points in time. We implement a difference-in-difference estimator to control for all time-invariant heterogeneity and show that our results are robust to the inclusion of time varying characteristics likely correlated with child birth. We find that becoming a mother increases time discounting especially in the first two years after childbirth and in particular for those women without a spouse at home. Having additional children does not have an effect and the effect for men seems to go in the opposite direction. These heterogeneous effects suggest that child rearing may affect time discounting due to generated stress or not fully anticipated spending needs.

Anomaly Detection in Noisy Images

Finding rare events in multidimensional data is an important detection problem that has applications in many fields, such as risk estimation in insurance industry, finance, flood prediction, medical diagnosis, quality assurance, security, or safety in transportation. The occurrence of such anomalies is so infrequent that there is usually not enough training data to learn an accurate statistical model of the anomaly class. In some cases, such events may have never been observed, so the only information that is available is a set of normal samples and an assumed pairwise similarity function. Such metric may only be known up to a certain number of unspecified parameters, which would either need to be learned from training data, or fixed by a domain expert. Sometimes, the anomalous condition may be formulated algebraically, such as a measure exceeding a predefined threshold, but nuisance variables may complicate the estimation of such a measure. Change detection methods used in time series analysis are not easily extendable to the multidimensional case, where discontinuities are not localized to a single point. On the other hand, in higher dimensions, data exhibits more complex interdependencies, and there is redundancy that could be exploited to adaptively model the normal data. In the first part of this dissertation, we review the theoretical framework for anomaly detection in images and previous anomaly detection work done in the context of crack detection and detection of anomalous components in railway tracks. In the second part, we propose new anomaly detection algorithms. The fact that curvilinear discontinuities in images are sparse with respect to the frame of shearlets, allows us to pose this anomaly detection problem as basis pursuit optimization. Therefore, we pose the problem of detecting curvilinear anomalies in noisy textured images as a blind source separation problem under sparsity constraints, and propose an iterative shrinkage algorithm to solve it. Taking advantage of the parallel nature of this algorithm, we describe how this method can be accelerated using graphical processing units (GPU). Then, we propose a new method for finding defective components on railway tracks using cameras mounted on a train. We describe how to extract features and use a combination of classifiers to solve this problem. Then, we scale anomaly detection to bigger datasets with complex interdependencies. We show that the anomaly detection problem naturally fits in the multitask learning framework. The first task consists of learning a compact representation of the good samples, while the second task consists of learning the anomaly detector. Using deep convolutional neural networks, we show that it is possible to train a deep model with a limited number of anomalous examples. In sequential detection problems, the presence of time-variant nuisance parameters affect the detection performance. In the last part of this dissertation, we present a method for adaptively estimating the threshold of sequential detectors using Extreme Value Theory on a Bayesian framework. Finally, conclusions on the results obtained are provided, followed by a discussion of possible future work.

Controladores repetitivos aplicados a filtros ativos de potência sob variações de carga e de frequência da rede

This work presents the development and modification of techniques to reduce the effects of load variation and mains frequency deviation in repetitive controllers applied to active power filters. To minimize the effects of aperiodic signals resulting from the connection or disconnection of non-linear loads is developed a technique which recognizes linear and nonlinear loads, and operates to reset the controller only when the error due to the transition of considerable value, and the transition is from non-linear to linear load. An algorithm to adapt the gain of the repetitive controller, based on a sigmoid function adaptation, in order to minimize the effects caused by random noise in the measurement system is also used. This work also analyzes the effects of frequency variation and presents the main methods to cope with this situation. Some solutions are the change in the number of samples per period and the variation of the sampling rate. The first has the advantage of using linear design techniques and results in a time invariant system. The second method changes the sampling frequency and leads to a time variant system that demands a difficult analysis of stability. The proposed algorithms were tested using the methods of truncation of the number of samples and the method of changing the sampling rate of the system to compensate possible frequency variations of the grid. Experimental results are presented to validate the proposal.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.

Reliability concepts applied to cutting tool change time

This paper presents a reliability-based analysis for calculating critical tool life in machining processes. It is possible to determine the running time for each tool involved in the process by obtaining the operations sequence for the machining procedure. Usually, the reliability of an operation depends on three independent factors: operator, machine-tool and cutting tool. The reliability of a part manufacturing process is mainly determined by the cutting time for each job and by the sequence of operations, defined by the series configuration. An algorithm is presented to define when the cutting tool must be changed. The proposed algorithm is used to evaluate the reliability of a manufacturing process composed of turning and drilling operations. The reliability of the turning operation is modeled based on data presented in the literature, and from experimental results, a statistical distribution of drilling tool wear was defined, and the reliability of the drilling process was modeled. (C) 2010 Elsevier Ltd. All rights reserved.

The reliability of video based time motion analysis

Time motion analysis is extensively used to assess the demands of team sports. At present there is only limited information on the reliability of measurements using this analysis tool. The aim of this study was to establish the reliability of an individual observer's time motion analysis of rugby union. Ten elite level rugby players were individually tracked in Southern Hemisphere Super 12 matches using a digital video camera. The video footage was subsequently analysed by a single researcher on two occasions one month apart. The test-retest reliability was quantified as the typical error of measurement (TEM) and rated as either good (10% TEM). The total time spent in the individual movements of walking, jogging, striding, sprinting, static exertion and being stationary had moderate to poor reliability (5.8-11.1% TEM). The frequency of individual movements had good to poor reliability (4.3-13.6% TEM), while the mean duration of individual movements had moderate reliability (7.1-9.3% TEM). For the individual observer in the present investigation, time motion analysis was shown to be moderately reliable as an evaluation tool for examining the movement patterns of players in competitive rugby. These reliability values should be considered when assessing the movement patterns of rugby players within competition.

Study of the Reliability of Statistical Timing Analysis for Real-Time Systems

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

Human immunodeficiency virus type 1 Brazilian subtype B variant showed an increasing avidity of the anti-V3 antibodies over time compared to the subtype B US/European strain in São Paulo, Brazil

The Brazilian variant of human immunodeficiency virus type 1 (HIV-1) subtype B, (serotype B"-GWGR), has a tryptophan replacing the proline in position 328 the HIV-1 envelope. A longer median time period from infection to acquired immunodeficiency syndrome (AIDS) for serotype B (B"-GWGR) infected subjects compared to the B-GPGR US/European strain was reported. In a cohort study, in São Paulo city, 10 B"-GWGR patients had a statistically significant increased avidity of the anti-V3 antibodies, from 79% ± 33% to 85% ± 75%, versus from 48% ± 59% to 32% ± 17% for the 10 B-GPGR subjects (p = 0.02). The T CD4+ cells showed a mean increase of + 0.45 cells/month for the B-GPGR subjects and for B"-GWGR the slope was + 1.24 cells/month (p = 0.06), for 62 and 55 months of follow up, respectively. RNA plasma viral load decreased from 3.98 ± 1.75 to 2.16 ± 1.54 log10 in the B"-GWGR group while B-GPGR patients showed one log10 reduction in viral load from 4.09 ± 0.38 to 3.17 ± 1.47 log10 over time (p = 0.23), with a decreasing slope of 0.0042 ± log10,/month and 0.0080 ± log10/month, for B-GPGR and B"-GWGR patients, respectively (p = 0.53). Neither group presented any AIDS defining events during the study, according to Center for Diseases Control criteria. Although the sample size is small, these results may indicate that differences in the pathogenicity of the 2 HIV-1 B serotypes which co-circulate in Brazil may be correlated to the avidity of anti-V3 antibodies.

Using time and stochastic models for software reliability forecasting and analysis

Tämä työ luo katsauksen ajallisiin ja stokastisiin ohjelmien luotettavuus malleihin sekä tutkii muutamia malleja käytännössä. Työn teoriaosuus sisältää ohjelmien luotettavuuden kuvauksessa ja arvioinnissa käytetyt keskeiset määritelmät ja metriikan sekä varsinaiset mallien kuvaukset. Työssä esitellään kaksi ohjelmien luotettavuusryhmää. Ensimmäinen ryhmä ovat riskiin perustuvat mallit. Toinen ryhmä käsittää virheiden ”kylvöön” ja merkitsevyyteen perustuvat mallit. Työn empiirinen osa sisältää kokeiden kuvaukset ja tulokset. Kokeet suoritettiin käyttämällä kolmea ensimmäiseen ryhmään kuuluvaa mallia: Jelinski-Moranda mallia, ensimmäistä geometrista mallia sekä yksinkertaista eksponenttimallia. Kokeiden tarkoituksena oli tutkia, kuinka syötetyn datan distribuutio vaikuttaa mallien toimivuuteen sekä kuinka herkkiä mallit ovat syötetyn datan määrän muutoksille. Jelinski-Moranda malli osoittautui herkimmäksi distribuutiolle konvergaatio-ongelmien vuoksi, ensimmäinen geometrinen malli herkimmäksi datan määrän muutoksille.

The Effect of Operational Disturbances on Reliability and Operation Time Distribution of NCmachine Tools in FMS

This thesis concentrates on studying the operational disturbance behavior of machine tools integrated into FMS. Operational disturbances are short term failures of machine tools which are especially disruptive to unattended or unmanned operation of FMS. The main objective was to examine the effect of operational disturbances on reliability and operation time distribution for machine tools. The theoretical part of the thesis covers the fimdamentals of FMS relating to the subject of this study. The concept of FMS, its benefits and operator's role in FMS operation are reviewed. The importance of reliability is presented. The terms describing the operation time of machine tools are formed by adopting standards and references. The concept of failure and indicators describing reliability and operational performance for machine tools in FMSs are presented. The empirical part of the thesis describes the research methodology which is a combination of automated (ADC) and manual data collection. By using this methodology it is possible to have a complete view of the operation time distribution for studied machine tools. Data collection was carried out in four FMSs consisting of a total of 17 machine tools. Each FMS's basic features and the signals of ADC are described. The indicators describing the reliability and operation time distribution of machine tools were calculated according to collected data. The results showed that operational disturbances have a significant influence on machine tool reliability and operational performance. On average, an operational disturbance occurs every 8,6 hours of operation time and has a down time of 0,53 hours. Operational disturbances cause a 9,4% loss in operation time which is twice the amount of losses caused by technical failures (4,3%). Operational disturbances have a decreasing influence on the utilization rate. A poor operational disturbance behavior decreases the utilization rate. It was found that the features of a part family to be machined and the method technology related to it are defining the operational disturbance behavior of the machine tool. Main causes for operational disturbances were related to material quality variations, tool maintenance, NC program errors, ATC and machine tool control. Operator's role was emphasized. It was found that failure recording activity of the operators correlates with the utilization rate. The more precisely the operators record the failure, the higher is the utilization rate. Also the FMS organizations which record failures more precisely have fewer operational disturbances.