Fundação de Amparo a Pesquisa no Estado do Rio Grande do Sul / The population growth s results and their great consumption caused the increase in the generation of municipal solid waste that become an environmental problem in the final disposition of these waste, in other words, they can cause contamination of the soil, of the superficial and underground waters, when disposed improperly in the soil, as in big garbage in the open sky. Therefore, the most adequate technical, economic and environmentally safe solution is the disposal in sanitary embankments. One of the greatest problems of the landfills are the elevated values of the vertical and horizontal shifts (settlements), because the waste are more compressible and suffer time degradation and consequently may cause damage in the structural systems of the sanitary embankments (coverage and waterproofing systems, superficial drainage and effluents). This article has the objective of evaluate the settlements of two landfills with measures of shifts by superficial landmarks, verifying the efficiency of some prevision s models of settlements in landfills of municipal solid waste existing in the literature. The evaluation was made in the São Leopoldo and Minas do Leão s landfills, comparing the settlements measured with the provided and adjust the models used basing in the monitoring data already made in the landfills in a five years period. The prevision s models of settlements that were used are: Yen and Scanlon (1975), Exponential of creep of Edil et al. (1990). Bjarngard and Edgers (1990), Rheological of Gibson and Lo (1961), Gandolla et al. (1992), Hyperbolic of Ling et al. (1998), Meruelo and the observational method of Asaoka s (1978) models. The repressions observed, at Minas do Leão s landfill, varied between 0,55 to 4,0 meters, corresponding a deformation between 4 and 24% related to the initial height of the settlement. And, about the São Leopoldo s landfill, the observed settlement, in the Remedied Landfill cell, varied between 0,1 and 1,03 meters, corresponding with a deformation between 1 and 5,8% related to the initial height of the settlement. And in the Phase I Landfill, the observed settlement varied between 0,5 and 2,4 meters, corresponding with a deformation between 8 and 16,5% of the initial height of the settlement. The values found are inside of the values zone found in the literature, except the values of the deformation of the Remedied landfill which were below of the values zone of the literature. From the analysis made in this article, it was possible to verify that the most adequate models to settlement prevision in both landfills analyzed was the Hyperbolic (1998), Exponential of creep, Bjarngard and Edgers (1990), Meruelo and the Gibson and Lo (1961) models, that obtained good adherence between the values measured and provided. Stands out that the Asaoka s (1978) method is very interesting for the accompaniment of the settlement and to verify the stabilization and the forecast of the final settlement. / O resultado do crescimento populacional e seu grande consumo causam o aumento na geração de resíduos sólidos urbanos (RSU) que se tornam um problema ambiental na disposição final destes resíduos, ou seja, podem causar contaminação no solo, nas águas superficiais e subterrâneas, quando dispostos inadequadamente no solo, como nos lixões a céu aberto. Sendo assim, a solução mais adequada técnica, econômica e ambientalmente segura é a disposição em aterros sanitários. Um dos grandes problemas dos aterros sanitários são os valores elevados de deslocamentos verticais (recalques) e horizontais, pois os resíduos são muito compressíveis e sofrem degradação com o tempo e consequentemente podem ocasionar danos nos sistemas estruturais dos aterros sanitários (sistemas de cobertura e impermeabilização, drenagem superficial e de efluentes). O presente trabalho tem como objetivo avaliar os recalques de dois aterros sanitários com medidas de deslocamento por meio de marcos superficiais, verificando a eficiência de alguns modelos de previsão de recalques em aterros sanitários de RSU existentes na literatura. A avaliação foi realizada nos aterros sanitários de São Leopoldo e de Minas do Leão, comparando os recalques medidos com os previstos e ajustar os modelos utilizados com base nos dados do monitoramento já realizado nos aterros no período de cinco anos. Os modelos de previsão de recalques que foram utilizados são: modelo de Yen e Scanlon (1975), Exponencial de creep (Potência) de Edil et al. (1990), Bjarngard e Edgers (1990), Reológico de Gibson e Lo (1961), Gandolla et al. (1992), Hiperbólico de Ling et al. (1998), Meruelo e o método observacional de Asaoka (1978). Os recalques observados, no aterro de Minas do Leão, variaram entre 0,55 a 4,0m, correspondendo a uma deformação entre 4 e 24% em relação à altura inicial dos resíduos. E, quanto ao aterro de São Leopoldo, os recalques observados, na célula Aterro Remediado, variaram entre 0,1 e 1,03m, correspondendo a uma deformação entre 1 e 5,8% em relação à altura inicial dos resíduos. E na célula Aterro Fase I, os recalques observados variaram entre 0,5 e 2,4m, correspondendo a deformações entre 8 e 16,5% da altura inicial de resíduos. Os valores encontrados estão dentro da faixa de valores encontrada na literatura, exceto os valores de deformação do aterro Remediado que foram abaixo da faixa de valores da literatura. A partir das análises realizadas neste trabalho, foi possível verificar que os modelos mais adequados para a previsão de recalques nos dois aterros sanitários analisados foram os modelos Hiperbólico (1998), Exponencial de creep (Potência), Bjarngard e Edgers (1990), Meruelo e o Gibson e Lo (1961), que obtiveram boa aderência entre os valores medidos e previstos. Destaca-se que o método de Asaoka (1978) é muito interessante para o acompanhamento de recalques e verificar a estabilização e previsão do recalque final.

Made available in DSpace on 2015-03-26T13:28:13Z (GMT). No. of bitstreams: 1 texto completo.pdf: 1839882 bytes, checksum: 7b04313dfd0b066f5ee10b45f9495ac7 (MD5) Previous issue date: 2013-02-27 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Airports present large water consumption and a great potential for the implementation of measures for its rational and efficient use. Knowing the future water demand is essential for assessing investments destined to increase capacity and the potential benefit from adopting such measures. However, for such environments, there is a lack of studies on water consumption profiles, factors which affect water demand and forecast models. Thus the objectives of this study were to assess the influence of airport movement variables on water consumption and develop multiple regression models to predict it. The database was provided by Infraero and consisted of the annual number of passengers and flights, the annual amounts of cargo and mail, and the annual water consumption for the most important airports in Brazil. The models were developed considering airports grouped in terms of passenger capacity and category (domestic or international flights), and the performance was assessed by the determination (R2) and the Nash-Sutcliffe (NSE) coefficients. The model developed for airports with capacity to transport at least 10 million passengers a year were able to explain 81% of water consumption variation, whereas the model for airports with inferior capacity explained 62% of the variation. The models developed for international and domestic airports presented R2 of 90% and 89%, respectively. The NSE coefficients were 0.93 and 0.88 for the models considering capacity and category, respectively. The model developed specifically for the Airport of Confins-MG showed good performance (NSE = 0.98) and presented great potential to enable the inclusion of other variables that can reflect characteristics of each airport which are not considered by movement variables. / Aeroportos consomem grandes volumes de água e possuem grande potencial para a implementação de medidas de uso racional. Conhecer a demanda futura é essencial para avaliar investimentos destinados à ampliação de capacidade e o potencial benefício advindo da adoção dessas medidas. Para esses ambientes, no entanto, são poucos os estudos sobre o perfil de consumo de água, fatores que o influenciam e modelos para sua previsão. Portanto, os objetivos deste estudo foram avaliar a influência das variáveis de movimentação aeroportuária sobre o consumo de água e utilizá-las na obtenção de modelos de regressão linear múltipla para estimar este consumo. A base de dados disponibilizada pela Infraero contém informações sobre a movimentação anual de passageiros, voos, carga e mala postal, além do consumo anual de água para os principais aeroportos do Brasil. Os modelos foram desenvolvidos considerando a distinção dos aeroportos em termos de porte e categoria, e os coeficientes de determinação (R2) e de Nash-Sutcliffe (NSE) foram utilizados para avaliação do desempenho. Os modelos desenvolvidos considerando o porte apresentaram R² iguais a 0,81, para aeroportos de grande porte, e 0,62, para aeroportos de médio e pequeno porte. Para aeroportos que operam apenas voos domésticos, foi obtido um modelo linear simples com r² igual a 0,89; para aeroportos que operam voos internacionais e domésticos, o modelo apresentou R² igual a 0,90. Os coeficientes NSE foram 0,93 e 0,88 para os modelos considerando o porte e a categoria, respectivamente. O modelo desenvolvido especificamente para o Aeroporto de Confins-MG apresentou melhor desempenho (NSE = 0,98) e o potencial para viabilizar a inclusão de outras variáveis capazes de refletir características específicas de cada aeroporto não consideradas pelas variáveis de movimentação.

Weather forecasting models are computationally intensive applications and traditionally they are executed in parallel machines. However, some issues prevent these models from fully exploiting the available computing power. One of such issues is load imbalance, i.e., the uneven distribution of load across the processors of the parallel machine. Since weather models are typically synchronous applications, that is, all tasks synchronize at every time-step, the execution time is determined by the slowest task. The causes of such imbalance are either static (e.g. topography) or dynamic (e.g. shortwave radiation, moving thunderstorms). Various techniques, often embedded in the application’s source code, have been used to address both sources. However, these techniques are inflexible and hard to use in legacy codes. In this thesis, we explore the concept of processor virtualization for dynamically balancing the load in weather models. This means that the domain is over-decomposed in more tasks than the available processors. Assuming that many tasks can be safely executed in a single processor, each processor is put in charge of a set of tasks. In addition, the system can migrate some of them from overloaded processors to underloaded ones when it detects load imbalance. This approach has the advantage of decoupling the application from the load balancing strategy. Our objective is to show that processor virtualization can be applied to weather models as long as an appropriate strategy for migrations is used. Our proposal takes into account the communication pattern of the application in addition to the load of each processor. In this text, we present the techniques used to minimize the amount of change needed in order to apply processor virtualization to a real-world application. Furthermore, we analyze the effects caused by the frequency at which the load balancer is invoked and a threshold that activates rebalancing. We propose an automatic strategy to find an optimal threshold to trigger load balancing. These strategies are centralized and work well for moderately large machines. For larger machines, we present a fully distributed algorithm and analyze its performance. As a study case, we demonstrate the effectiveness of our approach for dynamically balancing the load in Brams, a mesoscale weather forecasting model based on MPI parallelization. We choose this model because it presents a considerable load imbalance caused by localized thunderstorms. In addition, we analyze how other effects of processor virtualization can improve performance.

A Dissertação apresenta as principais mudanças verificadas no Setor Elétrico Brasileiro e os seus reflexos nas atividades de planejamento e estudos de mercado. Examina os desafios do mercado de energia para as distribuidoras de energia elétrica, advindos com o dinamismo comercial e as obrigações institucionais provenientes do novo contexto setorial. Evidencia que os estudos de mercado podem apoiar significativamente as distribuidoras, necessitando para tanto, efetuar mudanças estruturais e metodológicas. A utilização de modelos baseados em usos finais de energia e técnicas de cenários é a mais adequada. / After the restructuring of the Brazilian power sector during the 1990’s, a new set of rules and players (regulators, traders, etc.) was introduced. This situation resulted in significantly impacting the distribution companies in terms of market risks and commercial opportunities. Electric power market assessments that provide fundamental information to the system and tariff planning groups can also be used to support the distribution companies in analyzing various questions within the new rules that have been created. These questions include such items as: How much energy should be contracted in the future in the wholesale market? How much opportunity is available in offering commercial services to the customer? This work describes the main changes that have occurred due to the restructuring, such as: the privatization process, a wholesale market implementation, rules for energy trading, and planning and regulatory process. The main challenges for distribution companies as a result of these changes are identified, especially focusing on energy trading in retail and wholesale markets. The process of electric power market assessments is presented and describing the accepted methodology used for demand forecasting for distribution companies. Information required by distribution companies in order to deal with the market challenges are specified – e.g. energy trading, market risks and customer relationship. It is concluded there is a need to obtain detailed information about consumers and to develop market forecast for specific time frame. It must take into consideration all the issues around the retail market – the study needs to analyze the basic factors that impact customer consumption. In order to improve the electric market assessment, it has been useful to apply specific models. After reviewing the existing tools for electric power market assessments (analysis and forecast), it has been found that the models that combined methods of end use analysis with scenario analysis are most effective. In this way, the distribution companies needs are met and the process also results in better market data for planning and regulatory agencies.

Weather forecasting models are computationally intensive applications and traditionally they are executed in parallel machines. However, some issues prevent these models from fully exploiting the available computing power. One of such issues is load imbalance, i.e., the uneven distribution of load across the processors of the parallel machine. Since weather models are typically synchronous applications, that is, all tasks synchronize at every time-step, the execution time is determined by the slowest task. The causes of such imbalance are either static (e.g. topography) or dynamic (e.g. shortwave radiation, moving thunderstorms). Various techniques, often embedded in the application’s source code, have been used to address both sources. However, these techniques are inflexible and hard to use in legacy codes. In this thesis, we explore the concept of processor virtualization for dynamically balancing the load in weather models. This means that the domain is over-decomposed in more tasks than the available processors. Assuming that many tasks can be safely executed in a single processor, each processor is put in charge of a set of tasks. In addition, the system can migrate some of them from overloaded processors to underloaded ones when it detects load imbalance. This approach has the advantage of decoupling the application from the load balancing strategy. Our objective is to show that processor virtualization can be applied to weather models as long as an appropriate strategy for migrations is used. Our proposal takes into account the communication pattern of the application in addition to the load of each processor. In this text, we present the techniques used to minimize the amount of change needed in order to apply processor virtualization to a real-world application. Furthermore, we analyze the effects caused by the frequency at which the load balancer is invoked and a threshold that activates rebalancing. We propose an automatic strategy to find an optimal threshold to trigger load balancing. These strategies are centralized and work well for moderately large machines. For larger machines, we present a fully distributed algorithm and analyze its performance. As a study case, we demonstrate the effectiveness of our approach for dynamically balancing the load in Brams, a mesoscale weather forecasting model based on MPI parallelization. We choose this model because it presents a considerable load imbalance caused by localized thunderstorms. In addition, we analyze how other effects of processor virtualization can improve performance.

Theme Master’s thesis was studying of wind energy power supply. Comparison of character of wind power supply in Czech Republic to power supply abroad. Thesis begins with short introduction of historical wind applications. It continues by theory of wind engines, the wind engines construction and its facilities. Next part describes wind energy characteristics and physics. It describes wind speed influence to power supply of wind turbine, a physical limits of wind engines efficiency. Later, meteorological forecast possibilities are mentioned. Following chapter classifies wind power plants by geographical locations and characterizes them. It presents and explains individual cases of wind energy business growth in Czech Republic and other countries. There are also mentioned many suitable locations for wind parks in Czech Republic. There are described data analysis methods in chapter number 5. Analysis results of day period graph and year period graphs are shown. Unsophisticated forecast model is sketched out and created in following chapter. Here the regressive analysis methods are described, such as Autoregressive moving average model (ARMA), which can bring satisfactory results. Another example is Markov switching autoregressive model (MSAR). Next step from statistic forecast models is to sophisticated large forecasting systems. Those systems require meteorological forecast data and historical wind power data. Data are analyzed by statistical models. They have been developed recently and they are ordinary used nowadays.

Forecasts are important to decision-making and risk assessment in many domains. There has been recent interest in integrating forecast queries inside a DBMS. Answering a forecast query requires the creation of forecast models. Creating a forecast model is an expensive process and may require several scans over the base data as well as expensive operations to estimate model parameters. However, if forecast queries are issued repeatedly, answer times can be reduced significantly if forecast models are reused. Due to the possibly high number of forecast queries, existing models need to be found quickly. Therefore, we propose a model index that efficiently stores forecast models and allows for the efficient reuse of existing ones. Our experiments illustrate that the model index shows a negligible overhead for update transactions, but it yields significant improvements during query execution.

Submitted by Michelle Chan (michellechan@bancobbm.com.br) on 2010-05-30T23:53:11Z No. of bitstreams: 1 dissertacao_MichelleChan.pdf: 348582 bytes, checksum: a78d92ef3ddcf4c0fd546de43352a06d (MD5) / Approved for entry into archive by Vitor Souza(vitor.souza@fgv.br) on 2010-05-31T13:33:26Z (GMT) No. of bitstreams: 1 dissertacao_MichelleChan.pdf: 348582 bytes, checksum: a78d92ef3ddcf4c0fd546de43352a06d (MD5) / Made available in DSpace on 2010-06-01T19:58:56Z (GMT). No. of bitstreams: 1 dissertacao_MichelleChan.pdf: 348582 bytes, checksum: a78d92ef3ddcf4c0fd546de43352a06d (MD5) Previous issue date: 2009-12-16 / The central purpose of this essay is to analyze the important variables of the inflation for the central bank’s monetary decision. Having in mind the importance of forward looking reaction of the monetary authorities in an inflation targeting regime, we study some short term inflation forecast models in order to find out which one has the most accurate prediction. In order to understand the brazilian inflacionary dinamics in these last years since the introduction of the inflation targeting regime, we analyse the dinamics of the inflation inercia and the passthrough. / O objetivo dessa dissertação é analisar as variáveis importantes da inflação para a decisão de política econômica do Banco Central. Considerando a importância de reações forward looking das autoridades monetárias num regime de metas de inflação, estudam-se alguns modelos de projeção de inflação de curto prazo para verificar qual modelo possui maior capacidade de previsão. Com o objetivo de entender a dinâmica inflacionária brasileira ao longo desses anos desde a implementação do sistema de metas de inflação, procura-se analisar a dinâmica da inércia inflacionária e do repasse cambial.

Conselho Nacional de Desenvolvimento CientÃfico e TecnolÃgico / Esse estudo se propÃe estimar a demanda por energia elÃtrica para as classes residencial, comercial e industrial na regiÃo Nordeste do Brasil, no perÃodo de 1970 a 2003. Utilizando as metodologias desenvolvidas por Stock e Watson (1993) e Gregory e Hansen (1996), respectivamente, DOLS e MudanÃa de Regime para obter as elasticidades-preÃo e renda de longo prazo. A partir dos vetores de cointegraÃÃo sÃo estimados os Modelos de CorreÃÃes de Erros, os quais fornecem a base para se fazer previsÃes de longo prazo, no perÃodo de 2004 a 2010. A partir dos resultados apresentados por este estudo, sÃo feitas comparaÃÃes das elasticidades-preÃo e renda de curto e longo prazo com demais estudos para o Brasil, bem como para as previsÃes feitas pela EletrobrÃs e por Siqueira, Cordeiro Jr. e Castelar (2006). As metodologias utilizadas nesse estudo, apresentam previsÃes mais acuradas do que os demais estudos para os anos de 2004 a 2006. / The objective of this research is to estimate the residential, commercial and industrial demand for electric energy in the Northeast region of Brazil during the period of 1970 2003. Two different methodologies were used to compute the price and income elasticity of demand: i) DOLS, proposed by Stock and Watson (1993); and ii) Regime Switching by Gregory and Hansen (1996). Error Correction Models are estimated from the cointegration vectors. These models are used to perform long-run forecasts of the electricity demand for the period 2004- 2010. The results are then compared to those from other researches about Brazilianâs price and income elasticity of demand for electric energy. Furthermore, the computed forecasts are compared to those from EletrobrÃs and from Siqueira, Cordeiro Jr. e Castelar (2006). The methodologies used in this work present forecasts that are more accurate than those ones from nother works for the period 2004-2006.

With a changing global climate, plant pathologists must understand the impact aberrant weather events may have on the development of plant diseases. Fungal plant infections are largely dependent on temperature and precipitation, climate parameters that are predicted to change more in this century. Venturia inaequalis causes apple scab, one of the most destructive apple diseases of temperate growing regions. Temperature and precipitation drive apple scab infections and forecast models, which guide growers in efficient, effective fungicide applications. In some recent years in the Northeast, these models have failed to accurately predict when ascospores of this fungus are available to cause primary infections, prompting more fungicide intensive management. Identifying cause(s) of model failures will restore confidence in them, enabling growers to reduce fungicide use. As technology becomes an increasingly important component of on farm decision-making, so does educating new farmers and agricultural students in the benefits of Integrated Pest Management and challenges associated with models early on in their college educational experience. This research attempts to identify reasons for ascospore maturity model failures, determine to what degree critical ascospore maturity parameters have changed and create a tool that educators may use to engage undergraduate students in the complexities of Integrated Pest Management research and modern farming. It will more specifically do the following: 1) Dry periods will be analyzed to determine if frequency and duration are increasing, causing the fungus to mature over a longer period of time than models currently estimate. 2) Degree-days during fall and winter will be examined to estimate what effect a warming climate may have on ascospore and tree development, and ultimately apple scab occurrence. The research will use lab and field observations to track the development of V. inaequalis ascospores, the source of primary apple scab infections. These observations will be compared to infection events and spore maturation forecasts from models currently used by apple growers in the Northeast. 3) A case study developed for publication in American Phytopathological Societies’ Plant Health Instructor will provide early career college students with an introduction to forecasting models, Integrated Pest Management and the challenges associated with climate variability.