1000 resultados para Previsão de demanda
Resumo:
Foi avaliado o consumo energético das operações mecanizadas envolvidas na produção de silagem de planta inteira e silagem de grão úmido de milho, tendo como referência o processamento seco desse cereal. O ensaio foi conduzido na Fazenda Experimental Lageado, pertencente à Faculdade de Ciências Agronômicas, e nas instalações da Faculdade de Medicina Veterinária e Zootecnia - UNESP, localizada no município de Botucatu - SP. O delineamento experimental foi em blocos ao acaso, com parcelas subdivididas no tempo (três épocas de colheita: silagem de planta inteira, silagem de grão úmido e colheita de grãos secos), com 10 repetições. As análises estatísticas foram realizadas por meio do programa ESTAT, pelo teste de média de Tukey, a 5% de probabilidade. A silagem de planta inteira teve o maior consumo de combustível por área. A secagem dos grãos de 15,5% para 13% foi responsável por 87% do gasto de energia por área. A silagem de grão úmido demandou o menor uso de energia por área nas operações mecanizadas.
Resumo:
The correct selection of the operational sequence of soil tillage is essential to reduce the cost of agricultural mechanization in the regions that mobilize intensively the soil. The objective of this work was to evaluate the energetic demand and disaggregation of the soil in different operational sequences of subsoiling and systems of periodic soil tillage. The experimental design was blocks at random, in a factorial model 5 x 2 with 5 replications, being 5 tillage systems (D - Disc plow, Dn - disc plow followed at leveler rail, G - weight rail, Gn - weight rail followed of leveler rail and E - Stirrer.) and two sequencies of subsoiling (SP - Subsoiling - tillage and PS - Tillage - subsoiling). There were evaluated the energetic demand, fuel consumption by area and the soil disaggregation. The results showed that the operational sequence tillage of the soil subsoiling (PS) had a lower energetic requirement, except for the stirrer, the sequence tillage the soil - subsoiling consumed less fuel and soil disaggregation didn't show statistic variation.
Resumo:
Both the inadequate use and the ignorance of the different soil tillage implements available in the home market has become one of the leading motives of failures, related to soil and water conservation. The periodical tillage is traditionally utilized after subsoiling for soil clod breaking, leveling and residue incorporation. This work aimed to evaluate the energy requirement for different periodical soil tillage systems performed before and after subsoiling in a soil classified as Distroferric Red Nitosol. The periodic tillage systems were: disk plowing; disk plowing plus one leveling harrowing; disk harrow; disk harrow plus leveling harrowing stirring. The experimental design was a 5x2 factorial scheme with 5 completely randomized blocks. The results show that the periodic soil preparation systems based on disks have better energy efficiency when performed before the operation of subsoiling. The system of soil preparation with harrowing obtained the lower energy demand, in relation to other periodic soil preparation systems, when done after subsoiling.
Resumo:
This work aims to predict the total maximum demand of a transformer that will be used in power systems to attend a Multiple Unit Consumption (MUC) in design. In 1987, COSERN noted that calculation of maximum total demand for a building should be different from that which defines the scaling of the input protection extension in order to not overestimate the power of the transformer. Since then there have been many changes, both in consumption habits of the population, as in electrical appliances, so that this work will endeavor to improve the estimation of peak demand. For the survey, data were collected for identification and electrical projects in different MUCs located in Natal. In some of them, measurements were made of demand for 7 consecutive days and adjusted for an integration interval of 30 minutes. The estimation of the maximum demand was made through mathematical models that calculate the desired response from a set of information previously known of MUCs. The models tested were simple linear regressions, multiple linear regressions and artificial neural networks. The various calculated results over the study were compared, and ultimately, the best answer found was put into comparison with the previously proposed model
Resumo:
The opening of the Brazilian market of electricity and competitiveness between companies in the energy sector make the search for useful information and tools that will assist in decision making activities, increase by the concessionaires. An important source of knowledge for these utilities is the time series of energy demand. The identification of behavior patterns and description of events become important for the planning execution, seeking improvements in service quality and financial benefits. This dissertation presents a methodology based on mining and representation tools of time series, in order to extract knowledge that relate series of electricity demand in various substations connected of a electric utility. The method exploits the relationship of duration, coincidence and partial order of events in multi-dimensionals time series. To represent the knowledge is used the language proposed by Mörchen (2005) called Time Series Knowledge Representation (TSKR). We conducted a case study using time series of energy demand of 8 substations interconnected by a ring system, which feeds the metropolitan area of Goiânia-GO, provided by CELG (Companhia Energética de Goiás), responsible for the service of power distribution in the state of Goiás (Brazil). Using the proposed methodology were extracted three levels of knowledge that describe the behavior of the system studied, representing clearly the system dynamics, becoming a tool to assist planning activities
Resumo:
The aim of this study is to create an artificial neural network (ANN) capable of modeling the transverse elasticity modulus (E2) of unidirectional composites. To that end, we used a dataset divided into two parts, one for training and the other for ANN testing. Three types of architectures from different networks were developed, one with only two inputs, one with three inputs and the third with mixed architecture combining an ANN with a model developed by Halpin-Tsai. After algorithm training, the results demonstrate that the use of ANNs is quite promising, given that when they were compared with those of the Halpín-Tsai mathematical model, higher correlation coefficient values and lower root mean square values were observed
Resumo:
Anhydrous ethanol is used in chemical, pharmaceutical and fuel industries. However, current processes for obtaining it involve high cost, high energy demand and use of toxic and pollutant solvents. This problem occurs due to the formation of an azeotropic mixture of ethanol + water, which does not allow the complete separation by conventional methods such as simple distillation. As an alternative to currently used processes, this study proposes the use of ionic liquids as solvents in extractive distillation. These are organic salts which are liquids at low temperatures (under 373,15 K). They exhibit characteristics such as low volatility (almost zero/ low vapor ), thermal stability and low corrosiveness, which make them interesting for applications such as catalysts and as entrainers. In this work, experimental data for the vapor pressure of pure ethanol and water in the pressure range of 20 to 101 kPa were obtained as well as for vapor-liquid equilibrium (VLE) of the system ethanol + water at atmospheric pressure; and equilibrium data of ethanol + water + 2-HDEAA (2- hydroxydiethanolamine acetate) at strategic points in the diagram. The device used for these experiments was the Fischer ebulliometer, together with density measurements to determine phase compositions. The experimental data were consistent with literature data and presented thermodynamic consistency, thus the methodology was properly validated. The results were favorable, with the increase of ethanol concentration in the vapor phase, but the increase was not shown to be pronounced. The predictive model COSMO-SAC (COnductor-like Screening MOdels Segment Activity Coefficient) proposed by Lin & Sandler (2002) was studied for calculations to predict vapor-liquid equilibrium of systems ethanol + water + ionic liquids at atmospheric pressure. This is an alternative for predicting phase equilibrium, especially for substances of recent interest, such as ionic liquids. This is so because no experimental data nor any parameters of functional groups (as in the UNIFAC method) are needed
Resumo:
Piranhas-Açu basin is a Federal watershed with a drainage area of 43.681,5 km2, sited at Brazilian northeast semi arid, with 60% of your area in Paraiba State and 40% in Rio Grande do Norte State. The main river, Piranhas-Açu, has strategic importance for development of these states, because it s an essential source for many socio-economics activities developed along watercourse. The river s reach between Coremas-Mãe D`água Dam and Armando Ribeiro Gonçalves Dam has many irrigation projects, and supply many riverside cities. All this activities practiced in this river s reach consumes high water volumes. Due the importance of this stream and the necessity of an adequate management, this work aims for an impartial and detailed evaluation of real water supply conditions in this river s reach, by the application of hydrological modeling, including the arrangement of main dams in tributaries, and storage reservoir water balance. The rainfall-discharge model s applied in each sub-basins it was selected the model MODHISA- Hydrological Model of Semi Arid, that is a concentrated model with easy application. The simulation produced 50 years of inflows into the reservoirs, for which, were constructed the guaranties curves; and produced 50 years of synthetic discharge data in relevant points on the river and on its affluents; so it was constructed the permanence curves. Confronting the available discharge with the current and futures volumes of raw water captured in this river s reach, it was verified that de demands have high guaranties. This work concluded that the MODHISA Model is suitable to reproduce the hydrologic characteristics of Piranhas-Açu sub-basins, and showing good results
Resumo:
A Center for Weather Forecast and Climatic Studies of National Institute for Space Research (CPTEC/INPE) has provided to the Brazilian Geodetic community, since 2004, an alternative to correct the GNSS observables from the tropospheric refraction. Numerical Weather Prediction (NWP) Model is used to generate Zenital Tropospheric Delay (ZTD). For the version 1, it was developed a model with horizontal resolution of 100 km, which was updated with Eta model, with resolution of 20 km. This paper provides the most significative details of the current version, as well an evaluation of its quality, using for such ZTD estimates from GPS data collect at RBMC. Comparing to the old version, considerable improvement could be observed from the new model, mainly in Brasilia and Curitiba, reaching up to 55% improvement. When all stations were used in the quality control, almost null bias and RMS of about 4 to 5 cm could be observed.
Resumo:
Propõe-se metodologia analítica para a determinação da demanda química de oxigênio(DQO) em águas e efluentes pouco poluídos, pela espectrofotometria simultânea dos íons crômio(III) e dicromato, após a clássica oxidação sulfocrômica das amostras, à quente e catalisada por íons Ag+. Demonstra-se que a inter-relação entre as concentrações de DQO, de crômio(III) formado e de dicromato residual permite simplificar a resolução numérica do sistema - de multicomponente, envolvendo as concentrações desses dois íons, e medidas de absorbância em pelo menos dois comprimentos de onda para monocomponente, envolvendo diretamente a concentração em DQO, e medida de absorbância num único comprimento de onda.
Resumo:
The tree-frog Phyllomedusa ayeaye is a rare species. With its distribution mostly unknown in the southeastern region of Brazil, it is considered one of the most threatened anurans in the country. Here we use ecological niche modelling from only three known occurrence points to produce predictive maps of the distribution of this species, which should help target new field surveys in areas of occurrence predicted by the model. This is the first study in Brazil that uses ecological niche modelling as a tool for predicting the distribution of rare and threatened amphibian anuran species.
Resumo:
Um sistema de previsão numérica de tempo e de ondas oceânicas (SPTO) que possa ser operacionalizado no Atlântico Sul é proposto. O SPTO é composto por um modelo atmosférico de área limitada (MAL) e um modelo de ondas de superfície do oceano geradas pelo vento, aplicado em duas versões: uma de malha grossa (MPOMG) e outra de malha fina (MPOMF). O MPOMG abrange uma área de 10(6) km², e tem como finalidade gerar e propagar ondas em regiões remotas à costa brasileira. O MPOMF é aplicado em um domínio 10(4) km² com alta resolução, incorporando irregularidades batimétricas e com as condições iniciais e de fronteiras fomecidas pelo MPOMG. Os modelos utilizam dados de vento à 10 m acima da superfície do oceano. Os arquivos de vento, contendo a evolução espacial e temporais são gerados pelo MAL. Um exemplo de um evento real ocorrido no período de 9 a 11 de agosto de 1988 é apresentado utilizando o acoplamento proposto.
Resumo:
Oxigênio dissolvido (OD), demanda bioquímica do oxigênio (DBO) e demanda química do oxigênio (DQO) foram utilizados como parâmetros para se avaliar o grau e capacidade de autodepuração do ribeirão Lavapés, que atravessa a cidade de Botucatu - SP. Avaliou-se o perfil de poluição orgânica e identificadas as zonas de autodepuração, e pontualmente foi realizado uma coleta de 24 horas, de hora em hora, onde foi possível correlacionar a poluição orgânica com as atividades domésticas. A DQO mostrou-se como a melhor técnica para avaliar o perfil de poluição orgânica, identificar as zonas de depuração, e para avaliar a poluição orgânica, neste curso d água. A relação DQO/DBO foi em média 3,4 caracterizando um esgoto biodegradável, indicando que praticamente não existe adição de efluentes industriais, permitindo assim estimar a DBO através da DQO. Nos trechos de água limpa, nascente e foz, em que a DQO estava abaixo de 5 mg L-1 O2, foram utilizados os valores de oxigênio consumido (método do permanganato), o que não invalidou a identificação das zonas de depuração. No entanto pesquisas para desenvolver o método de DQO (dicromato) para baixas concentrações, abaixo de 5 mg L-1 são necessárias para uma melhor avaliação da recuperação do curso d água.
Resumo:
No Brasil, o uso de vários modelos de criação intensiva e semi-extensiva desfavorece a adoção generalizada de métodos de manejo do gado bovino, principalmente do gado leiteiro. Mesmo assim, a produção leiteira pode ser melhorada a partir do uso de tecnologias que possam garantir o manejo adequado do rebanho. O objetivo deste trabalho foi desenvolver um índice de previsão de produção de leite para vacas Jersey em lactação, de genética de alta produtividade, em regime semi-estabulado, nas condições tropicais. Para a obtenção do índice, consideraram-se a temperatura e a umidade relativa do ambiente e a velocidade do ar, assim como valores de precipitação pluviométrica, temperatura do solo do pasto e a radiação solar como agentes estressores, os quais podem alterar a produção de leite. O experimento considerou dois tratamentos: A - as vacas permaneceram em sala de espera guarnecida com chuveiro e ventiladores, por um período 30 min antes da ordenha; B - as vacas não tiveram acesso a essa sala de espera (controle). Fora do período de ordenha, as vacas tiveram acesso ao pasto. Observou-se que as diferenças de médias de produção entre os tratamentos não foram estatisticamente significativas. Foram procedidas as análises para efeito de elaboração do modelo e chegou-se a um modelo factível, considerando a relação entre produção e a precipitação, assim como a temperatura máxima do solo do pasto.
Resumo:
Uma equação de regressão múltipla MOS (da sigla em inglês para Model Output Statistics), para previsão da temperatura mínima diária do ar na cidade de Bauru, estado de São Paulo, é desenvolvida. A equação de regressão múltipla, obtida usando análise de regressão stepwise, tem quatro preditores, três do modelo numérico global do Centro de Previsão de Tempo e Estudos Climáticos (CPTEC) e um observacional da estação meteorológica do Instituto de Pesquisas Meteorológicas (IPMet), Bauru. Os preditores são prognósticos para 24 horas do modelo global, válidos para 00:00GMT, da temperatura em 1000hPa, vento meridional em 850hPa e umidade relativa em 1000hPa, e temperatura observada às 18:00GMT. Esses quatro preditores explicam, aproximadamente, 80% da variância total do preditando, com erro quadrático médio de 1,4°C, que é aproximadamente metade do desvio padrão da temperatura mínima diária do ar observada na estação do IPMet. Uma verificação da equação MOS com uma amostra independente de 47 casos mostra que a previsão não se deteriora significativamente quando o preditor observacional for desconsiderado. A equação MOS, com ou sem esse preditor, produz previsões com erro absoluto menor do que 1,5°C em 70% dos casos examinados. Este resultado encoraja a utilização da técnica MOS para previsão operacional da temperatura mínima e seu desenvolvimento para outros elementos do tempo e outras localidades.