Influence of vegetable oil in the viscosity of biodiesel-a review

Viscosity is a measure fluid resistance to flowing, affecting the fuel spray in the combustion chamber and, by this way, thus the formation of carbon deposits. The analysis of the influence of vegetable oil viscosity in biodiesel seems appropriate, because biodiesel viscosity is a function of vegetable oil. The increase of the fuel viscosity, promoted by biodiesel, has a major impact on the dynamics of jet fuel, increasing its speed and distance of penetration, obtaining therefore an increase in the amount of turbulent movement of the jet and thus an increase in the rate of preparation of the mixture, air-fuel, when adding biodiesel to diesel oil. The negative effect of this higher fuel viscosity is the increase of the wear of the train of gears, cam shaft, and valve push rod of all the injection pumps due to the higher pressure of injection. The viscosity of biodiesel is influenced by the size of its molecule and by the increase of molecule insaturations, is directly related with its origin vegetable oil or fat. This study is a review of the influence of vegetable oils in viscosity of biodiesel. Copyright © 2008 SAE International.

Avaliação de frequências não convencionais na obtenção de curvas de DMA de compósitos poliméricos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise de um sistema de cogeração empregando turbina a gás aplicada a uma indústria de malte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Previsão multi-passos a frente do preço de energia elétrica de curto prazo no mercado brasileiro

A predição do preço da energia elétrica é uma questão importante para todos os participantes do mercado, para que decidam as estratégias mais adequadas e estabeleçam os contratos bilaterais que maximizem seus lucros e minimizem os seus riscos. O preço da energia tipicamente exibe sazonalidade, alta volatilidade e picos. Além disso, o preço da energia é influenciado por muitos fatores, tais como: demanda de energia, clima e preço de combustíveis. Este trabalho propõe uma nova abordagem híbrida para a predição de preços de energia no mercado de curto prazo. Tal abordagem combina os filtros autorregressivos integrados de médias móveis (ARIMA) e modelos de Redes Neurais (RNA) numa estrutura em cascata e utiliza variáveis explanatórias. Um processo em dois passos é aplicado. Na primeira etapa, as variáveis explanatórias são preditas. Na segunda etapa, os preços de energia são preditos usando os valores futuros das variáveis exploratórias. O modelo proposto considera uma predição de 12 passos (semanas) a frente e é aplicada ao mercado brasileiro, que possui características únicas de comportamento e adota o despacho centralizado baseado em custo. Os resultados mostram uma boa capacidade de predição de picos de preço e uma exatidão satisfatória de acordo com as medidas de erro e testes de perda de cauda quando comparado com técnicas tradicionais. Em caráter complementar, é proposto um modelo classificador composto de árvores de decisão e RNA, com objetivo de explicitar as regras de formação de preços e, em conjunto com o modelo preditor, atuar como uma ferramenta atrativa para mitigar os riscos da comercialização de energia.

Caracterização isotópica do CO2 dissolvido em águas subterrâneas no município de Paulínia, SP

Pós-graduação em Geociências e Meio Ambiente - IGCE

Obtenção e caracterização de compósitos de benzoxazina/fibra de carbono

Pós-graduação em Engenharia Mecânica - FEG

Estudo da efetividade da atenuação natural de compostos BTEX em área contaminada por querosene de aviação

Pós-graduação em Geociências e Meio Ambiente - IGCE

Impactos Operacionais das Alterações no Contrato Futuro de Milho da BM&F-Bovespa na Mitigação de Risco

O mercado de milho possui importante participação no cenário agropecuário nacional, pela relevância dentro da indústria de carnes. Destacam-se as estratégias de comercialização do grão, em especial as relacionadas à mitigação do risco de preço com o uso de contratos futuros. Objetiva-se identificar e interpretar os efeitos causados pela modificação no contrato futuro do milho negociado na BM&F-Bovespa, que em setembro de 2008 passou de entrega física para liquidação financeira, sobre o desempenho do mercado futuro do grão comercializado. Avaliam-se a liquidez dos contratos, a volatilidade dos preços futuros e físico do milho, bem como a convergência da base. Identificaram-se como possíveis efeitos da alteração contratual o aumento da liquidez do contrato futuro de milho e a redução da volatilidade dos preços, além da melhoria na convergência da base. Os resultados alinham-se com a teoria e evidenciam impacto positivo da implementação da liquidação financeira no contrato futuro de milho.

Development of an optimization model for biofuel facility size and location and a simulation model for design of a biofuel supply chain

To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

LIFE CYCLE ASSESSMENT OF BIOFUEL PRODUCED FROM ALGAE

Algae are considered a promising source of biofuels in the future. However, the environmental impact of algae-based fuel has high variability in previous LCA studies due to lack of accurate data from researchers and industry. The National Alliance for Advanced Biofuels and Bioproducts (NAABB) project was designed to produce and evaluate new technologies that can be implemented by the algal biofuel industry and establish the overall process sustainability. The MTU research group within NAABB worked on the environmental sustainability part of the consortium with UOP-Honeywell and with the University of Arizona (Dr. Paul Blowers). Several life cycle analysis (LCA) models were developed within the GREET Model and SimaPro 7.3 software to quantitatively assess the environment viability and sustainability of algal fuel processes. The baseline GREET Harmonized algae life cycle was expanded and replicated in SimaPro software, important differences in emission factors between GREET/E-Grid database and SimaPro/Ecoinvent database were compared, and adjustments were made to the SimaPro analyses. The results indicated that in most cases SimaPro has a higher emission penalty for inputs of electricity, chemicals, and other materials to the algae biofuels life cycle. A system-wide model of algae life cycle was made starting with preliminary data from the literature, and then progressed to detailed analyses based on inputs from all NAABB research areas, and finally several important scenarios in the algae life cycle were investigated as variations to the baseline scenario. Scenarios include conversion to jet fuel instead of biodiesel or renewable diesel, impacts of infrastructure for algae cultivation, co-product allocation methodology, and different usage of lipid-extracted algae (LEA). The infrastructure impact of algae cultivation is minimal compared to the overall life cycle. However, in the scenarios investigating LEA usage for animal feed instead of internal recycling for energy use and nutrient recovery the results reflect the high potential variability in LCA results. Calculated life cycle GHG values for biofuel production scenarios where LEA is used as animal feed ranged from a 55% reduction to 127% increase compared to the GREET baseline scenario depending on the choice of feed meal. Different allocation methods also affect LCA results significantly. Four novel harvesting technologies and two extraction technologies provided by the NAABB internal report have been analysis using SimaPro LCA software. The results indicated that a combination of acoustic extraction and acoustic harvesting technologies show the most promising result of all combinations to optimize the extraction of algae oil from algae. These scenario evaluations provide important insights for consideration when planning for the future of an algae-based biofuel industry.

Live Cattle Futures and Options: How Have They Done?

Futures did reduce price risk. Hedging produced a higher minimum return and higher return at the 25th percentile (75% of the returns are better than this figure) than did the cash market. The 50th percentile, or median return, was higher for yearlings in the cash market than hedged cattle, and the calves had mixed results. Although the differences are not great, there have been months when the option strategies performed better than cash or futures, (i.e., January–April and September–October), and there are months when they did not fare well (i.e., June–August).

Viability study of sailing propulsion combined with a conventional system

For many years now, sails have been used as a propulsion system. At present, they are restricted to recreational/sport crafts since the appearance of the first steam vessels in the beginning of the 19 th century. But in the last years, due to the increase of fuel price and the pollution of the environment, it is being studied the possibility to introduce again the sail as a propulsive method combined with other conventional systems. In this paper, it is studied the viability of using a sail as a propellant with other conventional systems of propulsion. After considering the concept of apparent wind, the range of use of this complementary propulsion is presented. The calculation methodology, the numerical simulations and the wind inputs from a specific route are also included.

Compatibilidad de materiales con las mezclas de bioqueroseno de coco, babasú y palmiste con queroseno comercial

Actualmente existe un gran interés por ampliar las fuentes de energías alternativas para aviación y conseguir con ello una reducción de la huella de carbono y de la fuerte dependencia energética de los combustibles fósiles en diferentes países. Por ello, se están llevando a cabo muchos estudios de investigación que tienen por objetivo la conversión de la materia prima vegetal o biomasa en una nueva fuente de energía. Sin embargo, la sustitución exitosa de los combustibles derivados del petróleo por biocombustibles, requiere el cumplimiento de unos requisitos estrictos, y unas propiedades adecuadas. Este proyecto estudia la compatibilidad de materiales con las mezclas de bioqueroseno de coco (CBK20), babasú (BBK20) y palmiste (PBK20), con queroseno comercial Jet A-1 (K-2). Los materiales estudiados son poliméricos, metálicos y composites de aviación que forman parte del sistema combustible del avión. Este estudio pretende demostrar que tanto los materiales utilizados, como los combustibles investigados, son compatibles cuando se encuentran en contacto a cierta temperatura. Para ello, se han comparado sus propiedades siguiendo las normas de referencia establecidas. ABSTRACT Currently there is a strong interest to expand alternative energy sources for aviation and thereby achieve a reduction in carbon footprint and the strong energy dependence on fossil fuels in different countries. It is therefore being carried out many researches based on the conversion of vegetable feedstock in a new energy source. However, a successful replacement of petroleum fuels with biofuels, requires compliance with strict requirements and suitable properties. This project studies the materials compatibility with blends of coconut (CBK20), babassu (BBK20) and palm kernel (PBK20) biokerosene with commercial aviation jet fuel Jet A-1 (K-2). Polymeric and elastomeric materials, metals and aviation composites has been studied as part of the aircraft fuel system. The objective of this study is to demonstrate that both, the tested materials and the fuels investigated, are compatible when they are in contact at a certain temperature. For this reason, materials and kerosene properties have been compared using the standard test methods

Optimización del consumo de combustible de un vehículo dependiendo de las condiciones de la carretera

El consumo de combustible en un automóvil es una característica que se intenta mejorar continuamente debido a los precios del carburante y a la creciente conciencia medioambiental. Esta tesis doctoral plantea un algoritmo de optimización del consumo que tiene en cuenta las especificaciones técnicas del vehículo, el perfil de orografía de la carretera y el tráfico presente en ella. El algoritmo de optimización calcula el perfil de velocidad óptima que debe seguir el vehículo para completar un recorrido empleando un tiempo de viaje especificado. El cálculo del perfil de velocidad óptima considera los valores de pendiente de la carretera así como también las condiciones de tráfico vehicular de la franja horaria en que se realiza el recorrido. El algoritmo de optimización reacciona ante condiciones de tráfico cambiantes y adapta continuamente el perfil óptimo de velocidad para que el vehículo llegue al destino cumpliendo el horario de llegada establecido. La optimización de consumo es aplicada en vehículos convencionales de motor de combustión interna y en vehículos híbridos tipo serie. Los datos de consumo utilizados por el algoritmo de optimización se obtienen mediante la simulación de modelos cuasi-estáticos de los vehículos. La técnica de minimización empleada por el algoritmo es la Programación Dinámica. El algoritmo divide la optimización del consumo en dos partes claramente diferenciadas y aplica la Programación Dinámica sobre cada una de ellas. La primera parte corresponde a la optimización del consumo del vehículo en función de las condiciones de tráfico. Esta optimización calcula un perfil de velocidad promedio que evita, cuando es posible, las retenciones de tráfico. El tiempo de viaje perdido durante una retención de tráfico debe recuperarse a través de un aumento posterior de la velocidad promedio que incrementaría el consumo del vehículo. La segunda parte de la optimización es la encargada del cálculo de la velocidad óptima en función de la orografía y del tiempo de viaje disponible. Dado que el consumo de combustible del vehículo se incrementa cuando disminuye el tiempo disponible para finalizar un recorrido, esta optimización utiliza factores de ponderación para modular la influencia que tiene cada una de estas dos variables en el proceso de minimización. Aunque los factores de ponderación y la orografía de la carretera condicionan el nivel de ahorro de la optimización, los perfiles de velocidad óptima calculados logran ahorros de consumo respecto de un perfil de velocidad constante que obtiene el mismo tiempo de recorrido. Las simulaciones indican que el ahorro de combustible del vehículo convencional puede lograr hasta un 8.9% mientras que el ahorro de energía eléctrica del vehículo híbrido serie un 2.8%. El algoritmo fusiona la optimización en función de las condiciones del tráfico y la optimización en función de la orografía durante el cálculo en tiempo real del perfil óptimo de velocidad. La optimización conjunta se logra cuando el perfil de velocidad promedio resultante de la optimización en función de las condiciones de tráfico define los valores de los factores de ponderación de la optimización en función de la orografía. Aunque el nivel de ahorro de la optimización conjunta depende de las condiciones de tráfico, de la orografía, del tiempo de recorrido y de las características propias del vehículo, las simulaciones indican ahorros de consumo superiores al 6% en ambas clases de vehículo respecto a optimizaciones que no logran evitar retenciones de tráfico en la carretera. ABSTRACT Fuel consumption of cars is a feature that is continuously being improved due to the fuel price and an increasing environmental awareness. This doctoral dissertation describes an optimization algorithm to decrease the fuel consumption taking into account the technical specifications of the vehicle, the terrain profile of the road and the traffic conditions of the trip. The algorithm calculates the optimal speed profile that completes a trip having a specified travel time. This calculation considers the road slope and the expected traffic conditions during the trip. The optimization algorithm is also able to react to changing traffic conditions and tunes the optimal speed profile to reach the destination within the specified arrival time. The optimization is applied on a conventional vehicle and also on a Series Hybrid Electric vehicle (SHEV). The fuel consumption optimization algorithm uses data obtained from quasi-static simulations. The algorithm is based on Dynamic Programming and divides the fuel consumption optimization problem into two parts. The first part of the optimization process reduces the fuel consumption according to foreseeable traffic conditions. It calculates an average speed profile that tries to avoid, if possible, the traffic jams on the road. Traffic jams that delay drivers result in higher vehicle speed to make up for lost time. A higher speed of the vehicle within an already defined time scheme increases fuel consumption. The second part of the optimization process is in charge of calculating the optimal speed profile according to the road slope and the remaining travel time. The optimization tunes the fuel consumption and travel time relevancies by using two penalty factors. Although the optimization results depend on the road slope and the travel time, the optimal speed profile produces improvements of 8.9% on the fuel consumption of the conventional car and of 2.8% on the spent energy of the hybrid vehicle when compared with a constant speed profile. The two parts of the optimization process are combined during the Real-Time execution of the algorithm. The average speed profile calculated by the optimization according to the traffic conditions provides values for the two penalty factors utilized by the second part of the optimization process. Although the savings depend on the road slope, traffic conditions, vehicle features, and the remaining travel time, simulations show that this joint optimization process can improve the energy consumption of the two vehicles types by more than 6%.

Toxicological profile for JP-5 and JP-8 : draft /

"Comment period ends: January 27, 1997."--Cover.