A requirement for thermophysical property data of diesel fuels at conditions removed from ambient was identified. A series of measurements of the pressure-volume-temperature relations of diesel fuels was undertaken using a Micro-PVT apparatus at pressures to 300MPa in the temperature range 25 to 75°C. A new calibration procedure for this instrument was devised to enable measurements of high accuracy to be made. Viscosity measurements of diesel fuels over a range of temperature and pressure were made using the National Engineering Laboratory high pressure viscometer to pressures of 460MPa in the temperature range 25 to 100°C.Corresponding states theory was applied for compressed liquid density prediction. Improvement in density prediction in this region was found through use of iso-octane and heptadecane as reference fluids. Compressibility factors of these were represented by Tait-style equations. An iterative solution technique was developed to allow the corresponding states method to be applied to diesel fuelsusing limited density measurement and a guess value of boiling point as inputs. Densities predicted from this method agreed well with measurements made using the Micro-PVT apparatus. Hard sphere theory was applied as a method for viscosity prediction. Despite the complexity of the diesel fuel mixture, reasonable estimates of viscosity were made with limited measurement input at higher temperatures. At lower temperatures, an additional simple empirical correction term was required. A method of viscosity estimation of complex hydrocarbon mixtures based upon composition is presented. Further development of this would require additional measurements and greater characterisation of the fuel.

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Orientador: José Eduardo de Oliveira / Banca: Marcos Roberto Monteiro / Banca: Danilo Luiz Flumignan / Resumo: Tendo em vista que o óleo diesel é o derivado energético do petróleo mais consumido no Brasil, torna-se imprescindível o desenvolvimento de métodos de monitoramento capazes de avaliar a qualidade deste combustível de forma rápida, econômica e não destrutiva. Deste modo, este trabalho teve como objetivo o desenvolvimento de modelos quimiométricos com capacidade de estimar os parâmetros físico-químicos do óleo diesel (mistura B5) através de análises espectroscópicas nas regiões do infravermelho médio e próximo. Os parâmetros físico-químicos estimados foram: teor de biodiesel; massa específica; pontos de ebulição das frações 10%, 50% e 85% destiladas, índice de cetano; enxofre total e ponto de fulgor. Em oito meses, 409 amostras de óleo diesel S1800 e S500 da região Centro-Oeste Paulista foram selecionadas de forma representativa por Análise Hierárquica de Agrupamento e divididas em conjuntos de calibração (273 amostras) e validação (136 amostras). Os valores de referência foram obtidos por meio de ensaios realizados utilizando-se métodos ABNT e ASTM, estabelecidos na Resolução ANP Nº 65 de 2011. Os modelos de calibração foram desenvolvidos através dos métodos de regressão Mínimos Quadrados Parciais (PLS) e Regressão por Componentes Principais (PCR), avaliando-se o uso de pré-processamentos de dados e seleção de faixas espectrais. A validação dos modelos demonstrou que a eliminação de faixas espectrais ruidosas e o uso de derivação e suavização dos dados centrados na média resultaram em modelos mais ajustados, com maior coeficiente de correlação e menor erro de predição. Todos os modelos PLS desenvolvidos em ambas as regiões do infravermelho apresentaram valores de exatidão e precisão aceitáveis quando comparados aos valores de reprodutibilidade e repetibilidade dos... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Given that diesel is the most consumed petroleum derived fuel in Brazil, it is essential to develop monitoring methods capable of evaluating the quality of this fuel in a fast, economical and non-destructive analysis. Thus, this study aimed to develop chemometric models capable of estimating the physicochemical parameters of diesel (B5 blend) by spectroscopic analysis in the mid-infrared and near regions. The physicochemical parameters estimated were: biodiesel content, density, distillation temperatures at 10%, 50% and 85% recovery, cetane number, total sulfur, and flash point. In eight months, 409 samples of diesel S1800 and S500 of the Centro-Oeste Paulista region were representatively selected by Hierarchical Cluster Analysis and divided into sets of calibration (273 samples) and validation (136 samples). The reference values were obtained from tests using ABNT and ASTM methods, established in Resolution ANP Nº 65 of 2011. The calibration models were developed through regression methods Partial Least Squares (PLS) and Principal Component Regression (PCR), and the use of pre-processing data and selection of spectral regions were evaluated. Validation of the models demonstrated that the elimination of noisy spectral regions and the use of derivative, smooth and mean center data resulted in fitted models with higher correlation coefficient and lowers prediction error. All developed PLS models in both regions of the infrared showed acceptable values of accuracy and precision when compared to the values of reproducibility and repeatability of the reference methods. So the use of infrared spectroscopy coupled with chemometric models proved to be able to estimate the physicochemical parameters of diesel. Thus, the use of infrared spectroscopy associated with chemometric models proved able to... (Complete abstract click electronic access below) / Mestre

In this work, an investigation on the fraction of tyre pyrolysis oil with a similar distillation range to that of automotive diesel (150 – 360 oC) was carried out to determine its suitability as an alternative or additive to petro-diesel fuel. The quality of this oil was evaluated by comparing its key properties to the requirements of South African National Standards for Automotive diesel fuel (SANS-342) and to conventional automotive diesel fuel. The viscosity, density, copper strip corrosion of this fuel were found to be within the acceptable limits set by SANS while sulphur content and flash point were out of their respective set limits. In addition, mixing rule equations for predicting viscosity and density for both pure and blends of the oil as a function of temperature were developed and evaluated. The equations were found to be suitable due to their low Absolute Percentage Deviation. Engine performance tests were carried out with blends of Distilled Tyre Pyrolysis Oil (DTPO) and petro-diesel fuel in a single cylinder air cooled diesel engine. The performance, emission and combustion characteristics of the diesel engine while running on these blends were evaluated and subsequently, a comparative analysis was performed with conventional petro-diesel fuel as the reference fuel. It was found that, the engine could run with up to 60% (DTPO) without any problem. Beyond this level the engine became unstable. The power and torque were similar at low and medium speeds. However, at high speeds, the power dropped with increase in DTPO in the blend. Fuel consumption was very comparable for all the test fuels. Carbon monoxide and unburned hydrocarbons were higher for the blends compared to petro-diesel fuel but oxides of Nitrogen were lower. The peak pressure for petro-diesel fuel was marginally higher than that of the blends. Present results indicate that, petro-diesel fuel can be blended with up to 60% DTPO and produce acceptable performance. Testing the diesel engine under different operating conditions is a time consuming and expensive process that also requires the use of specialised equipment which may not be readily available. An Artificial Neural Network (ANN) model based on a back-propagation learning algorithm was developed to predict engine performance and emissions separately, based on fuel blend and speed. The performance and accuracy of the model were evaluated by comparing experimental and ANN predicted results. The ANN was able to predict both engine performance and emissions with acceptable levels of accuracy. The values of correlation coefficient between experimental and predicted data being greater than 0.99. From this work, it can be implied that engine emission and performance can be predicted using neural network-based mode, consequently, it will be able to do further investigations without running laboratory experiments. Energy recovery from waste is an interesting field for engineers and scientists. It is hoped that this work will prompt new research ideals on how tyre pyrolysis oil can be improved for use as diesel engine fuel and building better models for diesel engine performance and emissions

Made available in DSpace on 2014-06-11T19:29:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-05-21Bitstream added on 2014-06-13T20:59:13Z : No. of bitstreams: 1 nespeca_mg_me_araiq.pdf: 1633750 bytes, checksum: cb5fcc59adcaa9d8548eb6bb3fb6e853 (MD5) / Tendo em vista que o óleo diesel é o derivado energético do petróleo mais consumido no Brasil, torna-se imprescindível o desenvolvimento de métodos de monitoramento capazes de avaliar a qualidade deste combustível de forma rápida, econômica e não destrutiva. Deste modo, este trabalho teve como objetivo o desenvolvimento de modelos quimiométricos com capacidade de estimar os parâmetros físico-químicos do óleo diesel (mistura B5) através de análises espectroscópicas nas regiões do infravermelho médio e próximo. Os parâmetros físico-químicos estimados foram: teor de biodiesel; massa específica; pontos de ebulição das frações 10%, 50% e 85% destiladas, índice de cetano; enxofre total e ponto de fulgor. Em oito meses, 409 amostras de óleo diesel S1800 e S500 da região Centro-Oeste Paulista foram selecionadas de forma representativa por Análise Hierárquica de Agrupamento e divididas em conjuntos de calibração (273 amostras) e validação (136 amostras). Os valores de referência foram obtidos por meio de ensaios realizados utilizando-se métodos ABNT e ASTM, estabelecidos na Resolução ANP Nº 65 de 2011. Os modelos de calibração foram desenvolvidos através dos métodos de regressão Mínimos Quadrados Parciais (PLS) e Regressão por Componentes Principais (PCR), avaliando-se o uso de pré-processamentos de dados e seleção de faixas espectrais. A validação dos modelos demonstrou que a eliminação de faixas espectrais ruidosas e o uso de derivação e suavização dos dados centrados na média resultaram em modelos mais ajustados, com maior coeficiente de correlação e menor erro de predição. Todos os modelos PLS desenvolvidos em ambas as regiões do infravermelho apresentaram valores de exatidão e precisão aceitáveis quando comparados aos valores de reprodutibilidade e repetibilidade dos... / Given that diesel is the most consumed petroleum derived fuel in Brazil, it is essential to develop monitoring methods capable of evaluating the quality of this fuel in a fast, economical and non-destructive analysis. Thus, this study aimed to develop chemometric models capable of estimating the physicochemical parameters of diesel (B5 blend) by spectroscopic analysis in the mid-infrared and near regions. The physicochemical parameters estimated were: biodiesel content, density, distillation temperatures at 10%, 50% and 85% recovery, cetane number, total sulfur, and flash point. In eight months, 409 samples of diesel S1800 and S500 of the Centro-Oeste Paulista region were representatively selected by Hierarchical Cluster Analysis and divided into sets of calibration (273 samples) and validation (136 samples). The reference values were obtained from tests using ABNT and ASTM methods, established in Resolution ANP Nº 65 of 2011. The calibration models were developed through regression methods Partial Least Squares (PLS) and Principal Component Regression (PCR), and the use of pre-processing data and selection of spectral regions were evaluated. Validation of the models demonstrated that the elimination of noisy spectral regions and the use of derivative, smooth and mean center data resulted in fitted models with higher correlation coefficient and lowers prediction error. All developed PLS models in both regions of the infrared showed acceptable values of accuracy and precision when compared to the values of reproducibility and repeatability of the reference methods. So the use of infrared spectroscopy coupled with chemometric models proved to be able to estimate the physicochemical parameters of diesel. Thus, the use of infrared spectroscopy associated with chemometric models proved able to... (Complete abstract click electronic access below)

The purpose of this work is to develop a reliable procedure for determination of liquid phase heats of adsorption via a flow calorimetric technique. The second objective is to study heats of adsorption of target sulfur compounds on potential desulfurization sorbents. Thirdly, we strive to relate the data obtained to the properties of both the sorbent and sorbates studied. Finally, the ultimate goal of this research is to use the data obtained to develop a high capacity selective adsorbent for the desulfurization of diesel fuel. Liquid phase flow adsorption experiments were conducted on sodium-Y zeolite (NaY), nickel exchanged NaY zeolite (NiY) and cesium-exchanged NaY zeolite (CsY). The solutions used in calorimetric experiments included naphthalene in n-hexadecane (C16), dibenzothiophene (DBT) in C16, and quinoline in C16. These solutions were used to model the adsorption of aromatic, sulphur-containing and nitrogen-containing compounds in diesel fuel, respectively. Additional experiments were conducted using equimolar concentrations of all three species in C16 to examine competitive adsorption behaviour of the mixture. During heat flow experiments, effluent samples were collected and analysed to obtain breakthrough curves for the systems. Heat of adsorption data were obtained via flow microcalorimetry using a novel procedure developed by this group. In this study, some experiments were conducted to examine the repeatability and utility of this new method. Characterization experiments were also conducted including BET surface area analysis, X-Ray diffraction (XRD) analysis and Inductively Coupled Plasma – Optical Emission Spectroscopy (ICP-OES) analysis to determine the properties of the sorbents. These properties were then related to data obtained in flow adsorption calorimeter experiments. A detailed discussion on the development of a novel method for determination of liquid phase heats of adsorption is presented. Analysis of calculation results using this new method show good repeatability relative to the previous method used. Equilibrium adsorption relationships are developed using the Langmuir adsorption model, and these results are compared to flow adsorption results obtained from the calorimeter. Results indicate that in terms of desulfurization capability, NaY appeared to be the best sorbent. Heats of adsorption were only moderate on NaY, indicating that regeneration of the sorbent would not be difficult, and NaY had the highest sulfur capacity of the sorbents studied. This result was not in agreement with literature results, and it is proposed that the discrepancy is the result of disruption of the crystalline structure of our sorbents during the modification process. Recommendations are presented for ongoing work, including important calorimeter experiments, modifications for improvement of experimental procedure and apparatus, additional sorbent characterization for elucidation of adsorption mechanisms, and finally experiments for verification and further validation of our innovative experimental technique.

The purpose of this work is to develop a reliable procedure for determination of liquid phase heats of adsorption via a flow calorimetric technique. The second objective is to study heats of adsorption of target sulfur compounds on potential desulfurization sorbents. Thirdly, we strive to relate the data obtained to the properties of both the sorbent and sorbates studied. Finally, the ultimate goal of this research is to use the data obtained to develop a high capacity selective adsorbent for the desulfurization of diesel fuel. Liquid phase flow adsorption experiments were conducted on sodium-Y zeolite (NaY), nickel exchanged NaY zeolite (NiY) and cesium-exchanged NaY zeolite (CsY). The solutions used in calorimetric experiments included naphthalene in n-hexadecane (C16), dibenzothiophene (DBT) in C16, and quinoline in C16. These solutions were used to model the adsorption of aromatic, sulphur-containing and nitrogen-containing compounds in diesel fuel, respectively. Additional experiments were conducted using equimolar concentrations of all three species in C16 to examine competitive adsorption behaviour of the mixture. During heat flow experiments, effluent samples were collected and analysed to obtain breakthrough curves for the systems. Heat of adsorption data were obtained via flow microcalorimetry using a novel procedure developed by this group. In this study, some experiments were conducted to examine the repeatability and utility of this new method. Characterization experiments were also conducted including BET surface area analysis, X-Ray diffraction (XRD) analysis and Inductively Coupled Plasma – Optical Emission Spectroscopy (ICP-OES) analysis to determine the properties of the sorbents. These properties were then related to data obtained in flow adsorption calorimeter experiments. A detailed discussion on the development of a novel method for determination of liquid phase heats of adsorption is presented. Analysis of calculation results using this new method show good repeatability relative to the previous method used. Equilibrium adsorption relationships are developed using the Langmuir adsorption model, and these results are compared to flow adsorption results obtained from the calorimeter. Results indicate that in terms of desulfurization capability, NaY appeared to be the best sorbent. Heats of adsorption were only moderate on NaY, indicating that regeneration of the sorbent would not be difficult, and NaY had the highest sulfur capacity of the sorbents studied. This result was not in agreement with literature results, and it is proposed that the discrepancy is the result of disruption of the crystalline structure of our sorbents during the modification process. Recommendations are presented for ongoing work, including important calorimeter experiments, modifications for improvement of experimental procedure and apparatus, additional sorbent characterization for elucidation of adsorption mechanisms, and finally experiments for verification and further validation of our innovative experimental technique.

The objectives of this study are to use phytoremediation ecotechnology to improve the long-term soil pollution contaminated by petroleum and its refined products, and to explore the influence of environmental factors to the effective degradation of TPH.This study is divided into three stages.First, we selected the biofuel crops seeds to test their diesel fuel pollution tolerance.The crops include soybean¡Bsunflower¡Bcanola and corn.This four Taiwanese common energy crops were selected to manually configure three levels of diesel fuel pollution(1000¡B5000¡B10000 mg kg-1)in soil test the seed tolerance experiments.The experimental results in the first stage exhibited that the best energy crop species and non-edible crop(Jatropha),are selected in second phase for contaiminated soil degradation experiment to explore the possible influence of enviromented factors,such as soil moisture¡BpH¡Btotal plate¡Ketc,and to explore the applied fertilizer to increase soil nutrients,whether it will affect the degradation of diesel pollution.Finally, in the third phase, the energy crops were used in the oil-contaminated site to assess their decontamination efficiency. From June 2011 to November 2011, the experimental results shown in the first phase of seed tolerance test, for a period of 30 days showed that the soybean diesel-contaminated soil presented the best tolerance.Although the germination rate was increased with the concentration from 80% to 27%, it showed the best growth conditions.Therefore, in the second phase of test run, the speices of soybean and jatropha were selected prepared with concentrations of 1745¡B6271 and 10072 mg kg-1 dry soil. After 90 day for phytoremediation, soybean group(S) were found that the residual concentrations in soil were measured equal to 524¡B809 and 1913 mg kg-1 dry soil,with the removal rates of 69.97%¡B87.09% and 81.01% respectively.The concentration level of 10000 ppm was found not reach our control standard of 1000 ppm. The soil planted by jatropha(J) showed that residual concentration in soils equial to 303¡B1864 and 4837 mg kg-1 dry soil, with removal rates equal to 82.61%¡B70.27% and 51.98% respectively.Through statistical regression analytical results, the soybean can handle up to a concentration of 5300 mg/kg for diesel, while jatropha can handle up to 2170 mg/kg in this system. Except for the concentration level of 1000 ppm can reach our control standards, the other two groups were found below the control standard. To improve the removal efficieneies, it was suggested that phyto remediation time can be extended.