Prediction of Flash Point Temperature of Organic Compounds Using a Hybrid Method of Group Contribution ＋ Neural Network ＋ Particle Swarm Optimization

The flash points of organic compounds were estimated using a hybrid method that includes a simple group contribution method (GCM) implemented in an artificial neural network (ANN) with particle swarm optimization (PSO). Different topologies of a multilayer neural network were studied and the optimum architecture was determined. Property data of 350 compounds were used for training the network. To discriminate different substances the molecular structures defined by the concept of the classical group contribution method were given as input variables. The capabilities of the network were tested with 155 substances not considered in the training step. The study shows that the proposed GCM+ANN+PSO method represent an excellent alternative for the estimation of flash points of organic compounds with acceptable accuracy (AARD = 1.8%; AAE = 6.2 K).

A Quantitative Structure Property Relationship for Prediction of Flash Point of Alkanes Using Molecular Connectivity Indices

Many structure-property/activity studies use graph theoretical indices, which are based on the topological properties of a molecule viewed as a graph. Since topological indices can be derived directly from the molecular structure without any experimental effort, they provide a simple and straightforward method for property prediction. In this work the flash point of alkanes was modeled by a set of molecular connectivity indices （Х）, modified molecular connectivity indices （ ^mХ^v ） and valance molecular connectivity indices （ ^mХ^v ）, with ^mХ^v calculated using the hydrogen perturbation. A stepwise Multiple Linear Regression （MLR） method was used to select the best indices. The predicted flash points are in good agreement with the experimental data, with the average absolute deviation 4.3 K.

A new group contribution-based method for estimation of flash point temperature of alkanes

Flash point is a primary property used to determine the fire and explosion hazards of a liquid. New group contribution-based models were presented for estimation of the flash point of alkanes by the use of multiple linear regression(MLR)and artificial neural network(ANN). This simple linear model shows a low average relative deviation(AARD) of 2.8% for a data set including 50(40 for training set and 10 for validation set) flash points. Furthermore, the predictive ability of the model was evaluated using LOO cross validation. The results demonstrate ANN model is clearly superior both in fitness and in prediction performance.ANN model has only the average absolute deviation of 2.9 K and the average relative deviation of 0.72%.

Chemical Properties,Low-Temperature Performance,and Burning Performance of Bio-Jet Fuel

The effects of composition of bio-jet fuels on freezing point,smoke point,distillation range,and flash point are investigated.Performance tests using petroleum-based jet fuel with different compositions are conducted in line with standard test specifications.The results show that alkylbenzenes reduce the freezing point,with the amount of reduction becoming greater with increasing alkylbenzene content.For a 25%content of the C_8 aromatic xylene,the freezing point is in the range from-55.5℃to-60.1℃.The presence of monocyclic aromatic hydrocarbons leads to an increase in carbon deposition performance,especially when alkyl side chains are present.With cycloalkanes,carbon deposition is reduced,although alkyl side chains weaken this beneficial effect.Isomeric hydrocarbons are beneficial in reducing carbon deposition.The ASTM D7566 specifications for the distillation range are based on the average properties of petroleum-based aviation fuel,and if all the parameters governing the distillation range of an alternative jet fuel are at their lower limits,it is necessary to check whether other performance standards are met.Light components affect the flash point greatly,with 5%of benzene reducing the flash point by 17℃,whereas intermediate components(e.g.,xylene and ethylbenzene)and heavier components have less impact.Although alcohols provide better combustion performance,their content must be strictly limited owing to their effects in reducing the flash point.

Effect of Bio-Disc on Distillate Yield and Crude Oil Properties

The market worth of the crude oil transported to the international market has a great influence on the crude’s physical properties, as such demands that certain desirable physical properties ought to be possessed. The distillation of crude oil is the first process in the sequence of refining operation and is key to refinery operations profitability. In this work, five crude oil samples were collected from a reservoir in the Niger Delta designated as S11A, S12A, S13A, S14A and S15A. Sample S11A was not treated with bio-disc while samples S12A-S15A were treated with bio-disc at different number of times. This was necessary to ascertain the effect of the bio-disc on crude oil physical properties and their distillate yield. After the treatment, the specific gravity, American Petroleum Institute (API), pour point, flash point and viscosity of the treated and untreated crude samples were determined and then the samples distilled with a distillation tester. From the results obtained, the bio-disc had a great influence on the physical properties of the samples as well as on the distillate yield. The specific gravities of the oil samples decreased as the number of times the samples were treated with bio-disc increases and this in turn increased the crudes’ API. The pourpoint and viscosity decreased with increase in number of treatments of crude samples with bio-disc. As the number of treatments increased, the crude samples which were originally paraffinic were tending towards being naphthenic. The flash point and distillate yield increased with increase in number of treatments of crude samples with bio-disc. Thus, treatment of crude oil with bio-dic alters the physical properties of the crude.

Investigation on the Potential Production of Diesel from Waste Tires

An alternative fuel production was performed by catalytic-pyrolysis of waste tires under a nitrogen (N2) environment and with a zeolite catalyst. Pyrolysis of scrap tires has been pointed out as an alternative to the incorrect disposal of tire wastes. Pyrolysis processes can produce tire-derived oils that may be used as fuel or added to conventional fuels, producing fuel blends with improved properties and reduced cost. The pyrolysis process can contribute to removing tire residues from inadequate sites and it can be a sustainable process to produce alternative fuels. The project investigated the conversion of the waste tires into diesel as one way of waste management and also as a viable process which in turn helps to meet the fuel demand. Uses of the diesel and the by-products from the process were also outlined. Experiments were conducted on the pyrolysis process in order to find the optimum conditions for producing the diesel through pyrolysis;the temperature and residence time were optimized in order to get maximum output from the process. The optimum temperature of the reaction was found to be 520˚C and the optimum residence time was 92.5 minutes. Quality tests of the product were then conducted on the obtained product and most of the properties were found to meet the required standard specifications. The most critical properties which are density, final boiling point, flash point and kinematic viscosity, were found to be 0.8495 g/cm3, 370˚C, 50.5˚C and 3.681 cSt, respectively, and they were within the required specifications. Quality analysis showed that a quality product that is suitable for automobiles could be obtained from the process. The process also produces useful by-products such as char, which can aid in the purification process of the diesel after conversion to activated carbon. The process is environmentally friendly if the appropriate pollution prevention methods like gas absorption are thoroughly implemented. Waste tires are an alternative source of diesel and hence the feasibility of implementing the project on a large scale.

Synthesis and Characterization of Bio-Glycerol from Cameroon Palm Kernel Seed Oil

Bio-glycerol was synthesized from Cameroon palm kernel oil (PKO) through the transesterification procedure. Palm kernel oil extracted from palm kernel seeds using mechanical expression and solvent extraction was purified and characterized by physico-chemical methods and used in the transesterification process to give biodiesel and bio-glycerol. The biodiesel was purified and characterized as reported in previous articles. Our focus in this article is on glycerol, an important by-product of the transesterification process which has potential pharmaceutical, cosmetic and engineering applications. The bio-glycerol was purified by acidification and the purified glycerol was subjected to physical and chemical characterization. The specific gravity of glycerol was obtained as 1.2 kg/L, viscosity at 40&degC gave 1500 cSt and 500 cSt at 100&degC;pH was 7.4;the flash point was 160&degC, and the ASTM color was 2.0 before purification and zero after purification. The sulfur content was 0.016%w/v. This sulfur content is low thus posing no environment threat. The chemical composition of the synthesized bio-glycerol determined using IR spectroscopy and gas chromatography-mass spectrometry (GC-MS) confirmed the known chemical structure of glycerol. The purification and analysis of bio-glycerol is important as it can find applications in the pharmaceutical, cosmetic and food industries inter alia.

Prediction of the flash points of alkanes by group bond contribution method using artificial neural networks

A group bond contribution model using artificial neural networks,which had the high ability of nonlinear of prediction,was established to predict the flash points of alkanes.This model contained not only the information of group property but also connectivity in molecules.A set of 16 group bonds were used as input parameters of neural networks to study the correlation of molecular structures with flash points of 44 alkanes.The results showed that the predicted flash points were in good agreement with the experi-mental data that the absolute mean absolute error was 6.9 K and the absolute mean relative error was 2.29%,which were superior to those of traditional group contribution methods.The method can be used not only to reveal the quantitative correlation between flash points and molecular structures of alkanes but also to predict the flash points of organic compounds for chemical engineering.

The effects of storage time on fuel properties of Jatropha biodiesel blends

This study investigates the effects of storage time on fuel properties of biodiesel made from Jatropha oil and its blends with mineral diesel at different percentage compositions.The influence of storage stability on selected fuel properties such as kinematic viscosity,density,pour,cloud and flash points for Jatropha biodiesel and its blends at varying storage times were investigated using standard test methods.The biodiesel obtained through trans-esterification of Jatropha oil was blended with mineral diesel to obtain fractional samples of B20(20%biodiesel blend),B40(40%biodiesel blend),B60(60%biodiesel blend)and B100(100%neat biodiesel).Results show that kinematic viscosity and density increase for each blend over the 12 weeks of storage period.Flash,cloud and pour points decrease for each blend over the period of study.B20 was observed to be the optimum blend mix as its fuel properties were relatively unchanged over the storage period when compared to that of mineral diesel.It can be implied from the research that while properties like kinematic viscosity and density deteriorate with time;flash,cloud and pour points are observed to have improved with storage time.