The Role of Isopropyl Alcohol in the Properties of Sudanese Reformat Gasoline
The role of isopropyl alcohol in the properties of Sudanese reformat gasoline (produced by the refinery located at Algily, Khartoum North city, in Sudan) was studied. The properties of the reformat gasoline which were investigated include , distillation, sulfur content, density, vapor pressure, oxidation stability, copper strip corrosion, gum existence, lead content, and the octane number . The addition of isopropyl alcohol (5 and 10% (v/v)) improved the properties of the Sudanese reformat gasoline to the limits assigned by American Society For Testing And Materials (ASTM) and Khartoum refinery. The motor octane number (MON) of the reformat gasoline was determined initially by the Cooperative Fuels Research engine (CFR engine), MON was found to be 88.5. Results revealed that the addition of isopropyl alcohol 5 and 10 % (v/v) to the Sudanese reformat gasoline shift the value of the (MON) to 94.1 and 96 respectively. keywords: Isopropyl alcohol, Sudanese gasoline properties, Motor octane number, Cooperative fuels research engine.
Quality improvement of Sudanese gasoline by using Di isopropyl ether and Moringa oil
The main objective of this project blending of Di isopropyl ether and Moringa oil with Sudanese gasoline, which intent of enhancing octane number to reformat gasoline was product from Khartoum refinery. Reformat gasoline was tested by ASTM standard methods, such as Distillation temperatures, Sulfur content, density, vapor pressure, oxidation stability , cupper corrosion , Gum existent, lead content, and octane number measuring by CFR. Reformat gasoline MON was recorded (88.5). Di isopropyl ether and Moringa oil were added to the reformat gasoline. Octane number of blends was measured by CFR engine .additives were add in (5, 10%vol) to reformat gasoline, increasing MON was (2.1-6.5).
Automatic Learning of Chemical Concepts: Research Octane Number and Molecular Substructures
Abstract A set of 230 hydrocarbons is analyzed with respect to the research octane number (RON) using an extended version of the ID3 machine learning method of Quinlan. The basic ID3 method produces a decision tree. The questions within the decision tree ask whether given substructures are present or absent within a molecule (for example, is the hexane carbon skeleton present as a substructure?). The decision to be made is whether the RON value is within a given range (for example, is the RON greater than or equal to 90). In addition to the normal usage of decision trees to predict the RON value, qualitative information is extracted: for example, which substructures are significant in which RON ranges. The best results were found for those molecules having RON values between 90 and 105. This was due to the high density of samples in this region. The ID3 method is used to prune down an overabundance of parameters to a reasonable size. From the original set of 230 substructures, it was found that only 31 were needed for the RON description. The presence or absence of the substructures n -hexane, methylbenzene and benzene were particularly significant in determining the RON value. Considering that ID3 is not a traditional method of analysis, especially within chemistry, an effort is made to explain its principles using the problem at hand as an example. In addition, its use as the first step in analysis to gain intuitive information is explained.