A Methodology for Designing Octane Number of Fuels Using Genetic Algorithms and Artificial Neural Networks

Abstract

Refineries often blend fuels in order to achieve mandated fuel properties based on international and domestic standards. One of the mandated properties for gasoline is Octane Number (ON). There are two forms of measuring ON: Research Octane Number (RON) and Motor Octane Number (MON). Although there have been efforts to optimize the blending operation in refineries, the implementations of advanced machine learning models are limited. The intention behind exploring and enhancing this field is to avoid undesirable scenarios, such as off-specification products and quality giveaways, as these scenarios overburden refineries' operational expenditures. The current work presents an innovative approach to predict the optimum fuel blending mechanism. This is accomplished through utilizing an integrated system composed of genetic algorithms (GA) and artificial neural networks (ANN). In addition, this work presents the polygonal algorithms that govern the optimization process. The system analyzes fuel inputs consisting of pure hydrocarbons, hydrocarbon−ethanol blends, and FACE (fuels for advanced combustion engines) gasoline−ethanol blends. There are ten pure hydrocarbons and six FACE gasoline's that are the base of 243 fuels used. These components are presented as multiple input streams to the blending stage, at which the system computes multiple recipes utilizing the GA. The system derives these recipes by capitalizing on the polygonal method. This method offers a systematic approach to design optimal fuel with the lowest addition of relatively high octane components. The system is evaluated using 243 blends. The produced recipes are designed to meet the desired antiknocking index (AKI). The coefficient of determination (R 2 ) result is 0.99 for RON, MON, and AKI, respectively. Furthermore, the mean absolute error (MAE) values are 1.99, 1.23, and 1.40 for RON, MON, and AKI, respectively. These results signify the success of the integrated system and its significant potential impact in mitigating undesirable blending scenarios.

Unraveling the Superior Role of Characterizing Methyl Ester of Isohexene as an Innovative High-Octane Gasoline Mixing Component

“…Therefore, we must diminish the percentages of olefins on isohexene to make it suitable as a high-octane gasoline mixing component. 14 Moreover, the methoxylation process of isohexene allowed us to solve the following assignments, involving decreased olefin percentages, as well as guarantee the existence of high-octane ethers in the gasoline recipe of the fuel. 15 This can invariably influence not only the ecological friendship of motor gasoline in accordance with the existence of oxygen atoms in the molecule but also the gasoline antidetonation properties.…”

“…Given the great concentrations of isoolefinic hydrocarbons in the composition of isohexene production, it is preferable to measure the process of refining isohexene employing the methoxylation process, wherein the olefin content of isohexene was 94% volumetrically and is an impressive quantity of olefins, which impacted the chemical oxidation and storage stability under atmospheric conditions. Therefore, we must diminish the percentages of olefins on isohexene to make it suitable as a high-octane gasoline mixing component . Moreover, the methoxylation process of isohexene allowed us to solve the following assignments, involving decreased olefin percentages, as well as guarantee the existence of high-octane ethers in the gasoline recipe of the fuel .…”