Optimization of biodiesel production from Nahar oil using Box-Behnken design, ANOVA and grey wolf optimizer

Van Nhanh Nguyen, Prabhakar Sharma, Anurag Kumar, Minh Tuan Pham, H. C. Le, Thanh H. Truong, Dao Nam Cao
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引用次数: 1

Abstract

Biodiesel manufacturing from renewable feedstocks has received a lot of attention as a viable alternative to fossil fuels. The Box-Behnken design, analysis of variance (ANOVA), and the Grey Wolf Optimizer (GWO) algorithm were used in this work to optimise biodiesel production from Nahar oil. The goal was to determine the best operating parameters for maximising biodiesel yield. The Box-Behnken design is used, with four essential parameters taken into account: molar ratio, reaction duration and temperature, and catalyst weight percentage. The response surface is studied in this design, and the key factors influencing biodiesel yield are discovered. The gathered data is given to ANOVA analysis to determine the statistical significance. ANOVA analysis is performed on the acquired data to determine the statistical significance of the components and their interactions. The GWO algorithm is used to better optimise the biodiesel production process. Based on the data provided, the GWO algorithm obtains an optimised yield of 91.6484% by running the reaction for 200 minutes, using a molar ratio of 7, and a catalyst weight percentage of 1.2. As indicated by the lower boundaries, the reaction temperature ranges from 50 °C. The results show that the Box-Behnken design, ANOVA, and GWO algorithm were successfully integrated for optimising biodiesel production from Nahar oil. This method offers useful insights into process optimisation and indicates the possibilities for increasing the efficiency and sustainability of biodiesel production. Further study can broaden the use of these strategies to various biodiesel production processes and feedstocks, advancing sustainable energy technology.
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利用Box-Behnken设计、方差分析和灰狼优化算法优化Nahar油生产生物柴油
利用可再生原料生产生物柴油作为化石燃料的可行替代品受到了广泛关注。在这项工作中,使用Box-Behnken设计、方差分析(ANOVA)和灰狼优化(GWO)算法来优化Nahar油的生物柴油生产。目的是确定最大限度提高生物柴油产量的最佳操作参数。采用Box-Behnken设计,考虑了四个基本参数:摩尔比、反应持续时间和温度、催化剂重量百分比。本设计对响应面进行了研究,发现了影响生物柴油产率的关键因素。将收集到的数据进行方差分析以确定统计显著性。对获得的数据进行方差分析,以确定各成分及其相互作用的统计显著性。采用GWO算法对生物柴油生产过程进行优化。结果表明,在摩尔比为7、催化剂质量分数为1.2的条件下,反应时间为200 min, GWO算法的优化产率为91.6484%。由下边界可知,反应温度范围为50℃。结果表明,Box-Behnken设计、方差分析和GWO算法成功地集成在一起,以优化Nahar油生产生物柴油。该方法为过程优化提供了有用的见解,并指出了提高生物柴油生产效率和可持续性的可能性。进一步的研究可以将这些策略扩大到各种生物柴油生产过程和原料的使用,推进可持续能源技术。
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来源期刊
CiteScore
4.50
自引率
16.00%
发文量
83
审稿时长
8 weeks
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