微波反应器中食用油生物柴油的工艺优化——以机器学习和Box-Behnken设计为例

IF 2.8 Q2 ENGINEERING, CHEMICAL
A. Buasri, Phensuda Sirikoom, Sirinan Pattane, Orapharn Buachum, V. Loryuenyong
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引用次数: 0

摘要

本研究将响应面方法(RSM)和机器学习(ML)应用于甘油三酯(TG)的酸催化酯交换和酯化生产生物柴油的过程。为了优化在微波反应器中用废食用油生产生物柴油的工艺,还对这些模型进行了比较。在此过程中,使用Box-Behnken设计(BBD)和人工神经网络(ANN)来评估催化剂含量(3.0–7.0 wt.%)、甲醇/UCO摩尔比(12:1–18:1)和辐照时间(5.0–9.0分钟)的影响。通过RSM方法和ANN模型,利用BBD对工艺条件进行了调整和开发,以预测生物柴油的最高产量。在催化剂含量为4.94wt%、甲醇/UCO摩尔比为16.76:1、辐照时间为8.13min的最佳工艺参数下,产率约为98.62%。BBD模型的决定系数(R2)为0.9988,ANN模型的相关系数(R)为0.9994。研究结果表明,应用RSM和ANN模型对生物柴油生产工艺进行优化和预测是有利的。这种可再生、环保的工艺有可能为利用废油合成低成本、高酸值的高质量生物柴油提供一条可持续的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Process Optimization of Biodiesel from Used Cooking Oil in a Microwave Reactor: A Case of Machine Learning and Box–Behnken Design
In the present investigation, response surface methodology (RSM) and machine learning (ML) are applied to the biodiesel production process via acid-catalyzed transesterification and esterification of triglyceride (TG). In order to optimize the production of biodiesel from used cooking oil (UCO) in a microwave reactor, these models are also compared. During the process, Box–Behnken design (BBD) and an artificial neural network (ANN) were used to evaluate the effect of the catalyst content (3.0–7.0 wt.%), methanol/UCO mole ratio (12:1–18:1), and irradiation time (5.0–9.0 min). The process conditions were adjusted and developed to predict the highest biodiesel yield using BBD with the RSM approach and an ANN model. With optimal process parameters of 4.94 wt.% catalyst content, 16.76:1 methanol/UCO mole ratio, and 8.13 min of irradiation time, a yield of approximately 98.62% was discovered. The coefficient of determination (R2) for the BBD model was found to be 0.9988, and the correlation coefficient (R) for the ANN model was found to be 0.9994. According to the findings, applying RSM and ANN models is advantageous when optimizing the biodiesel manufacturing process as well as making predictions about it. This renewable and environmentally friendly process has the potential to provide a sustainable route for the synthesis of high-quality biodiesel from waste oil with a low cost and high acid value.
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来源期刊
ChemEngineering
ChemEngineering Engineering-Engineering (all)
CiteScore
4.00
自引率
4.00%
发文量
88
审稿时长
11 weeks
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