基于响应面法和遗传算法的人工神经网络对再生漂白废土可漂白性的统计建模与优化

IF 1 Q4 ENGINEERING, CHEMICAL Chemical Product and Process Modeling Pub Date : 2022-11-14 DOI:10.1515/cppm-2022-0031
Almoruf O. F. Williams, Oluwaseun D. Akanbi
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引用次数: 1

摘要

摘要在本研究中,对废漂白土再生用于棕榈油粗漂白的统计建模和优化进行了检验。拥有一个好的模型将有助于SBE的成功优化再生,从而最大限度地减少与目前基于倾倒作为垃圾填埋场的处理方法相关的环境污染。SBE样品采用索氏提取法,使用正己烷在60°C下脱油1小时;在300–500°C的温度范围内处理;碳化时间在30和45分钟之间;以及盐酸浓度分别在1M和2M之间,在30分钟的恒定搅拌时间下。实验的操作条件根据中央复合材料设计(CCD)实验设计,使用Design Expert软件版本13。采用响应面法(RSM)和人工神经网络(ANN)技术对SBE再生过程进行了建模和优化。根据RSM方法开发了五个回归模型,并根据文献中推荐的模型选择参数选择了最佳模型。类似地,考虑了隐藏层中神经元数量从2到16不等的十个ANN模型,并使用均方误差(MSE)和相关系数(R)选择了用于训练、验证和测试性能的最佳模型。结果表明,人工神经网络技术建立的模型比RSM模型具有更好的预测能力。在炭化温度为500°C、盐酸浓度为2M、炭化时间为45min的条件下,再生脱油SBE的最佳实验漂白率为71.5%。采用遗传算法(GA),在468.19°C、2M和45min条件下,ANN模型的最佳漂白率为70.87%,而在498.99°C、1.57M和41.14min条件下,对炭化温度、酸浓度和炭化时间,RSM方法的最佳漂白度分别为73.52%。再生SBE的最佳漂白性能比原漂白土(VBE)提高12.5%。
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Statistical modeling and optimization of the bleachability of regenerated spent bleaching earth using response surface methodology and artificial neural networks with genetic algorithm
Abstract In this study, the statistical modeling and optimization of the regeneration of spent bleaching earth (SBE) for re-use in the bleaching of crude palm oil (CPO) oil was examined. Having a good model will assist with the successful optimal regeneration of SBE and hence minimize the environmental pollution associated with its current disposal method which is based on dumping as landfills. The SBE samples were de-oiled with the Soxhlet extraction method, using n-hexane for 1 h at 60 °C; treated at temperatures ranging from 300–500 °C; at carbonization time between 30 and 45 min; and with hydrochloric acid concentrations between 1 and 2 M, at a constant stirring time of 30 min, respectively. The operating conditions for the experiment were according to the Central Composite Design (CCD) experimental design using the Design Expert software version 13. The modeling and optimization of the SBE regeneration process was carried out with the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) techniques. Five regression models were developed from the RSM approach and the best one selected based on model selection parameters recommended in the literature. Similarly, ten ANN models with the number of neurons in the hidden layer that varied from 2 to 16 were considered and the best one selected using the mean square error (MSE) and correlation coefficients (R) for the training, validation and testing performances. Results showed that the ANN technique led to a model with a better predictive ability than the RSM one. The optimum experimental bleachability of 71.5% for the regenerated de-oiled SBE was obtained at carbonization temperature of 500 °C, hydrochloric acid concentration of 2M and carbonization time of 45min. Using the Genetic Algorithm (GA), the ANN model resulted in an optimum bleachability of 70.87% with corresponding optimum factors at 468.19 °C, 2 M and 45 min, while the RSM approach gave an optimum bleachability of 73.52% at the corresponding factors of 498.99 °C, 1.57 M and 41.14 min for the carbonization temperature, acid concentration and carbonization time, respectively. The optimum experimental bleachability of the regenerated SBE achieved was 12.5% higher than that of virgin bleaching earth (VBE).
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来源期刊
Chemical Product and Process Modeling
Chemical Product and Process Modeling ENGINEERING, CHEMICAL-
CiteScore
2.10
自引率
11.10%
发文量
27
期刊介绍: Chemical Product and Process Modeling (CPPM) is a quarterly journal that publishes theoretical and applied research on product and process design modeling, simulation and optimization. Thanks to its international editorial board, the journal assembles the best papers from around the world on to cover the gap between product and process. The journal brings together chemical and process engineering researchers, practitioners, and software developers in a new forum for the international modeling and simulation community. Topics: equation oriented and modular simulation optimization technology for process and materials design, new modeling techniques shortcut modeling and design approaches performance of commercial and in-house simulation and optimization tools challenges faced in industrial product and process simulation and optimization computational fluid dynamics environmental process, food and pharmaceutical modeling topics drawn from the substantial areas of overlap between modeling and mathematics applied to chemical products and processes.
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