基于近似分析的农业废弃物高热值建模

Alexandre Houemenou, P. Chetangny, David G. F. Adamon, V. Zogbochi, S. Houndedako, L. Fagbemi, G. Barbier, A. Vianou, D. Chamagne
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引用次数: 0

摘要

本文通过对贝宁农业废弃物的接近性分析,提出了一个干燥基础上较高热值的模型。该模型是利用农业残留物开发的,如乳木果壳和饼、棉花和大豆秸秆、玉米芯和花生壳,作为实验系统实施的一部分。在较高热值(HHV)为18.07 ~ 25.91 MJ/kg、挥发分率(%VM)为66.8% ~ 79.87%、固定碳率(13.83% ~ 29.59%)和灰分(%Ash)为3.47% ~ 6.3%范围内,建立了该模型的有效性。模型的平均绝对误差为2.79%,偏倚误差为0.034%,显著优于最准确的文献预测模型,其偏倚误差的平均绝对误差为5.97%,-4.66%。这项工作也提出了来自贝宁农业残留物接近分析的第一批数据。这些分析是使用结构良好的方法进行的,该方法尊重简单随机抽样的标准和措施。在适当条件下制备的样品采用标准化的农业废弃物处理方案进行分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling of Agricultural Waste Higher Heating Value Based on Proximate Analysis
A model of the higher heating value on a dry basis from the proximity analysis of agricultural wastes in Benin has been proposed in this article. This model was developed using agricultural residues such as shea shells and cakes, cotton and soybean stalks, corn cobs and peanut shells identified as part of the implementation of an experimental system. The validity of this model has been established for the Higher Heating Value (HHV) between 18.07 MJ/kg to 25.91 MJ/kg, Volatile Matter rate (%VM) 66.8% to 79.87%, Fixed Carbon rate 13.83% to 29.59%, and Ash content (%Ash) 3.47% to 6.3%. The model has an average absolute error of 2.79% and a bias error of 0.034%, significantly better than the most accurate literature prediction model, which offers a mean absolute error of 5.97% and –4.66% for the bias error. This work presents as well the first data from the proximity analysis of agricultural residues in Benin. These analyzes are carried out using a well-structured methodology that respects the standards and measures of simple random sampling forsample collection. Samples prepared under appropriate conditions are analyzed using standardized protocols for the agricultural wastes studied.
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