Purpose

Brewer's spent grain (BSG) is the main by-product of the brewing industry, holding significant potential for biomass applications. The purpose of this paper was to determine the effective thermal conductivity (k_eff) of BSG and to develop an Artificial Neural Network (ANN) to predict k_eff, since this property is fundamental in the design and optimization of the thermochemical conversion processes toward the feasibility of bioenergy production.

Design/methodology/approach

The experimental determination of k_eff as a function of BSG particle diameter and heating rate was performed using the line heat source method. The resulting values were used as a database for training the ANN and testing five multiple linear regression models to predict k_eff under different conditions.

Findings

Experimental values of k_eff were in the range of 0.090–0.127 W m⁻¹ K⁻¹, typical for biomasses. The results showed that the reduction of the BSG particle diameter increases k_eff, and that the increase in the heating rate does not statistically affect this property. The developed neural model presented superior performance to the multiple linear regression models, accurately predicting the experimental values and new patterns not addressed in the training procedure.

Originality/value

The empirical correlations and the developed ANN can be utilized in future work. This research conducted a discussion on the practical implications of the results for biomass valorization. This subject is very scarce in the literature, and no studies related to k_eff of BSG were found.

中文翻译：

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一种基于神经的建模方法，用于预测啤酒糟的有效导热率

 目的

啤酒糟 (BSG) 是啤酒工业的主要副产品，在生物质应用方面具有巨大潜力。本文的目的是确定 BSG 的有效热导率 ( k _eff ) 并开发人工神经网络 (ANN) 来预测k _eff ，因为该特性对于热化学转化过程的设计和优化至关重要。生物能源生产的可行性。

设计/方法论/途径

使用线热源法对k _eff作为 BSG 粒径和加热速率的函数进行了实验测定。所得值用作训练 ANN 和测试五个多元线性回归模型的数据库，以预测不同条件下的k _eff 。

 发现

k _eff的实验值在0.090–0.127 W m ^-1 K ^-1范围内，这是生物质的典型值。结果表明，BSG 粒径的减小会增加k _eff ，并且加热速率的增加不会对这一特性产生统计上的影响。开发的神经模型表现出优于多元线性回归模型的性能，准确预测实验值和训练过程中未解决的新模式。

 原创性/价值

经验相关性和开发的人工神经网络可以在未来的工作中使用。本研究讨论了结果对生物质增值的实际影响。这个课题在文献中非常稀少，没有发现与BSG的k _eff相关的研究。