Supplementary information dataset for "The implementation of a simplex-centroid mixture design approach to generate components of sugar industry by-products for usage as biomass pellets"

It is the supplementary data to the paper "The implementation of a simplex-centroid mixture design approach to generate components of sugar industry by-products for usage as biomass pellets"AbstractThe current study aimed to improve the efficiency of raw materials that were by-products of the sugar industry, such as sugarcane trash leaves (SCL), sugarcane bagasse (SCB), and filter cake (FTC), in order to obtain a mixture ratio with good thermal properties that could be used as a renewable energy source. The generated model offered an acceptable estimate of HHV with an R² of 96.46, a mean absolute error (MAE) of 3.45%, and a mean bias error (MBE) of -1.83%, while the second portion was a simplex-centroid mixture design used to assess LHV of sugar industrial waste mixture ratios. The results of the LHV prediction equation were found to have an R² of 93.66%. The prediction equation's assessment and validation generated average absolute error (AAE) of 7.07% and average bias error (ABE) of 6.02%. The outcomes from the design elements applying the simplex-centroid mixture design approach revealed biomass's potential as a fuel and served as essential in advancing the use of byproducts as an alternative energy source in the sugar industry.

本数据集为论文《单纯形质心混料设计法制备糖业副产物组分以用作生物质颗粒原料》的补充数据。本研究旨在提升糖业副产物原料的利用效率，所用原料包括甘蔗残叶（Sugarcane Trash Leaves, SCL）、甘蔗渣（Sugarcane Bagasse, SCB）与滤饼（Filter Cake, FTC），以期获得具备优良热性能的混合配比，用作可再生能源。所构建的模型对高位发热量（Higher Heating Value, HHV）的预测表现优异，决定系数（R²）达96.46%，平均绝对误差（Mean Absolute Error, MAE）为3.45%，平均偏差误差（Mean Bias Error, MBE）为-1.83%。本数据集的第二部分采用单纯形质心混料设计，用于评估糖业废弃物混合配比的低位发热量（Lower Heating Value, LHV）。该低位发热量预测方程的决定系数为93.66%。对该预测方程的评估与验证结果显示，其平均绝对误差（Average Absolute Error, AAE）为7.07%，平均偏差误差（Average Bias Error, ABE）为6.02%。本研究通过单纯形质心混料设计得到的结果，证实了生物质作为燃料的应用潜力，同时为推动糖业副产物作为替代能源的产业应用提供了重要支撑。