Data for the enhancement of predictive models for steam biomass gasification

The data included in this dataset corresponds to the experimental data of biomass steam gasification, obtained through a systematic literature review. A total of 17 articles and 103 data entries were obtained, including a wide range of types of biomass, gasifier temperature, and steam-to-biomass ratio.
The file titled "Training dataset" includes the 103 data entries, which were normalized to ensure that the sum of the molar fractions of hydrogen, carbon monoxide, carbon dioxide, and methane equals 1. Besides, ultimate analysis was converted to dry basis, including ash content.
The file titled "Validation" shows the procedure to evaluate four predictive models for steam biomass gasification: A stoichiometric model, built on MATLAB, an equilibrium model, based on ASPEN Plus, and a machine learning model, built on Python and based on the H2O AutoML module.

本数据集收录的内容为通过系统性文献综述获取的生物质蒸汽气化实验数据。本次研究共检索筛选得到17篇相关文献，整理出103组有效数据条目，涵盖多种生物质类型、气化炉温度及蒸汽与生物质配比等核心参数。名为"Training dataset"的文件包含全部103组数据条目，所有数据均经过归一化处理，以确保氢气、一氧化碳、二氧化碳及甲烷的摩尔分数之和为1。此外，元素分析结果已转换为干基形式，其中包含灰分含量。名为"Validation"的文件则展示了针对生物质蒸汽气化的4种预测模型的评估流程：基于MATLAB构建的化学计量模型、依托ASPEN Plus开发的平衡模型，以及基于Python并采用H2O AutoML模块的机器学习模型。