Data underlying the PhD thesis "Mixtures in Motion: High-Velocity DEM Modeling of Blast Furnace Charging"

This dataset contains numerical and experimental data generated in the context of my PhD research on particle-scale flow and packing behavior in high-velocity blast furnace mixture charging, where the mixture consists of granular iron ore pellets and sinter. The work combines computational research, using Discrete Element Method (DEM) simulations, and laboratory experiments for model calibration and validation. The numerical data comprise DEM simulation outputs used to analyze flow, segregation, and packing behavior under blast-furnace-relevant conditions (corresponding to Chapters 4, 7 and 8 of the PhD thesis). The experimental data originate from high-velocity piling tests designed to calibrate DEM model parameters (Chapters 5 and 6), and include measurements of hopper discharge and subsequent heap formation characteristics for pellets, sinter, and their mixture. Together, these data support the development, calibration, and assessment of a DEM model for industrial-scale charging applications.

本数据集涵盖了本人博士研究中产生的数值与实验数据，研究主题为高速高炉混合料装料过程中的颗粒尺度流动与堆积行为，所涉混合料由粒状铁矿石球团与烧结矿构成。本研究结合了基于离散元法（Discrete Element Method, DEM）模拟的计算研究，以及用于模型校准与验证的实验室实验。数值数据部分包含用于分析高炉工况下流动、偏析与堆积行为的DEM模拟结果，对应博士论文的第4、7、8章。实验数据部分源自用于校准DEM模型参数的高速堆料试验，对应博士论文第5、6章，涵盖了球团、烧结矿及其混合料的料仓卸料特性与后续堆体成型特征的测量数据。上述数据集共同支撑了面向工业规模装料应用的DEM模型的开发、校准与评估工作。