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<p>This study investigates the impact of calcination temperature (700&#xa0;°C, 750&#xa0;°C, and 800&#xa0;°C) on the particle size distribution (PSD) of brown and red clays from Kongo-Central province in the D.R. Congo, using laser granulometry. Three mathematical models—Rosin-Rammler, Swebrec, and LogNormal—were applied to analyze the PSD data. The results show that calcination temperature significantly influences PSD, with greater variability observed for red clay. Specifically, for brown clay calcined at 700&#xa0;°C, the distributions of percentiles (Dv) revealed notable discrepancies between experimental values and model predictions. For example, for Dv(10), the differences from experimental values are − 0.352 for the Rosin-Rammler model, − 0.1774 for Swebrec, and + 0.0161 for LogNormal. Similarly, for Dv(50), the difference is − 2.1308 with Rosin-Rammler and − 0.147 with LogNormal. Finally, for Dv(90), the observed differences range from − 46.1713 for the Rosin-Rammler model to − 3.7037 for LogNormal. The LogNormal model showed the best performance with an R² of 0.9995, RMSE of 0.0078, and χ² of 0.0308. The Swebrec model also provided acceptable fits, with R² values above 0.998 and χ² values below 0.0106. These results indicate that using the LogNormal and Swebrec models allows for more accurate PSD characterization, which can enhance the optimization of cement manufacturing processes and geopolymer design.</p>

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Impact of calcination temperature on particle distribution size of clays: a comparative analysis using Rosin-Rammler, LogNormal, and Swebrec models for cement production optimization

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月16日

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  • Seke Vangu Max,
  • Mayavangua Marc Klesh,
  • Kitombole Tonny,
  • Kale Sayi Kenny,
  • Lufungula Nkwambiaya Prosper,
  • Patient M. Zamukulu,
  • Kindembo Matondo Isaac

摘要

This study investigates the impact of calcination temperature (700 °C, 750 °C, and 800 °C) on the particle size distribution (PSD) of brown and red clays from Kongo-Central province in the D.R. Congo, using laser granulometry. Three mathematical models—Rosin-Rammler, Swebrec, and LogNormal—were applied to analyze the PSD data. The results show that calcination temperature significantly influences PSD, with greater variability observed for red clay. Specifically, for brown clay calcined at 700 °C, the distributions of percentiles (Dv) revealed notable discrepancies between experimental values and model predictions. For example, for Dv(10), the differences from experimental values are − 0.352 for the Rosin-Rammler model, − 0.1774 for Swebrec, and + 0.0161 for LogNormal. Similarly, for Dv(50), the difference is − 2.1308 with Rosin-Rammler and − 0.147 with LogNormal. Finally, for Dv(90), the observed differences range from − 46.1713 for the Rosin-Rammler model to − 3.7037 for LogNormal. The LogNormal model showed the best performance with an R² of 0.9995, RMSE of 0.0078, and χ² of 0.0308. The Swebrec model also provided acceptable fits, with R² values above 0.998 and χ² values below 0.0106. These results indicate that using the LogNormal and Swebrec models allows for more accurate PSD characterization, which can enhance the optimization of cement manufacturing processes and geopolymer design.