Title: Toward Smart and Sustainable Cement Manufacturing Process: Analysis and Optimization of Cement Clinker Quality Using Thermodynamic and Data-Informed Approaches
Presented By: Taihao Han, Missouri University of Science and Technology
Description: Cement manufacturing is widely recognized for its harmful impacts on the natural environment. In recent years, efforts have been made to improve the sustainability of cement manufacturing through the use of renewable energy, the capture of CO2 emissions, and the partial replacement of cement with supplementary cementitious materials. To further enhance sustainability, optimizing the cement manufacturing process is essential. This can be achieved through the prediction and optimization of clinker phases in relation to chemical compositions of raw materials and manufacturing conditions. Cement clinkers are produced by heating raw materials in kilns, where raw materials and processing conditions all play roles in determining chemical phases of final clinkers. This study uses thermodynamic simulations to analyze phase assemblages of clinkers based on chemical compositions of raw materials and create a database. The thermodynamic simulations can accurately reproduce clinker phases in comparison with experimental results. Subsequently, the simulated database is employed to train a data-informed model, and the predictions are used to determine the optimal composition domains that produce high quality clinker (C3S greater than 50%) at different calcination temperatures. Additionally, optimal lime saturation factor and alumina modulus are investigated to achieve target clinker phases. Overall, this study demonstrates the potential of using the data-informed approach to achieve smart manufacturing process and improve its sustainability.
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