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Materials Science and Engineering

Missouri University of Science and Technology

Doctoral Dissertations

Theses/Dissertations

Machine Learning

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Full-Text Articles in Engineering

Studying The Effects Of Various Process Parameters On Early Age Hydration Of Single- And Multi-Phase Cementitious Systems, Rachel Cook Jan 2020

Studying The Effects Of Various Process Parameters On Early Age Hydration Of Single- And Multi-Phase Cementitious Systems, Rachel Cook

Doctoral Dissertations

”The hydration of multi-phase ordinary Portland cement (OPC) and its pure phase derivatives, such as tricalcium silicate (C3S) and belite (ß-C2S), are studied in the context varying process parameters -- for instance, variable water content, water activity, superplasticizer structure and dose, and mineral additive type and particle size. These parameters are studied by means of physical experiments and numerical/computational techniques, such as: thermodynamic estimations; numerical kinetic-based modelling; and artificial intelligence techniques like machine learning (ML) models. In the past decade, numerical kinetic modeling has greatly improved in terms of fitting experimental, isothermal calorimetry to kinetic-based modelling …


Thermodynamic Investigations Of Pure And Blended Cement Mixtures, Jonathan Lapeyre Jan 2020

Thermodynamic Investigations Of Pure And Blended Cement Mixtures, Jonathan Lapeyre

Doctoral Dissertations

” This research is made up of several studies. The first study focused on understanding the reaction kinetics of Ca3SiO5 and metakaolin (MK) mixtures compared to Ca3SiO5 and silica fume (SF) mixtures. It was shown that MK was a more effective additive than SF at small replacement levels (i.e. ≥ 10% by mass) while higher replacement levels of MK became a detriment due to excess (Al(OH)4¯) ions preventing the nucleation and growth of C-S-H. In a follow-up study where the MK particle size distribution (PSD) was modified, similar effects were observed but …