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Machine Learning For High-Fidelity Prediction Of Cement Hydration Kinetics In Blended Systems, Rachel Cook, Taihao Han, Alaina Childers, Cambria Ryckman, Kamal Khayat, Hongyan Ma, Jie Huang, Aditya Kumar
Machine Learning For High-Fidelity Prediction Of Cement Hydration Kinetics In Blended Systems, Rachel Cook, Taihao Han, Alaina Childers, Cambria Ryckman, Kamal Khayat, Hongyan Ma, Jie Huang, Aditya Kumar
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
The production of ordinary Portland cement (OPC), the most broadly utilized man-made material, has been scrutinized due to its contributions to global anthropogenic CO2 emissions. Thus -- to mitigate CO2 emissions -- mineral additives have been promulgated as partial replacements for OPC. However, additives -- depending on their physiochemical characteristics -- can exert varying effects on OPC's hydration kinetics. Therefore -- in regards to more complex systems -- it is infeasible for semi-empirical kinetic models to reveal the underlying nonlinear composition-property (i.e., reactivity) relationships. In the past decade or so, machine learning (ML) has arisen as a promising, …
Machine Learning Enables Prompt Prediction Of Hydration Kinetics Of Multicomponent Cementitious Systems, Jonathan Lapeyre, Taihao Han, Brooke Wiles, Hongyan Ma, Jie Huang, Gaurav Sant, Aditya Kumar
Machine Learning Enables Prompt Prediction Of Hydration Kinetics Of Multicomponent Cementitious Systems, Jonathan Lapeyre, Taihao Han, Brooke Wiles, Hongyan Ma, Jie Huang, Gaurav Sant, Aditya Kumar
Civil, Architectural and Environmental Engineering Faculty Research & Creative Works
Carbonaceous (e.g., limestone) and aluminosilicate (e.g., calcined clay) mineral additives are routinely used to partially replace ordinary portland cement in concrete to alleviate its energy impact and carbon footprint. These mineral additives—depending on their physicochemical characteristics—alter the hydration behavior of cement; which, in turn, affects the evolution of microstructure of concrete, as well as the development of its properties (e.g., compressive strength). Numerical, reaction-kinetics models—e.g., phase boundary nucleation-and-growth models; which are based partly on theoretically-derived kinetic mechanisms, and partly on assumptions—are unable to produce a priori prediction of hydration kinetics of cement; especially in multicomponent systems, wherein chemical interactions among …