Meta has developed an AI model to create low-carbon concrete, which it utilized in constructing new datacenters. These datacenters require substantial concrete, which poses environmental concerns due to CO2 emissions. Meta's model employs Bayesian optimization, predicting compressive strength curves for various concrete mixtures. Collaboration with Amrize and the University of Illinois Urbana-Champaign facilitated this advancement. The concrete design process is complex, involving various components affecting performance. This model accelerates the validation of new mixes, addressing the need for long-term testing for concrete performance in demanding environments.
"Designing concrete formulas is a complex, multi-objective problem. The designer must choose between various types and proportions of cement, lower-carbon supplementary cementitious materials (SCMs), water-to-binder ratios, coarse and fine aggregate types, and admixtures."
"Meta has created a model that employs Bayesian optimization to predict the compressive strength curves associated with different concrete mixtures, speeding the testing process for concrete used in datacenters."
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