Trade Journals for the Concrete Industry

Rapid advances in concrete technology put demands on constituent materials and present new challenges for the production of concrete mixes. The required flexibility in the properties of concrete can be achieved by complexifying mix compositions and adding new constituents. This inevitably leads to a complication in mix design optimization, which is a task that the industry faces in everyday routine. The goal of this article is to demonstrate how modern data science and machine learning methods can be used to tackle optimization problems for multi-component concrete, using an example of mixtures involving quartz flour and fly ash.