Data-driven optimization tool for the functional, economic, and environmental properties of blended cement concrete using supplementary cementitious materials

The need to produce more sustainable concrete is proving imminent given the rising environmental concerns facing industry. Blended cement concrete, based on any of prominent supplementary cementitious materials (SCMs) such as fly ash, ground granulated blast-furnace slag, silica fume, calcined clay and limestone powder, have proven be best candidates for mixes. However, a reliable sustainability measure includes not only impact, but also economic functional ones. Within these five SCMs, their environmental, properties are found conflicting at times, making clear judgement what would optimum mix straightforward path. A recent framework tool assessment ECO2, sets methodology including performance depending project-based specifications. Therefore, in this study, recently published regression model, Pre-bcc was used predict wide grid search potentially suitable blended Hence, an open access novel genetic algorithm “Opt-bcc” developed optimize score mixes set selection user-defined project-specific criteria. optimized using Opt-bcc model each strength class were compared against design proposed by other optimization models from literature least 70% cheaper 30% less impact.