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A Multivariate Computational Framework to Characterize and Rate Virtual Portland Cements
Author(s) -
Tao Chengcheng,
Watts Benjamin,
Ferraro Christopher C.,
Masters Forrest J.
Publication year - 2019
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/mice.12413
Subject(s) - cementitious , computer science , cement , particle swarm optimization , environmental science , materials science , composite material , algorithm
This article presents a novel application of metaheuristic optimization and rating techniques to virtual test results for cement and mortar, and presents objective computational methods for the evaluation and selection of cementitious materials based on simulated material testing. A scalable approach based on particle swarm optimization of the National Institute of Standards and Technology Virtual Cement and Concrete Testing Laboratory (VCCTL) is successfully demonstrated using ∼150,000 combinations of cement phase distributions and water‐to‐cement ratios, with as few as 10% of the VCCTL runs required to obtain the optimal solutions. The application of Pareto front analysis reveals an inherent trade‐off between the modulus of elasticity, time of set, and kiln temperature (using alite:belite as a proxy) at the performance limits. This study also provides a means to objectively characterize cements in these contexts using a maximum likelihood estimator to calculate a score from the cumulative distribution function, using a random subset of the 150,000 simulated cement pastes. The proposed approach provides a new pathway to optimally proportion raw materials (and eventually waste by‐products) to reduce production costs, extend the life of a quarry, or reduce the carbon footprint of cement plants.