A Multivariate Computational Framework to Characterize and Rate Virtual Portland Cements

Abstract

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.

A Review of Rheological Modeling of Cement Slurry in Oil Well Applications

“…Optimization algorithms including the deterministic simplex method and the stochastic genetic method were applied to determine the parameters in the Herschel-Bulkley model for fresh cement suspensions [9]. Multi-objective optimization methods, such as support vector regression (SVR), model tress (MT), M5 model rules, mix and design approach, particle swarm optimizations (PSO) and response surface method (RSM) are also used in cement chemistry and hydration processes to obtain optimal chemical combination and proportion for better cement performance, workability, and energy consumptions [201,[301][302][303][304].…”

“…Cements with larger w/c have a smaller concentration. At early stages, w/c has little effect on cement hydration while it has a bigger effect on the physical properties such as strength development, and the setting time [201,202]. The viscosity was found to decrease when the water-to-cement ratio increased [98,115,116,145], shown in Figure 17.…”

An Error Prediction Model for Construction Bulk Measurements Using a Customized Low-Cost UAS-LIDAR System

“…The median value shown in Equation ( 10) is expected to be a robust estimation. To better find all the points, some optimization methods will be applied in future work [55].…”

Calibration of the descent local search algorithm parameters using orthogonal arrays

“…According to Stork et al [21] optimization techniques can be classified into the following three groups: (1) Exact optimization methods, (2) Surrogate-based optimization methods, and (3) Heuristic and Metaheuristic optimization methods. Among these tools it is important to highlight the Heuristic Algorithms, as they provide adequate solutions for realistic and complex optimization problems [22][23][24][25][26][27][28][29][30][31][32][33][34].…”