Time Series Analysis for Prediction of ASR-Induced Expansions
The aim of this study was to predict and classify ASR reactivity of mortar bars submerged in 1, 0.5 and 0.25N NaOH solutions. The experimental expansion data were recorded from the mortar specimens prepared with twelve different aggregate groups for the three alkali solutions. The dataset were then fitted in a Time Series (TS) regression model to predict the ASR-induced expansion of each aggregate group for up to 98 days. The results showed that, regardless of aggregate source, the TS model was very suitable in prediction of mortar expansions when compared to those obtained experimentally. The ASR classification of the investigated aggregates obtained from the predicted expansions of the TS regression model was nearly identical to the classification determined by using experimental mortar expansions.
Aggregates (Building materials); Alkali-silica reactivity; Building; Building materials; Cracks; Mortar bar; Expansion; Regression analysis; Regression analysis--Mathematical models; Solution concentration; Test duration; Time-series analysis; Time-series analysis--Mathematical models; Time Series model
Civil and Environmental Engineering | Civil Engineering | Construction Engineering and Management | Structural Engineering
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Time Series Analysis for Prediction of ASR-Induced Expansions.
Construction and Building Materials, 49