Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network

In this study, experiments were conducted on the freeze–thaw performance of manufactured sand cement concrete with different sand ratios and fly ash contents. The research found that during 200 freeze–thaw cycles, as the fly ash content increased, the concrete exhibited a higher mass loss rate and a decline in the relative dynamic modulus of elasticity. This was due to the lower activity of SiO2 and Al2O3 in the fly ash, which reduced the hydration products. Incorporating an optimal amount of manufactured sand can increase the density of concrete, thereby improving its resistance to freeze–thaw cycles. However, when the content of manufactured sand was high, its large surface area could interfere with the hydration process and reduce strength, thereby diminishing the freeze–thaw resistance of the concrete. Given that studying the freeze–thaw resistance of manufactured sand concrete is time-consuming and influenced by many factors, a prediction model based on a BP (back propagation) neural network was developed to estimate the mass loss rate and the relative dynamic modulus of elasticity following freeze–thaw cycles. After validation, the model was found to be highly reliable and could serve as a foundation for mix design decisions and freeze–thaw performance prediction of manufactured sand cement concrete.

Authors

Institutions

Publication Details

Journal
Buildings
Published
2024-09-19
DOI
https://doi.org/10.3390/buildings14092952
Citations
6
Primary Topic
Materials Engineering and Processing
Type
article
Field-Weighted Citation Impact
1.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network

Hengyu Wu, Qiju Gao
6 citations
Buildings
Materials Engineering and Processing
1.28
article

Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network

Hengyu Wu, Qiju Gao
article en
6 citations

Abstract

In this study, experiments were conducted on the freeze–thaw performance of manufactured sand cement concrete with different sand ratios and fly ash contents. The research found that during 200 freeze–thaw cycles, as the fly ash content increased, the concrete exhibited a higher mass loss rate and a decline in the relative dynamic modulus of elasticity. This was due to the lower activity of SiO2 and Al2O3 in the fly ash, which reduced the hydration products. Incorporating an optimal amount of manufactured sand can increase the density of concrete, thereby improving its resistance to freeze–thaw cycles. However, when the content of manufactured sand was high, its large surface area could interfere with the hydration process and reduce strength, thereby diminishing the freeze–thaw resistance of the concrete. Given that studying the freeze–thaw resistance of manufactured sand concrete is time-consuming and influenced by many factors, a prediction model based on a BP (back propagation) neural network was developed to estimate the mass loss rate and the relative dynamic modulus of elasticity following freeze–thaw cycles. After validation, the model was found to be highly reliable and could serve as a foundation for mix design decisions and freeze–thaw performance prediction of manufactured sand cement concrete.

BuildingsVol. 14(9)
Suzhou University of Science and Technology (CN)
National Natural Science Foundation of China, Suzhou University of Science and Technology, Suzhou University
Openalex Percentile: Top 23%
Materials Engineering and Processing
1.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network — Hengyu Wu, Qiju Gao · Buildings (2024) | TGRS Research Map | TGRS