Study on the degradation and prediction model of concrete compressive strength under composite salt erosion

To investigate the evolution of concrete compressive strength in a Na2SO4–NaHCO3 composite salt – flowing water environment typical of karst tunnel groundwater, accelerated erosion tests were conducted based on the representative ionic system of Guangxi. The influences of sulfate concentration, carbonate concentration, seepage velocity, and exposure age were examined, and a BP neural network model was developed using these environmental variables as inputs. Results show a unimodal two-stage behavior of ‘initial enhancement followed by deterioration.’ Across 18 conditions, peak strength ranged from 46.2–54.2 MPa (1.2%–13.6% higher than 30 d), with 7.8%–19.9% reduction by 90 d. Increased flow velocity advanced the peak age by about 15 d and accelerated post-peak degradation. Under high concentration and velocity (6% + 18%, 0.3 m/s), strength declined from 49.9 MPa to 40.1 MPa, revealing a strong concentration – velocity coupling effect. The BP model achieved high correlation (R2 = 0.836 at 30 d; 0.958 at 90 d) with stable and accurate predictions, providing a practical tool for durability assessment of tunnel linings.

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Publication Details

Journal
Journal of the Chinese Institute of Engineers
Published
2026-06-24
DOI
https://doi.org/10.1080/02533839.2026.2683466
Primary Topic
Dam Engineering and Safety
Type
article
Field-Weighted Citation Impact
0.00

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article

Study on the degradation and prediction model of concrete compressive strength under composite salt erosion

Mengkun Ran, Jia’an Niu, Haonan Long, Chunfa Xiong et al.
Journal of the Chinese Institute of Engineers
Dam Engineering and Safety
article

Study on the degradation and prediction model of concrete compressive strength under composite salt erosion

Mengkun Ran, Jia’an Niu, Haonan Long, Chunfa Xiong, Sun Hao, Tingwei Yang, Shiheng Yang, Bo Liang
article en

Abstract

To investigate the evolution of concrete compressive strength in a Na2SO4–NaHCO3 composite salt – flowing water environment typical of karst tunnel groundwater, accelerated erosion tests were conducted based on the representative ionic system of Guangxi. The influences of sulfate concentration, carbonate concentration, seepage velocity, and exposure age were examined, and a BP neural network model was developed using these environmental variables as inputs. Results show a unimodal two-stage behavior of ‘initial enhancement followed by deterioration.’ Across 18 conditions, peak strength ranged from 46.2–54.2 MPa (1.2%–13.6% higher than 30 d), with 7.8%–19.9% reduction by 90 d. Increased flow velocity advanced the peak age by about 15 d and accelerated post-peak degradation. Under high concentration and velocity (6% + 18%, 0.3 m/s), strength declined from 49.9 MPa to 40.1 MPa, revealing a strong concentration – velocity coupling effect. The BP model achieved high correlation (R2 = 0.836 at 30 d; 0.958 at 90 d) with stable and accurate predictions, providing a practical tool for durability assessment of tunnel linings.

Journal of the Chinese Institute of Engineers
Shanghai Tunnel Engineering (China) (CN), Guangxi Transportation Research Institute (CN), Chongqing Jiaotong University (CN)
National Natural Science Foundation of China, Guangxi Key Research and Development Program
Life in Land
Openalex Percentile: Top 11%
Dam Engineering and Safety
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