寒冷地区腈纶纤维混凝土力学性能及多层感知器神经网络预测

doi:10.11896/cldb.23110143

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Abstract To extend the service life of concrete materials in cold regions and minimize resource expenditure during the construction and maintenance of water conservancy projects, polyacrylonitrile fiber reinforced concrete (PANFRC) has been developed through the incorporation of polyacrylonitrile fibers. This work investigated the influence of curing methods, curing ages, and fiber content on dynamic elastic modulus, surface rebound hardness, compressive strength, and splitting strength of PANFRC under cold climate conditions. The findings indicate that concrete cured in outdoor in cold region winter is susceptible to frost damage to hardly achieve the target compressive strength at 28 days. A fiber content of 1.5—1.8 kg/m³ can enhance the concrete's properties, especially for tensile performance, and improve its crack resistance. Moreover, based on existing empirical correlations, a mathematical model for converting mechanical indices suitable for PANFRC had been established. Furthermore, based on experimental data, neural network prediction models (RBFN and MLPN) for the compressive and tensile properties of PANFRC had been developed. Model accuracy evaluations reveal that the MLPN model outperforms the RBFN model here. The absolute errors for compressive strength and splitting tensile strength predictions in the test set are confined to within 3 MPa and 0.17 MPa, respectively, with relative errors kept below 9% and 6%, respectively, and the correlation coefficient (R²) exceeding 0.9. This research provides a theoretical foundation for the broader application of PANFRC in canal lining and other water conservancy infrastructure construction in cold regions.

Key words： acrylic fiber concrete mechanical property strength prediction neural network canal lining

Published: 25 March 2025 Online: 2025-03-24

CLC number:

TV43

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	Articles by authors
	DUAN Minghan
	QIN Yuan
	LI Yang
	GENG Kaiqiang

Cite this article:

DUAN Minghan,QIN Yuan,LI Yang, et al. Mechanical Properties of Polyacrylic Fiber Concrete in Cold Areas and Prediction by Multilayer Perceptron Neural Network[J]. Materials Reports, 2025, 39(6): 23110143-9.

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https://www.mater-rep.com/EN/10.11896/cldb.23110143 OR https://www.mater-rep.com/EN/Y2025/V39/I6/23110143

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