Title: Prediction of compressive strength of nano concrete used in construction under freeze-thaw cycles

Authors: Xiaoyuan Xiong; Xuyang Li

Addresses: School of Civil Engineering, Henan Vocational University of Science and Technology, Zhoukou, Henan, 466000, China ' Henan Zhongxiangrui Engineering Consulting Co., Ltd, Zhoukou, Henan, 466000, China

Abstract: In order to clarify the compressive strength performance of nano concrete under harsh conditions of freeze-thaw cycles, a study was conducted on the prediction of compressive strength of nano concrete for construction under freeze-thaw cycles. Firstly, analyse the preparation raw materials and properties of nano concrete, and prepare nano concrete specimens according to the preparation process of nano concrete. Secondly, set the conditions for freeze-thaw cycles and select the pressure machine for the experiment. Finally, taking the dosage of nano SiO₂ as input and the predicted compressive strength as output, a BP neural network was used to construct a nano concrete compressive strength prediction model, and the predicted compressive strength results were obtained. The research results indicate that the relative error in predicting the compressive strength of nano concrete proposed in this article is relatively small, with a maximum relative error not exceeding 8%.

Keywords: freeze-thaw cycle; building nano concrete; prediction of compressive strength; BP neural network.

DOI: 10.1504/IJMMP.2025.143422

International Journal of Microstructure and Materials Properties, 2025 Vol.18 No.1/2, pp.48 - 58

Received: 03 Apr 2024
Accepted: 07 Aug 2024
Published online: 19 Dec 2024 *

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