盐冻条件下纤维混凝土耐久性及强度预测  

Predicting the durability and strength of fiber-reinforced concrete exposed to salt and freezing conditions

作　　者：徐存东 陈家豪 李准 连海东 XU Cundong;CHEN Jiahao;LI Zhun;LIAN Haidong(School of Water Conservancy,North China University of Water Resources and Electric Power,Zhengzhou 450046,China;Key Laboratory for Technology in Rural Water Management of Zhejiang Province,Hangzhou 310018,China;Henan Provincial Hydraulic Structure Safety Engineering Research Center,Zhengzhou 450046,China)

机构地区：[1]华北水利水电大学水利学院,河南郑州450046 [2]浙江省农村水利水电资源配置与调控关键技术重点实验室,浙江杭州310018 [3]河南省水工结构安全工程技术研究中心,河南郑州450046

出　　处：《水利水运工程学报》2024年第1期94-103,共10页Hydro-Science and Engineering

基　　金：中原科技创新领军人才支持计划(204200510048);浙江省基础公益研究计划项目(LZJWD22E090001);河南省科技攻关项目(212102310273)。

摘　　要：为探明玄武岩纤维细石混凝土在盐冻条件下的耐久性,准确预测混凝土在非线性特征及外界多因素影响下的强度变化,以甘肃景电灌区盐碱地的水工建筑物群及其服役环境条件为验证原型,通过开展室内材料试验,改变冻融介质(清水、3%NaCl溶液、5%Na2SO4溶液)及玄武岩纤维体积掺量(0、0.05%、0.10%、0.15%、0.20%),初步探究玄武岩纤维细石混凝土在不同盐冻环境下的单轴抗压强度变化规律。基于室内试验结果,通过构建天牛须搜索算法(BAS)与BPNN结合的BAS-BP模型,预测了盐冻条件变化下玄武岩纤维细石混凝土的抗压强度;为验证BAS算法的准确性,同时构建经两个智能算法改进的BPNN模型,对不同模型计算得出的性能指标进行分析及误差对比。试验结果表明:适量的玄武岩纤维掺入可以提高细石混凝土的抗盐冻性能,纤维体积掺量为0.15%时,细石混凝土的各方面性能最优;NaCl溶液中的试件比Na2SO4溶液的冻融损伤更严重。模型预测误差对比表明,BAS-BP模型具有较好的准确性和稳定性。This study aims to determine the influence of salt-freezing conditions on the durability of basalt fiber fine stone concrete and accurately predict strength changes considering nonlinear characteristics and external factors.Hydraulic structures and their environmental conditions in the saline-alkali land of Jingdian irrigation area in Gansu,China served as a test case.Indoor material tests were conducted by varying the freezing and thawing medium(clean water,3%NaCl solution,5%Na2SO4 solution)and basalt fiber content(0,0.05%,0.10%,0.15%,0.20%).This provided preliminary insights into uniaxial compressive strength changes of basalt fiber fine stone concrete under different salt-freeze environments.Based on laboratory results,a basic-BP model combining BPNN and the beetle antennae search algorithm(BAS)was developed to predict compressive strength changes considering varying saltfreezing conditions.Additionally,two other BPNN models improved by intelligent algorithms were constructed for comparison.Model performance and error analysis revealed the BAS-BP model predictions agreed closely with tests,demonstrating good accuracy and stability.This can greatly improve efficiency in obtaining durability test results for basalt fiber fine stone concrete.Appropriate basalt fiber content,such as 0.15%,was found to enhance salt freezing resistance,with optimal performance across factors.NaCl exposure caused more severe damage than Na2SO4 during freezing and thawing.The error analysis revealed that the BAS-BP model's predictions most closely matched the test results,demonstrating strong predictive accuracy and stability.

关 键 词：细石混凝土 玄武岩纤维 抗压强度 神经网络 天牛须搜索算法(BAS) 

分 类 号：TV431[水利工程—水工结构工程]