
为预测连续高湿度环境下混凝土碳化深度,通过制备9组不同配合比的混凝土试件并开展碳化试验,系统研究碳化龄期、水胶比、粉煤灰掺量、矿粉掺量及相对湿度对混凝土碳化深度的影响。基于试验数据,建立BP和GA-BP神经网络模型,并对两种模型预测结果进行对比分析。结果表明:GA-BP模型的R
2
较BP模型提高了0.91%
MAE、MSE和RMSE均有所降低,显示出更优的预测性能;碳化龄期和水胶比是影响碳化深度的主导因素,相对湿度和矿物掺合料也具有显著影响。该研究可为实际工程中混凝土配合比的优化设计提供理论支持和实践指导。
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