Explosive spalling is a severe threat to concrete at high temperature. The addition of steel fibers is believed to be useful to mitigate explosive spalling of concrete. But predicting explosive spalling of steel fiber reinforced concrete remains to be a challenging topic. This paper adopted a popular machine learning approach, i.e., artificial neural network (ANN), to predict explosive spalling of steel fiber reinforced concrete and furthermore study the effect of steel fibers on explosive spalling resistance of concrete. Two ANN models were developed, with ANN1 concrete mix-based and ANN2 concrete strength-based. Twenty groups of heating tests were conducted to validate the proposed ANN models. Both ANN models showed the prediction accuracy of 100%, which demonstrates that ANN is a powerful tool for assessing explosive spalling risk of steel fiber reinforced concrete. A parametric study was also conducted to investigate the effect of steel fibers on explosive spalling resistance of concrete using the well-validated ANN1.

中文翻译：

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使用人工神经网络预测加热钢纤维混凝土的爆炸剥落

爆炸性剥落是高温下混凝土的严重威胁。相信添加钢纤维可用于减轻混凝土的爆炸性剥落。但预测钢纤维混凝土的爆炸性剥落仍然是一个具有挑战性的课题。本文采用一种流行的机器学习方法，即人工神经网络（ANN）来预测钢纤维混凝土的爆炸剥落，并进一步研究钢纤维对混凝土爆炸抗剥落性能的影响。开发了两种 ANN 模型，ANN1 基于混凝土配合比和 ANN2 基于混凝土强度。进行了 20 组加热测试以验证所提出的 ANN 模型。两种 ANN 模型都显示出 100% 的预测准确率，这表明人工神经网络是评估钢纤维混凝土爆炸剥落风险的有力工具。还进行了参数研究，以使用经过充分验证的 ANN1 来研究钢纤维对混凝土抗爆裂性剥落的影响。