首页> 外文期刊>Fire and materials >Properties of pumice aggregate concretes at elevated temperatures and comparison with ANN models
【24h】

Properties of pumice aggregate concretes at elevated temperatures and comparison with ANN models

机译:浮石骨料混凝土的高温性能及与人工神经网络模型的比较

获取原文
获取原文并翻译 | 示例
       

摘要

The mechanical properties and thermal conductivity of concretes including pumice aggregate (PA) exposed to elevated temperature were analyzed by thermal conductivity, compressive strength, flexure strength, dynamic elasticity modulus (DEM) and dry unit weight tests. PA concrete specimens were cast by replacing a varying part of the normal aggregate (0-2 mm) with the PA. All concrete samples were prepared and cured at 23 +/- 10C lime saturated water for 28 days. Compressive strength of concretes including PA decreased that reductions were 14, 19, 25 and 34% for 25, 50, 75 and 100% PA, respectively. The maximum thermal conductivity of 1.9382W/mK was observed with the control samples containing normal aggregate. The tests were carried out by subjecting the samples to a temperature of 0, 100, 200, 300, 400 500, 600 and 700 degrees C for 3 h, then cooling by air cooling or in water method. The results indicated that all concretes exposed to a temperature of 500 and 700 degrees C occurred a significant decrease in thermal conductivity, compressive strength, flexure strength and DEM. An artificial neural network (ANN) approach was used to model the thermal and mechanical properties of PA concretes. The predicted values of the ANN were in accordance with the experimental data. The results indicate that the model can predict the concrete properties after elevated temperatures with adequate accuracy. Copyright (C) 2016 John Wiley & Sons, Ltd.
机译:通过热导率,抗压强度,挠曲强度,动态弹性模量(DEM)和干重测试,分析了包括暴露于高温的浮石骨料(PA)在内的混凝土的机械性能和热导率。通过用PA代替普通骨料的不同部分(0-2 mm)来铸造PA混凝土标本。制备所有混凝土样品并在23 +/- 10℃的石灰饱和水中固化28天。包括PA在内的混凝土的抗压强度降低,其中25%,50%,75%和100%PA分别降低了14%,19%,25%和34%。对于含有正常骨料的对照样品,观察到最大热导率为1.9382W / mK。通过将样品置于0、100、200、300、400 500、600和700摄氏度的温度下3小时,然后通过空冷或水冷法进行测试。结果表明,所有暴露于500和700摄氏度温度的混凝土的导热系数,抗压强度,挠曲强度和DEM均显着降低。人工神经网络(ANN)方法用于模拟PA混凝土的热和力学性能。人工神经网络的预测值与实验数据一致。结果表明,该模型可以准确预测高温后的混凝土性能。版权所有(C)2016 John Wiley&Sons,Ltd.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号