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首页> 美国政府科技报告 >Modeling the Durability of Aggregate Used in Concrete Pavement Construction: ANeuro-Reliability-Based Approach
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Modeling the Durability of Aggregate Used in Concrete Pavement Construction: ANeuro-Reliability-Based Approach

机译：混凝土路面施工中骨料耐久性建模：基于神经可靠性的方法

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In this report, backpropagation neural networks are developed from a largedatabase containing data pertinent to 750 different experimental investigations on concrete durability. The database was acquired from the Kansas Department of Transportation (KDOT). The networks are designed to enable determination of the durability factor and percent expansion from five basic physical of the durability factor and percent expansion from five basic physical properties of the aggregate. The developed neural models were found to classify the aggregates with regard to their durability with a relatively high degree of accuracy. The experimental data and predictions were used to produce reliability factors that indicate the probability that tested aggregate will meet specifications. In a second phase, the developed neural models were also validated against 778 new experimental durability data sets. The matrix was also found to truly represent the model characterization based on new experimental data. This indicates that the reliability matrix has stabilized.

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