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首页> 外文期刊>Materials Science and Technology >Combining predictions in a simplified 4-Θ methodology for creep life assessment: an application to 2Cr—1Mo steel
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Combining predictions in a simplified 4-Θ methodology for creep life assessment: an application to 2Cr—1Mo steel

机译:在简化的4-Θ方法中结合预测进行蠕变寿命评估:在2Cr-1Mo钢中的应用

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摘要

A simplification of the 4-Θ methodology is proposed and then used to predict creep properties under non-accelerated test conditions using data on 2Cr-1Mo steel. In the proposed simplification, creep rates at very low strains were first used to predict the minimum creep rates which are then used in the Monkman-Grant relation to predict times to failure. Because various strains can be used in this simplification, predictions using creep rates at various strains were combined in an optimal manner. These predictions were then compared with those obtained through the traditional application of the 4-Θ methodology. These predictions were assessed using the mean absolute percentage error (MAPE) and mean square error (MSE) which were further decomposed into systematic and random components.When considering the accuracy of the extrapolations for both minimum creep rates and times to failure, most of the simplified 4-Θ models produced lower MSE and MAPE compared with the traditional implementation of the 4-Θ methodology. All models also had very similar random components of the MSE. A simplified 4-Θ model that used creep rates measured at higher strain usually produced better extrapolations (as measured by the MAPE) than those obtained by combing the extrapolations from a number of simplified 4-Θ models. However, combing predictions in this way tended to increase the random component of the MSE.
机译:提出了一种简化的4-Θ方法,然后使用2Cr-1Mo钢上的数据来预测非加速测试条件下的蠕变性能。在提议的简化中,首先使用非常低应变下的蠕变速率来预测最小蠕变速率,然后将其用于Monkman-Grant关系中以预测失效时间。由于可以在此简化中使用各种应变,因此以最佳方式组合了使用各种应变下的蠕变速率进行的预测。然后将这些预测与通过4-Θ方法的传统应用获得的预测进行比较。这些预测是使用平均绝对百分比误差(MAPE)和均方误差(MSE)进行评估的,这些误差进一步分解为系统和随机分量。考虑最小蠕变率和失效时间的外推法准确性时,大多数与传统的4-Θ方法相比,简化的4-Θ模型产生的MSE和MAPE更低。所有模型还具有非常相似的MSE随机成分。简化的4-Θ模型使用较高应变下测得的蠕变速率,通常产生的外推效果(通过MAPE测量),其结果要好于通过组合多个简化的4-Θ模型得出的推论得出的结果。但是,以这种方式进行组合预测会增加MSE的随机成分。

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