考虑不确定性的少量核心试验无损检测混凝土强度估算

IF 1.8 Q2 ENGINEERING, MULTIDISCIPLINARY
S. Dauji, Soubhagya Karmakar
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引用次数: 2

摘要

20世纪最后几十年建造的重要设施已接近设计寿命。为了延长其使用寿命或评估这些新要求(载荷),必须评估现有结构中的混凝土强度,这项任务通常通过无损检测(NDT)进行;超声波脉冲速度和回弹锤是最常用的。抗压强度是利用无损检测与部分破坏试验(PDT)(如岩心试验)相关的经验表达式来估计的。对于结构特异性表达式的开发,足够数量的PDT结果(取决于可变性和期望的置信水平)是必不可少的,但由于操作限制,这些结果可能无法获得。文献中的相关表达式可以在这种情况下使用,但由于针对不同的成分、固化制度和环境暴露条件而开发,因此会存在相关的不确定性。估计这些不确定度的实用方法在文献中还没有找到。本文提出了用文献表达式对间接强度估计的不确定度进行再抽样量化的统计方法。使用参数(概率分布)和非参数(自举)工具,并通过印度的案例研究进行了演示。参数方法和非参数方法都可以捕获跨成员的可变性,而非参数方法的总体不确定性整合和可重复性更好。与非参数方法相比,参数方法具有一定的优势,是一种传统的方法,为实践者所接受。文中列举的详细方法对全世界的从业者都非常有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating Concrete Strength From Non-Destructive Testing with Few Core Tests Considering Uncertainties
Important facilities constructed during last decades of 20th century are near completion of design life. For extending their service life or to evaluate these for new demands (loads), assessment of strength of concrete in existing structure becomes necessary, a task generally performed with non-destructive tests (NDT); ultrasonic pulse velocity and rebound hammer being most commonly executed. Compressive strength is estimated using empirical expressions relating NDT to partially destructive tests (PDT) such as core test. For development of structure-specific expressions, results of adequate number (depending on variability and desired confidence level) of PDT are essential but these might not be available due to operational constraints. Correlation expressions from literature could be used in such cases but having been developed for different ingredients, curing regimes, and environmental exposure conditions, there would be associated uncertainties. A practical method for estimation of these uncertainties is not readily available in literature. This article proposes the statistical approach of re-sampling for quantifying uncertainty of indirect strength estimates using expressions from literature. Parametric (probability distribution) and nonparametric (bootstrap) tools are employed and demonstrated with a case study from India. Both parametric and nonparametric approaches could capture across-member variability whereas overall uncertainty incorporation as well as repeatability was better in nonparametric approach. Parametric approach is traditionally used and well accepted by practitioners in contrast to nonparametric methods, which have certain advantages. The detailed methodology enumerated in the article would be very useful for practitioners across the world.
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来源期刊
CiteScore
5.20
自引率
13.60%
发文量
34
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