Optimization of Accelerated Destructive Degradation Testing of Cementitious Materials for Their Performances Qualification under Aggressive Environments: The Case of Carbonation
Optimization of Accelerated Destructive Degradation Testing of Cementitious Materials for Their Performances Qualification under Aggressive Environments: The Case of Carbonation
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DOI：
10.1155/2020/5295627
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发表时间：
2020-04
影响因子：
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通讯作者：
Weian Yan;D. Bigaud;Nadare Matoiri Chaibati;L. Izoret
中科院分区：
文献类型：
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作者：
Weian Yan;D. Bigaud;Nadare Matoiri Chaibati;L. Izoret
为了保证性能或资格的胶凝材料随着时间的推移的非性能的风险，大量的实验数据从模拟各种降解机制的测试获得的是必需的。材料在环境服务条件下的缓慢降解是一个问题，因此，需要加速策略以在较短时间内获得可靠和全面的结果。这项研究工作的目的是提供一个通用的框架，设计最佳的加速破坏性降解试验（ADDT）的胶凝材料资格。实验的最佳设计的定义取决于捕捉来自任何来源的数据可变性和不确定性的影响的能力;它们是从物理模型或实验测试中提取的。在这项研究中，碳化深度的演变特征与维纳过程的形式主义，并考虑到有关的材料的非均匀性的随机效应。一旦过程参数估计通过最大似然估计（MLE），与期望最大化（EM）算法，我们提供了一个逐步的和详细的方法来研究ADDT的最优设计。后者被定义为一个，我们可以估计耐久性指标，如平均失效时间的最佳精度的基础上三个标准（D-V-A最优性）考虑时间的限制，样本总数，或有限的成本。确定了加速碳化试验的最优总样本量和各应力水平下的最优样本量分配比例，并讨论了应力水平对目标函数和试验时间约束的影响。最佳三电平ADDT与最佳两电平ADDT的相对效率的比较完成了这项工作。
In order to guarantee the performance or to qualify the risk of nonperformance of cementitious materials over time, a significant number of experimental data obtained from tests mimicking various degradation mechanisms are required. The slowness of the materials’ degradation under environmental service conditions is an issue, and thus, acceleration strategies are required to obtain reliable and comprehensive results in a shorter time. The objective of this research work is to provide a generic framework for the design of optimal accelerated destructive degradation tests (ADDTs) for cementitious materials qualification. The definition of the optimal design of experiments depends on the capacity to capture the influence of data variability and uncertainty from any sources; they are extracted either from physical models or from experimental tests. In this research, the evolution of carbonation depth is characterized with the Wiener process formalism and the random effects related to the material heterogeneity are taken into account. Once the process parameters are estimated through the maximum likelihood estimation (MLE), associated with the expectation-maximization (EM) algorithm, we provide a step-by-step and detailed method to investigate the optimal design of ADDTs. The latter is defined as the one for which we can estimate durability indicators such as mean-time-to-failure with the best accuracy based on three criteria (D-V-A optimality) considering constraints of time, total number of samples, or limited costs. The optimal total sample size for the accelerated carbonation test and the optimal sample size allocation proportions for each stress level are determined, and the effects of the stress level on the objective functions and of test time duration constraint are also discussed. A comparison of the relative efficiency of optimal three-level versus optimal two-level ADDT completes this work.