Guštin Agnieszka Zuzanna, Žužek Borut, Podgornik Bojan
Institute of Metals and Technology, Lepi pot 11, 1000 Ljubljana, Slovenia.
Materials (Basel). 2022 Jun 23;15(13):4431. doi: 10.3390/ma15134431.
Creep is defined as the permanent deformation of materials under the effect of sustained stress and elevated temperature for long periods of time, which can essentially lead to fracture. Due to very time-consuming and expensive testing requirements, existing experimental creep data are often analyzed using derived engineering parameters and models to predict and find the correlations between creep life (time to rupture), temperature and stress. The objective of this study was to analyze and compare different numerical algorithms by using the Larson-Miller parameter (LMP) extrapolation model. Calculations were performed using the classical LMP equation where different values of parameter C were selected, as well as using a modified LMP equation in which parameter C was stress dependent C(σ). The impact of two different approaches of extrapolation and correlation functions (linear and polynomial) applied to fit the LMP model was also investigated. A detailed analysis was performed to choose the best extrapolation fit function and error tolerance. The numerical algorithm implemented was validated through creep rupture testing performed on 10CrMo9-10 steel at 600 °C (873 K) and 80 MPa. Creep model behavior analysis proved that different values of C can significantly change the estimated time to rupture. An excellent response of the LMP model was obtained by considering polynomial dependency when parameter C was assumed to be 18, especially for the temperature range from 773 to 873 K. Promising results were also achieved when parameter C was taken as stress-dependent, but only for linear fitting, which requires further analysis. However, at validation stage it turned out that only the linear extrapolation function and C taken as a constant value provided adequate time-to-rupture prediction. In the case of C = 18, estimated time was slightly overestimated (~8%) and for C = 20 it was underestimated by 27%. In all other cases error largely exceeded 50%.
蠕变被定义为材料在持续应力和高温长时间作用下的永久变形,这基本上会导致断裂。由于测试要求非常耗时且昂贵,现有的实验蠕变数据通常使用推导的工程参数和模型进行分析,以预测并找出蠕变寿命(断裂时间)、温度和应力之间的相关性。本研究的目的是使用拉森 - 米勒参数(LMP)外推模型分析和比较不同的数值算法。计算使用经典的LMP方程进行,其中选择了不同的参数C值,还使用了参数C与应力相关C(σ)的修正LMP方程。还研究了应用于拟合LMP模型的两种不同外推和相关函数方法(线性和多项式)的影响。进行了详细分析以选择最佳的外推拟合函数和误差容限。通过在600°C(873K)和80MPa下对10CrMo9 - 10钢进行蠕变断裂试验,对所实施的数值算法进行了验证。蠕变模型行为分析证明,不同的C值会显著改变估计的断裂时间。当假设参数C为18时,考虑多项式相关性可获得LMP模型的良好响应,特别是对于773至873K的温度范围。当参数C被视为与应力相关时也取得了有希望的结果,但仅适用于线性拟合,这需要进一步分析。然而,在验证阶段发现,只有线性外推函数和C取恒定值才能提供足够的断裂时间预测。在C = 18的情况下,估计时间略有高估(约8%),而在C = 20时低估了27%。在所有其他情况下,误差大大超过50%。