A probability approach to the estimation of the process of accumulation of the high-cycle fatigue damage considering the natural aging of a material

Abstract

This work deals with the development of a new approach to a high-cycle fatigue lifetime prediction, which is made in the stochastic framework and allows taking into account the natural degradation (aging) of material properties. Degradation of properties has been modeled as a process of the reduction of fatigue (endurance) limit. Kinetics of damage accumulation is introduced in the context of the effective stress concept. Mathematical expectation, correlation function and the continuum damage parameter variance have been obtained as functions of time. Analysis of the influence of natural aging process on statistical parameters of damage accumulation as well as on the lifetime has been carried out.

Probabilistic fatigue life prediction and reliability assessment of a high pressure turbine disc considering load variations

“…In general, high reliability of hot section components like turbine discs can be achieved by improving its material performance, life prediction capability, and highly conservative design strategy (Zhu et al., 2012). In practical applications, material properties, structural geometries, and loads, such as rotational speeds of the high pressure turbine (HPT) disc in this analysis, are stochastic or inherently random nature, which usually lead to the scatter in their usage lives (De Jesus et al., 2010; Fernández-Canteli et al., 2014; Larin and Vodka, 2015; Liang and Chen, 2016; Mao et al., 2017; Muniz-Calvente et al., 2017; Sanches et al., 2015; Wang et al., 2017; Yuan et al., 2015; Zhu et al., 2012). For the structures designed with a long target life, Larin and Vodka(2015) analyzed the influence of natural degradation process of material properties on statistical analysis of damage accumulation as well as the usage lifetime.…”

“…In practical applications, material properties, structural geometries, and loads, such as rotational speeds of the high pressure turbine (HPT) disc in this analysis, are stochastic or inherently random nature, which usually lead to the scatter in their usage lives (De Jesus et al., 2010; Fernández-Canteli et al., 2014; Larin and Vodka, 2015; Liang and Chen, 2016; Mao et al., 2017; Muniz-Calvente et al., 2017; Sanches et al., 2015; Wang et al., 2017; Yuan et al., 2015; Zhu et al., 2012). For the structures designed with a long target life, Larin and Vodka(2015) analyzed the influence of natural degradation process of material properties on statistical analysis of damage accumulation as well as the usage lifetime. Thus, a better understanding of load variations to which today’s engine hot section components are subjected as well as developing accurate lifing methods is necessary (Beretta et al., 2016; Sandberg et al., 2017; Zhu et al., 2012, 2016).…”

Statistical Estimation of Residual Strength and Reliability of Corroded Pipeline Elbow Part Based on a Direct Fe-Simulations

“…Appearance of corrosion defects, the features of their growth and the effect on residual durability structural elements are of interest for engineers (Larin & Vodka, 2015). The scientists focus on analyzing and predicting the initiation of corrosion, as well as modeling its growth.…”

A new fatigue damage accumulation model considering loading history and loading sequence based on damage equivalence

“…In addition to the aforementioned popular classic methods, there are some other classic theories and their improved methods: models based on modifying life-curve (Hashin and Rotem, 1978; Subramanyan, 1976); energy-based damage theories (Golos and Ellyin, 1987; Kreiser et al., 2007; Meneghetti, 2007; Niu, 1987; Niu et al., 1987; Scott-Emuakpor et al., 2008; Zhu and Huang, 2010; Zhu et al., 2011a, 2012b); continuum damage mechanics approaches (Besson, 2010; Chaboche and Lesne 1988; Chaboche, 1974; Chow and Wei, 1991; Grammenoudis et al., 2009a, 2009b; Lemaitre and Plumtree, 1979; Oller et al., 2005; Tikri et al., 2014; Van Do et al., 2015; Wang, 1992; Yuan et al., 2013; Zhan et al., 2016); damage theories based on physical property degradation (Cheng and Plumtree, 1998; Lv et al., 2015; Seweryn et al., 2008; Shang and Yao, 1999; Ye and Wang, 2001; Yuan et al., 2015); ductility exhaustion based methods (Goswami, 2004; Hales, 1983; Priest and Ellison, 1981; Zhu et al., 2011b, 2012a, 2013); and thermodynamic entropy based damage theories (Macha et al., 2006; Marco and Starkey, 1954; Naderi et al., 2010). With the development and application of new technology and new theory, many new predicting methods are presented for the modern situation: probability prediction method (Grell and Laz, 2010; Larin and Vodka, 2015; Li et al., 2012; Ontiveros et al., 2010; Rathod et al., 2011; Xie et al., 2015); root mean square model (Kim et al. 2006); methodology using ent...…”