Stochastic Creep Damage Estimation in Pipings with Spatial Non-gaussian Uncertainties Using Spectral Stochastic Finite Element Method

Probabilistic creep with the Wilshire–Cano–Stewart model

“…Several "single-source" uncertainty models have been developed. [19][20][21][22][23][24][25][26] Appalanaidu developed a stochastic creep damage growth model where temperature uncertainty is modeled using white noise functions. 20 It was found that choice of noise function significantly influences damage predictions.…”

“…24 Appalanaidu et al developed a stochastic finite element methodology for pipe where material properties are spatially uncertain (i.e., inhomogeneous) using 2-D non-Gaussian random fields. 25 Kim and colleagues employed four different probabilistic methods to add material constants uncertainty into a creep-crack-growth-rate model (least square fitting method, mean value method, probabilistic distribution method, and Monte Carlo method). 26 A comparison between the four methods showed that the Monte Carlo method is expected to achieve a more accurate and economically viable solution due to the inherent conservatism of the technique.…”

“…Several “single‐source” uncertainty models have been developed 19–26 . Appalanaidu developed a stochastic creep damage growth model where temperature uncertainty is modeled using white noise functions 20 .…”

Generalization of spectral stochastic finite element method for analysis of structures with elastoplastic materials

“…Three different size of meshing have been utilized in this example to demonstrate how to get the desired solution and the impact of meshing dimensions. The findings were produced for varying M and p using two forms of meshing 1 and 2 and compared to the values acquired using the Monte Carlo approach (figures [14][15][16][17][18][19][20][21].By viewing the PDF and CDF diagrams (figures 14, 15-17 and 19-21) obtained for the displacements, it can be seen that by increasing the KL and PCE terms, the accuracy of the results is increased to the point that in both meshings with p = 4, M = 4, the mean value and standard deviation of displacement in the nodes with an error percentage of less than 4% correspond to the values obtained from Monte Carlo (figures 17, 21 and 24). For the third meshing, only p = 4, M = 4 were used in modeling the probabilistic parameters, the results of which can be observed in figures 22, 23 and 24.…”

“…Since the SSFEM has good accuracy and efficiency, it is very popular among researchers and has been used in many studies. Some studies have used the aforementioned strategy to investigate the following topics: wave propagation analysis Vibration analysis of fiber-reinforced composites [19], composite plates [11], [20], random creep failure prediction [21], earth dams [22], shells [10], [11], wooden structures [23], elastodynamic issues in the time domain [24], and a variety of other instances have all been investigated. Lacour et al looked into the nonlinear behavior of uncertain materials without taking into account the loading system's uncertainty, and their findings are provided [17].…”