Pressure probes are typically used to measure the pressure of a fluid stream. These probes are designed to serve for 25 years life under operating pressure and temperature conditions. Therefore, such pressure probes are also designed for safe creep behavior. Typically creep is time dependent phenomenon and it can be classified as Primary, Secondary and Tertiary creep. In the literature, the creep phenomenon is studied analytically and numerically. Literature review reveals that creep analysis requires special material models and its selection depends on operating conditions. This work presents FEA based probabilistic design and analysis of pressure measuring probes using ANSYS which has several creep models depending on type of creep phenomenon. Probes in this study are subjected to primary and secondary creep. Therefore, this work proposes combined time hardening creep model. Combined time hardening model has 7 coefficients. This further increases the complexity of the model. Apart from the model complexity, there are various other design and operating parameters which further complicates the creep behavior. Some of the important design and operating parameters are length, diameter and tip dimensions along with pressure and temperature. Thus there are around 16 parameters which controls the creep behavior of pressure measuring probe. Traditional design process of probe is based on deterministic analysis which involves the use of safety factors as a way of accounting for uncertainty in design input parameters. This can often results in overly conservative designs. Moreover, to understand optimal creep behavior of probes under several uncertainties in input parameters becomes a challenging. Therefore, this work presents probabilistic approach as opposed to a deterministic approach to understand the combined effect of several uncertain parameters on creep behavior of probes. This work not only determines probability of probe failure more accurately but also determines the sensitivity of each parameter during creep phenomenon using FEA.

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