An Adaptive Creep Modeing Approach Using Metamodeling
Abstract
Recent drives to increase the efficiency of existing fossil energy power plants and the development of Advanced Ultrasupercritical power plants, have led to designs with steam pressures above 4000 psi and temperatures exceeding 1400°F. The complexity of the applied thermo-mechano chemical boundary conditions makes it critically important to consider creep and creep related failures. A primary concern to FE practitioners is the determination of which constitutive models are the “best”, capable of reproducing the mechanisms expected in an intended design accurately; as well as what experimental data sets are proper or “best” to use for fitting the constitutive parameters needed for the model(s) of interest. In this dissertation the work completed towards these questions are presented. Various forms of creep data are collected and statistical analysis are performed. It is observed that data pre-processing and inclusion of disparate datasets into the calibration process can significantly improve the prediction accuracy. Realistic extrapolation and interpolation is possible for wide range of service condition leading to the development of Creep Design Maps. Towards the development of an approach for determining the “best” model; it is hypothesized that, “a general model (metamodel) derived by combining and exploiting creep models where the submodels (existing and new models that are exploited to develop the metamodel) are special case can facilitate instantaneous and efficient evaluation of the submodels leading to the selection of “best” model”. Successful metamodeling examples for stress-rupture, creep deformation, and CDM based models are provided. A guideline for metamodeling and multiaxiality function by combing the international standards (e. g. ASME PVP III, ASTM, ECCC, RCC-MR, R5) is presented.
Subject Area
Mechanical engineering
Recommended Citation
Haque, Mohammad Shafinul, "An Adaptive Creep Modeing Approach Using Metamodeling" (2018). ETD Collection for University of Texas, El Paso. AAI10792340.
https://scholarworks.utep.edu/dissertations/AAI10792340