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Parameter estimation in a thermoelastic composite problem via adjoint formulation and model reduction
Author(s) -
GarciaCardona Cristina,
Lebensohn Ricardo,
Anghel Marian
Publication year - 2017
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.5530
Subject(s) - thermoelastic damping , monte carlo method , reduction (mathematics) , markov chain monte carlo , sensitivity (control systems) , computer science , characterization (materials science) , mathematical optimization , sampling (signal processing) , residual , algorithm , mathematics , thermal , materials science , engineering , physics , geometry , statistics , filter (signal processing) , electronic engineering , meteorology , nanotechnology , computer vision
Summary Advances in nondestructive material characterization are providing a wealth of information that could be exploited to gain insight into general aspects of material performance and, in particular, discover relationships between microstructure and thermo‐mechanical properties in polycrystalline and other complex composite materials. In order to facilitate the integration of such measurements into existing models, as well as inform new physics‐based predictions, we developed a C++/MPI computational framework for sensitivity analysis and parameter estimation. The framework utilizes a micro‐mechanical modeling based on fast Fourier transforms, direct and adjoint formulations, and Markov chain Monte Carlo sampling techniques. We illustrate the characteristics of this framework and demonstrate its utility by computing the residual stresses arising from thermal expansion of an elastic composite and using data from simulated experiments. We show that the availability of nondestructive 3‐D measurements is crucial to reduce the uncertainty in predictions, emphasizing the importance of an integrated experimental/modeling/data analysis approach for improved material characterization and design. Copyright © 2017 John Wiley & Sons, Ltd.