The Maximum Entropy (ME) method is shown to provide a new approach for quantifying model uncertainty in the presence of complex, heterogeneous data. This is important in model validation of a variety of multifunctional constitutive relations. For example, multifunctional materials contain field-coupled material parameters that should be self-consistent regardless of the measurement. A classical example is piezoelectricity which may be quantified from charge induced by stress or strain induced by an electric field. The proposed tools provide new statistical information to address measurement discrepancies, guide model development, and catalyze materials discovery for data fusion problems. The error between the model outputs and heterogeneous data is quantified and used to formulate a second moment constraint within the entropy functional. This leads to an augmented likelihood function that weights each individual set of data by its respective variance and covariance between each data set. As a first step, the method is evaluated on a piezoelectric ceramic to illustrate how the covariance matrix influences piezoelectric parameter estimation from heterogeneous electric displacement and strain data.
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ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 18–20, 2017
Snowbird, Utah, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5825-7
PROCEEDINGS PAPER
A Maximum Entropy Approach for Uncertainty Quantification and Analysis of Multifunctional Materials
Wei Gao,
Wei Gao
Florida State University, Tallahassee, FL
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William S. Oates,
William S. Oates
Florida State University, Tallahassee, FL
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Ralph C. Smith
Ralph C. Smith
North Carolina State University, Raleigh, NC
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Wei Gao
Florida State University, Tallahassee, FL
William S. Oates
Florida State University, Tallahassee, FL
Ralph C. Smith
North Carolina State University, Raleigh, NC
Paper No:
SMASIS2017-3919, V001T08A013; 8 pages
Published Online:
November 9, 2017
Citation
Gao, W, Oates, WS, & Smith, RC. "A Maximum Entropy Approach for Uncertainty Quantification and Analysis of Multifunctional Materials." Proceedings of the ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Mechanics and Behavior of Active Materials; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies. Snowbird, Utah, USA. September 18–20, 2017. V001T08A013. ASME. https://doi.org/10.1115/SMASIS2017-3919
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