Abstract
The present work sets up a methodology that allows the estimation of the spatial distribution of the second-order error of the response, as a function of the number of terms used in the truncated Karhunen-Loève (KL) series representation of the random field involved in the problem. For this purpose, the concept of the variability response function (VRF) is adopted, as it is well recognized that VRF depends only on deterministic parameters of the problem as well as on the standard deviation of the random parameter. The criterion for selecting the number of KL terms at different parts of the structure is the uniformity of the spatial distribution of the second-order error. This way a significantly reduced number of polynomial chaos (PC) coefficients, with respect to classical PC expansion, is required in order to reach a target second-order error.
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Acknowledgements
This work has been supported by the European Research Council Advanced Grant MASTER – Mastering the computational challenges in numerical modeling and optimum design of CNT reinforced composites (ERC-2011-ADG-20110209).
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Giovanis, D.G., Papadopoulos, V. (2014). A Variability Response-Based Adaptive SSFEM. In: Papadrakakis, M., Stefanou, G. (eds) Multiscale Modeling and Uncertainty Quantification of Materials and Structures. Springer, Cham. https://doi.org/10.1007/978-3-319-06331-7_13
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DOI: https://doi.org/10.1007/978-3-319-06331-7_13
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