期刊名称：Multidisciplinary Journal for Education, Social and Technological Sciences
印刷版ISSN：2341-2593
出版年度：2019
卷号：6
期号：2
页码：1-10
DOI：10.4995/muse.2019.12374
出版社：Editorial UPV
摘要：Characterizing mechanical properties play a major role in several fields such as biomedical and manufacturing sectors. In this study, a stochastic inverse model is combined with a finite element (FE) approach to infer full-field mechanical properties from scarce experimental data. This is achieved by means of non-linear combinations of material property realizations, with a certain spatial structure, for constraining stochastic simulations to data within a non-multiGaussian framework. This approach can be applied to the design of highly heterogenous materials, the uncertainty assessment of unknown mechanical properties or to provide accurate medical diagnosis of hard and soft tissues. The developed methodology has been successfully applied to a complex case study..
其他摘要：Characterizing mechanical properties play a major role in several fields such as biomedical and manufacturing sectors. In this study, a stochastic inverse model is combined with a finite element (FE) approach to infer full-field mechanical properties from scarce experimental data. This is achieved by means of non-linear combinations of material property realizations, with a certain spatial structure, for constraining stochastic simulations to data within a non-multiGaussian framework. This approach can be applied to the design of highly heterogenous materials, the uncertainty assessment of unknown mechanical properties or to provide accurate medical diagnosis of hard and soft tissues. The developed methodology has been successfully applied to a complex case study.
