Multiscale identification of apparent elastic properties at meso-scale for materials with complex microstructure using experimental imaging measurements (original) (raw)

This research addresses the complexities involved in modeling heterogeneous materials at the mesoscale, where traditional approaches may fall short due to the materials' intricate microstructures. By employing a probabilistic approach that utilizes displacement field measurements, the study enhances a prior methodology to effectively identify the tensor-valued random fields representing apparent elastic properties at this scale. The improvement involves introducing a new meso-scale indicator that enables a more efficient fixed-point iterative algorithm, significantly reducing computational costs while maintaining accuracy in the identification process.