Recent work has shown that deep convolutional neural network is capable of solving
inverse problems in computational imaging, and recovering the stress field of the loaded …

Stress field evaluation, through fringe order maps, has always been of great importance in
various engineering domains, providing essential insights into the mechanical response of …

Quantifying the stress field induced into a piece when it is loaded is important for
engineering areas since it allows the possibility to characterize mechanical behaviors and …

Featured Application This research has pivotal applications in geotechnical and civil
engineering fields, particularly in improving the reliability and precision of stress and strain …

This study introduces FringeNet, an innovative deep learning-based cyclic model to
enhance the fringe order demodulation from single isochromatic images. A Continuity …

Metal powder bed fusion additive manufacturing (AM) processes have gained widespread
adoption for the ability to produce complex geometries with high performance. However, a …

Establishing fast and accurate structure-to-property relationships is an important component
in the design and discovery of advanced materials. Physics-based simulation models like …

Digital photoelasticity is a non-contact inspection technique, that requires new strategies to
unwrap the stresses map based on color images. Therefore, this paper presents a new three …