A mesh-based global DIC framework with automatic element deletion tracks cracks in lattice materials by solving correlations on the intact topology and using a residual criterion for damage detection.
Strain 42, 69–80
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
abstract
An increasingly important challenge in network analysis is efficient detection and tracking of communities in dynamic networks for which changes arrive as a stream. There is a need for algorithms that can incrementally update and monitor communities whose evolution generates huge realtime data streams, such as the Internet or on-line social networks. In this paper, we propose LabelRankT, an online distributed algorithm for detection of communities in large-scale dynamic networks through stabilized label propagation. Results of tests on real-world networks demonstrate that LabelRankT has much lower computational costs than other algorithms. It also improves the quality of the detected communities compared to dynamic detection methods and matches the quality achieved by static detection approaches. Unlike most of other algorithms which apply only to binary networks, LabelRankT works on weighted and directed networks, which provides a flexible and promising solution for real-world applications.
citation-role summary
background 1
citation-polarity summary
years
2026 4verdicts
UNVERDICTED 4roles
background 1polarities
background 1representative citing papers
An adaptive database and iterative pattern recognition algorithm lets Material Fingerprinting discover arbitrary linear combinations of polyconvex isotropic and anisotropic hyperelastic features from experimental data.
A Bayesian optimal experimental design framework with Gaussian approximation of expected information gain and surrogate Fisher information enables optimized uniaxial tests that significantly improve identifiability of history-dependent constitutive parameters over random designs.
Experimental inflation tests show that a transversely isotropic Humphrey-Yin hyperelastic model captures the biaxial nonlinear response of porcine diaphragmatic central tendon better than isotropic models like Fung or Yeoh.
citing papers explorer
-
Element-deletion-enhanced digital image correlation for automated crack detection and tracking in lattice materials
A mesh-based global DIC framework with automatic element deletion tracks cracks in lattice materials by solving correlations on the intact topology and using a residual criterion for damage detection.
-
Adaptive Material Fingerprinting for the fast discovery of polyconvex feature combinations in isotropic and anisotropic hyperelasticity
An adaptive database and iterative pattern recognition algorithm lets Material Fingerprinting discover arbitrary linear combinations of polyconvex isotropic and anisotropic hyperelastic features from experimental data.
-
Optimal Experimental Design for Reliable Learning of History-Dependent Constitutive Laws
A Bayesian optimal experimental design framework with Gaussian approximation of expected information gain and surrogate Fisher information enables optimized uniaxial tests that significantly improve identifiability of history-dependent constitutive parameters over random designs.
-
On the Hyperelastic Behavior of the Boar Diaphragmatic Tendon Membrane by Inflation Tests and Modeling
Experimental inflation tests show that a transversely isotropic Humphrey-Yin hyperelastic model captures the biaxial nonlinear response of porcine diaphragmatic central tendon better than isotropic models like Fung or Yeoh.