Methodology for diagnosing crack patterns in masonry structures using photogrammetry and distinct element modeling

2019 ◽  
Vol 181 ◽  
pp. 519-528 ◽  
Author(s):  
Rebecca Napolitano ◽  
Branko Glisic
Keyword(s):  
Distinct Element ◽  
Masonry Structures ◽  
Crack Patterns ◽  
Element Modeling ◽  
Distinct Element Modeling

Understanding cracks in historic structures: Quantitative assessment though numerical simulation and manifold learning

2019 ◽  
Author(s):  
Rebecca K. Napolitano ◽  
Wesley F. Reinhart ◽  
David W. Sroczynski ◽  
Anna C. Blyth ◽  
Branko Glisic
Keyword(s):  
Manifold Learning ◽  
Failure Modes ◽  
Distinct Element ◽  
Masonry Structures ◽  
Crack Patterns ◽  
Historic Structures ◽  
Small Set ◽  
Distinct Element Modeling ◽  
Perceptual Hash ◽  
Perceptual Hashing

<p>For projects focused on restoration and strengthening of historic structures, information about the origins, magnitude, and stability implications of damage to a structure are required. The objective of this work is to create a novel methodology for understanding the causes of cracks in masonry structures and the resulting effects on global stability. Using Distinct Element Modeling (DEM), the crack patterns of a building can be simulated for a combination of loading scenarios. The results of this method are benchmarked against experimental results and applied to three case studies. The limitations of current physics-based approaches are discussed and a solution using manifold learning is outlined. Manifold learning can be applied to ensembles of crack patterns observed on real or simulated structures to infer damage pathways when the mechanism is unknown. This technique uses a perceptual hashing of the crack patterns to produce an affinity matrix, which is then analyzed by spectral methods to learn a small set of parameters which can describe the ensemble. Because the affinity is derived from a sparse perceptual hash, these descriptors can then be used to interrogate the manifold via a "lifting" operation which reveals the dominant failure modes in the sample.</p>

Sign in / Sign up

Export Citation Format

Share Document