Hybrid physics-based modeling and data-driven method for diagnostics of masonry structures

Before implementing monitoring systems or reinforcements on a historic structure, it is essential to understand how crack patterns may have originated and how they affect the stability of the structure. Previous methods combining photogrammetry with physics-based modeling have been successful in diagnosing the cause of crack formation. However, a limitation of existing methods is the manual comparison process to ascertain damage origins. This research outlines a method combining physics-based modeling and data-driven approaches to automate diagnostics for existing masonry structures. This method was shown to quantitatively reproduce the cause of damage for complex, 3D structures and was validated against a laboratory-scale experimental masonry wall. The newly automated procedure increases throughput by 10⁵ times compared to our prior method, allowing for the testing of orders of magnitude more hypotheses than were previously possible. Although the approach is demonstrated here for settlement-induced cracking, it has important implications for the broader topic of data-driven masonry diagnostics.