Cracks are the most important source of information about the damage that occurs to unreinforced masonry piers under seismic actions. To predict the structural state of unreinforced masonry piers after an earthquake, research models have been developed to quantify important features of crack patterns. One of the most used crack features is the width, but this can be influenced by several parameters such as the axial load ratio, the shear span ratio, and the loading protocol, which have not been fully studied in previous research studies.

In this study, we use experimental data to investigate the evolution of cracking in stone masonry piers during the application of cyclic shear–compression loading. The data consists of gray-scale images taken during quasi-static shear–compression tests performed on six plastered rubble-stone masonry walls subjected to constant axial force and cycles of increasing drift demand. Through the combined use of digital image correlation and a pre-trained deep learning model, crack pixels are identified, post-processed, and quantified based on their width. The dependency of the crack width on the axial load ratio, the shear span ratio, and the loading protocol at the peak force and ultimate drift limit states of the piers is clarified by a displacement vector field analysis, histogram of the crack width, and the concentration of deformation in the cracks.

We show that, as opposed to flexural cracks, diagonal shear cracks do not fully close when moving from the applied drift demand to the residual drift measured upon removal of the lateral load. Furthermore, we provide the maximum residual crack width at peak force and ultimate drift limit states. This study will improve the decision making abilities of future models used to quantify earthquake-induced damage to stone masonry buildings.

裂缝是有关地震作用下无钢筋砌体桥墩发生损坏的最重要信息来源。为了预测地震后无钢筋砌体桥墩的结构状态，已经开发了一些研究模型来量化裂缝模式的重要特征。最常用的裂纹特征之一是宽度，但这会受到轴向载荷比、剪跨比和载荷协议等几个参数的影响，这些参数在以前的研究中尚未得到充分研究。

在这项研究中，我们使用实验数据来研究在应用循环剪切 - 压缩载荷期间砌石墩中开裂的演变。数据包括在受恒定轴向力和不断增加的漂移需求循环的六个抹灰碎石砌体墙上进行的准静态剪切压缩测试期间拍摄的灰度图像。通过结合使用数字图像相关性和预先训练的深度学习模型，根据宽度对裂纹像素进行识别、后处理和量化。通过位移矢量场分析、裂缝宽度直方图和桥墩峰值力和极限漂移极限状态下的裂缝宽度对轴向荷载比、剪跨比和荷载协议的依赖性。裂纹中的变形集中。

我们表明，与弯曲裂缝相反，当从施加的漂移需求移动到去除横向载荷后测量的残余漂移时，对角剪切裂缝不会完全闭合。此外，我们提供了峰值力和极限漂移极限状态下的最大残余裂纹宽度。这项研究将提高未来模型的决策能力，用于量化石砌建筑的地震引起的损坏。