Abstract This study examines whether wall material, hollow concrete block or solid clay brick, was associated with collapse-related failure in 516 nonengineered legacy rural masonry buildings in Antakya, Hatay, after the 2023 Kahramanmaraş earthquake sequence. Damage states were grouped into binary Failure and Nonfailure classes within a spatially constrained observational comparison. Because nonfailure outcomes were sparse, Firth penalized logistic regression was applied to reduce small-sample bias. The overall failure rate was 89.9% (95% confidence interval (CI) = 87.0%–92.2%). Solid brick buildings showed a higher observed failure rate (96.4%) than hollow block buildings (89.2%), but the association was not statistically significant [odds ratio (OR) = 2.56; 95% profile-penalized-likelihood interval = 0.83–12.66; p = 0.109 ]; building height was likewise nonsignificant (OR = 1.16; p = 0.746 ). Adjustment for construction period and neighborhood gave a similar material estimate (OR = 2.47; p = 0.134 ), whereas neighborhood showed the strongest recorded association with failure ( p < 0.001 ), with failure rates of 78.9% to 96.0% across three adjacent neighborhoods. A design-based simulation indicated limited detection probability; the data therefore neither demonstrates nor excludes a material effect. System-level features were not recorded as building-level variables. Wall material alone is insufficient as a standalone screening criterion.
Historical masonry buildings located in seismic regions are highly vulnerable to earthquake-induced damage due to material degradation, geometric irregularities, and limited tensile capacity. This study investigates the structural and seismic performance of a protected historical mansion located in & Idot;zmir, T & uuml;rkiye. The methodology integrates architectural surveying, on-site damage assessment, laboratory testing of masonry materials, and geotechnical characterization based on borehole drilling and multichannel analysis of surface waves (MASW) measurements. A three-dimensional finite element model was developed using the macromodeling approach, and static and spectral analyses were conducted in accordance with the Turkish Building Earthquake Code (TBDY). The results indicate that whereas the structure remains within acceptable limits under gravity loads, seismic loading leads to excessive shear stresses (up to 0.51 MPa) and shear strains exceeding code-based thresholds, particularly in load-bearing masonry walls and slender entrance columns. These findings reveal a significant seismic vulnerability primarily associated with low masonry strength and structural irregularities. The study provides quantitative evidence to support the need for targeted strengthening interventions and contributes a data-driven framework for the seismic assessment and conservation of complex historical masonry buildings.
This article presents a reduced-order computational modeling approach to quantify the potential for disproportionate collapse in the design of precast concrete framed buildings under column removal scenarios using only the framing geometry and configuration, connection detailing, code provisions, and material specifications. This approach includes the development and validation of mechanics-based moment-rotation curves for novel threaded rod and bolted precast concrete beam-to-column moment connections, which were designed for enhanced robustness under a middle column removal scenario. These moment-rotation curves were then assigned to the beam ends of a 10-story exterior precast concrete moment frame. Nonlinear dynamic analyses were performed to quantify the robustness of each connection under three individual column removal scenarios: middle column, penultimate column, and corner column. Results from an approximate energy-based procedure formulated based on a single nonlinear static analysis are also presented and compared to the nonlinear dynamic analysis results. The results show that, for both connection types, the precast concrete frame was able to arrest collapse for middle and penultimate column removal scenarios with a quantified degree of reserve capacity. The corner column removal scenario, for which the connections were not designed, resulted in collapse, but only by a small margin. A comparison between the results of the nonlinear dynamic analyses and the approximate energy-based procedure yielded close agreement for both connection types; percent differences in their determined ultimate capacity were less than 1% for the middle and penultimate column removal scenarios and less than 4% for the corner column removal scenario.
Passive fire safety has traditionally been addressed in terms of compartmentalization and the fire resistance of individual structural elements. However, facility-scale fire performance depends not only on material resistance but also on the continuity and interaction of structural segments. Expansion joints, often used to accommodate thermal and differential movement, are not fire-resisting elements by themselves; fire performance at these interfaces is provided by fire-rated joint systems and adjacent fire-resistant assemblies. When integrated with such systems, they can function as system-level segmentation interfaces regulating the spatial spread of fire-induced damage. This study investigates the performance-based role of expansion joints, as part of integrated structural segmentation systems, when used in conjunction with appropriate fire-resistant vertical assemblies (e.g., shear walls, partition walls), in limiting fire spread, controlling the distribution of structural damage, and improving postfire serviceability. A qualitative comparative analysis of documented fire cases was conducted to examine how structural compartmentalization affects fire behavior and salvage feasibility. To support the structured comparison, a simplified semiquantitative performance index framework was developed, incorporating indicators of damage localization potential, structural damage severity, and postfire serviceability. The framework employs an interpretive mapping approach of qualitative observations into normalized index values. The findings indicate that expansion joints contribute to fire performance primarily through enabling structural segmentation and, when properly protected, maintaining interface integrity, rather than directly enhancing fire resistance at the material level. Partitioned configurations demonstrate improved capacity for selective repair, phased reconstruction, and functional continuity following fire incidents. The proposed framework repositions expansion joints within the broader context of segmentation-based fire performance, highlighting that fire performance is governed by the combined action of structural partitioning and fire-rated interface systems rather than expansion joints in isolation, thereby enhancing plant integrity and postincident operability.
Accurate measurement of bridge cracks is essential for assessing structural safety and durability. In recent years, binocular vision technology has been widely used in the size measurement of concrete cracks due to its noncontact and highly efficient advantages. However, current crack size measurement has shortcomings in dense point cloud modeling and long crack splicing, resulting in inaccurate measurement. Hence, this paper proposed an intelligent measurement of concrete crack length and width using three-dimensional (3D) reconstruction of binocular vision. For length measurement, a cumulative summation method of 3D interpoint distances in the crack centerline is proposed, as well as considering the splicing of a long crack that cannot be completely captured in a single image; for width measurement, a method of calculating the shortest distance from the crack centerline to crack boundary lines in the 3D point cloud is proposed. During the cost-matching phase in the 3D reconstruction of concrete cracks, the census algorithm is selected as the optimal cost calculation method. During the splicing period of a long crack for iterative closest point (ICP) splicing, the SURF algorithm is selected as the optimal feature matching algorithm, and the relative-distance-square-normalization weight is selected as the optimal calculation function for ICP weight parameters. In the field test, the relative error of the whole crack length is 4.2%, the average error between the calculated and measured crack widths is 0.15 mm, and the relative average error is 4.28%, which verifies high accuracy of the intelligent measurement of concrete crack length and width using 3D reconstruction of binocular vision, providing robust support for subsequent bridge management and maintenance.
