Masonry infill walls, although commonly treated as non-structural elements in reinforced concrete (RC) buildings, have a significant influence on the lateral response of RC frames. This study investigates the effects of masonry infills, opening configurations, and wall-post systems on the nonlinear lateral behavior of RC moment-resisting frames under quasi-static loading using advanced numerical modeling. Three-dimensional finite element models were developed in ABAQUS and validated against reliable experimental results. The numerical program includes bare frames, fully infilled frames, infilled frames with various opening sizes, and wall-post-strengthened configurations, all subjected to displacement-controlled quasi-static lateral loading up to large deformation levels. The results indicate that masonry infills considerably increase the initial stiffness and lateral strength of RC frames, while simultaneously increasing the potential for brittle behavior and stress concentration in the columns. The presence of openings reduces stiffness and disrupts the load transfer mechanism, leading to localized damage concentration around opening corners. In contrast, wall-post systems effectively mitigate these adverse effects by redistributing stresses, improving damage uniformity, and enhancing post-peak stability. The combined use of wall-posts and infilled walls with openings provides a more controlled lateral response in terms of strength, stiffness, and ductility, highlighting wall-posts as an efficient solution for improving the structural performance of infilled RCframes under lateral loading conditions.
Vision-language models (VLMs) have shown strong performance on multimodal reasoning tasks, yet their ability to perform quantitative analysis of technical drawings remains largely unexplored. This study evaluates the instruction-guided zero-shot performance of three open-source VLMs, on the task of estimating room areas from color-coded residential floor plan images. Of the three models tested, two produced quantitatively evaluable structure outputs. A dataset of 100 floor plans, comprising 472 plan-level room-type evaluation comparisons derived from 894 ground-truth room instances, was used to compare predicted and ground truth areas. Results show moderate predictive correlation (R2 approximate to 0.71), but substantial estimation errors (MAPE approximate to 43%), with noticeably larger errors for smaller rooms. A classical pixel counting baseline, using color segmentation, achieved MAPE = 5.68% at the room-instance level, and MAPE = 1.58% when evaluated at the floor plan level, highlighting the limitations of the tested VLMs for precise geometric estimation under this controlled setup. These findings suggest that while the evaluated open-source VLMs can approximate spatial proportions in simplified color-coded layouts, their quantitative accuracy remains significantly below that of deterministic image analysis methods.
Strategic investment in shared mobility infrastructure necessitates balancing multiple conflicting criteria. This study develops and applies an integrated Best-Worst Method (BWM) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) framework to prioritize urban zones for shared mobility hub investment in Budapest, Hungary. Vector normalization was adopted in the TOPSIS stage for its scale-invariance properties, ensuring robust cross-criteria comparability. The methodology incorporates 17 sub-criteria across five main dimensions: Transport Connectivity, Demand Density, Infrastructure Readiness, Environmental Impact, and Social Equity. Expert judgments were synthesized using BWM and applied to evaluate four distinct urban typologies: the Historic Central Business District (Zone A), Mixed-Use Residential Corridor (Zone B), Major Transport Hub & University Area (Zone C), and Residential Suburb (Zone D). Results identify Zone B (& Uacute;jlip & oacute;tv & aacute;ros-Angyalf & ouml;ld) as the top priority, offering the best balance between high demand and implementation feasibility. Zone A (Belv & aacute;ros-Lip & oacute;tv & aacute;ros), the historic CBD, ranks second, as its superior connectivity is offset by severe spatial constraints. Zone C(Kelenf & ouml;ld-Albertfalva), a major transport hub, places third, while Zone D (P & eacute;terhegy-K & odblac;b & aacute;nya), a residential suburb, ranks fourth due to lower current connectivity despite strong environmental and social equity scores. The analysis reveals a core planning trade-off: zones with the highest immediate demand face the greatest physical implementation challenges. The proposed framework provides municipal planners with a transparent, quantitative tool for optimizing phased infrastructure investment, with future work recommended to incorporate real-time and time-dependent mobility data for dynamic scenario analysis.
Polycarboxylate ether (PCE) superplasticizers are widely used in cementitious systems. They are also used to disperse solid particles in aqueous suspensions, including cement particles and nano-additives such as graphene oxide (GO). Their performance depends on both polymer formulation and dosage. This study compared four commercial PCEs in a NaOH-adjusted alkaline model medium. The electrokinetic and hydrodynamic behavior of GO suspensions was evaluated over GO:PCE mass ratios from 1:0 to 1:6. Zeta potential (ZP) and dynamic light scattering (DLS) were used as comparative descriptors. The control GO suspension showed a mean ZP of -58 mV, a Z-average hydrodynamic size of 531 nm, and a polydispersity index (PDI) of 0.37. After PCE addition, the PDI decreased to 0.26-0.30, indicating lower DLS-derived apparent heterogeneity relative to the control suspension. The response depended on PCE formulation. ACE 300 and MC-PowerFlow 2695 gave the most negative ZP values, reaching -76 mV and -65 mV, respectively, at a GO:PCE ratio of 1:5. At 1:6, the magnitude decreased relative to the peak values. By contrast, the ViscoCrete series showed a more moderate ZP response, from -53 to -58 mV, while the smallest apparent sizes were obtained with the ViscoCrete series, reaching 477 nm. These results show that GO dispersion in this alkaline model medium cannot be inferred from a single descriptor or from applying a single dosage rule across different PCE formulations. Joint interpretation of electrokinetic and hydrodynamic measurements is therefore needed for comparative screening.
The Leeb hardness (HL) method, which is one of the surface hardness measurement techniques used for materials, has recently gained widespread application in rock mechanics and engineering geology studies. However, limited research has been conducted on the factors influencing HL values. This study aims to investigate the effect of phenocryst-sized minerals on HL values in granitic rocks originating from T & uuml;rkiye. Within this scope, HL values were determined on 72 surfaces belonging to two different rock types (Kaman Rose and Dusty Rose). Subsequently, high-resolution images obtained from each sample surface were evaluated using image analysis techniques, and the orthoclase mineral percentage (OMP) on the surfaces was quantitatively determined. The relationships between HL and OMP values obtained from the cube sample surfaces of both rock groups were investigated through simple regression analysis, and strong positive linear correlations were identified. The OMP value on the sample surface was determined to be a decisive parameter directly influencing the HL values of the rocks. Textural heterogeneities caused by phenocrysts influenced the HL test results, thereby limiting the applicability of the method to such rock types.
