Search

The goal of this study was to investigate a novel approach of predicting the ultimate capacity of axially loaded circular concrete-filled steel tube (CCFST) columns. A hybrid intelligent system, namely GAP-BART, was developed based on the Bayesian additive regression tree (BART) combining with three nature-inspired optimization algorithms such as Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Particle Swarm Optimization (PSO), and then applied. Three sub-hybrid models of the system were built, abbreviated as G-BART, A-BART, and P-BART, respectively, using 504 experimental data collected from published research. The compiled database covered five input variables, including the diameter of the circular cross-section—section (D), the wall thickness of the steel tube (t), the length of the column (L), the compressive strength of the concrete (fc′), and the yield strength of the steel tube (fy). The coefficient of determination (R2) values of (0.9971, 0.9982, and 0.9986) and (0.9891, 0.9923 and 0.9931) were achieved for training and testing of G-BART, A-BART, and P-BART models, respectively. The P-BART model performed the lowest RMSE and MAE values for the training and testing set of (66.85 kN and 49.60 kN) and (141.24 kN and 102.04 kN), respectively. These results indicated that although the proposed models were able to estimate ultimate axial capacity with high accuracy, the P-BART model had the best performance among them. For benchmarking, the obtained results were validated against several mathematical approaches as well as other AI techniques (MARS, ANN). The findings of the comparative analysis clearly showed superior ability to predict the CFST ultimate axial capacity relative to the benchmark models. The relative importance of each predictor was investigated to find the most significant input variables. The results confirmed that the hybrid GAP-BART system can serve as a reliable and accurate tool for the design of CCFST columns and to predict their performance.

The 3D printing technique for sand mold exhibited the good response of precast concrete structure manufacturing process. The designed sandwich core structure, including solid core, diamond core, honeycomb core, pyramid core and round O core were constructed by silica sand with different thickness and different relative density ratios from 0.5 to 0.9 and investigated by mechanical experiment, finite element modeling and digital image correlation. The solid block showed the greatest compressive strength 6.15 MPa and flexural strength 3.85 MPa. The sand core with density ratios of 0.9 performed a significant response with greater 10-50% in strength, compared with specimens with ratios 0.5 and 0.7. The sandwich composites with honeycomb and pyramid core showed a sequence of stability and enhancement with 2-3 times in difference. The experimental, numerical and digital results indicate that the core structure can be optimized to control and apply to 3D printing sand mold and precast concrete structure with a good agreement with under 15% in comparison and verification. These findings offered a good insight into the study of mechanical behavior of sandwich structure in the application and industry.

Abstract: In this paper, Buckling-Restrained Knee Bracing (BRKB) system was developed through sub-assemblage tests. The core plate of the BRKB was restrained with two channel sections. Tests of the five BRKBs were carried out under cyclic loading as specified in the AISC (2005) Seismic Provisions. It was observed that the ductility and energy dissipation capacity of the BRKBs were mainly affected by the variables: size of core plate, size of channel sections, and size of end plate. Four out of five specimens satisfied the compression-strength adjustment factor and cumulative plastic ductility specified in the provisions. The BRKB, which showed the best performance among the test specimens, was applied to a piloti type reinforced concrete building. Static pushover and non-linear time history analyses were performed to confirm the retrofit effect. The analysis results showed that the installation of the BRKBs improved the seismic behavior of the building significantly in terms of strength and story drift.