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This paper describes a methodology in designing high-performance concrete for simply supported beams, using a hybrid optimization strategy based on a variable neighborhood search threshold acceptance algorithm. Three strategies have been applied to discrete optimization of reinforced concrete beams: Variable Neighborhood Descent (VND), Reduced Neighborhood Search (RNS) and Basic Variable Neighborhood Search (BVNS). The problem includes 14 variables: two geometrical one material type one mix design and 10 variables for the reinforcement setups. The algorithms are applied to two objective functions: the economic cost and the embedded CO2 emissions. Firstly, this paper presents the application of these three different optimization strategies, which are evaluated by fitting the set of solutions obtained to a three-parameter Weibull distribution function. The Variable Neighborhood Descent with Threshold Accepting acceptance strategy algorithm (VND-TA) results as the most reliable method. Finally, the study presents a parametric study of the span length from 10 to 20 m in which it can be concluded that economic and ecological beams show a good parabolic correlation with the span length.

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An experimental study on the impact performance of silica fume concrete and steel fiber reinforced concrete at 28 days and 56 days under the action of repeated dynamic loading was carried out. In this experimental investigation, w/cm ratios of 0.4 and 0.3, silica fume replacement at 10% and 15% and crimped steel fibers with an aspect ratio of 80 were used. Results indicated that addition of fibers in high-performance concrete (HPC) can effectively restrain the initiation and propagation of cracks under stress, and enhance the impact strengths, toughness and ductility of HPC. Pulse velocity test was carried out for quality measurements of high-performance steel fiber reinforced concrete. Steel fibers were observed to have significant effect on flexural strength of concrete. The maximum first crack strength and ultimate failure strength at 28 days were 1.51 times and 1.78 times, respectively at 1.5% volume fraction to that of HPC. Based on the experimental data, failure resistance prediction model was developed with correlation coefficient (R) = 0.96 and absolute variation determined is 1.82%.