Cost optimization of reinforced concrete building frames using genetic algorithms is presented. Unlike previous works that used simplified discrete or continuous optimization models, this work considers constructability issues as well as the effects of shear and torsional actions in the design optimization of reinforced concrete frames. An integrated software system has been developed to implement the proposed optimization procedure using genetic algorithms. Examples have been incorporated in order to compare the results from the proposed study with that of a previous work which follows a different heuristic and with the traditional “design–check–revise” method. The structural design procedures recommended in the Eurocode-2 have been strictly followed in this work. Special emphasis has been given to structural analysis methods and studying computational efficiency of the developed framework. To improve the performance and computational complexity of the algorithm, the effect of genetic parameters such as mutation and crossover on the optimization process has been thoroughly studied. The method developed in this work proves to have a lot of advantages over the traditional “design–check–revise” paradigm and other heuristic methods.

Tuned liquid dampers (TLDs) are introduced in structural systems to suppress vibration of the structure due to dynamic actions. Using a grid-based Finite Volume Method-Finite Element Method (FVM/FEM), efficiency of TLDs of cylindrical and rectangular geometries was evaluated by performing a two-way Fluid-Structure Interaction (FSI) analysis. The nonlinear sloshing response of fluid was simulated by employing a three-dimensional Navier–Stokes equation as the governing equation and occurrence of wave breaking was accounted by using Volume of Fluid (VOF) method for free surface tracking. Utilizing the developed numerical model, a series of three-dimensional transient analysis were conducted on a structure with and without TLDs aiming to investigate effect of base excitation amplitude. The result show that maximum performance of TLDs at resonance is obtained when the forcing ratio is limited to 0.1, and for this case, both cylindrical and rectangular TLDs displayed comparable efficiency. Effect of excitation frequency fe was also investigated under a wide range of the forcing ratio showing that as fe increases, the natural frequency of coupled TLD-structural system approaches the natural frequency of un-damped structural system.

Simplicity and optimality are commonly associated with the particle swarm optimization (PSO) algorithm. As a result, numerous variants and hybrids of PSO have been developed and implemented to address structural optimization problems. The undeniable importance of the initialization technique in determining the overall performance of a given optimization algorithm cannot be overstated. Optimization algorithms, such as PSO, typically rely on a random, uniformly distributed initialization. Through multiple iterations and updates, these algorithms aim to achieve optimal results. The underlying assumption behind such an initialization approach is that a fair or reasonable arrangement of particles is best accomplished through randomization, and thus the entire optimization process is iterated based on this assumption. However, this initialization technique raises concerns regarding the attainment of optimality and convergence, leaving room for further examination. In this paper, we challenge this assumption by introducing a priority concept. The key idea is that particles should not be initialized randomly since randomness alone does not guarantee a reasonable allocation of design variable values in iterative optimization. This can lead to misguided velocity updates and ultimately, a time-consuming pursuit of optimality. To address this issue, we formulate priority criteria (PC) and propose an enhanced PSO variant called Priority Criteria PSO (PCPSO). The PC can be incorporated into any PSO variant or hybrid without impacting the parameter settings, constraints, and penalty approaches of the respective algorithms. A case study involving 2D reinforced concrete frames was conducted to compare the performance of the ordinary PSO algorithm with the PCPSO. The results clearly demonstrate that the introduction of the PC leads to a significant cost reduction when compared to PSO with an inertia damping factor. Additionally, the PCPSO algorithm exhibits accelerated convergence. Furthermore, to alleviate the computational burden associated with structural analysis at each iteration, a reanalysis approach called Combined Approximations (CA) is mathematically formulated and implemented.

The paper presents the progressive collapse analysis of structures, focusing on the impact of the initial conditions (particularly initial velocity) and the damage. It proposes a method that calculates the residual axial load capacity and damage of columns based on their strain profile and considers the effects of multiple blast locations. The methodology involves the conventional design of a three-story moment-resisting frame, selecting blast parameters, calculating blast pressures, and performing structural and progressive collapse analyses. The findings reveal that the Alternate Load Path Method (APM) overestimates the capacity compared to a benchmark blast–structure interaction analysis, especially when unsuitable initial conditions and damage properties are used. To address this limitation, the paper concludes the recommendations for incorporating appropriate initial conditions and damage considerations for a relatively accurate progressive collapse analysis.