Interfaz Gráfica de Usuario para la optimización de estructuras aporticadas de H.A
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Medina Salabarría, Yosniel
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Universidad Central “Marta Abreu” de Las Villas. Facultad de Construcciones. Departamento de Ingeniería Civil.
Resumen
En la siguiente investigación se presenta la elaboración de una Interfaz Gráfica de Usuario (GUI) para la optimización de estructuras aporticadas de hormigón armado, para facilitar la interacción del usuario con el algoritmo de optimización.
Una vez elaborada la GUI se elaboraron cuatro modelos para su optimización, en los cuales se incluyen aspectos usualmente ignorados en la modelación como la reducción de inercia por fisuración y el análisis de segundo orden mediante el efecto P-Delta.
Por otra parte, se utilizó el criterio de optimización del costo mínimo de la estructura por lo que se definió la función costo como función objetivo, identificándose hasta 12 variables discretas por modelo y restricciones asociadas fundamentalmente al intervalo de movimiento de las variables.
Un aspecto novedoso fue la inclusión de la resistencia a compresión del hormigón (f´c) como variable en el proceso de optimización, estableciendo dos grupos: para vigas y para columnas, llegando a la conclusión que para vigas la mejor opción es utilizar hormigones de baja resistencia (20, 25 MPa) mientras que para columnas ocurre lo contrario (30, 35 MPa). Otro aspecto evaluado fue la relación L/h óptima en vigas, donde se obtuvieron relaciones ligeramente más grandes en comparación con investigaciones previas, inducido fundamentalmente por el uso de acero G-60, a diferencia de los trabajos previos.
Debido a la complejización del proceso de optimización (función objetivo más compleja, variables discretas y mayor número de estas, etc.) se utilizaron tres métodos metaheurísticos de optimización: Algoritmos Genéticos (GA), Optimización por Enjambre de Partículas (PSO) y Recocido Simulado (SA), con
el objetivo de comparar su funcionamiento en este tipo de optimización, obteniéndose mejores resultados utilizando PSO.
The following research presents the development of a Graphical User Interface (GUI) for the optimization of reinforced concrete structures, to facilitate user interaction with the optimization algorithm. Once the GUI was elaborated, four models were developed for its optimization, in which aspects usually ignored in the modeling are included, such as the reduction of inertia due to cracking and second order analysis through the P-Delta effect. On the other hand, the criterion for optimizing the minimum cost of the structure was used, so the cost function was defined as an objective function, identifying up to 12 discrete variables per model and restrictions associated mainly with the range of movement of the variables. A novel aspect was the inclusion of the compressive strength of the concrete (f'c) as a variable in the optimization process, establishing two groups: for beams and for columns, reaching the conclusion that for beams the best option is to use concrete from low resistance (20, 25 MPa) while for columns the opposite occurs (30, 35 MPa). Another aspect evaluated was the optimum L / h ratio in beams, where slightly larger ratios were obtained compared to previous investigations, mainly induced by the use of steel G-60, unlike previous works. Due to the complexity of the optimization process (more complex objective function, discrete variables and greater number of these, etc.) three metaheuristic optimization methods were used: Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA), with the aim of comparing its operation in this type of optimization, obtaining better results using PSO.
The following research presents the development of a Graphical User Interface (GUI) for the optimization of reinforced concrete structures, to facilitate user interaction with the optimization algorithm. Once the GUI was elaborated, four models were developed for its optimization, in which aspects usually ignored in the modeling are included, such as the reduction of inertia due to cracking and second order analysis through the P-Delta effect. On the other hand, the criterion for optimizing the minimum cost of the structure was used, so the cost function was defined as an objective function, identifying up to 12 discrete variables per model and restrictions associated mainly with the range of movement of the variables. A novel aspect was the inclusion of the compressive strength of the concrete (f'c) as a variable in the optimization process, establishing two groups: for beams and for columns, reaching the conclusion that for beams the best option is to use concrete from low resistance (20, 25 MPa) while for columns the opposite occurs (30, 35 MPa). Another aspect evaluated was the optimum L / h ratio in beams, where slightly larger ratios were obtained compared to previous investigations, mainly induced by the use of steel G-60, unlike previous works. Due to the complexity of the optimization process (more complex objective function, discrete variables and greater number of these, etc.) three metaheuristic optimization methods were used: Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA), with the aim of comparing its operation in this type of optimization, obtaining better results using PSO.