نوع مقاله : مقاله پژوهشی
نویسندگان
1 دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران
2 دانشکده مهندسی عمران، دانشگاه علم و صنعت ایران، تهران، ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
In this research, the optimal design of space structures considering the actual stiffness of connections is performed using a surrogate model based on a machine learning algorithm. Space structures, as one of the most important types of lightweight and robust structural systems, often have semi-rigid connections whose behavior is conventionally idealized as either rigid or pinned. This unrealistic assumption can lead to an increase in structural weight or construction costs. Therefore, incorporating the actual stiffness of connections into the optimal design process can result in reduced overall structural weight and improved efficiency. Since accurately calculating the total structural weight including the weight and costs associated with connections which account for approximately 15 to 45 percent of the total weight is essential, connection weight has also been included in the objective function. To reduce computational costs, a surrogate model based on a machine learning algorithm is employed. Moreover, to enhance the accuracy and efficiency of the surrogate model, an active learning method is used for the intelligent selection of training data. The results indicate that the proposed method is capable of finding optimal solutions with fewer analyses compared to metaheuristic algorithms. According to the results, 800-member and 1016-member space structures with semi-rigid connections have 4.25% and 14.48% less weight, respectively, compared to structures with pinned and rigid connections.
کلیدواژهها [English]
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