• فهرست مقالات Truss Structure

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        1 - Sizing optimization of truss structures with discrete design variables using combined PSO algorithm with Special Particles Method
        Ali Gheibi Reza SojoudiZadeh Hadi Azizian Mahdi Gheibi
        This paper proposes a modified particle swarm optimization (MPSO) algorithm for discrete sizing optimization of truss structures. The original particle swarm optimization (PSO) is a population-based metaheuristic that fluctuates the search agents about the best solution چکیده کامل
        This paper proposes a modified particle swarm optimization (MPSO) algorithm for discrete sizing optimization of truss structures. The original particle swarm optimization (PSO) is a population-based metaheuristic that fluctuates the search agents about the best solution based on Eberhart functions. The efficiency of the PSO in solving standard optimization problems of well-known problems of truss structures has been demonstrated in literature. However, its performance in tackling the discrete optimization problems of truss structures is not competitive compared with the recent existing metaheuristic algorithms. In the framework of the proposed MPSO a number of worst solutions of the current population is replaced by some variants of the global best solution found so far. Moreover, an efficient mutation operator is added to the algorithm that reduces the probability of getting stuck in local optima. The efficiency of the proposed MPSO is illustrated through two benchmark optimization problems of truss structures. پرونده مقاله
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        2 - A Discrete Hybrid Teaching-Learning-Based Optimization algorithm for optimization of space trusses
        Siamak Talatahari Vahid Goodarzimehr
        In this study, to enhance the optimization process, especially in the structural engineering field two well-known algorithms are merged together in order to achieve an improved hybrid algorithm. These two algorithms are Teaching-Learning Based Optimization (TLBO) and Ha چکیده کامل
        In this study, to enhance the optimization process, especially in the structural engineering field two well-known algorithms are merged together in order to achieve an improved hybrid algorithm. These two algorithms are Teaching-Learning Based Optimization (TLBO) and Harmony Search (HS) which have been used by most researchers in varied fields of science. The hybridized algorithm is called A Discrete Hybrid Teaching-Learning Based Optimization (DHTLBO) that is applied to optimization of truss structures with discrete variables. This new method is consisted of two parts: in the first part the TLBO algorithm applied as conventional TLBO for local optimization, in the second stage the HS algorithm is applied to global optimization and exploring all the unknown places in the search space. The new hybrid algorithm is employed to minimize the total weight of structures. Therefore, the objective function consists of member’s weight, which is depends on the form of stress and deflection limits. To demonstrate the efficiency and robustness of this new algorithm several truss structures which are optimized by most researchers are presented and then their results are compared to other meta-heuristic algorithm and TLBO and HS standard algorithms. پرونده مقاله
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        3 - بهینه سازی سازه های خرپایی به روش توده ذرات با در نظر گرفتن قیود دینامیکی
        سیامک طلعت حامد ابراهیم زاده
        امروزه سازه های خرپایی باتوجه به کاربردهای گوناگون آنها بیش از پیش اهمیت پیدا کرده اند. علت استفاده فراوان از این نوع خاص سازه ها مزایای آنها شامل مشارکت اغلب اعضای سازه درتقسیم وتوزیع بار، ویژگی مقاوم بودن آنها (به طوری که فرو ریختن تعداد محدودی از اعضا لزوماً منجر به چکیده کامل
        امروزه سازه های خرپایی باتوجه به کاربردهای گوناگون آنها بیش از پیش اهمیت پیدا کرده اند. علت استفاده فراوان از این نوع خاص سازه ها مزایای آنها شامل مشارکت اغلب اعضای سازه درتقسیم وتوزیع بار، ویژگی مقاوم بودن آنها (به طوری که فرو ریختن تعداد محدودی از اعضا لزوماً منجر به فروپاشی سازه نمی شود)، پوشاندن دهانه های بزرگ با حداقل مواد مصرفی، راحتی اجرا وغیره می- باشد. از این رو بهینه سازی سازه های خرپایی در پایین آوردن هزینه ها می تواند نقش قابل ملاحظه ای را ایفا کند. این الگوریتم دارای یک سری مزایا می باشد که در مقایسه با سایر الگوریتم ها آن را شاخص تر میکند از جمله این مزایا می توان به اختیار تعداد کم پارامترهای تنظیمی، استفاده مفید از حافظه مورد نیاز و سرعت همگرایی مناسب نام برد. انتخاب فرکانسها به عنوان قیود مسئله برای جلوگیری از پدیده تشدید در سازه و در نتیجه تغییر شکلهای بزرگ و تخریب سازه است. نتایج حاصل از بهینه سازی سازه های خرپایی با در نظر گرفتن قیود دینامیکی توسط الگوریتم پیشنهادی هم از نظر سرعت همگرایی و هم از نظر کیفیت جوابها به مراتب بهتر ازالگوریتم اصلی PSO و الگوریتم های دیگر مورد استفاده در این زمینه تحقیقاتی می باشد. پرونده مقاله
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        4 - Damage Detection in Truss Structures Using Grasshopper Optimization Algorithm
        Pouria Foroutanrad Behnam Adhami
        Structural engineers' goal has constantly been identifying, restoring, repairing, or replacing damaged members. As a result, one of the most crucial and necessary steps in the upkeep and restoration of structures is identifying damaged members. Damage detection tec چکیده کامل
        Structural engineers' goal has constantly been identifying, restoring, repairing, or replacing damaged members. As a result, one of the most crucial and necessary steps in the upkeep and restoration of structures is identifying damaged members. Damage detection techniques from structural dynamic response measurements can often be used to detect and locate damage. This paper proposes a structural damage identification method based on changing natural frequency, finite element modeling, and the Grasshopper Optimization Algorithm (GOA). This algorithm mathematically models and mimics the behavior of grasshopper swarms in nature for solving optimization problems. As numerical examples, the 13-bar and a 31-bar planar truss are considered to examine the suggested methodology's precision. According to the findings, the recommended method is workable for systems with few members and minor damage. However, the accuracy of the diagnosed damage in structures with medium-sized members and considerable damages was poor, making it more likely to converge to local optimum points conditions. پرونده مقاله