توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Simulating Flow in Partly Porous Region Using RBF Neural Network and the Bees Algorithm
اطلاعات انتشار: بیستمین کنفرانس سالانه مهندسی مکانیک، سال
تعداد صفحات: ۴
The ability of neural network to solve Simultaneous flow in saturated porous medium and free fluid in various Reynolds ranges is studied. These regions must be solved by Naviar–Stocks equation and equation of motion in porous region with proper interface boundary condition. Considering Darcy, Forchheimer and Brinkman terms in equation of motion in porous medium compels us to solve whole domain numerically. In order to reduce the computational cost, different kinds of neural networks are used. Various Reynolds numbers are applied as the input feature for the neural networks. This paper presents an algorithm using optimized radial basis neural network via the Bees Algorithm for simulation of flow in partly porous region to enhance accuracy and performance. The optimum neural network results are in good agreement with numerical one and run time of the solution decreases noticeably.<\div>

۲Optimized fuzzy logic for nonlinear vibration control of aircraft semi–active shock absorber with input constraint (TECHNICAL NOTE)
نویسنده(ها): ، ،
اطلاعات انتشار: International Journal of Engineering، بيست و نهم،شماره۹، Sep ۲۰۱۶، سال
تعداد صفحات: ۷
Landing impact and runway unevenness have proximate consequence on performance of landing gear system and conduce to discomfort of passengers and reduction of the pilot’s capability to control aircraft. Finally, vibrations caused by them result in structure fatigue. Fuzzy logic controller is used frequently in different applications because of simplicity in design and implementation. In the present paper, this control approach is performed by minimum error criteria procedure and bees algorithm as the optimization technique for the model of semi–active suspension system that chooses damping performance of shock absorber at touchdown to be the purpose of control on landing gear and its efficiency is evaluated with the competence of passive control. Results of numerical simulation by matlab\simulink software indicate that the force induced to body and the vertical vibration of fuselage have significant improvement about 60% and 50% averagely for fuzzy intelligent method optimized by bees algorithm compared to passive performance which lead to increase in quality of landing, easiness of passengers and structure’s fatigue life in various operation conditions.
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