با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
دسته بندی:
یادگیری عمیق - deep learning
سال انتشار:
2019
عنوان انگلیسی مقاله:
A novel deep learning based method for the computational material design of flexoelectric nanostructures with topology optimization
ترجمه فارسی عنوان مقاله:
یک روش مبتنی بر یادگیری عمیق برای طراحی مواد محاسباتی نانوساختارهای فلکسوالکتریک با بهینه سازی توپولوژی
منبع:
Sciencedirect - Elsevier - Finite Elements in Analysis & Design, 165 (2019) 21-30: doi:10:1016/j:finel:2019:07:001
نویسنده:
Khader M. Hamdia b,c, Hamid Ghasemi d, Yakoub Bazi a, Haikel AlHichri a, Naif Alajlan a, Timon Rabczuk
چکیده انگلیسی:
We present a deep learning method to investigate the effect of flexoelectricity in nanostructures. For this purpose,
deep neural network (DNN) algorithm is employed to map the relation between the inputs and the material
response of interest. The DNN model is trained and tested making use of database that has been established
by solving the governing equations of flexoelectricity using a NURBS-based IGA formulation at design points in
the full probability space of the input parameters. Firstly, pure flexoelectric cantilever nanobeam is investigated
under mechanical and electrical loading conditions. Then, structures of composite system constituted by two nonpiezoelectric
material phases are addressed in order to find the optimized topology with respect to the energy
conversion factor. The results show promising capabilities of the proposed method, in terms of accuracy and
computational efficiency. The deep learning method we used have produced superior optimal designs compared
to the numerical methods. The findings of this study will be of profound interest to researcher involved further
in the optimization and design of flexoelectric structures.
Keywords: Flexoelectricity | Piezoelectricity | Isogeometric analysis (IGA) | Machine learning | Deep neural network | Topology optimization
قیمت: رایگان
توضیحات اضافی:
تعداد نظرات : 0