کد مقاله کد نشریه سال انتشار مقاله انگلیسی ترجمه فارسی نسخه تمام متن
12220828 865960 1997 12 صفحه PDF سفارش دهید دانلود کنید
عنوان انگلیسی مقاله ISI
A hybrid numerical/neurocomputing strategy for sensitivity analysis of nonlinear structures
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
A hybrid numerical/neurocomputing strategy for sensitivity analysis of nonlinear structures
چکیده انگلیسی
A hybrid numerical/neurocomputing (HN/N) strategy is presented for the evaluation of selective sensitivity coefficients of nonlinear structures. In the hybrid strategy, multilayer feedforward neural networks are used to extend a range of the validity of predictions of sensitivity coefficients made by Padé approximants. To further increase the accuracy and the range of network predictions, a data expansion strategy is used in which additional training data are generated by using extrapolated values of the coefficients in a Taylor series. Within this strategy a number of techniques are examined for evaluating derivatives of response functions. The effectiveness of the HNN strategy is assessed by performing numerical experiments for composite panels subjected to combined thermal and mechanical loads. It is shown that the HNN strategy reduces the number of full-system analyses and allows obtaining selective information about the structural response and the sensitivity coefficients.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Structures - Volume 65, Issue 6, December 1997, Pages 869-880
نویسندگان
, ,