ニューラルネットワークを用いた不均質平板の熱応力緩和のための材料組成最適化問題 : 非定常温度場のもとで任意の熱伝達条件を考慮した場合
スポンサーリンク
概要
- 論文の詳細を見る
In this study, a neural network is applied to optimization problems of material compositions for a nonhomogeneous plate with arbitrarily distributed and continuously varied material properties such as Functionally Graded Material. Unsteady temperature distribution for such nonhomogeneous plate is evaluated by taking into account the bounds of the number of the layers. Furthermore, the thermal stress components for an infinitely long nonhomogeneous plate are formulated under the mechanical condition of being traction free. As a numerical example, the plate composed of zirconium oxide and titanium alloy is considered. And, as the optimization problem of minimizing the thermal stress distribution, the numerical calculations are carried out making use of neural network, and the optimum material composition is determined taking into account the effect of temperaturedependency of material properties. Furthermore, the results obtained by neural network and ordinary nonlinear programming method are compared.
- 1998-07-25
論文 | ランダム
- マグネシウムの臨床的意義
- 著明な低Na,低Cl血を呈した肺嚢胞性疾患の1剖検例
- 真珠腫のコレステロール分析
- RFP治療により菌陰性化を示した再治療肺結核症例よりの再陽転症例の検討
- 鳥型結核菌のCysteine desulfhydraseについて