High nonlinear problem which is often met in Chemical engineering, taking the study of tray leakage mode as example, is treated by adopted BP (back propagation) algorithm in artificial neural network.
针对化工中经常遇到的高度非线性问题，以塔板研究中的泄漏模型为例，采用人工神经网络中的BP(反向传播)算法进行处理。
Numerical results indicate that the generalized conforming element has the advantages of high accuracy and uniform convergence to geometrically nonlinear problem of structures.
计算结果表明，广义协调元对于求解结构几何非线性问题同样具有精度高、收敛快等优点。
Different from the problem on static intensity, the relation between structural dynamic response and design variables is even more complex, and is high nonlinear.
与结构静态强度问题不同，结构动态响应与设计变量的关系更为复杂，是高度非线性的。
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