A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm.Initially,a finite element method(FEM) model was set up a...A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm.Initially,a finite element method(FEM) model was set up and then experimentally verified.And the relation between depth increment and the minimum thickness tmin as well as its location was analyzed through the FEM model.Afterwards,the variation of depth increments was defined.The designed part was divided into three areas according to the main deformation mechanism,with Di(i=1,2) representing the two dividing locations.And three different values of depth increment,Δzi(i=1,2,3) were utilized for the three areas,respectively.Additionally,an orthogonal test was established to research the relation between the five process parameters(D and Δz) and tmin as well as its location.The result shows that Δz2 has the most significant influence on the thickness distribution for the corresponding area is the largest one.Finally,a single evaluating indicator,taking into account of both tmin and its location,was formatted with a linear weighted model.And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index.The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.展开更多
溢流坝下游收缩断面水深 hc 的计算对水工消能设计十分重要． 目前常用的方法有试算法、图解法和迭代法，这些方法计算精度不高，人工计算量大或要求较高的计算数学的理论知识等，不便于在生产实际中推广应用． 为此，把 hc 的计算问题...溢流坝下游收缩断面水深 hc 的计算对水工消能设计十分重要． 目前常用的方法有试算法、图解法和迭代法，这些方法计算精度不高，人工计算量大或要求较高的计算数学的理论知识等，不便于在生产实际中推广应用． 为此，把 hc 的计算问题归结为非线性优化问题，用作者研制的加速遗传算法 （AGA） 来处理． 应用 AGA 方法的实例计算结果说明 AGA 比常用方法简便 计算精度高且具有通用性．展开更多
文摘A method utilizing variable depth increments during incremental forming was proposed and then optimized based on numerical simulation and intelligent algorithm.Initially,a finite element method(FEM) model was set up and then experimentally verified.And the relation between depth increment and the minimum thickness tmin as well as its location was analyzed through the FEM model.Afterwards,the variation of depth increments was defined.The designed part was divided into three areas according to the main deformation mechanism,with Di(i=1,2) representing the two dividing locations.And three different values of depth increment,Δzi(i=1,2,3) were utilized for the three areas,respectively.Additionally,an orthogonal test was established to research the relation between the five process parameters(D and Δz) and tmin as well as its location.The result shows that Δz2 has the most significant influence on the thickness distribution for the corresponding area is the largest one.Finally,a single evaluating indicator,taking into account of both tmin and its location,was formatted with a linear weighted model.And the process parameters were optimized through a genetic algorithm integrated with an artificial neural network based on the evaluating index.The result shows that the proposed algorithm is satisfactory for the optimization of variable depth increment.
文摘溢流坝下游收缩断面水深 hc 的计算对水工消能设计十分重要． 目前常用的方法有试算法、图解法和迭代法，这些方法计算精度不高，人工计算量大或要求较高的计算数学的理论知识等，不便于在生产实际中推广应用． 为此，把 hc 的计算问题归结为非线性优化问题，用作者研制的加速遗传算法 （AGA） 来处理． 应用 AGA 方法的实例计算结果说明 AGA 比常用方法简便 计算精度高且具有通用性．
