首页>
外国专利>
STRUCTURAL NON-GRADIENT TOPOLOGY OPTIMIZATION METHOD BASED ON SEQUENTIAL KRIGING SURROGATE MODEL
STRUCTURAL NON-GRADIENT TOPOLOGY OPTIMIZATION METHOD BASED ON SEQUENTIAL KRIGING SURROGATE MODEL
展开▼
机译：基于顺序克里格替代模型的结构非梯度拓扑优化方法
展开▼
页面导航
摘要
著录项
相似文献
摘要
A structural non-gradient topology optimization method based on a sequential Kriging surrogate model mainly comprises three parts: reduced series expansion of a material field of design domain, building of a non-gradient topology optimization model and solving optimization model using a sequential Kriging surrogate model algorithm. Design variables of the topology optimization problem are considerably reduced through the series expansion of a material-field function, and then the topology optimization problem involving fewer than 50 design variables can be effectively solved using the sequential Kriging surrogate model algorithm with an adaptive design space adjustment strategy. Without requiring the information of design sensitivity of a performance function, this method is suitable for solving complex multi-physical, multidisciplinary and highly nonlinear topology optimization problems. It not only inherits the simple form of density-based topology optimization model, but also makes the final topology clear and smooth in structural boundary.
展开▼
