The renewal of ancient cities is an important part of the urban renewal work in China.However,there are few studies on the general historical ancient cities at the county level in China,and there is no guidance on the...The renewal of ancient cities is an important part of the urban renewal work in China.However,there are few studies on the general historical ancient cities at the county level in China,and there is no guidance on the renewal path.Through the practice of the renewal design project of Suining County,Xuzhou City,it makes an exploratory study on the renewal concept and mode.It first interprets the connotation and implementation path of the renewal concept of“endowing the old with the new”.Based on the texture analysis of the ancient city of Suining,it finally determines the design theme that tracing the historical context of the ancient city.Using the renewal techniques such as“extraction-transformationactivation”,through the renewal strategies such as“building new space,shaping new landscape,inheriting new culture and pregnant with new environment”,it realizes the regeneration of urban historical context and meets the needs of residents'modern life,so as to provide reference and guidance for the renovation of general historical ancient cities at the county level in China.展开更多
Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task ow...Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity （LF） model provides physics-based approximation of the high-fidelity （HF） model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.展开更多
文摘The renewal of ancient cities is an important part of the urban renewal work in China.However,there are few studies on the general historical ancient cities at the county level in China,and there is no guidance on the renewal path.Through the practice of the renewal design project of Suining County,Xuzhou City,it makes an exploratory study on the renewal concept and mode.It first interprets the connotation and implementation path of the renewal concept of“endowing the old with the new”.Based on the texture analysis of the ancient city of Suining,it finally determines the design theme that tracing the historical context of the ancient city.Using the renewal techniques such as“extraction-transformationactivation”,through the renewal strategies such as“building new space,shaping new landscape,inheriting new culture and pregnant with new environment”,it realizes the regeneration of urban historical context and meets the needs of residents'modern life,so as to provide reference and guidance for the renovation of general historical ancient cities at the county level in China.
文摘Advanced engineering systems, like aircraft, are defined by tens or even hundreds of design variables. Building an accurate surrogate model for use in such high-dimensional optimization problems is a difficult task owing to the curse of dimensionality. This paper presents a new algorithm to reduce the size of a design space to a smaller region of interest allowing a more accurate surrogate model to be generated. The framework requires a set of models of different physical or numerical fidelities. The low-fidelity （LF） model provides physics-based approximation of the high-fidelity （HF） model at a fraction of the computational cost. It is also instrumental in identifying the small region of interest in the design space that encloses the high-fidelity optimum. A surrogate model is then constructed to match the low-fidelity model to the high-fidelity model in the identified region of interest. The optimization process is managed by an update strategy to prevent convergence to false optima. The algorithm is applied on mathematical problems and a two-dimen-sional aerodynamic shape optimization problem in a variable-fidelity context. Results obtained are in excellent agreement with high-fidelity results, even with lower-fidelity flow solvers, while showing up to 39% time savings.
