Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NV...Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).展开更多
[Objective]The aim was to research on construction of yield formation model of winter wheat.[Method]In the case of variety Shijiazhuang 8,the process of yield trait formation was studied by the dynamic ideal and unifo...[Objective]The aim was to research on construction of yield formation model of winter wheat.[Method]In the case of variety Shijiazhuang 8,the process of yield trait formation was studied by the dynamic ideal and uniform experimental design;the differences between plant dry weight and population indexes were analyzed by using multiple comparison analysis,and the yield formation model was developed by multiple regression analysis.[Result]The results showed that multiple correlation coefficients of yield formation model ranged from 0.91 to 0.97.[Conclusion]The model was significant which provide certain theoretical base for high yield and high efficiency cultivation of winter wheat.展开更多
文摘Statistical Energy Analysis(SEA) is one of the conventional tools for predicting vehicle high-frequency acoustic responses.This study proposes a new method that can provide customized optimization solutions to meet NVH targets based on the specific needs of different project teams during the initial project stages.This approach innovatively integrates dynamic optimization,Radial Basis Function(RBF),and Fuzzy Design Variables Genetic Algorithm(FDVGA) into the optimization process of Statistical Energy Analysis(SEA),and also takes vehicle sheet metal into account in the optimization of sound packages.In the implementation process,a correlation model is established through Python scripts to link material density with acoustic parameters,weight,and cost.By combining Optimus and VaOne software,an optimization design workflow is constructed and the optimization design process is successfully executed.Under various constraints related to acoustic performance,weight and cost,a globally optimal design is achieved.This technology has been effectively applied in the field of Battery Electric Vehicle(BEV).
基金Supported by the National Support Project (2006BAD29B04)National High Technology Research and Development (863)Projects(2006AA10A303-1)~~
文摘[Objective]The aim was to research on construction of yield formation model of winter wheat.[Method]In the case of variety Shijiazhuang 8,the process of yield trait formation was studied by the dynamic ideal and uniform experimental design;the differences between plant dry weight and population indexes were analyzed by using multiple comparison analysis,and the yield formation model was developed by multiple regression analysis.[Result]The results showed that multiple correlation coefficients of yield formation model ranged from 0.91 to 0.97.[Conclusion]The model was significant which provide certain theoretical base for high yield and high efficiency cultivation of winter wheat.