For thin-walled parts,uniform allowance to each machining surface is allocated by the traditional machining method.Considering the sequence of the adjacent machining features,it may cause poor stiffness for some side ...For thin-walled parts,uniform allowance to each machining surface is allocated by the traditional machining method.Considering the sequence of the adjacent machining features,it may cause poor stiffness for some side walls due to a minor wall thickness,which may cause the deformation of the final formed parts to be large,or deduce machining efficiency for some machining features due to too thick remains.In order to address this issue,a non-uniform allowance allocation method based on interim state stiffness of machining features for the finishing of thin-walled structural parts is proposed in this paper.In this method,the interim state model of machining features is constructed according to the machining sequence of the parts,and the stiffness of the side wall is taken as the evaluation index to allocate reasonable allowance value to the corresponding machining surface to ensure the stiffness requirement of the parts in the machining process.According to the finite element simulation results,the non-uniform allowance allocation method proposed in this paper can effectively improve the stiffness of the parts and reduce the deformation of the parts,when compared with the traditional uniform allowance machining method.展开更多
Owing to reliability and high strength-to-weight ratio,large thin-walled components are widely used in the aviation and aerospace industry.Due to the complex features and sequence involved in the machining process of ...Owing to reliability and high strength-to-weight ratio,large thin-walled components are widely used in the aviation and aerospace industry.Due to the complex features and sequence involved in the machining process of large thin-walled components,machining deformation of component is easy to exceed the specification.In order to address the problem,it is important to retain the appropriate finishing allowance.To find the overall machining deformation,finishing allowance-induced deformation(web finishing allowance,sidewall finishing allowance)and initial residual stress-induced deformation were considered as major factors.Meanwhile,machined surface residual stress-induced deformation,clamping stress-induced deformation,thermal deformation,gravity-induced deformation and inertial force-induced deformation were neglected in the optimization model.Six-peak Gaussian function was introduced to fit the initial residual stress.Based upon the obtained function of initial residual stress,a deformation prediction model between initial residual stress and finishing allowance was established to attain the finishing allowanceinduced deformation.In addition,linear programming optimization model based on the simplex algorithm was developed to optimize the overall machining deformation.Results have concluded that the overall machining deformation reached the minimum value when sidewall finishing allowance and web finishing allowance varied between 1 and 2 mm.Additionally,web finishing allowance-induced deformation and sidewall finishing allowance-induced deformation were1.05 mm and 0.7 mm.Furthermore,the machining deformation decreased to 0.3–0.38 mm with the application of optimized finishing allowance allocation strategy,which made 39–56%reduction of the overall machining deformation compared to that in conventional method.展开更多
With the rapid development of big data and artificial intelligence(AI),the cloud platform architecture system is constantly developing,optimizing,and improving.As such,new applications,like deep computing and high-per...With the rapid development of big data and artificial intelligence(AI),the cloud platform architecture system is constantly developing,optimizing,and improving.As such,new applications,like deep computing and high-performance computing,require enhanced computing power.To meet this requirement,a non-uniform memory access(NUMA)configuration method is proposed for the cloud computing system according to the affinity,adaptability,and availability of the NUMA architecture processor platform.The proposed method is verified based on the test environment of a domestic central processing unit(CPU).展开更多
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(No.2015ZX04001002).
文摘For thin-walled parts,uniform allowance to each machining surface is allocated by the traditional machining method.Considering the sequence of the adjacent machining features,it may cause poor stiffness for some side walls due to a minor wall thickness,which may cause the deformation of the final formed parts to be large,or deduce machining efficiency for some machining features due to too thick remains.In order to address this issue,a non-uniform allowance allocation method based on interim state stiffness of machining features for the finishing of thin-walled structural parts is proposed in this paper.In this method,the interim state model of machining features is constructed according to the machining sequence of the parts,and the stiffness of the side wall is taken as the evaluation index to allocate reasonable allowance value to the corresponding machining surface to ensure the stiffness requirement of the parts in the machining process.According to the finite element simulation results,the non-uniform allowance allocation method proposed in this paper can effectively improve the stiffness of the parts and reduce the deformation of the parts,when compared with the traditional uniform allowance machining method.
基金co-supported by the National Natural Science Foundation of China(No.51405226)Postgraduate Research&Practice Innovation Program of Jiangsu Province of China(No.KYCX19_0165)。
文摘Owing to reliability and high strength-to-weight ratio,large thin-walled components are widely used in the aviation and aerospace industry.Due to the complex features and sequence involved in the machining process of large thin-walled components,machining deformation of component is easy to exceed the specification.In order to address the problem,it is important to retain the appropriate finishing allowance.To find the overall machining deformation,finishing allowance-induced deformation(web finishing allowance,sidewall finishing allowance)and initial residual stress-induced deformation were considered as major factors.Meanwhile,machined surface residual stress-induced deformation,clamping stress-induced deformation,thermal deformation,gravity-induced deformation and inertial force-induced deformation were neglected in the optimization model.Six-peak Gaussian function was introduced to fit the initial residual stress.Based upon the obtained function of initial residual stress,a deformation prediction model between initial residual stress and finishing allowance was established to attain the finishing allowanceinduced deformation.In addition,linear programming optimization model based on the simplex algorithm was developed to optimize the overall machining deformation.Results have concluded that the overall machining deformation reached the minimum value when sidewall finishing allowance and web finishing allowance varied between 1 and 2 mm.Additionally,web finishing allowance-induced deformation and sidewall finishing allowance-induced deformation were1.05 mm and 0.7 mm.Furthermore,the machining deformation decreased to 0.3–0.38 mm with the application of optimized finishing allowance allocation strategy,which made 39–56%reduction of the overall machining deformation compared to that in conventional method.
基金the National Key Research and Development Program of China(No.2017YFC0212100)National High-tech R&D Program of China(No.2015AA015308).
文摘With the rapid development of big data and artificial intelligence(AI),the cloud platform architecture system is constantly developing,optimizing,and improving.As such,new applications,like deep computing and high-performance computing,require enhanced computing power.To meet this requirement,a non-uniform memory access(NUMA)configuration method is proposed for the cloud computing system according to the affinity,adaptability,and availability of the NUMA architecture processor platform.The proposed method is verified based on the test environment of a domestic central processing unit(CPU).
