当今,企业信息化建设已成为企业生存与发展不可或缺的竞争力要素。云计算平台的技术进步和应用普及更为企业信息化平台的选择提供了新途径。当前,提供基础设施即服务(IaaS)和平台即服务(IaaS)的云计算服务商众多,既有世界一流的科技公...当今,企业信息化建设已成为企业生存与发展不可或缺的竞争力要素。云计算平台的技术进步和应用普及更为企业信息化平台的选择提供了新途径。当前,提供基础设施即服务(IaaS)和平台即服务(IaaS)的云计算服务商众多,既有世界一流的科技公司如微软、亚马逊、谷歌、IBM等,也有一些中小型公司,如Rackspace、(RoR)Ruby on Rail、SalesForce等。本文以某公司开发管理信息系统选择使用的微软Windows Azure Platform平台为例,对比传统信息化平台,分析了选择云计算平台成本及其他优势,为企业在新技术平台下尝试企业信息化系统构建提供有益的参考与借鉴。展开更多
Casing treatment(CT) has the potential to extend the stable operating range of a centrifugal compressor.A multi-objective optimization method is proposed to optimize the CT of centrifugal compressors. The method consi...Casing treatment(CT) has the potential to extend the stable operating range of a centrifugal compressor.A multi-objective optimization method is proposed to optimize the CT of centrifugal compressors. The method consists of Kriging metamodel, Genetic Algorithm(GA), data-mining techniques and CFD code. Firstly, data-mining techniques are used to analyze the initial design space. The correlations between design variables and objectives are extracted,resulting in a refined design space. Then, the global optimization of CT is conducted by GA based on data-mining results. After optimization, the performance of the centrifugal compressor shows a considerable improvement over the whole speed line. The isentropic efficiency increases by 2.05%, and the stall margin improves by 7.11%. Finally, the mechanism behind the performance improvement is further clarified by detailed flow analysis.展开更多
文摘当今,企业信息化建设已成为企业生存与发展不可或缺的竞争力要素。云计算平台的技术进步和应用普及更为企业信息化平台的选择提供了新途径。当前,提供基础设施即服务(IaaS)和平台即服务(IaaS)的云计算服务商众多,既有世界一流的科技公司如微软、亚马逊、谷歌、IBM等,也有一些中小型公司,如Rackspace、(RoR)Ruby on Rail、SalesForce等。本文以某公司开发管理信息系统选择使用的微软Windows Azure Platform平台为例,对比传统信息化平台,分析了选择云计算平台成本及其他优势,为企业在新技术平台下尝试企业信息化系统构建提供有益的参考与借鉴。
基金National Natural Science Foundation of China,No.11672206
文摘Casing treatment(CT) has the potential to extend the stable operating range of a centrifugal compressor.A multi-objective optimization method is proposed to optimize the CT of centrifugal compressors. The method consists of Kriging metamodel, Genetic Algorithm(GA), data-mining techniques and CFD code. Firstly, data-mining techniques are used to analyze the initial design space. The correlations between design variables and objectives are extracted,resulting in a refined design space. Then, the global optimization of CT is conducted by GA based on data-mining results. After optimization, the performance of the centrifugal compressor shows a considerable improvement over the whole speed line. The isentropic efficiency increases by 2.05%, and the stall margin improves by 7.11%. Finally, the mechanism behind the performance improvement is further clarified by detailed flow analysis.
