基于网络共享的材料性能数据库系统研究

Cuifang Zheng, Jiaju Wu, Linggang Kong, Shujun Kang, Zheng Cheng, Bin Luo
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引用次数: 0

摘要

在分析材料性能数据管理需求的基础上,提出了一种材料性能数据网络共享方案。针对现有材料性能数据库网络共享、数据融合与多学科支持、智能服务标准化与数据安全控制不足等问题,设计了包括材料性能数据采集、数据查询、数据分析、数据可视化、数据安全管理与控制等模块的材料性能数据库系统。本文采用分层访问控制策略。用户登录材料性能数据库系统后,可以对材料性能数据进行标准化存储,形成一个共享的材料性能数据库。数据库系统的标准化材料性能数据,在权限控制下进行查询和共享。然后,数据库系统对受控查询共享得到的材料性能数据进行比较分析。最后,数据库系统将控制查询的共享结果和得到的比较分析结果可视化。数据库系统采用基于B/S (client/server)跨平台J2EE的MVC架构。系统集成了第三方计算平台。用户可以通过浏览器和网络方便地使用材料性能数据和相关服务。数据存储采用MongoDB数据库,支持分布式存储和高效查询。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Research on Material Properties Database System Based on Network Sharing
Based on the analysis of material performance data management requirements, a network-sharing scheme of material performance data is proposed. A material performance database system including material performance data collection, data query, data analysis, data visualization, data security management and control modules is designed to solve the problems of existing material performance database network sharing, data fusion and multidisciplinary support, and intelligent services Inadequate standardization and data security control. This paper adopts hierarchical access control strategy. After logging into the material performance database system, users can standardize the material performance data and store them to form a shared material performance database. The standardized material performance data of the database system shall be queried and shared under control according to the authority. Then, the database system compares and analyzes the material performance data obtained from controlled query sharing. Finally, the database system visualizes the shared results of controlled queries and the comparative analysis results obtained. The database system adopts the MVC architecture based on B/S (client/server) cross platform J2EE. The Third-party computing platforms are integrated in System. Users can easily use material performance data and related services through browsers and networks. MongoDB database is used for data storage, supporting distributed storage and efficient query.
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