ImG-complex: graph data model for topology of unstructured meshes

Alireza Rezaei Mahdiraji, P. Baumann, G. Berti
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引用次数: 8

Abstract

Although, many applications use unstructured meshes, there is no specialized mesh database which supports storing and querying mesh data. Existing mesh libraries do not support declarative querying and are expensive to maintain. A mesh database can benefit the domains in several ways such as: declarative query language, ease of maintenance, etc. In this paper, we propose the Incidence multi-Graph Complex (ImG-Complex) data model for storing topological aspects of meshes in a database. ImG-Complex extends incidence graph (IG) model with multi-incidence information to represent a new object class which we call ImG-Complexes. We introduce optional and application-specific constraints to limit the ImG model to smaller object classes and validate mesh structures based on the modeled object class properties. We show how Neo4j graph database can be used to query mesh topology based on the (possibly constrained) ImG model. Finally, we experiment Neo4j and PostgreSQL performance on executing topological mesh queries.
ImG-complex:用于非结构化网格拓扑的图形数据模型
尽管许多应用程序使用非结构化网格,但没有专门的网格数据库来支持存储和查询网格数据。现有的网格库不支持声明式查询,而且维护成本很高。网格数据库可以在几个方面使这些领域受益,例如:声明性查询语言、易于维护等。在本文中,我们提出了关联多图复合体(ImG-Complex)数据模型用于在数据库中存储网格的拓扑方面。ImG-Complex扩展了具有多关联信息的关联图(IG)模型来表示一个新的对象类,我们称之为ImG-Complex。我们引入了可选的和特定于应用程序的约束,将ImG模型限制为较小的对象类,并根据建模的对象类属性验证网格结构。我们展示了Neo4j图形数据库如何用于基于(可能受约束的)ImG模型查询网格拓扑。最后,我们测试了Neo4j和PostgreSQL在执行拓扑网格查询方面的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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