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Lookup NU author(s): Professor Mohamad Kassem
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© 2019 Elsevier B.V. Mechanical, Electrical and Plumbing (MEP) models are generally characterized by information redundancy and a high density of irregularly shaped components. Consequently, they require large storage spaces and are not conducive for interchange purposes. Geometric optimization of MEP models can play a significant role in facilitating model exchange and handover by increasing storage, transmission and display efficiency. To date, the body of knowledge on such geometric optimization, unfortunately, is still very narrow. This paper presents and tests a solution for the optimization of storage, transmission, and display of MEP models. Storage optimization was achieved through a mapping-based model description method and a novel Quadric-Error-Metric (QEM) mesh simplification algorithm, reducing required storage while maintaining the contour of components. For transmission optimization, a normal vector compression algorithm and a fixed-dictionary specific compression algorithm were proposed to achieve efficient compression of data thus, fulfilling the need for cross-platform interchange. Display optimization was obtained through a normal vector regeneration algorithm for clustering triangle meshes to improve 3D display effects. The evaluation of the solution, performed for each individual component separately as well as for an entire solution, proved successful. Volume of storage data was reduced by 40% to 50% through mesh simplification. Data transmission volume was reduced by more than 80% for components with complicated geometry without affecting the topology of the components. Finally, the display process was capable of decreasing the number of triangles and delivering very good quality of displayed models.
Author(s): Hu Z-Z, Yuan S, Benghi C, Zhang J-P, Zhang X-Y, Li D, Kassem M
Publication type: Article
Publication status: Published
Journal: Automation in Construction
Print publication date: 01/11/2019
Online publication date: 10/09/2019
Acceptance date: 29/08/2019
ISSN (print): 0926-5805
ISSN (electronic): 1872-7891
Publisher: Elsevier BV
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