Multi-Source Data Fusion and Management for Virtual Wind Tunnels and Physical Wind Tunnels

  • Huijie Hu
  • Xinhua Lin
  • Min-You Wu
Conference paper

We can make the full use of vast multi-source data by adopting flexible methods that are used to integrate and manage them. However, current works do not consider the database features on fusing and managing data. The main objective of this paper is to design a specific framework between client and database server to fuse and manage a mass of data which come from both physical and digital wind tunnel experiments. The system always adopts the latest data fusion and database conceptions. Therefore, the user could use the physical wind tunnels’ results to verify the data worked out from virtual wind tunnels, and to utilize the latter to supplement the former. Furthermore, the data of the virtual wind tunnel could replace some practical results which cannot be acquired in the real condition.


Computational Fluid Dynamics Wind Tunnel Data Fusion Wind Tunnel Experiment Virtual Reality Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Tgomas Connolly, Carolyn Begg. “Database Systems - A Practical Approach to Design, Implementation, and Management.” (Third Edition) January, 2004.Google Scholar
  2. 2.
    A. Paventhan, Kenji Takeda, Simon J. Cox and Denis A. Nicole. “Federated Database Service for Wind Tunnel Experiment Workflows.” Science Programming 14(2006), 173-184.Google Scholar
  3. 3.
    A. Paventhan, Kenji Takeda, Simon J. Cox, and Denis A. Nicole. “Workflows for Wind Tunnel Grid Applications.” ICCS 2006, Part III, LNCS 3993, pp. 928-935, 2006.Google Scholar
  4. 4.
    S. Thamarai Selvi, S. Rame, E. Mahendran. “Neural Network Based Interpolation of Wind Tunnel Test Data.” DOI.10.1109/ICCIMA.2007.176.Google Scholar
  5. 5.
    Kurt Severance, Paul Brewster, Barry Lazos, Daniel Keefe. “Wind Tunnel Data Fusion and Immersive Visualization: A case Study.” IEEE Visualization 2001, 21-26 October, 2001.Google Scholar
  6. 6.
    Lioyd A. Treinish, “Visual Data Fusion for Decision Support Application of Numerical Weather Prediction.” IBM T.J. Watson Research Center.Google Scholar

Copyright information

© Springer Science + Business Media B.V 2008

Authors and Affiliations

  • Huijie Hu
    • 1
  • Xinhua Lin
    • 1
  • Min-You Wu
    • 1
  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityChina

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