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Determination of Gas and Water Volume Fraction in Oil Water Gas Pipe Flow Using Neural Networks Based on Dual Modality Densitometry

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3973))

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Abstract

The models of dual modality densitometry were developed. It can be used for measuring the gas volume fraction and water volume fraction in oil water gas pipe flow. The models are complex. In order to solve models, it often uses simplified models. This reduces measurement precision. The method of measuring gas and water volume fraction using neural networks was presented. The simulation data was gotten using Geant4. The radial basis function networks were trained and tested on computer simulation data. The results show that networks predicted gas volume fraction fit true gas fraction well and water volume fraction has some deviations.

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References

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Author information

Authors and Affiliations

  1. Yanshan University, Qinhuangdao, 066004, China

    Chunguo Jing, Guangzhong Xing & Bin Liu

  2. Northeastern University at Qinhuangdao, Qinhuangdao, 066004, China

    Chunguo Jing & Qiuguo Bai

Authors
  1. Chunguo Jing
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  2. Guangzhong Xing
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  3. Bin Liu
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  4. Qiuguo Bai
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Jing, C., Xing, G., Liu, B., Bai, Q. (2006). Determination of Gas and Water Volume Fraction in Oil Water Gas Pipe Flow Using Neural Networks Based on Dual Modality Densitometry. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_182

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  • DOI: https://doi.org/10.1007/11760191_182

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34482-7

  • Online ISBN: 978-3-540-34483-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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