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Journal of Hydrodynamics

, Volume 30, Issue 4, pp 632–641 | Cite as

Navigable flow condition simulation based on two-dimensional hydrodynamic parallel model

  • Shang-hong Zhang (张尚弘)
  • Yu Wu (吴昱)
  • Zhu Jing (荆柱)
  • Yu-jun Yi (易雨君)
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Abstract

Navigable flow condition simulations can provide detailed information on water depth and velocity distribution, simulation speed is one of the key factors which influence real-time navigation. In this paper, a navigable flow condition simulation system is developed to provide useful information for waterway management and shipping safety. To improve the simulation speed of 2-D hydrodynamic model, an explicit finite volume method and OpenMP are used to realize parallel computing. Two mesh schemes and two computing platforms are adopted to study the parallel model’s performance in the Yangtze River, China. The results show that the parallel model achieves dramatic acceleration, with a maximum speedup ratio of 34.94×. The parallel model can determine the flow state of the navigable channel in about 4 min, efficiency is further improved by a flow simulation scheme database. The developed system can provide early warning information for shipping safety, allowing ships to choose better routes and navigation areas according to real-time navigable flow conditions.

Key words

2-D hydrodynamic model finite volume method parallel computation OpenMP navigable flow condition 
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References

  1. [1]
    Roberts S. E., Pettit S. J., Marlow P. B. Casualties and loss of life in bulk carriers from 1980 to 2010 [J]. Marine Policy, 2013, 42 (14): 223–235.CrossRefGoogle Scholar
  2. [2]
    Lao S. C. Three accidents in the history of the Yangtze River [J]. Labour Protection, 2015, (7): 76–78 (in Chinese).Google Scholar
  3. [3]
    Yang W. J., Sun E. Y., Rao G. S. et al. Research on the influence of unsteady flow produced by operation of TGP on navigationΠ: Reach between TGP and Gezhouba project [J]. Journal of Hydroelectric Engineering, 2006, 25 (1): 50–55 ( in Chinese).Google Scholar
  4. [4]
    Ahmed H. S., Hasan M. M., Tanaka N. T. Analysis of flow around impermeable groynes on one side of symmetrical compound channel: An experimental study [J]. Water Science and Engineering, 2010, 3 (1): 56–66.Google Scholar
  5. [5]
    Samuel M. G. Limitations of navigation through Nubaria canal, Egypt [J]. Journal of Advanced Research, 2014, 5 (2): 147–155.CrossRefGoogle Scholar
  6. [6]
    Bellos V., Tsakiris G. A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques [J]. Journal of Hydrology, 2016, 540: 331–339.CrossRefGoogle Scholar
  7. [7]
    Liang Q., Chen K. C, Hou J. et al. Hydrodynamic modelling of flow impact on structures under extreme flow conditions [J]. Journal of Hydrodynamics, 2016, 28 (2): 267–274.CrossRefGoogle Scholar
  8. [8]
    Gallegos H. A., Schubert J. E., Sanders B. F. Two-dimensional, high-resolution modeling of urban dam-break flooding: A case study of Baldwin Hills, California [J]. Advances in Water Resources, 2009, 32 (8): 1323–1335.CrossRefGoogle Scholar
  9. [9]
    Mohamed K. A finite volume method for numerical simulation of shallow water models with porosity [J]. Computers and Fluids, 2014, 104: 9–19.MathSciNetCrossRefzbMATHGoogle Scholar
  10. [10]
    Jang T. U., Wu Y., Xu Y. et al. A scheme for improving computational efficiency of quasi-two-dimensional model [J]. Journal of Hydrodynamics, 2017, 29 (2): 243–250.CrossRefGoogle Scholar
  11. [11]
    Zoppou C., Roberts S. Explicit schemes for dam-break simulations [J]. Journal of Hydraulic Engineering, ASCE, 2002, 129 (1): 11–34.CrossRefGoogle Scholar
  12. [12]
    Neal J. C., Fewtrell T. J., Bates P. D. et al. A comparison of three parallelisation methods for 2D flood inundation models [J]. Environmental Modelling and Software, 2010, 25 (4): 398–411.CrossRefGoogle Scholar
  13. [13]
    Brodtkorb A. R., Sætra M. L., Altinakar M. Efficient shallow water simulations on GPUs: implementation, visualization, verification, and validation [J]. Computers and Fluids, 2012, 55 (4): 1–12.MathSciNetCrossRefzbMATHGoogle Scholar
  14. [14]
    Bellos V., Tsakiris G. A hybrid method for flood simulation in small catchments combining hydrodynamic and hydrological techniques [J]. Journal of Hydrology, 2016, 540: 331–339.CrossRefGoogle Scholar
  15. [15]
    Lončar V., Young-S L. E., Škrbić S. et al. OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross-Pitaevskii equation [J]. Computer Physics Communications, 2016, 209: 190–196.CrossRefzbMATHGoogle Scholar
  16. [16]
    Zhang S., Yuan R., Wu Y. et al. Parallel computation of a dam-break flow model using OpenACC applications [J]. Journal of Hydraulic Engineering, ASCE, 2016, 143 (1): 04016070.CrossRefGoogle Scholar
  17. [17]
    Jin H. Q., Jespersen D., Mehrotra P. et al. High performance computing using MPI and OpenMP on multicore parallel systems [J]. Parallel Computing, 2011, 37 (9): 562–575.CrossRefGoogle Scholar
  18. [18]
    Barve A., Joshi B. K. Improved parallel lexical analysis using OpenMP on multicore machines [J]. Procedia Computer Science, 2015, 49 (1): 211–219.CrossRefGoogle Scholar
  19. [19]
    Sanders B. F., Schubert J. E., Detwiler R. L. ParBreZo: A parallel, unstructured grid, Godunov-type, shallow-water code for high-resolution flood inundation modeling at the regional scale [J]. Advances in Water Resources, 2010, 33 (12): 1456–1467.CrossRefGoogle Scholar
  20. [20]
    Zhang S., Xia Z., Yuan R. et al. Parallel computation of a dam-break flow model using OpenMP on a multicore computer [J]. Journal of Hydrology, 2014, 512 (6): 126–133.CrossRefGoogle Scholar

Copyright information

© China Ship Scientific Research Center 2018

Authors and Affiliations

  • Shang-hong Zhang (张尚弘)
    • 1
  • Yu Wu (吴昱)
    • 1
  • Zhu Jing (荆柱)
    • 1
  • Yu-jun Yi (易雨君)
    • 2
  1. 1.Renewable Energy SchoolNorth China Electric Power UniversityBeijingChina
  2. 2.State Key Laboratory of Water Environment Simulation and Pollution Control, School of EnvironmentBeijing Normal UniversityBeijingChina

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