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Evaluation of Optimal River Training Work Using GA Based Linked Simulation-Optimization Approach

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  • Hriday Kalita
  • Arup Sarma
  • Rajib Bhattacharjya

Abstract

Use of structural measures for controlling a river to minimize its devastating effect and to utilize it for the benefit of mankind is a common practice all over the world. Because of high investment, such measures require prior investigation through model study. As lab based physical model study is very expensive and time consuming, mathematical modeling is generally used for investigating different alternatives of river training works. In this study, a new approach is proposed for deciding appropriate river training measure in a particular reach of a river or channel. In this methodology, an optimization model is linked with the hydrodynamic model for obtaining cost effective combination of groynes which will maintain a user defined flow speed in a pre-decided portion of a river reach. The optimization model is developed using binary coded Genetic Algorithm (GA) and the flow simulation model uses the Beam and Warming scheme for solving the two dimensional (2D) hydrodynamic equations of unsteady flow. The performance of the model is tested by applying the methodology in a rectangular channel for attaining different target speed values at a pre-defined portion of the channel and logical results have been obtained for all the tested scenarios. Copyright Springer Science+Business Media Dordrecht 2014

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  • Hriday Kalita & Arup Sarma & Rajib Bhattacharjya, 2014. "Evaluation of Optimal River Training Work Using GA Based Linked Simulation-Optimization Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(8), pages 2077-2092, June.
    • Handle: RePEc:spr:waterr:v:28:y:2014:i:8:p:2077-2092
    DOI: 10.1007/s11269-014-0593-3
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    References listed on IDEAS

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    Cited by:

    1. Zhenghua Gu & Xiaomeng Cao & Minxiong Cao & Weizhen Lu, 2023. "Integrative Study on Flow Characteristics and Impact of Non-Submerged Double Spur Dikes on the River System," IJERPH, MDPI, vol. 20(5), pages 1-13, February.
    2. Zhenghua Gu & Xiaomeng Cao & Yueteng Jiao & Wei-Zhen Lu, 2016. "Appropriate CFD Models for Simulating Flow around Spur Dike Group along Urban Riverways," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4559-4570, October.
    3. Qin Tu & Hong Li & Xinkun Wang & Chao Chen & Yin Luo & Frank Dwomoh, 2014. "Multi-Criteria Evaluation of Small-Scale Sprinkler Irrigation Systems Using Grey Relational Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(13), pages 4665-4684, October.
    4. Riddick Kakati & Vinay Chembolu & Subashisa Dutta, 2022. "Experimental and Numerical Investigation of Hybrid River Training Works using OpenFOAM," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2847-2863, June.
    5. Gokmen Tayfur, 2017. "Modern Optimization Methods in Water Resources Planning, Engineering and Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3205-3233, August.

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