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Vertical and Horizontal Water Penetration Velocity Modeling in Nonhomogenous Soil Using Fast Multi-Output Relevance

Babak Vaheddoost1, Shervin Rahimzadeh Arashloo2, Mir Jafar Sadegh Safari3

  • 1Department of Civil Engineering, Bursa Technical University, Bursa, Turkey.

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|March 14, 2023
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Summary
This summary is machine-generated.

This study introduces fast multi-output relevance vector regression (FMRVR) for joint determination of water movement in porous media. FMRVR accurately predicts horizontal and vertical water velocities, outperforming other regression models.

Keywords:
cutoff walldummy variablefast multi-output relevance vector regressionporous mediumtracer

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Area of Science:

  • Hydrogeology
  • Computational Fluid Dynamics
  • Machine Learning

Background:

  • Understanding water movement in porous media is crucial for various environmental and engineering applications.
  • Accurate joint determination of horizontal and vertical velocities is challenging due to complex flow dynamics.

Purpose of the Study:

  • To develop and evaluate a novel method for the joint estimation of horizontal and vertical water movement in porous media.
  • To compare the performance of fast multi-output relevance vector regression (FMRVR) against alternative machine learning models.

Main Methods:

  • Experimental setup using a sand box with controlled dimensions and sand properties.
  • Utilized FMRVR with independent variables including tracer coordinates, time, wall length, and dummy variables.
  • Compared FMRVR results with multi-linear regression, random forest, and support vector regression.

Main Results:

  • FMRVR demonstrated superior performance in estimating both horizontal and vertical water velocities compared to alternative methods.
  • The study identified that estimation uncertainty for horizontal water penetration is greater than for vertical penetration.

Conclusions:

  • FMRVR is an effective and efficient tool for the joint determination of water movement in porous media.
  • The findings highlight the importance of considering directional uncertainties in hydrological modeling.