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Related Concept Videos

Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

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Newtonian fluids exhibit a constant viscosity, meaning their shear stress and shear strain rate are directly proportional. This property ensures a predictable and stable response to applied forces, maintaining a linear relationship between force and flow. Examples include water, air, and light oils, consistently demonstrating this proportional behavior regardless of external conditions.
A velocity gradient forms within the fluid when a Newtonian fluid is placed between two parallel plates, with...
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Typical Model Studies01:30

Typical Model Studies

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Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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Turbulent Flow: Problem Solving01:09

Turbulent Flow: Problem Solving

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Carbonation is a process used to dissolve carbon dioxide gas in a liquid, commonly used in the production of carbonated beverages. Achieving efficient carbonation requires careful control of temperature, pressure, and flow conditions. By adjusting these parameters, carbonation efficiency can be maximized, producing a higher concentration of CO2 in the liquid.
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Laminar Flow: Problem Solving01:24

Laminar Flow: Problem Solving

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Laminar flow occurs when a fluid moves smoothly in parallel layers with minimal mixing and turbulence. In fluid mechanics, ensuring laminar flow within a pipe is essential for precise control of flow characteristics, especially in engineering applications. The key factor in determining whether flow remains laminar is the Reynolds number, a dimensionless quantity that depends on the fluid's velocity, density, viscosity, and the pipe's diameter. A Reynolds number of 2100 or lower...
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Uniform Depth Channel Flow: Problem Solving01:18

Uniform Depth Channel Flow: Problem Solving

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To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...
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Accelerating Fluids01:17

Accelerating Fluids

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When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
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Updated: May 15, 2025

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A New Explicit Solver for MODFLOW Enabling Small Time Step Simulations.

Babak Azari1, Brian Waldron1, Farhad Jazaei2

  • 1Center for Applied Earth Science and Engineering Research (CAESER), Department of Civil Engineering, Herff College of Engineering, University of Memphis, Memphis, Tennessee, USA.

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A new explicit solver (EXP1) for MODFLOW 2005 enables groundwater modeling with small time steps, matching surface water models. This approach significantly reduces computational time while maintaining accuracy in simulating surface water-groundwater interactions.

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Area of Science:

  • Hydrology
  • Hydrogeology
  • Computational Modeling

Background:

  • Surface water (SW) and groundwater (GW) models like MODFLOW and HEC-RAS simulate SW-GW interactions.
  • Individual models have limitations in capturing the full complexity of these interactions.
  • Model coupling addresses shortcomings but faces challenges with temporal scale disparities.

Purpose of the Study:

  • Introduce a novel explicit solver (EXP1) for MODFLOW 2005.
  • Enable GW modeling at small time steps (e.g., 15 minutes) to match SW models.
  • Reduce runtime and computational burden for GW simulations.

Main Methods:

  • Developed the EXP1 solver for MODFLOW 2005 with an integrated stability criterion.
  • Evaluated EXP1 against the Preconditioned Conjugate Gradient (PCG) solver.
  • Tested across 1D, 2D, and 3D model scenarios.

Main Results:

  • EXP1 demonstrated efficiency and accuracy in predicting groundwater heads and water budget.
  • Achieved runtimes up to 33% shorter than the PCG solver.
  • Maintained less than 0.4% discrepancy in water budget compared to PCG.

Conclusions:

  • EXP1 effectively facilitates groundwater simulations at small time steps.
  • The solver bridges the temporal scale gap between SW and GW models.
  • Offers a computationally efficient and accurate solution for coupled SW-GW modeling.