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Related Concept Videos

Viscosity of Fluid01:19

Viscosity of Fluid

Viscosity measures the resistance a fluid offers to flow and deformation. It results from internal friction between layers of fluid moving relative to one another. Dynamic viscosity, denoted by the Greek letter mu (μ), quantifies the force needed to move one fluid layer over another. For Newtonian fluids like water and air, the relationship between the shearing stress and the rate of shearing strain is linear, meaning their viscosity remains constant regardless of the applied stress.
Newtonian Fluid: Problem Solving01:18

Newtonian Fluid: Problem Solving

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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Accelerating Fluids

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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Colloids and Suspensions01:17

Colloids and Suspensions

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Laminar and Turbulent Flow01:07

Laminar and Turbulent Flow

Fluid dynamics is the study of fluids in motion. Velocity vectors are often used to illustrate fluid motion in applications like meteorology. For example, wind—the fluid motion of air in the atmosphere—can be represented by vectors indicating the speed and direction of the wind at any given point on a map. Another method for representing fluid motion is a streamline. A streamline represents the path of a small volume of fluid as it flows. When the flow pattern changes with time, the streamlines...
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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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Published on: December 4, 2017

Coherent light scattering on nanofluids: computer simulation results.

Dan Chicea1

  • 1Physics Department, University Lucian Blaga of Sibiu, Sibiu, Romania. dan.chicea@ulbsibiu.ro

Applied Optics
|April 3, 2008
PubMed
Summary

A new computer code simulates how nanoparticles in nanofluids scatter light, revealing time fluctuations in speckle patterns. This simulation method aids in quickly assessing nanoparticle size.

Area of Science:

  • Optics and Photonics
  • Materials Science
  • Nanotechnology

Background:

  • Coherent light interacting with nanoparticles produces a time-fluctuating "speckle" pattern due to particle motion (sedimentation and Brownian motion).
  • Understanding these dynamics is crucial for characterizing nanofluids and their optical properties.

Purpose of the Study:

  • To develop and validate a computer code for simulating coherent light scattering dynamics in nanofluids.
  • To analyze the far-field intensity variations based on nanoparticle size.
  • To propose an experimental application for rapid nanoparticle size assessment.

Main Methods:

  • Development of a computer code to simulate the scattering of coherent light by nanoparticles.
  • Testing and validation of the simulation code.

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  • Calculation of far-field intensity variations for nanofluids with varying particle sizes.
  • Main Results:

    • The simulation successfully modeled the time fluctuations in speckle patterns caused by nanoparticle dynamics.
    • Calculated far-field intensity variations correlated with different nanoparticle sizes.
    • The study provides insights into the relationship between particle size and light scattering dynamics.

    Conclusions:

    • The developed simulation code is a valuable tool for studying light scattering in nanofluids.
    • The findings suggest a potential for a novel experimental technique for rapid nanoparticle size determination.
    • Further research can explore advanced applications of this simulation in nanofluid characterization.