Navier Stokes: Spherical form

In summary, Sam is trying to convert the cartesian form of the N-S equation to cylindrical/spherical form. They are struggling with representing the velocity terms (v_x, v_y, v_z) in terms of v_r and v_theta. They have figured out v_r to be v_x / cos(theta), but are unsure how to find v_theta. They are seeking help and any ideas are appreciated.
  • #1
sam2
22
0
Hi,

I'm trying to understand how to convert the cartesian form of the N-S equation to cylinderical/spherical form. Rather than re-derive the equation for spherical/cylindrical systems, I am trying to directly convert the cartesian PDE.

I'm ok with converting the d/dx and d2/dx2 terms. What I am struggling with a little, is the v_x, v_y and v_z terms which represent velocity in the x, y and z directions respectively.

Start simple with cylindrical...

Any idea on how to represent v_x and v_y in terms of v_r and v_theta?

I make v_r to be v_x / cos(theta). But can't see how to find v_theta. Any help is much appreciated.

Regards,

Sam
 
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  • #2
Any ideas at all?

Thanks,

Sam
 
  • #3


Hi Sam,

Converting the cartesian form of the Navier-Stokes equation to cylindrical or spherical form can be a bit tricky, but it is definitely doable. First, let's start with the cylindrical form. The x, y, and z directions in cartesian coordinates correspond to r, θ, and z directions in cylindrical coordinates. So, we can represent v_x and v_y in terms of v_r and v_θ as follows:

v_x = v_r cos(θ) - v_θ sin(θ)
v_y = v_r sin(θ) + v_θ cos(θ)

To understand why this is the case, think about the components of velocity in the x and y directions. The x component (v_x) is related to the radial direction (v_r) and the tangential direction (v_θ). Similarly, the y component (v_y) is related to the radial direction and the tangential direction, but with a rotation of 90 degrees. This is why we have the cos(θ) and sin(θ) terms in the equations above.

For the spherical form, the x, y, and z directions correspond to r, θ, and φ directions. Again, we can represent v_x and v_y in terms of v_r, v_θ, and v_φ as follows:

v_x = v_r sin(θ) cos(φ) - v_θ cos(θ) cos(φ) + v_φ sin(φ)
v_y = v_r sin(θ) sin(φ) - v_θ cos(θ) sin(φ) - v_φ cos(φ)

To understand this representation, think about the components of velocity in the x and y directions in spherical coordinates. The x component (v_x) is related to the radial direction (v_r), the meridional direction (v_θ), and the azimuthal direction (v_φ). Similarly, the y component (v_y) is related to these three directions, but with different combinations of sin and cos functions to account for the different orientations.

I hope this helps you understand how to convert the cartesian form of the Navier-Stokes equation to cylindrical and spherical forms. Good luck with your studies!


 

1. What is Navier-Stokes: Spherical form?

Navier-Stokes: Spherical form is a mathematical formulation of the Navier-Stokes equations that describes the motion of a fluid in a spherical coordinate system.

2. How is Navier-Stokes: Spherical form different from the traditional form?

The traditional form of the Navier-Stokes equations uses a Cartesian coordinate system, while the spherical form uses a spherical coordinate system. This allows for the study of fluid motion in spherical objects or systems, such as planets or stars.

3. What are the applications of Navier-Stokes: Spherical form?

Navier-Stokes: Spherical form has various applications in the fields of geophysics, astrophysics, and meteorology. It can be used to model the atmospheric dynamics of planets, the motion of fluids in stars, and the behavior of ocean currents.

4. Is Navier-Stokes: Spherical form a complete solution to fluid motion?

No, Navier-Stokes: Spherical form is only one of many formulations of the Navier-Stokes equations. While it is useful for studying fluid motion in spherical systems, it does not provide a complete solution to all types of fluid flow.

5. What are the limitations of Navier-Stokes: Spherical form?

Navier-Stokes: Spherical form assumes that the fluid is incompressible and has a constant density, which may not always be the case in real-world situations. It also does not take into account the effects of turbulence, which can significantly impact fluid motion. Additionally, it may be computationally expensive to solve, especially for complex systems.

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