Using a time gradient to compute velocity

In summary, the conversation discusses the process of computing the normal velocity of an evolving front in two dimensions using collected position data and fitting a parametric surface. It also questions the physical meaning of evaluating the temporal gradient and calculating the normal velocity as the reciprocal of the magnitude of grad(t).
  • #1
HughJass
1
0
I need to compute the normal velocity of an evolving front in two dimensions (x,y). Let's say that I have collected numerous x and y position data as a function of time. If I plot these data on a set of x,y,t coordinate axes and fit a surface through them in a manner analogous to fitting a curve through 2D data, I've generated a smooth, parametric surface that expresses time as a function of the x and y coordinates, that is t = f(x,y). I can then visualize the evolution of the physical front by plotting time contours of the surface in the xy plane.

If I want to calculate the velocity of the front (the normal velocity associated with each time contour), is it at all physically meaningful to evaluate the temporal gradient (grad(t)) of my surface and calculate the magnitude of the normal velocity as the reciprocal of the magnitude of grad(t)?

Thanks in advance!
 
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  • #2
If I understood your description correctly, then yes, if you change reciprocal by orthogonal. I'm not quite sure whether you can define a parametric curve ##y(t)=(x_0(t),y_0(t))## of the front point though.
 

FAQ: Using a time gradient to compute velocity

What is a time gradient?

A time gradient is a mathematical concept that measures the rate of change of a quantity over a specific period of time. It is often used in physics and engineering to calculate velocity, acceleration, and other important parameters.

How is a time gradient used to compute velocity?

A time gradient is used to compute velocity by dividing the change in position by the change in time. This results in a value that represents the rate of change of an object's position over time, or in other words, its velocity.

Why is using a time gradient important in scientific research?

Using a time gradient is important in scientific research because it allows for precise and accurate measurements of various quantities, such as velocity, acceleration, and force. It also helps to analyze and predict the behavior of physical systems.

What are some real-life applications of using a time gradient to compute velocity?

Some real-life applications of using a time gradient to compute velocity include calculating the speed of moving objects, determining the rate of change of weather patterns, and analyzing the motion of celestial bodies in space.

Are there any limitations to using a time gradient to compute velocity?

Yes, there are limitations to using a time gradient to compute velocity. It assumes that the velocity of an object is constant over the given time interval, which may not always be the case in real-world scenarios. Additionally, it may not take into account external factors such as air resistance or friction, which can affect an object's velocity.

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