Best fit value of eddy thermal diffusivity

In summary, a mathematical model for temperature T as a function of depth y and time t is given by equation (2). To obtain the best fit value of α, the data for July 19th is fitted to this equation. A non-linear least squares fit is recommended, minimizing the error with respect to the eddy diffusivity. Another approach is to plot T(y,t)-T(0) vs y^2 on a semi-log plot and draw the best fit line, with the slope being equal to -1/(4αt). The points where T(y,t) < T(0) are omitted as they are essentially equal to T(0). By solving for the slope, the value of α can be calculated.
  • #1
rico22
51
0

Homework Statement



A mathematical model for temperature T as a function of depth y (in m) and time t (in days) is:

(T(y,t)-T0)/(Tsurf(t)-T0)=e^(-y2/4αt) (2)where Tsurf(t) is the water temperature of the lake surface at time t, α is a property called the “eddy thermal diffusivity” and T0 is the lake temperature at time zero. Time zero must be chosen to be on a day when the lake temperature is more or less uniform.

Fit equation (2) to the data for July 19th to obtain the best fit value of α.

20-Dec 18-Apr 16-May 19-Jul
y (m) T(C) T(C) T(C) T(C)
0 10.8 19.1 22.2 28.4
1 10.7 18.7 21.8 27.9
2 10.5 18 21.4 28
3 10.5 17.4 21.2 27.9
4 10.5 17 21.1 27.4
5 10.5 16.4 20.7 26.2
6 10.5 16 19.3 23.6
7 10.5 15.2 17.1 21.4
8 10.5 14.7 15.6 19.3
9 10.5 13.7 14.6 17.9
10 10.5 12.9 14.1 16.8
11 10.5 12.1 13.2 15.9
12 10.5 11.6 12.7 15
13 10.5 11.1 12.1 14.1
14 10.5 10.7 11.6 13.2
15 10.4 10.4 11.3 12.4
20 10.3 9.3 9.9 10.6
25 10.3 8.9 9.4 9.8
30 10.1 8.7 9.1 9.3
35 10.3 8.7 8.8 9.1

Homework Equations


T0=10.5
t=211 since Dec. 20th is t=0

The Attempt at a Solution


I solved for α which gives the equation -y^2/[844ln(T - 10.5)/17.9]

so I started going down the list using the values from July 19th which gave me a different value for every value of T but once i got to T=9.8 I couldn't get any value for alpha because it would be the ln of a negative number... my question is how exactly should I look for the best fit value of α? is it the average value of the ones I was able to calculate? Or maybe I am missing something? Any help would greatly be appreciated.
 
Last edited:
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  • #2
Sorry, here is a better look at the Temperatures from July 19th

19-Jul
T(C)
28.4
27.9
28
27.9
27.4
26.2
23.6
21.4
19.3
17.9
16.8
15.9
15
14.1
13.2
12.4
10.6
9.8
9.3
9.1
 
  • #3
You probably want to do a non-linear least squares fit to the data, minimizing the error with respect to the eddy diffusivity.
 
  • #4
Chestermiller said:
You probably want to do a non-linear least squares fit to the data, minimizing the error with respect to the eddy diffusivity.

Im not quite sure how I would go about doing that; but thanks for the reply.
 
  • #5
Make a plot of T(y,t)-T(0) vs y2 on a semi-log plot, including only the points for which T(y,t) > T(0). The semi-log parameter should be T(y,t) - T(0). You should get something close to a straight line. The slope of this line should be -1/(4αt). Draw your best straight line in, and then calculate the slope. The points where T(y,t) < T(0) are omitted because, within experimental uncertainty, they are essentially equal to T(0).
 
  • #6
so once I have the slope just solve for α?
 
  • #7
Yes.
 

FAQ: Best fit value of eddy thermal diffusivity

What is the "best fit value" of eddy thermal diffusivity?

The "best fit value" of eddy thermal diffusivity refers to the numerical value that best represents the diffusion of heat by eddies in a given system. This value is determined through data analysis and statistical methods.

Why is it important to determine the "best fit value" of eddy thermal diffusivity?

Determining the "best fit value" of eddy thermal diffusivity allows scientists to accurately model and predict heat transfer in various systems, such as in the Earth's atmosphere and ocean. It also helps in understanding the impact of heat transfer on climate and weather patterns.

How is the "best fit value" of eddy thermal diffusivity calculated?

The "best fit value" of eddy thermal diffusivity is calculated using various methods, such as regression analysis, maximum likelihood estimation, and Bayesian inference. These methods involve fitting mathematical models to observed data and determining the value that best describes the relationship between eddy thermal diffusivity and other variables.

Can the "best fit value" of eddy thermal diffusivity change over time?

Yes, the "best fit value" of eddy thermal diffusivity can change over time due to various factors, such as changes in environmental conditions or data collection methods. It is important for scientists to regularly reassess and update the best fit value to ensure accurate predictions and understanding of heat transfer processes.

What are the limitations of determining the "best fit value" of eddy thermal diffusivity?

There are several limitations to determining the "best fit value" of eddy thermal diffusivity. These include uncertainties in data collection, assumptions made in mathematical models, and the complexity of heat transfer processes. It is important for scientists to consider and address these limitations when interpreting the results of their analyses.

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