Why is alpha mentioned in the cooling process equation?

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In summary: It's just a technical detail that has been mentioned for the sake of completeness.Yes, solving the partial differential equation doesn't involve \(\alpha\) since it's related to the scale used for measuring time. It's just a technical detail that has been mentioned for the sake of completeness.In summary, The cooling process is described by a set of equations with dimensionless variables. The diffusivity parameter \(\alpha\) is mentioned in the context of the time-scale used for measuring time, and it does not need to be considered when solving the equations. It is simply mentioned for completeness.
  • #1
Dustinsfl
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Why is $\alpha$ mentioned? I don't see an $\alpha$.With proper non-dimensionalization and assuming for convenience that the ratio of convection and conduction parameters $h/k = 1$, the cooling process is described by the following equations:
\begin{alignat*}{4}
T_t & = & T_{xx} & \\
T_x(0,t) & = & 0 & \\
T_x + T & = & 0 & \quad \text{at} \ x = 1\\
T(x,0) & = & f(x) &
\end{alignat*}
Here, $x$ and $t$ are dimensionless positions and times wherein the original interval has been mapped from $[0,L]$ to $[0,1]$ and a time-scale based on the diffusivity $\alpha$ has been used; also, the temperature definition is such that the ambient temperature has a reference value of zero.
 
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  • #2
dwsmith said:
Why is $\alpha$ mentioned? I don't see an $\alpha$.With proper non-dimensionalization and assuming for convenience that the ratio of convection and conduction parameters $h/k = 1$, the cooling process is described by the following equations:
\begin{alignat*}{4}
T_t & = & T_{xx} & \\
T_x(0,t) & = & 0 & \\
T_x + T & = & 0 & \quad \text{at} \ x = 1\\
T(x,0) & = & f(x) &
\end{alignat*}
Here, $x$ and $t$ are dimensionless positions and times wherein the original interval has been mapped from $[0,L]$ to $[0,1]$ and a time-scale based on the diffusivity $\alpha$ has been used; also, the temperature definition is such that the ambient temperature has a reference value of zero.

Hi dwsmith, :)

Well, the conduction timescale is based on diffusivity \((\alpha)\). That is,

\[t_{0}^{c}=\frac{L^2}{\alpha}\]

where \(t_{0}^{c}\) is the initial time. This is what is meant by "...time-scale based on the diffusivity $\alpha$ has been used..."

Reference: http://nd.edu/~msen/Teaching/IntHT/IntHTNotes.pdf (Page 6)

Kind Regards,
Sudharaka.
 
  • #3
Sudharaka said:
Hi dwsmith, :)

Well, the conduction timescale is based on diffusivity \((\alpha)\). That is,

\[t_{0}^{c}=\frac{L^2}{\alpha}\]

where \(t_{0}^{c}\) is the initial time. This is what is meant by "...time-scale based on the diffusivity $\alpha$ has been used..."

Reference: http://nd.edu/~msen/Teaching/IntHT/IntHTNotes.pdf (Page 6)

Kind Regards,
Sudharaka.

So I can just solve this problem without having to worry about it then, correct?
 
  • #4
dwsmith said:
So I can just solve this problem without having to worry about it then, correct?

Yes, solving the partial differential equation doesn't involve \(\alpha\) since it's related to the scale used for measuring time.
 
  • #5


The symbol $\alpha$ in the equation represents the thermal diffusivity, which is a material property that relates to how quickly heat can be transferred through a material. It is defined as the ratio of thermal conductivity ($k$) to heat capacity per unit volume ($c_p \rho$). In the cooling process equation, it appears in the time-scale used to non-dimensionalize the problem, indicating its importance in determining the rate of heat transfer. Additionally, it is also present in the boundary condition at $x=1$, where the temperature gradient is related to the rate of heat transfer at the surface. Therefore, $\alpha$ is mentioned in the cooling process equation because it plays a crucial role in determining the rate of cooling and the behavior of the system.
 

Related to Why is alpha mentioned in the cooling process equation?

1. Why is alpha mentioned in scientific research?

Alpha is mentioned in scientific research as it represents the level of significance or the probability of making a Type I error in a statistical analysis. It is an important measure that helps researchers determine if their results are due to chance or have a real effect.

2. What is the significance of alpha in hypothesis testing?

Alpha plays a crucial role in hypothesis testing as it is the threshold value used to determine whether the null hypothesis should be rejected or not. It helps researchers make informed decisions about the validity of their findings and the strength of their evidence.

3. How is alpha related to p-values?

Alpha and p-values are closely related as they both represent the likelihood of making a Type I error. The alpha value is usually set by the researcher before conducting the study, while the p-value is calculated based on the data collected. If the p-value is less than the alpha value, it is considered statistically significant.

4. Can alpha be changed in a study?

Yes, alpha can be changed in a study, but it should only be done if there is a valid reason for doing so. Changing the alpha value can affect the outcome of the study and the interpretation of the results, so it should be done with caution and with proper justification.

5. What is a common alpha value used in scientific research?

The most commonly used alpha value in scientific research is 0.05, which means that there is a 5% chance of making a Type I error. However, the alpha value can vary depending on the type of study, the research field, and the level of significance desired by the researcher.

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