Newton's Law of Cooling

Suppose that a hot object is placed in a surrounding medium of constant temperature (such as a large room). According to Newton, the rate at which the object cools down is proportional to the difference between the temperature of the object and that of the medium. If $T=T(t)$ denotes the temperature of the object at time $t$, and if $S$ denotes the constant temperature of the surrounding medium, then the law translates into the differential equation $$ \frac{dT}{dt} = k (T-S) $$ where $k<0$ is a constant. The solution of this equation, as we have seen, is $$ T=(T_0-S) e^{kt} + S \qquad \qquad (*) $$ where $T_0$ is the initial temperature.

We put this law to a simple test during the lecture on 4/27/17. The temperature of the room was $S=74.6^{\circ}$F. A cup of hot water was left on the table to cool down, and the temperature was recorded every $10$ minutes for one and a half hours, resulting in a total of $10$ samples. The readings were made using an instant digital thermometer:

time $t$ (min) 0 10 20 30 40 50 60 70 80 90
temperature $T$ ($^{\circ}$F) 182.0 151.7 133.9 122.0 113.1 106.2 101.1 96.7 93.5 90.9

To examine the accuracy of Newton's law, we noted that the exponential model $(*)$ is equivalent to $\log(T-S)$ being linear in time: $$ \log(T-S) = kt+C, \qquad \text{where} \ C=\log(T_0-S). $$ Here are the corresponding $\log (T-S)$ data rounded to 2 decimals, and the resulting plot versus time:

time $t$ (min) 0 10 20 30 40 50 60 70 80 90
$\log(T-74.6)$ 4.67 4.34 4.08 3.85 3.65 3.45 3.27 3.09 2.93 2.79

As seen from this plot, the data nearly follows a linear model. To obtain an empirical value for $k$, we used the standard least-squares method to obtain $$ L(t) = -0.020416 \ t + 4.535718 $$ as the best fitting line (shown in blue), giving $k \approx -0.020416$.

The resulting model $\exp(L(t))+S$ of $T$ along with the sample temperatures are shown below. The horizontal dotted line corresponds to the room temperature $S=74.6$, which is supposed to be $\lim_{t \to +\infty} T(t)$.


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