Figure E.2.4: Fully enclosed netbook with SS500 eGRAF Spreadershield inside. Results Figure (E.2.5) shows the temperature at the interface of resistive heater and the graphite sheet as a function of time until the temperature reaches a steady state as defined in procedure (ΔT < ± 0.5 °C/min). Test results are shown for a thermal power input of 10 and 12W. Figure E.2.5: Temperature vs. time results of the graphite sheet. Analysis In analyzing the data the temperature is graphed as a function of time from start of wattage setting. This should produce a roughly logarithmic increase curve. However, the software used did not allow a logarithmic recession due to low R values. A polynomial recession was used in its stead. To find the approximate temperature that the heater would reach given more time the maximum of the 2nd order polynomial was found for each test. This maximum was found by the standard of finding the derivative of the function and setting it equal to 0 and solving for time and then temperature. Example The polynomial regression from Microsoft Excel for the enclosed .76mm cut graphite sheet with 12 Watts of power added is calculated using equations (E.2.2) through (E.2.6). y = -0.0062x^2 + 0.3447x + 54.414 (E.2.2) dy/dx = -0.0124x + .3447 = 0 (E.2.3) x = 27.8 min (E.2.4) y = -.0062(27.8^2) + .3447(27.8) + 54.414 (E.2.5) y = 59.2°C (E.2.6) The steady state temperature calculated for the maximum graphite temperature is shown in table (E.2.1) for a thermal power input of 10 and 12W.
Figure E.2.4: Fully enclosed netbook with SS500 eGRAF Spreadershield inside. Results Figure (E.2.5) shows the temperature at the interface of resistive heater and the graphite sheet as a function of time until the temperature reaches a steady state as defined in procedure (ΔT < ± 0.5 °C/min). Test results are shown for a thermal power input of 10 and 12W. Figure E.2.5: Temperature vs. time results of the graphite sheet. Analysis In analyzing the data the temperature is graphed as a function of time from start of wattage setting. This should produce a roughly logarithmic increase curve. However, the software used did not allow a logarithmic recession due to low R values. A polynomial recession was used in its stead. To find the approximate temperature that the heater would reach given more time the maximum of the 2nd order polynomial was found for each test. This maximum was found by the standard of finding the derivative of the function and setting it equal to 0 and solving for time and then temperature. Example The polynomial regression from Microsoft Excel for the enclosed .76mm cut graphite sheet with 12 Watts of power added is calculated using equations (E.2.2) through (E.2.6). y = -0.0062x^2 + 0.3447x + 54.414 (E.2.2) dy/dx = -0.0124x + .3447 = 0 (E.2.3) x = 27.8 min (E.2.4) y = -.0062(27.8^2) + .3447(27.8) + 54.414 (E.2.5) y = 59.2°C (E.2.6) The steady state temperature calculated for the maximum graphite temperature is shown in table (E.2.1) for a thermal power input of 10 and 12W.
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