Ultrasonic time of flight measurements have been used to estimate the interior temperature of propulsion systems remotely. All that is needed is acoustic access to the boundary in question and a suitable model for the heat transfer along the path of the pulse train. The interior temperature is then deduced from a change in the time of flight and the temperature dependent velocity factor, which is obtained for various materials as a calibration step. Because the acoustic pulse samples the entire temperature distribution, inverse data reduction routines have been shown to provide stable and accurate estimates of the unknown temperature boundary. However, this technique is even more interesting when applied to unknown heat flux boundaries. Normally, the estimation of heat fluxes is even more susceptible to uncertainty in the measurement compared to temperature estimates. However, ultrasonic sensors can be treated as extremely high-speed calorimeters where the heat flux is directly proportional to the measured signal. Through some simple one-dimensional analyses, this work will show that heat flux is a more natural and stable quantity to estimate from ultrasonic time of flight. We have also introduced an approach for data reduction that makes use of a composite velocity factor, which is easier to measure.
Heat Flux Data Reduction Using a Preconditioning Trial Function
