Publications
Uncertainty analysis of heat flux measurements estimated using a one-dimensional, inverse heat-conduction program
The measurement of heat flux in hydrocarbon fuel fires (e.g., diesel or JP-8) is difficult due to high temperatures and the sooty environment. Un-cooled commercially available heat flux gages do not survive in long duration fires, and cooled gages often become covered with soot, thus changing the gage calibration. An alternate method that is rugged and relatively inexpensive is based on inverse heat conduction methods. Inverse heat-conduction methods estimate absorbed heat flux at specific material interfaces using temperature/time histories, boundary conditions, material properties, and usually an assumption of one-dimensional (1-D) heat flow. This method is commonly used at Sandia.s fire test facilities. In this report, an uncertainty analysis was performed for a specific example to quantify the effect of input parameter variations on the estimated heat flux when using the inverse heat conduction method. The approach used was to compare results from a number of cases using modified inputs to a base-case. The response of a 304 stainless-steel cylinder [about 30.5 cm (12-in.) in diameter and 0.32-cm-thick (1/8-in.)] filled with 2.5-cm-thick (1-in.) ceramic fiber insulation was examined. Input parameters of an inverse heat conduction program varied were steel-wall thickness, thermal conductivity, and volumetric heat capacity; insulation thickness, thermal conductivity, and volumetric heat capacity, temperature uncertainty, boundary conditions, temperature sampling period; and numerical inputs. One-dimensional heat transfer was assumed in all cases. Results of the analysis show that, at the maximum heat flux, the most important parameters were temperature uncertainty, steel thickness and steel volumetric heat capacity. The use of a constant thermal properties rather than temperature dependent values also made a significant difference in the resultant heat flux; therefore, temperature-dependent values should be used. As an example, several parameters were varied to estimate the uncertainty in heat flux. The result was 15-19% uncertainty to 95% confidence at the highest flux, neglecting multidimensional effects.