Accounting for Temperature Measurement Bias

. Inverse heat conduction analyses generally consider the effects of random measurement errors on the resulting solution. However, all contact sensor measurements will result in a bias error due to imperfect contact of the sensor with the parent material and the finite volume of the sensing element which has different thermal properties from the parent material. Bias error can be mitigated through modeling of the sensor installation. The model may be used to in the IHCP solution to provide a more appropriate response function for the kernel in a deconvolution. The model may also be used to directly correct the temperature measurement to obtain a better value for the true temperature of the parent material at the measurement location. This study investigates the effect of various thermal sensor installations on measurement bias error through numerical experiments. A correction scheme involving a kernel devised through consideration of the physical installation is described and demonstrated through examples. Internal subsurface thermocouple measurements and surface thermocouple measurements are considered.