  The laser flash method is highly regarded due to its applicability to a wide
temperature range, from cryogenic temperatures to the melting point of
refractory metals, and to extreme environments involving radioactive or
hazardous materials. Although instruments implementing this method are mostly
produced on a commercial basis by major manufacturers, there is always room for
improvement both in terms of experimental methods and data treatment
procedures. The measurement noise, either due to the detector performance or
electromagnetic interferences, presents a significant problem when accurate
determination of thermal properties is desired. Noise resilience of the laser
flash method is rarely mentioned in published literature; there are currently
no data treatment procedures which could guarantee adequate performance under
any operating conditions. In this paper, a computational framework combining
finite-difference solutions of the heat conduction problem with nonlinear
optimization techniques based on the use of quasi-Newton direction search and
stochastic linear search with the Wolfe conditions is presented. The
application of this framework to data with varying level of noise is
considered. Finally, cross-verification and validation using an external
standard, a commercial and an in-house built laser flash instrument are
presented. The open-source software implementing the described computational
method is benchmarked against its industrial counterpart.
