The result is a model faithful to both the fundamental kinetics and system data, one that can be reliably employed for modeling purposes. Not all data or targets are created equal. The solution mapping paradigm allows the use of data of disparate types to refine rate parameters, thermochemistry or other parameters. Gaps or inconsistencies in the data set, and parameters which contribute large collective uncertainty and deserve more investigation, can be identified. A heuristic process and exercise of judgment is also involved in arriving at the final optimized mechanism in step 8 above.
Several factors are at work.
This effect occurs when the target sensitivities to a reaction are relatively low or parallel that of another. Hence a significant part of the mechanism optimization process consists of locating these shallow or insignificant variables, and freezing their values at the baseline evaluated kinetic expressions. This involves some subjective judgment on how large an error to permit in the predicted target values. Sometimes variables optimize near their starting values, and thus need not be altered. We have typically removed the majority of the variables from the final optimization.