Comparison with Harris’ data

Harris, K. R. (1992). The self-diffusion coefficient and viscosity of the hard-sphere fluid revised A comparison with experimental data for xenon, methane, ethene and trichloromethane. Mol. Phys., 77,1153-1167. 

Quigley, Johnson, and Harris (Ql) find that the surface tension has no effect on the bubble size. A comparison of their data with the present general model is not possible because they conducted their experiments under constant pressure, not constant flow, conditions. However, the flow rates employed by them are high in such cases, even for constant flow conditions, the influence of surface tension is small. 

Harris and Dranoff [115] appear to have been the first to use the LSPP model to study the performance of a photochemical reactor for scale-up purposes. Experimentally, two sizes of perfectly mixed photochemical reactor were used for the decomposition of hexachloroplatinic acid in dilute aqueous solution, and the result of the theoretical analysis was acceptable in comparison with the experimental data. 

The values given in Table IT and referring to the potassium silicate solution already considered before (paragraph entitled "Comparison with the experimental data obtained by Harris at al. ") show a good agreement between experimental and calculated concentrations for the main oligomers. Satisfactory agreement was found as well for the other species not mentioned in Table IT. 

Control system performance can be assessed by comparison with a benchmark. For example, historical data representing periods of satisfactory control can be used as a benchmark. Alternatively, the benchmark could be an ideal control system performance, such as minimum variance control. As the name implies, a minimum variance controller minimizes the variance of the controlled variable when unmeasured, random disturbances occur. This ideal performance hmit can be estimated from closed-loop operating data then the ratio of minimum variance to the actual variance is used as the measure of control system performance. This statistically based approach has been commercialized, and many successful industrial applications have been reported (Kozub, 1997 Desborough and Miller, 2002 Harris and Seppala, 2002 Hoo et al., 2003 Paulonis and Cox, 2003). 

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