Experimental model validation

Experiments have been conducted to validate the impedance and actuation models for IPMCs. The experimental setup is illustrated in Fig. 4.5. A cantilevered IPMC beam was placed in a small water tank and its tip displacement was measured with a laser displacement sensor (OADM 20I6441/S14F, Baumer Electric). The IPMC was subject to a voltage input generated from a dSPACE system (DS1104, dSPACE Inc.), and its current was measured for the validation of the impedance model. 

Three IPMC samples, obtained from Environmental Robots Inc., Albuquerque, NM, were used in the experiments. The samples had dimensions as listed in Table 4.1 and were labeled as Big, Slim, and Short for ease of referencing. Table 4.2 lists the parameters for the impedance model that were identified based on the Slim sample. Details on parameter identification can be found in Chen and Tan (2008). 

We have also experimentally validated the scalability of the impedance model, by first identifying the model parameters for the Slim sample, and then using these parameters (except the geometric dimensions) to predict the impedance response for the Big and Short samples. The results are shown in Figs 4.7 and 4.8. The good agreement between the model predictions with the empirical measurement, for both the Big and Short samples, indicates that the proposed model is indeed geometrically scalable. 

Experiments were further performed to validate the actuation model. The electromechanical coupling constant ao was identified to be 0.129 J/C. 

For the Big sample, we identified a second-order model for its mechanical dynamics based on the measurement of damped oscillations in the passive 

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Altman, E., Kreis, P., Van Gerven, T., Stefanidis, G. D., Stankiewicz, A., Gorak, A. (2010). Pilot plant s3mthesis of n-propyl propionate via reactive distillation with decanter separator for reactant recovery. Experimental model validation and simulation studies. Chemical Engineering and Processing, 49, 965—972. 

Experimental model validation, 352 Characterizing mudeake properties, 356... 

PARAMETER ESTIMATION AND MODEL VALIDATION 17.4.1 Experimental Data... 

This is valid for any Newtonian fluid in any (circular) pipe of any size (scale) under given dynamic conditions (e.g., laminar or turbulent). Thus, if the values of jV3 (i.e., the Reynolds number 7VRe) and /V, (e/D) for an experimental model are identical to the values for a full-scale system, it follows that the value of N6 (the friction factor) must also be the same in the two systems. In such a case the model is said to be dynamically similar to the full-scale (field) system, and measurements of the variables in N6 can be translated (scaled) directly from the model to the field system. In other words, the equality between the groups /V3 (7VRc) and N (e/D) in the model and in the field is a necessary condition for the dynamic similarity of the two systems. 

As seen in Chapter 2 for turbulent flow, the length-scale information needed to describe a homogeneous scalar field is contained in the scalar energy spectrum E k, t), which we will look at in some detail in Section 3.2. However, in order to gain valuable intuition into the essential physics of scalar mixing, we will look first at the relevant length scales of a turbulent scalar field, and we develop a simple phenomenological model valid for fully developed, statistically stationary turbulent flow. Readers interested in the detailed structure of the scalar fields in turbulent flow should have a look at the remarkable experimental data reported in Dahm et al. (1991), Buch and Dahm (1996) and Buch and Dahm (1998). 

The IEM model is a simple example of an age-based model. Other more complicated models that use the residence time distribution have also been developed by chemical-reaction engineers. For example, two models based on the mixing of fluid particles with different ages are shown in Fig. 5.15. Nevertheless, because it is impossible to map the age of a fluid particle onto a physical location in a general flow, age-based models cannot be used to predict the spatial distribution of the concentration fields inside a chemical reactor. Model validation is thus performed by comparing the predicted outlet concentrations with experimental data. 

Because PB-PK models are based on physiological and anatomical measurements and all mammals are inherently similar, they provide a rational basis for relating data obtained from animals to humans. Estimates of predicted disposition patterns for test substances in humans may be obtained by adjusting biochemical parameters in models validated for animals adjustments are based on experimental results of animal and human in vitro tests and by substituting appropriate human tissue sizes and blood flows. Development of these models requires special software capable of simultaneously solving multiple (often very complex) differential equations, some of which were mentioned in this chapter. Several detailed descriptions of data analysis have been reported. 

Accurate modeling of the temperature distribution in a PEFC requires accurate information in four areas heat source, thermal properties of various components, thermal boundary conditions, and experimental temperature-distribution data for model validation. The primary mechanism of heat removal from the catalyst layers is through lateral heat conduction along the in-plane direction to the current collecting land (like a heat sink). Heat removed by gas convection inside the gas channel accounts for less than 5% under typical PEFC operating conditions. 

Calculated descriptors have generally fallen into two broad categories those that seek to model an experimentally determined or physical descriptor (such as ClogP or CpKJ and those that are purely mathematical [such as the Kier and Hall connectivity indices (4)]. Not surprisingly, the latter category has been heavily populated over the years, so much so that QSAR/QSPR practitioners have had to rely on model validation procedures (such as leave-k-out cross-validation) to avoid models built upon chance correlation. Of course, such procedures are far less critical when very few descriptors are used (such as with the Hansch, Leo, and Abraham descriptors) it can even be argued that they are unnecessary. 

Different sets of experimental data were used for model validation at real gas scale. Urea was used to supply NH3 an adequate residence time in the exhaust... 

To build a QSPR model, one should carefully select available experimental data, and choose the initial pool descriptors (from which the program selects the most appropriate ones) as well as a mathematical approach linking those descriptors with a given property. Then, a suitable strategy of model validation should be applied in order to obtain a quantitative assessment of the quality of predictions. Finally, some rules should be established in order to prevent the application of the models to compounds too different from those used for obtaining the models. 

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