Transit time distributions experimental data

Transit Time Distributions, Linear Response, and Extracting Kinetic Information from Experimental Data... 

The transition probabilities Ptj and Pjt in 0.2 s for both the impellers are estimated based on the experimental data in Challenge 2.3 (the change in the spatial distribution of the tracer concentration with time when the tracer is injected into an impeller position under an impeller rotational speed of 200 rpm) by using a computer. Based on the transition probabilities, the local mixing capacity and whole mixing capacity of both the impellers are calculated by using Eqs. (2.27) and (2.30) under the condition of V0 = 100 cm3. 

Analysis of experimental human small-intestine transit time data collected from 400 studies revealed a mean small-intestinal transit time (TSi) = 199 min [173]. Since the transit rate constant kt is inversely proportional to (TSj), namely, kt = to/ (TSi), (6.12) was further fitted to the cumulative curve derived from the distribution frequency of the entire set of small-intestinal transit time data in order to estimate the optimal number of mixing tanks. The fitting results were in favor of seven compartments in series and this specific model, (6.10) and (6.11) with to = 7, was termed the compartmental transit model. 

A clearer picture of the nature of the a P transition and the disorder of P-phases at high temperature can be drawn from the radial distribution function (RDF) (Fig. 3) and the distribution of Si-O-Si inter-tetrahedral angle (Fig. 4) which were obtained by analysis of the atom positions. The RDF represents the average distance between the different order neighboring atoms and can often be compared with NMR experimental data (Dove et al. 1997). The angle distribution gives the statistical distribution of the Si-O-Si angle in space and time. The RDFs for Si-0 and 0-0 distances show that... 

The application of the above-described model to the experimental H-NMR data demonstrates that the only plausible scenario for the PN-N transition in LCEs is the one that considers both the field G taking up values that are comparable to the critical value Gq, as well as the heterogeneity, which is manifested as a distribution of LdG parameters. This is best illustrated in Fig. 14, where two diagrams show the experimentally determined My i and My 2 temperature dependencies of a typical above-critical side-chain LCE together with three sets of theoretical My i T) and My 2(T) curves. The parameters for the theoretical curves were selected in such a way that aU three theoretical My i(T) profiles give a very good fit to the My i(T) experimental data and, at the same time, correspond to the three very different scenarios, none of which considers a distribution of the mechanical field (gq = 0) ... 

Fig. 13 (A) Schematic drawing of the dual-plate nano-fluidic device and simulation of the number of randomly diffusing molecules present in the device as a function of time. (B) Simulated current response (consistent with experimental data) generated by convolving the data with a measurement circuit response function and adding background noise. (C) Probability distribution of the occupancy times of a ferrocene molecule in the dual-plate electrode channel. The solid curve shows the probability that a molecule remains in the channel for a given occupancy time. The dashed curve is the probability distribution of occupancy times, with the additional condition that the molecule enters from one side of the channel and exits from the other (average transit time of (length) /6D. The shaded region denotes events too short to be individually resolved by experiment (taken from ref. 69).

Vapor temperatures in the core are overpredicted and in general are underpredicted in the upper plenum. Qualitatively the temperature distributions compare well with the experimental data. One possible explanation for the quantitative differences is due to an overestimated loss coefficient for the upper core plate and top nozzle assembly which separate the core from the upper plenum. This high resistance restricts the circulation between the two regions, increases the transit times in each region, and results in hotter vapor temperatures in the core and cooler temperatures in the upper plenum. An additional calculation is planned to evaluate the sensitivity of the temperature to this resistance. Another possible cause of errors is the three dimensional nature of the flows and the simplifications associated with simulating them with a one dimensional code. 

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