Analysis of Parameters

Final shape of the gel at a = 10 is wave shaped. This phenomenon was observed in simulation at first and observed in experiments afterward. We will deal with waving pattern formation in chapter 7, in the context of shape control. 

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Cronin WJ, Oswald EJ, Shelley ML, et al. 1995. A trichloroethylene risk assessment using a Monte Carlo analysis of parameter uncertainty in conjunction with physiologically-based pharmacokinetic modeling. Risk Anal 15 555-565. 

Reliability analysis of parameters estimated in differential equations should be performed rigorously via sensitivity analysis. The details of this analysis can be found in the paper by Froment and Hosten (1981). 

The objective of this chapter is to give an overview of the optimization of petrochemical networks and to set up the deterministic model which will be used in the analysis of parameter uncertainties in Chapter 8. 

Baes CF, Sharp RD, Sjoreen Al, et al. 1984. A review and analysis of parameters for assessing transport of environmentally released radionuclides through agriculture. US Department of Energy. ORNL-5786. 

Sagiv, A. and Semiat, R. (2004) Analysis of parameters affecting boron permeation through reverse osmosis membranes. Journal of Membrane Science, 243 (1—2), 79-87. 

Inspired by the beauty and efficiency with which Nature controls macroscopic three-dimensional space as seen in the branching networks of trees [58], coral [59], and physiological structures [60, 61], one of us (D.A.T.) sought to mimic such branched assemblies at the molecular level. Analysis of parameters involved in synthetically mimicking such branching included the following hypothetical steps (see Fig. 9) ... 

The standard statistical analysis of parameters is based on linearization and does not always give a realistic picture of the accuracy of the parameters. For example, the variance expresses the confidence interval of the parameter in a symmetric way, which can sometimes lead to misunderstandings. For example, small parameter, e.g. a rate constant has a big variance, which means that even negative values of the parameter could be accepted. This is of course not true. A very simple and illustrative approach is to check the objective function (Q) as a function of each parameter value. All of the parameters except one is given the value which corresponds to the minimum value of the objective function, Q, and the influence on the numerical value of the objective function, Q, is investigated as a function of the parameter under consideration. Examples of these kinds of plots are shown in Figure 10.15 for two variables. 

Lloyd, P. J. (ed.). Particle Size-Analysis, Wiley-Interscience, New York, (1988). Allen, T., Particle Size Measurement, 4th ed.. Chapman and Hall, London, 1991. Malghan, S. G., et al.. Statistical analysis of parameters affecting measurement of particle size-distribution of silicon nitride by sedigraph. Powder Technol., 73, 275-284, (1992). 

The increase in mechanistic detail of process description is often accompanied by loss of parameter identifiability (Beck, 1999). This makes it extremely important to combine such model extensions with a careful analysis of parameter identifiability. Such an approach can clearly communicate not only the goodness of fit, but also the potential for gaining knowledge about parameter values, the conditionalities of parameters estimated from data, and the remaining degrees of freedom for parameter choices (Brun et al., 2001 Omlin et al., 2001b Reichert and Van-rolleghem, 2001). 

In addition, the efficiency of electric contact between bipolar plates and gas diffusion layers was measured using special test station comprising a hydraulic press with a temperature control, current supply and control systems. The purpose of provided measurements is the comparative analysis of parameters of different bipolar plates and gas diffusion layers, and also obtaining of the necessary data for use in calculations on mathematical model. Resistance tests of gas diffusion layers and bipolar plates were performed both in a longitudinal direction (four-contact method) and in a transverse direction. 

The aim of this chapter is to give a critical analysis of parameters that must be taken into account each time an economic study on membrane reactors is performed. In particular, nonporous inorganic membrane reactors for reactions involving gases are considered. 

The analysis of parameters showed, that 0.031 % Ak/k positive reactivity had been inserted into the core during this period, while the core pressure drop increase and sodium flow rate decrease by 2.5 3% took place. 

Analysis of parameters changes showed that carbon and hydrogen contaira ng substances penetrated into the primary sodium and deposited on the walls of SA feet and core diagrid. This was the cause of the flow rate decrease through SA in some sections of the reactor core. 

Ravipati, S., Punnathanam, S.N., Analysis of parameter values in the van der Waals and Platteeuw theory for methane hydrates using Monte Carlo molecular simulations, bid. Eng. Chem. Res., 51 (2012) 9419-9426. 

Ward, J.W., Muiford, R.N.R., Bivins, R.L. (1967) Study of some parameters affecting Knudsen effusion. II. A Monte Cario computer analysis of parameters deduced from experiment. The Journal of Physical Chemistry, 47, 1718-1723. 

Zhu YY, Xu J.M., Lu C.D. 2008. Analysis of parameters for structural cracks using digital image technique. Concrete 7 22-25. (in Chinese). 

Numerical Example Simulation and Sensitivity Analysis of Parameters... 

Numerical Example Simulation and Sensitivity Analysis of Parameters Table 5.3 Finished goods price distribution of the supply chain cell core enterprise... 

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