Empirical Application - Illustrative Case

In parallel with the conceptual development of the Framework, empirical investigations were conducted seeking to collect, stmcture and analyze the practice based evidence. This was necessary to ensuring greater correlation or fit between the Framework and practice, enhancing its robustness and improving the quality of guidance that may be proffered. The in-depth case analysis approach addressed four questions  

To what extent are the supply chain members aware of SCRM  

How do the supply chain members identify, evaluate and prioritise the risk drivers  

How do they perceive risk and the risk/performance interaction  

What are the primary risk management responses employed  

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Problem Solving Methods Most, if not aU, problems or applications that involve mass transfer can be approached by a systematic-course of action. In the simplest cases, the unknown quantities are obvious. In more complex (e.g., iTmlticomponent, multiphase, multidimensional, nonisothermal, and/or transient) systems, it is more subtle to resolve the known and unknown quantities. For example, in multicomponent systems, one must know the fluxes of the components before predicting their effective diffusivities and vice versa. More will be said about that dilemma later. Once the known and unknown quantities are resolved, however, a combination of conservation equations, definitions, empirical relations, and properties are apphed to arrive at an answer. Figure 5-24 is a flowchart that illustrates the primary types of information and their relationships, and it apphes to many mass-transfer problems. 

Perhaps the best methods for demonstrating the existence of adsorption in a soil are optical, magnetic resonance, and X-ray photoelectron spectroscopy, which give direct evidence for the presence of adsorbed species. These methods currently are under development for application to soils extensive calibration with well-characterized, reference soil minerals. Until this calibration is completed, it is possible to use kinetics data to make an operational distinction between adsorption and precipitation. This strictly empirical method of analyzing sorption data can be illustrated with the important case of o-phosphate reactions. 

To model chemical production processes, time series methods are used. Theoretical and empirical indications are given that this class of models is able to capture the characteristic short-term time-dependency patterns of physical and chemical transformation processes. Simultaneously, the models complexity is kept at an acceptable level. To model the change of production modes of chemical production plants in the long run, Markov chains are used. The application of these models is illustrated by real-world case studies. 

Note that this approach is in principle not restricted to the domain of aviation. In fact, it is completely domain-independent, as long as it is applied to systems that consists of multiple interacting agents, and of which it is possible to obtain empirical data in the form of scenario descriptions. Nevertheless, the main purpose of the current paper is to smdy the applicability of this approach to the domain of aviation. Hence, in the remainder of the paper, the 7 steps are illustrated by means of the mnway incursion case smdy. 

The thermodynamic implications of reactions in the liquid state are important. Let us consider the case where a gas, liquid, or solid is dissolved in a solvent, and the products also remain in solution (i.e., the reaction occurs in the liquid phase). The method illustrated in the previous example is applicable to such cases. Because all of these involve energy changes associated with condensation, as well as dissolution and mixing with solvents, they are far more complicated than reactions in the gaseous state. As will be emphasized in the following discussion, the formal thermodynamic approach fails to give predictive correlations for such cases, and resort to empirical combinations of the microscopic effects of solvents with the formal macroscopic approach becomes necessary. 

As illustrated in Fig. 1, there are essentially four methods for obtaining thermochemical data for the species in our reaction mechanism. The first choice is to find the needed data in databases or in the literature in general. This includes both published experimental data and published quantum chemical calculations, which can also be a reliable source of thermochemical data. If no information on a substance is available in the literature, one should consider whether it can be treated by group additivity methods. If a well-constructed group additivity method is available for the class of molecules of interest, the results, which can be obtained with minimal effort, will be comparable in accuracy to those from the best quantum chemistry calculations. If group additivity is not applicable to the molecules of interest, then we may want to carry out quantum chemistry calculations for them, as discussed in detail in an earlier chapter. In some cases, the effort required to carry out the quantum chemical calculations may not be warranted, and we may want to make coarser, empirical estimates of thermochemical properties. 

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