Process-Specific Models

As mentioned earlier, the common feature of these models is that they look at MIC as a whole without particularly focusing on a given type of microorganism/macroorganism. In this respect, they tend to be more generalized in their universe of discourse in the sense that MIC is taken as a possibility among other corrosion processes and factors that can happen in a system. 

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There have been many attempts to explain MIC in terms of models. We will look at just some of them, reminding the readers that more can be found in the references of the works that are quoted here. The models about MIC can be grouped into two categories those that try to explain MIC in terms of involvement of a certain species of bacteria, mainly SRB (bacteria-specific models), and those that try to encompass the MIC phenomenon as a whole and explain—as well as predict—it (process-specific models). 

A second way of dealing with the relationship between aj and the experimental concentration requires the use of a statistical model. We assume that the system consists of Nj molecules of type 1 and N2 molecules of type 2. In addition, it is assumed that the molecules, while distinguishable, are identical to one another in size and interaction energy. That is, we can replace a molecule of type 1 in the mixture by one of type 2 and both AV and AH are zero for the process. Now we consider the placement of these molecules in the Nj + N2 = N sites of a three-dimensional lattice. The total number of arrangements of the N molecules is given by N , but since interchanging any of the I s or 2 s makes no difference, we divide by the number of ways of doing the latter—Ni and N2 , respectively—to obtain the total number of different ways the system can come about. This is called the thermodynamic probabilty 2 of the system, and we saw in Sec. 3.3 that 2 is the basis for the statistical calculation of entropy. For this specific model... 

The first is the relational model. Examples are hnear (i.e., models linear in the parameters and neural network models). The model output is related to the input and specifications using empirical relations bearing no physical relation to the actual chemical process. These models give trends in the output as the input and specifications change. Actual unit performance and model predictions may not be very close. Relational models are usebil as interpolating tools. 

The accuracy of QRA results is also dependent on the analysis resources. Obviously, more complete QRA models can produce more accurate results. But even the best model is worthless if the input data are speculative or erroneous. Fortunately, the scarcity of process-specific data for some applications may not be an insurmountable problem. There exist a few industrywide databases, such as those in Table 2, that... 

In its simplest form, a model requires two types of data inputs information on the source or sources including pollutant emission rate, and meteorological data such as wind velocity and turbulence. The model then simulates mathematically the pollutant s transport and dispersion, and perhaps its chemical and physical transformations and removal processes. The model output is air pollutant concentration for a particular time period, usually at specific receptor locations. 

Of these, the most extensive use is to identify adsorbed molecules and molecular intermediates on metal single-crystal surfaces. On these well-defined surfaces, a wealth of information can be gained about adlayers, including the nature of the surface chemical bond, molecular structural determination and geometrical orientation, evidence for surface-site specificity, and lateral (adsorbate-adsorbate) interactions. Adsorption and reaction processes in model studies relevant to heterogeneous catalysis, materials science, electrochemistry, and microelectronics device failure and fabrication have been studied by this technique. 

What Is the Expected Process for Their Work. This requires a clear presentation of the approach (TQM, process redesign, model programs, other), which will to some extent dictate the working process. In addition, specifics about team leadership, the role (if any) of facilitators or advisors. 

It has been proposed " that the mechanism(s) of action of gymnemic acids and ziziphins is a biphasic, model-membrane penetration-process. The model suggested that the modifier molecules interact first with the receptor-cell plasma-membrane surface. It was postulated that this initial interaction involves a selective effect on taste perception, including the transduction and quality specification of the sweet stimuli, and selective depression of sweetness perception. Following the initial interaction, the modifier molecules interact with the membrane-lipid interior to produce a general disruption of membrane function and a nonselective effect on taste... 

The goal of this paper Is to present the current status of model validation and field testing of chemical fate and transport models other papers in this symposium discuss the state-of-the-art of modeling specific processes, environments, and multimedia problems. The process of model validation, and its various components, is described considerations in field testing, where model results are compared to field observations, are discussedp an assessment of the current extent of field testing for various processes and media is presented and future field testing and data needs are enumerated. 

The research and application of improvement in energy efficiency at the turret level is highly process specific and therefore less appropriate to general application. As a reflection of this, less research has been published at this level. Most research is evaluative with little scope provided for developing models. Consequently, only a few examples reviewed here are used in further analysis in this chapter. 

The computational results for the case studies allow the comparison and study of the efficiency and limitations of specific modeling approaches. However, it is worth mentioning that problem data involves only integer processing times, which represents a fortunate situation for discrete time models since no special provisions... 

The distribution of charges on an adsorbate is important in several respects It indicates the nature of the adsorption bond, whether it is mainly ionic or covalent, and it affects the dipole potential at the interface. Therefore, a fundamental problem of classical electrochemistry is What does the current associated with an adsorption reaction tell us about the charge distribution in the adsorption bond In this chapter we will elaborate this problem, which we have already touched upon in Chapter 4. However, ultimately the answer is a little disappointing All the quantities that can be measured do not refer to an individual adsorption bond, but involve also the reorientation of solvent molecules and the distribution of the electrostatic potential at the interface. This is not surprising after all, the current is a macroscopic quantity, which is determined by all rearrangement processes at the interface. An interpretation in terms of microscopic quantities can only be based on a specific model. 

Specifications, models, and designs built with the three preceding constructs all show recurring patterns. The collaborations for processing an order for a book at an on-line bookstore and for accepting a request to schedule a seminar are also similar in structure—a generic collaboration. 

The process of modeling and designing is recursive throughout business, component specification, and internal design. Similarly, specification and implementation activities are also recursive across the business or domain model, component spec, and internal design. 

Commodity-related models focus on demand volatility and uncertainty in volumes and prices as with sales quantity flexibility. Several authors proposed models to handle demand uncertainty in general focusing on quantities (Cheng et al. 2003 Gupta/Maranas 2003 Cheng et al. 2004 Chen/Lee 2004). Uncertainty is reflected by demand quantity scenarios and/or probabilities. Proposed models maximize expected or robust profit. Process industry-specific models use simulation to address demand uncertainty and to determine optimal inventory levels (Jung et al. 2004). 

The case study demonstrated how the company can use the developed model in decision support. Having implementing the global value chain planning process and model the company could significantly improve overall profitability of the business. Specifically, the spot price mechanism used to better coordinate sales and supply decisions showed a significant impact for the company. 

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