Generic modeling approach

As a generic modeling approach, the developed R MM system needs to satisfy the requirements in different industrial areas. As well, the reliability assessment and relative maintenance decisionmaking need to be interpretable and accurate sufficiently. The ability and success of the developed R MM system can be proved by the study of two appUcation cases. 

In the following sections, thermodynamic models, kinetic models, and CFD approaches for gasification modeling are introduced. Basic equations and scientific background are explained as far as necessary for understanding. Chapter 5 ends with a description of the generic modeling approach that is used in Chapter 6 and discusses the sensitivity of selected models to the applied boundary conditions. 

From the theoretical perspective, the need to assess the nature of the Coulom-bic phase transition has led to many activities. Thus, most theories have relied on the RPM as a generic model for the ionic phase transition. From the various theoretical tools for deriving the EOS, only MSA- and DH-based approaches have found wide application. Applications of the HNC, which is a standard theory in general electrolyte thermodynamics, have remained scarce because of numerical problems when approaching phase transitions. However, pure DH and MSA theory are linear theories that fail at low T. It is known for a long time that, at least in parts, this failure can be remedied by accounting for ion pair formation. More recently, it has become clear that at near- and subcritical temperatures, free-ion-ion-pair and ion-pair-ion-pair interactions play a crucial role. Just in this regard, DH theory seems to provide a particularly flexible and transparent scheme for such theoretical extensions. 

It appears from the above that microcosm and/or mesocosm tests are limited by the constraints of experimentation, in that usually only a limited number of recovery scenarios can be investigated. Consequently, modeling approaches may provide an alternative tool for investigating likely recovery rates under a range of conditions. Generic models, like the logistic growth mode (for example, see Barnthouse 2004) and life history and individual-based (meta)population models, which also may be spatially explicit, provide mathematical frameworks that offer the opportunity to explore the recovery potential of individual populations. For an overview of these life history and individual-based models, see Bartell et al. (2003) and Pastorok et al. (2003). 

Tier-1 A simple generic approach. In this case, the uncertainties encountered in the assessment are captured by a UF, or by a simple generic model. When used in a deterministic way, the UF increases or decreases according to estimated uncertainties in the data. The following values for UFs are frequently encountered ... 

The approach used is that outlined by Dodd B. and Humphries L.L., (1988) although significant input was also obtained from IAEA Safety Series No. 57, Generic Models and Parameters for Assessing the Environmental Transfer of Radionuclides from Routine Releases Exposures of Critical Groups (1982). 

Class variable is a subclass of the basic class generic-variable. From the class variable emanates the tree of subclasses, a partial view of which is shown in Fig. 19. Unlike other modeling approaches, MODEL.LA. does not represent variables through their values alone, but it provides an extensive structure that includes many additional attributes in the description of a variable. The additional attributes allow MODEL. LA. to reason about these variables and not just acquire their values. Thus, a set of methods in the class variable allow any of the subclasses to monitor their values, react with predefined procedures when the value of the variable changes, invoke values from external databases, and so on. 

The simplicity of the interatomic forces means that some of the generic features and problems of nanomaterials should be tractable to theoretical and/or computer modeling approaches for these particular systems. 

The organization of the chapter is as follows. Section 12.2 presents our generic model and lists some of the main challenges. Sections 12.3 through 12.5 describe the theoretical approaches, followed by several applications. Section 12.6 discusses recent experimental results. Section 12.7 concludes, presenting some long-term goals. 

In another approach, the micellizatiOTi can be seen as a journey on a multidimensional energy landscape (phase space, i.e., a space spanned by all parameters) towards an equilibrium state that represents a global minimum on the landscape. One can imagine that the most probable path corresponds to the path of minimal energy, which naturally introduces a constraint. Such an approach was recently used by Diamant and coworkers for surfactant micelles [67]. Here, we will briefly review a generic model for block copolymers. 

To take into account the evolution of the living conditions, the generic failure rate A,j that represents the probability density that the component fails to mode k in the interval t,t + dt knowing that it has survived with no failures up to the time t, should be continuously updated to account for its dependence from the evolving IPs. In the proposed modeling approach, Xj is updated at time steps of length at most Dt and then remains constant within the time step. In practice, the duration of the time step must be chosen so as to satisfy the hypothesis. 

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