Model Framework Overview

Although in the open literature few works have dealt with FBMRs from an experimental point of view, many researchers have addressed their efforts toward the con-stmction of an accurate modeling framework for this technology. Therefore, in the next paragraph, an overview on FBMR and PBMR modeling is given. 

In addition, the chapter will provide an overview of htunan reliability quantification techniques, and the relationship between these techniques and qualitative modeling. The chapter will also describe how human reliability is integrated into chemical process quantitative risk assessment (CPQRA). Both qualitative and quantitative techniques will be integrated within a framework called SPEAR (System for Predictive Error Analysis and Reduction). 

This chapter has provided an overview of a recommended framework for the assessment of human error in chemical process risk assessments. The main emphasis has been on the importance of a systematic approach to the qualitative modeling of human error. This leads to the identification and possible reduction of the human sources of risk. This process is of considerable value in its own right, and does not necessarily have to be accompanied by the quantification of error probabilities. 

A generic overview of the main building blocks of models and the framework of logic connecting the components. 

In this chapter we have provided an overview of mathematical modeling from inception of design through specification of solution method, production of solution, and analysis of results. Additionally, we have provided a framework for including computers, particularly current and emerging application software, as vital agents in the modeling process. 

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). 

The advantages of this approach are manifold. The breakdown into small models makes it easier to validate each individual facet, to overview its role in the total metabolism, and to relate it to more complex frameworks. It also becomes possible to combine different facets to model new scenarios and to predict the outcome of new experimental setups. The approach is also valuable in demonstrating how a biosimulation model can be created via a quantitative argumentation based on experimental results. 

In the previous chapters the purposes of near miss reporting have been outlined and a framework of designing such a safety management tool has been presented. The importance of human behaviour as a dominant factor in incident sequences was stressed by developing a system failure classification scheme largely based on a theoretical model of operator behaviour. Also an overview was given of the organisational factors necessary for a successful implementation of a NMMS. 

I expect that SA of stochastic and multiscale models will be important in traditional tasks such as the identification of rate-determining steps and parameter estimation. I propose that SA will also be a key tool in controlling errors in information passing between scales. For example, within a multiscale framework, one could identify what features of a coarse-level model are affected from a finer scale model and need higher-level theory to improve accuracy of the overall multiscale simulation. Next a brief overview of SA for deterministic systems is given followed by recent work on SA of stochastic and multiscale systems. 

The overwhelming majority of the theoretical studies were performed on cluster models of the catalytic site, hi spite of the fact that the role of space confinement and the secondary interactions with the framework atoms is well-known, there are only a few electronic structure calculations on lattice models involving hydrocarbons, using either periodic DFT calculations, or embedding methods. In this brief account of the subject we attempt to overview some of the recent computational results of the literature and present some new data obtained from ab initio DFT pseudopotential plane wave calculations on Cl - C4 alkanes in the chabazite framework. 

Until 10 to 15 years ago the combined approach of macromixing and micromixing models was very widely used in the field of CRE but gradually CFD-based strategies have replaced the first mentioned strategy. In this respect it should be noted that this change also introduced big conceptual differences because the traditional CRE approach is usually formulated in the age space of fluid parcels whereas in CFD approaches a Eulerian framework is often adopted. Subsequently a brief overview of CFD-based approaches for reacting flows is presented and the current limitations are also indicated. 

Figure 1 Overview of the framework definition of design stages and appropriate modeling approaehes as well as evaluation indicators for each stage.

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