Agent-based models discussion

In this section we introduce a mobile CA model of land combat called EINSTein, developed at the Center for Naviil Analyses for the US Marine Corps. We include a discussion of this model here becau.se it is an interesting blend of CA-like local dynamics and agent-based modeling techniques. 

This chapter begins with an overview of these three components of the Project De-sign approach. Representation is described as modeling of sociotechnical characteristics include scope, teams, complexity, distribution, coordination as activity, and con-current and mutual dependence. Next, agent-based simulation of the engineering project is described which analyzes realistic outcomes including limits due to technical complexity, human priorities, capacities, interactions, and mistakes. These models and analytics are then shown as they are used in collaborative workshops. Two industrial cases are discussed, followed by a comparison with contemporary approaches and discussion of the benefits of Project Design. 

The same authors also presented an example of the use of the population balance equation (PBE) (distribution of biomass m) coimected to the multi-zone/CFD model. This example is in several respects relevant for the assessment of the modeling approach. The coupling of the integro-differential equation of the population balance is a numerical challenge, which can nowadays be tackled within the environment of a CFD approach, albeit without consensus on the proper closure assumptions. Still, the computational effort for the numerical solution of the population balance embedded in the multizonal model is extensive, and it is difficult to extend this approach to multiple state variables necessary for dynamic metabolic models. This is an important argument to favor the alternative method of an agent-based Lagrange-Euler approach discussed in Section 3.5. 

Flash photolysis techniques were unsuitable for measuring the slow off reactions for the iron(II) model complexes such as Fen(TPPS)(NO), since the experimental uncertainties in the extrapolated intercepts of kohs vs. [NO] plots were larger than the values of the intercepts themselves. When trapping methods were used to evaluate NO labilization from FeII(TPPS)(NO), k(,n values were found to be quite small but were sensitive to the nature of the trapping agents used. Lewis bases that could coordinate the metal center appeared to accelerate NO loss. More reliable estimates for the uncatalyzed off reaction were obtained by using Ru(edta)- as an NO scavenger, and the koS values listed in Table I were obtained in this manner (21c). The small kQ values found for Fe(II) models are consistent with the trend observed for the ferro-heme proteins discussed above. 

Theories of leveling by additives are based on (1) the correlation between an increase in polarization produced by the leveling agents (29) and (2) preferential adsorption of a leveling agent on high points (peaks or flat surfaces) (30). Theories and modeling of superconformal electrodeposition are discussed in Section 19.4. 

---