Advanced occupant behavioural features of the building-EXODUS evacuation model

The purpose of this paper is to describe and demonstrate some of the advanced behavioral features currently being developed for the building-EXODUS evacuation model. These advanced features involve the ability to specify roles for particular individuals during the evacuation. With these enhancements to the Behavioral Sub model of building-EXODUS, it is possible to include a number of procedural and behavioral aspects previously ignored in evacuation simulations. These include the behavioral aspect of group bonding, the procedural aspects involved with the role of the fire warden and rescue operations undertaken by the fire services. The importance of these enhancements are discussed and demonstrated through three simple simulations.

The centrality of groups and classes

This paper extends the standard network centrality measures of degree, closeness and betweenness to apply to groups and classes as well as individuals. The group centrality measures will enable researchers to answer such questions as ‘how central is the engineering department in the informal influence network of this company?’ or ‘among middle managers in a given organization, which are more central, the men or the women?’ With these measures we can also solve the inverse problem: given the network of ties among organization members, how can we form a team that is maximally central? The measures are illustrated using two classic network data sets. We also formalize a measure of group centrality efficiency, which indicates the extent to which a group's centrality is principally due to a small subset of its members.

Breast milk levels of zinc and omega-6 polyunsaturated fatty acids and growth of healthy Chinese infants

AIM: To examine the concentrations of zinc and omega-6 polyunsaturated fatty acids (omega-6 PUFAs) in breast milk, the impact of zinc on omega-6 PUFA metabolism, and the growth rate of infants. METHODS: Forty-one mother-term infant pairs from a rural area of northern Beijing, China, who were 1 month (n = 18, group I) and 3 months (n = 23, group II) old and exclusively breastfed, were studied. The dietary records and the concentrations of zinc and omega-6 PUFAs in the milk of lactating women and the increase in weight and length of their infants during 1 and 3 postnatal months were analysed. RESULTS: The dietary intakes of mothers in the two groups were the same, i.e. high in carbohydrate and low in fat, protein and energy. The maternal zinc intake was 7.5mg/d and thus reached only 34.6% of the current Recommended Nutrient Intake (RNI). The levels of zinc and arachidonic acid (AA, C20:4 omega-6) in the milk of group I were significantly higher than those in group II. Furthermore, significant positive correlations were found between the concentrations of zinc and AA in the breast milk and between the level of milk AA and weight gain. CONCLUSION: Zinc may be a co-factor and essential for essential fatty acids (EFA) metabolism. Thus suboptimal zinc intake may cause EFA imbalance. Further studies of Chinese rural mother-infant pairs are necessary to determine whether zinc supplementation should be recommended when lactation exceeds 3 months.

Advanced occupant behavioural features of the building - Exodus evacuation model

The purpose of this paper is to describe and demonstrate some of the advanced behavioural features currently being developed for the building-EXODUS evacuation model. These advanced features involve the ability to specify roles for particular individuals during the evacuation. With these enhancements to the Behavioural Submodel of building-EXODUS, it is possible to include a number of procedural and behavioural aspects previously ignored in evacuation simulations. These include the behavioural aspect of group bonding, the procedural aspects involved with the role of the fire warden and rescue operations undertaken by the fire services. The importance of these enhancements are discussed and demonstrated through three simple simulations.

Enhancing the numerical performance of fire field models (CMS Paper)

This paper describes two new techniques designed to enhance the performance of fire field modelling software. The two techniques are "group solvers" and automated dynamic control of the solution process, both of which are currently under development within the SMARTFIRE Computational Fluid Dynamics environment. The "group solver" is a derivation of common solver techniques used to obtain numerical solutions to the algebraic equations associated with fire field modelling. The purpose of "group solvers" is to reduce the computational overheads associated with traditional numerical solvers typically used in fire field modelling applications. In an example, discussed in this paper, the group solver is shown to provide a 37% saving in computational time compared with a traditional solver. The second technique is the automated dynamic control of the solution process, which is achieved through the use of artificial intelligence techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxation using an integrated production rule engine with a blackboard to monitor and implement the required control changes during solution processing. Initial results for a two-dimensional fire simulation are presented that demonstrate the potential for considerable savings in simulation run-times when compared with control sets from various sources. Furthermore, the results demonstrate the potential for enhanced solution reliability due to obtaining acceptable convergence within each time step, unlike some of the comparison simulations.

SMARTFIRE: an integrated computational fluid dynamics code and expert system for fire field modelling

SMARTFIRE, an open architecture integrated CFD code and knowledge based system attempts to make fire field modeling accessible to non-experts in Computational Fluid Dynamics (CFD) such as fire fighters, architects and fire safety engineers. This is achieved by embedding expert knowledge into CFD software. This enables the 'black-art' associated with the CFD analysis such as selection of solvers, relaxation parameters, convergence criteria, time steps, grid and boundary condition specification to be guided by expert advice from the software. The user is however given the option of overriding these decisions, thus retaining ultimate control. SMARTFIRE also makes use of recent developments in CFD technology such as unstructured meshes and group solvers in order to make the CFD analysis more efficient. This paper describes the incorporation within SMARTFIRE of the expert fire modeling knowledge required for automatic problem setup and mesh generation as well as the concept and use of group solvers for automatic and manual dynamic control of the CFD code.

Two-machine shop scheduling: Compromise between flexibility and makespan value

In this paper, we consider the problem of providing flexibility to solutions of two-machine shop scheduling problems. We use the concept of group-scheduling to characterize a whole set of schedules so as to provide more choice to the decision-maker at any decision point. A group-schedule is a sequence of groups of permutable operations defined on each machine where each group is such that any permutation of the operations inside the group leads to a feasible schedule. Flexibility of a solution and its makespan are often conflicting, thus we search for a compromise between a low number of groups and a small value of makespan. We resolve the complexity status of the relevant problems for the two-machine flow shop, job shop and open shop. A number of approximation algorithms are developed and their worst-case performance is analyzed. For the flow shop, an effective heuristic algorithm is proposed and the results of computational experiments are reported.

An improved approximation algorithm for the two-machine open shop scheduling problem with family setup times

We consider the problem of scheduling families of jobs in a two-machine open shop so as to minimize the makespan. The jobs of each family can be partitioned into batches and a family setup time on each machine is required before the first job is processed, and when a machine switches from processing a job of some family to a job of another family. For this NP-hard problem the literature contains (5/4)-approximation algorithms that cannot be improved on using the class of group technology algorithms in which each family is kept as a single batch. We demonstrate that there is no advantage in splitting a family more than once. We present an algorithm that splits one family at most once on a machine and delivers a worst-case performance ratio of 6/5.