The introduction of social adaptation within evacuation modelling

In recent history, a number of tragic events have borne a consistent message; the social structures that existed prior to and during the evacuation significantly affected the decisions made and the actions adopted by the evacuating population in response to the emergency. This type of influence over behaviour has long been neglected in the modelling community. This paper is an attempt to introduce some of these considerations into evacuation models and to demonstrate their impact. To represent this type of behaviour within evacuation models a mechanism to represent the membership and position within social hierarchies is established. In addition, individuals within the social groupings are given the capacity to communicate relevant pieces of data such as the need to evacuate—impacting the response time—and the location of viable exits—impacting route selection. Furthermore, the perception and response to this information is also affected by the social circumstances in which individuals find themselves. Copyright © 2005 John Wiley & Sons, Ltd.

Implementation of cognitive mapping, spatial representation and wayfinding behaviours of people within evacuation modelling tools

Within the building evacuation context, wayfinding describes the process in which an individual located within an arbitrarily complex enclosure attempts to find a path which leads them to relative safety, usually the exterior of the enclosure. Within most evacuation modelling tools, wayfinding is completely ignored; agents are either assigned the shortest distance path or use a potential field to find the shortest path to the exits. In this paper a novel wayfinding technique that attempts to represent the manner in which people wayfind within structures is introduced and demonstrated through two examples. The first step is to encode the spatial information of the enclosure in terms of a graph. The second step is to apply search algorithms to the graph to find possible routes to the destination and assign a cost to the routes based on their personal route preferences such as "least time" or "least distance" or a combination of criteria. The third step is the route execution and refinement. In this step, the agent moves along the chosen route and reassesses the route at regular intervals and may decide to take an alternative path if the agent determines that an alternate route is more favourable e.g. initial path is highly congested or is blocked due to fire.

Evacuation modelling analysis within the operational research context: a combined approach for improving enclosure designs

Evacuation models have been playing an important function in the transition process from prescriptive fire safety codes to performance-based ones over the last three decades. In fact, such models became also useful tools in different tasks within fire safety engineering field, such as fire risks assessment and fire investigation. However, there are some difficulties in this process when using these models. For instance, during the evacuation modelling analysis, a common problem faced by fire safety engineers concerns the number of simulations which needs to be performed. In other terms, which fire designs (i.e., scenarios) should be investigated using the evacuation models? This type of question becomes more complex when specific issues such as the optimal positioning of exits within an arbitrarily structure needs to be addressed. Therefore, this paper presents a methodology which combines the use of evacuation models with numerical techniques used in the operational research field, such as Design of Experiments (DoE), Response Surface Models (RSM) and the numerical optimisation techniques. The methodology here presented is restricted to evacuation modelling analysis, nevertheless this same concept can be extended to fire modelling analysis.

Computer modelling of human behaviour in aircraft fire accidents

The mathematical simulation of the evacuation process has a wide and largely untapped scope of application within the aircraft industry. The function of the mathematical model is to provide insight into complex behaviour by allowing designers, legislators, and investigators to ask ‘what if’ questions. Such a model, EXODUS, is currently under development, and this paper describes its evolution and potential applications. EXODUS is an egress model designed to simulate the evacuation of large numbers of individuals from an enclosure, such as an aircraft. The model tracks the trajectory of each individual as they make their way out of the enclosure or are overcome by fire hazards, such as heat and toxic gases. The software is expert system-based, the progressive motion and behaviour of each individual being determined by a set of heuristics or rules. EXODUS comprises five core interacting components: (i) the Movement Submodel — controls the physical movement of individual passengers from their current position to the most suitable neighbouring location; (ii) the Behaviour Submodel — determines an individual's response to the current prevailing situation; (iii) the Passenger Submodel — describes an individual as a collection of 22 defining attributes and variables; (iv) the Hazard Submodel — controls the atmospheric and physical environment; and (v) the Toxicity Submodel — determines the effects on an individual exposed to the fire products, heat, and narcotic gases through the Fractional Effective Dose calculations. These components are briefly described and their capabilities and limitations are demonstrated through comparison with experimental data and several hypothetical evacuation scenarios.

A multi-scale atomistic-continuum modelling of crack propagation in a two-dimensional macroscopic plate

A novel multi-scale seamless model of brittle-crack propagation is proposed and applied to the simulation of fracture growth in a two-dimensional Ag plate with macroscopic dimensions. The model represents the crack propagation at the macroscopic scale as the drift-diffusion motion of the crack tip alone. The diffusive motion is associated with the crack-tip coordinates in the position space, and reflects the oscillations observed in the crack velocity following its critical value. The model couples the crack dynamics at the macroscales and nanoscales via an intermediate mesoscale continuum. The finite-element method is employed to make the transition from the macroscale to the nanoscale by computing the continuum-based displacements of the atoms at the boundary of an atomic lattice embedded within the plate and surrounding the tip. Molecular dynamics (MD) simulation then drives the crack tip forward, producing the tip critical velocity and its diffusion constant. These are then used in the Ito stochastic calculus to make the reverse transition from the nanoscale back to the macroscale. The MD-level modelling is based on the use of a many-body potential. The model successfully reproduces the crack-velocity oscillations, roughening transitions of the crack surfaces, as well as the macroscopic crack trajectory. The implications for a 3-D modelling are discussed.

The numerical simulation of the noncharring pyrolysis process and fire development within a compartment

A pyrolysis model for noncharring solid fuels is presented in this paper. Model predictions are compared with experimental data for the mass loss rates of polymethylmethacrylate (PMMA) and very good agreement is achieved. Using a three-dimensional CFD environment, the pyrolysis model is then coupled with a gas-phase combustion model and a thermal radiation model to simulate fire development within a small compartment. The numerical predictions produced by this coupled model are found to be in very good agreement with experimental data. Furthermore, numerical predictions of the relationship between the air entrained into the fire compartment and the ventilation factor produce a characteristic post-flashover linear correlation with constant of proportionality 0.38 kg/sm5=2. The simulation results also suggest that the model is capable of predicting the onset of "flashover" and "post-flashover" type behaviour within the fire compartment.

Fire field modelling using the SMARTFIRE automated dynamic solution control environment

SMARTFIRE is a fire field model based on an open architecture integrated CFD code and knowledge-based system. It makes use of the expert system to assist the user in setting up the problem specification and new computational techniques such as Group Solvers to reduce the computational effort involved in solving the equations. This paper concentrates on recent research into the use of artificial intelligence techniques to assist in dynamic solution control of fire scenarios being simulated using fire field modelling techniques. This is designed to improve the convergence capabilities of the software while further decreasing the computational overheads. The technique automatically controls solver relaxations 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 enhanced solution reliability due to obtaining acceptable convergence within each time step unlike some of the comparison simulations.

A review of the methodologies used in evacuation modelling

Computer based analysis of evacuation can be performed using one of three different approaches, namely optimization, simulation and risk assessment. Furthermore, within each approach different means of representing the enclosure, the population and the behaviour of the population are possible. The myriad of approaches that are available has led to the development of some 22 different evacuation models. This review attempts to describe each of the modelling approaches adopted and critically review the inherent capabilities of each approach. The review is based on available published literature.

Multiphysics modelling for electronics design

The future of many companies will depend to a large extent on their ability to initiate techniques that bring schedules, performance, tests, support, production, life-cycle-costs, reliability prediction and quality control into the earliest stages of the product creation process. Important questions for an engineer who is responsible for the quality of electronic parts such as printed circuit boards (PCBs) during design, production, assembly and after-sales support are: What is the impact of temperature? What is the impact of this temperature on the stress produced in the components? What is the electromagnetic compatibility (EMC) associated with such a design? At present, thermal, stress and EMC calculations are undertaken using different software tools that each require model build and meshing. This leads to a large investment in time, and hence cost, to undertake each of these simulations. This paper discusses the progression towards a fully integrated software environment, based on a common data model and user interface, having the capability to predict temperature, stress and EMC fields in a coupled manner. Such a modelling environment used early within the design stage of an electronic product will provide engineers with fast solutions to questions regarding thermal, stress and EMC issues. The paper concentrates on recent developments in creating such an integrated modeling environment with preliminary results from the analyses conducted. Further research into the thermal and stress related aspects of the paper is being conducted under a nationally funded project, while their application in reliability prediction will be addressed in a new European project called PROFIT.

Magnetic modelling and magneto-hydro-dynamic simulations of an aluminium production electrolytic cell

A simulation of the motion of molten aluminium inside an electrolytic cell is presented. Since the driving term of the aluminium motion is the Lorentz (j × B) body force acting within the fluid,this problem involves the solution of the magneto-hydro-dynamic equations. Different solver modules for the magnetic field computation and for the fluid motion simulation are coupled together. The interactions of all these are presented and discussed.

Distributed belief revision as applied within a descriptive model of jury deliberations

Belief revision is a well-research topic within AI. We argue that the new model of distributed belief revision as discussed here is suitable for general modelling of judicial decision making, along with extant approach as known from jury research. The new approach to belief revision is of general interest, whenever attitudes to information are to be simulated within a multi-agent environment with agents holding local beliefs yet by interaction with, and influencing, other agents who are deliberating collectively. In the approach proposed, it's the entire group of agents, not an external supervisor, who integrate the different opinions. This is achieved through an election mechanism, The principle of "priority to the incoming information" as known from AI models of belief revision are problematic, when applied to factfinding by a jury. The present approach incorporates a computable model for local belief revision, such that a principle of recoverability is adopted. By this principle, any previously held belief must belong to the current cognitive state if consistent with it. For the purposes of jury simulation such a model calls for refinement. Yet we claim, it constitutes a valid basis for an open system where other AI functionalities (or outer stiumuli) could attempt to handle other aspects of the deliberation which are more specifi to legal narrative, to argumentation in court, and then to the debate among the jurors.

Modelling occupant interaction with fire conditions using the buildingEXODUS evacuation model

When evacuating through fire environments, the presence of smoke may not only have a physiological impact on the evacuees but may also lead occupants to adapt their evacuation strategy through the adoption of another exit. This paper attempts to introduce this type of adaptive behaviour within the buildingEXODUS evacuation model through enabling occupants to make decisions concerning the selection of the most viable available exit during an evacuation involving fire. The development of this adaptive behaviour requires the introduction of several new capabilities namely, the representation of the occupants’ familiarity with the structure, the behaviour of an occupant that is engulfed in smoke and the behaviour of an occupant that is faced with a smoke barrier. The appropriateness of the redirection decision is dependent upon behavioural data gathered from real fire incidents (in the UK and USA) that is used to construct the redirection probabilities. The implementation is shown to provide a more complex and arguably more realistic representation of this behaviour than that provided previously.

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.

Fitting host-parasitoid models with CV² > 1 using hierarchical generalized linear models

The powerful general Pacala-Hassell host-parasitoid model for a patchy environment, which allows host density–dependent heterogeneity (HDD) to be distinguished from between-patch, host density–independent heterogeneity (HDI), is reformulated within the class of the generalized linear model (GLM) family. This improves accessibility through the provision of general software within well–known statistical systems, and allows a rich variety of models to be formulated. Covariates such as age class, host density and abiotic factors may be included easily. For the case where there is no HDI, the formulation is a simple GLM. When there is HDI in addition to HDD, the formulation is a hierarchical generalized linear model. Two forms of HDI model are considered, both with between-patch variability: one has binomial variation within patches and one has extra-binomial, overdispersed variation within patches. Examples are given demonstrating parameter estimation with standard errors, and hypothesis testing. For one example given, the extra-binomial component of the HDI heterogeneity in parasitism is itself shown to be strongly density dependent.