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.

Safer by design: using computer simulation to predict the evacuation performance of passenger ships

When designing a new passenger ship or modifiying an existing design, how do we ensure that the proposed design is safe from an evacuation point of view? In the building and aviation industries, computer based evacuation models are being used to tackle similar issues. In these industries, the traditonal restrictive prescriptive approach to design is making way for performance based design methodologies using risk assessment and computer simulation. In the maritime industry, ship evacuation models off the promise to quickly and efficiently bring these considerations into the design phase, while the ship is "on the drawing board". This paper describes the development of evacuation models with applications to passenger ships and further discusses issues concerning data requirements and validation.

Dynamic load-balancing of finite element applications with the DRAMA library

The DRAMA library, developed within the European Commission funded (ESPRIT) project DRAMA, supports dynamic load-balancing for parallel (message-passing) mesh-based applications. The target applications are those with dynamic and solution-adaptive features. The focus within the DRAMA project was on finite element simulation codes for structural mechanics. An introduction to the DRAMA library will illustrate that the very general cost model and the interface designed specifically for application requirements provide simplified and effective access to a range of parallel partitioners. The main body of the paper will demonstrate the ability to provide dynamic load-balancing for parallel FEM problems that include: adaptive meshing, re-meshing, the need for multi-phase partitioning.

Load-balancing for mesh-based applications on heterogeneous cluster computers

This paper discusses load-balancing issues when using heterogeneous cluster computers. There is a growing trend towards the use of commodity microprocessor clusters. Although today's microprocessors have reached a theoretical peak performance in the range of one GFLOPS/s, heterogeneous clusters of commodity processors are amongst the most challenging parallel systems to programme efficiently. We will outline an approach for optimising the performance of parallel mesh-based applications for heterogeneous cluster computers and present case studies with the GeoFEM code. The focus is on application cost monitoring and load balancing using the DRAMA library.

Dynamic multi-partitioning for parallel finite element applications

The central product of the DRAMA (Dynamic Re-Allocation of Meshes for parallel Finite Element Applications) project is a library comprising a variety of tools for dynamic re-partitioning of unstructured Finite Element (FE) applications. The input to the DRAMA library is the computational mesh, and corresponding costs, partitioned into sub-domains. The core library functions then perform a parallel computation of a mesh re-allocation that will re-balance the costs based on the DRAMA cost model. We discuss the basic features of this cost model, which allows a general approach to load identification, modelling and imbalance minimisation. Results from crash simulations are presented which show the necessity for multi-phase/multi-constraint partitioning components

On a flexible elimination algorithm with applications to panel element equations

A flexible elimination algorithm is presented and is applied to the solution of dense systems of linear equations. Properties of the algorithm are exploited in relation to panel element methods for potential flow and subsonic compressible flow. Further properties in relation to distributed computing are also discussed.

A robust tri-state election algorithm for scalable applications

Existing election algorithms suffer limited scalability. This limit stems from the communication design which in turn stems from their fundamentally two-state behaviour. This paper presents a new election algorithm specifically designed to be highly scalable in broadcast networks whilst allowing any processing node to become coordinator with initially equal probability. To achieve this, careful attention has been paid to the communication design, and an additional state has been introduced. The design of the tri-state election algorithm has been motivated by the requirements analysis of a major research project to deliver robust scalable distributed applications, including load sharing, in hostile computing environments in which it is common for processing nodes to be rebooted frequently without notice. The new election algorithm is based in-part on a simple 'emergent' design. The science of emergence is of great relevance to developers of distributed applications because it describes how higher-level self-regulatory behaviour can arise from many participants following a small set of simple rules. The tri-state election algorithm is shown to have very low communication complexity in which the number of messages generated remains loosely-bounded regardless of scale for large systems; is highly scalable because nodes in the idle state do not transmit any messages; and because of its self-organising characteristics, is very stable.

Emergence: a paradigm for robust and scalable distributed applications

Natural distributed systems are adaptive, scalable and fault-tolerant. Emergence science describes how higher-level self-regulatory behaviour arises in natural systems from many participants following simple rulesets. Emergence advocates simple communication models, autonomy and independence, enhancing robustness and self-stabilization. High-quality distributed applications such as autonomic systems must satisfy the appropriate nonfunctional requirements which include scalability, efficiency, robustness, low-latency and stability. However the traditional design of distributed applications, especially in terms of the communication strategies employed, can introduce compromises between these characteristics. This paper discusses ways in which emergence science can be applied to distributed computing, avoiding some of the compromises associated with traditionally-designed applications. To demonstrate the effectiveness of this paradigm, an emergent election algorithm is described and its performance evaluated. The design incorporates nondeterministic behaviour. The resulting algorithm has very low communication complexity, and is simultaneously very stable, scalable and robust.

Microwave cure of conductive adhesives for flip-chip & microsystems applications

The curing of conductive adhesives and underfills can save considerable time and offer cost benefits for the microsystems and electronics packaging industry. In contrast to conventional ovens, curing by microwave energy generates heat internally within each individual component of an assembly. The rate at which heat is generated is different for each of the components and depends on the material properties as well as the oven power and frequency. This leads to a very complex and transient thermal state, which is extremely difficult to measure experimentally. Conductive adhesives need to be raised to a minimum temperature to initiate the cross-linking of the resin polymers, whilst some advanced packaging materials currently under investigation impose a maximum temperature constraint to avoid damage. Thermal imagery equipment integrated with the microwave oven can offer some information on the thermal state but such data is based on the surface temperatures. This paper describes computational models that can simulate the internal temperatures within each component of an assembly including the critical region between the chip and substrate. The results obtained demonstrate that due to the small mass of adhesive used in the joints, the temperatures reached are highly dependent on the material properties of the adjacent chip and substrate.

Investigation into the performance of turbulence models for fluid flow and heat transfer phenomena in electronic applications

Computational Fluid Dynamics (CFD) is gradually becoming a powerful and almost essential tool for the design, development and optimization of engineering applications. However the mathematical modelling of the erratic turbulent motion remains the key issue when tackling such flow phenomena. The reliability of CFD analysis depends heavily on the turbulence model employed together with the wall functions implemented. In order to resolve the abrupt changes in the turbulent energy and other parameters situated at near wall regions a particularly fine mesh is necessary which inevitably increases the computer storage and run-time requirements. Turbulence modelling can be considered to be one of the three key elements in CFD. Precise mathematical theories have evolved for the other two key elements, grid generation and algorithm development. The principal objective of turbulence modelling is to enhance computational procedures of efficient accuracy to reproduce the main structures of three dimensional fluid flows. The flow within an electronic system can be characterized as being in a transitional state due to the low velocities and relatively small dimensions encountered. This paper presents simulated CFD results for an investigation into the predictive capability of turbulence models when considering both fluid flow and heat transfer phenomena. Also a new two-layer hybrid kε / kl turbulence model for electronic application areas will be presented which holds the advantages of being cheap in terms of the computational mesh required and is also economical with regards to run-time.

Lifetime assessment of electronic components for high reliability aerospace applications

This paper details a modelling approach for assessing the in-service (field) reliability and thermal fatigue life-time of electronic package interconnects for components used in the assembly of an aerospace system. The Finite Element slice model of a Plastic Ball Grid Array (PBGA) package and suitable energy based damage models for crack length predictions are used in this study. Thermal fatigue damage induced in tin-lead solder joints are investigated by simulating the crack growth process under a set of prescribed field temperature profiles that cover the period of operational life. The overall crack length in the solder joint for all different thermal profiles and number of cycles for each profile is predicted using a superposition technique. The effect of using an underfill is also presented. A procedure for verifying the field lifetime predictions for the electronic package by using reliability assessment under Accelerated Thermal Cycle (ATC) testing is also briefly outlined.

Self-optimising data farming for web applications

Many Web applications walk the thin line between the need for dynamic data and the need to meet user performance expectations. In environments where funds are not available to constantly upgrade hardware inline with user demand, alternative approaches need to be considered. This paper introduces a ‘Data farming’ model whereby dynamic data, which is ‘grown’ in operational applications, is ‘harvested’ and ‘packaged’ for various consumer markets. Like any well managed agricultural operation, crops are harvested according to historical and perceived demand as inferred by a self-optimising process. This approach aims to make enhanced use of available resources through better utlilisation of system downtime - thereby improving application performance and increasing the availability of key business data.

On the persistence of computer dreams: an application framework for robust adaptive deployment

The anticipated rewards of adaptive approaches will only be fully realised when autonomic algorithms can take configuration and deployment decisions that match and exceed those of human engineers. Such decisions are typically characterised as being based on a foundation of experience and knowledge. In humans, these underpinnings are themselves founded on the ashes of failure, the exuberance of courage and (sometimes) the outrageousness of fortune. In this paper we describe an application framework that will allow the incorporation of similarly risky, error prone and downright dangerous software artefacts into live systems – without undermining the certainty of correctness at application level. We achieve this by introducing the notion of application dreaming.

Pseudo-spectral solutions for fluid flow and heat transfer in electro-metallurgical applications

The pseudo-spectral solution method offers a flexible and fast alternative to the more usual finite element/volume/difference methods, particularly when the long-time transient behaviour of a system is of interest. Since the exact solution is obtained at the grid collocation points superior accuracy can be achieved on modest grid resolution. Furthermore, the grid can be freely adapted with time and in space, to particular flow conditions or geometric variations. This is especially advantageous where strongly coupled, time-dependent, multi-physics solutions are investigated. Examples include metallurgical applications involving the interaction of electromagnetic fields and conducting liquids with a free sutface. The electromagnetic field then determines the instantaneous liquid volume shape and the liquid shape affects in turn the electromagnetic field. In AC applications a thin "skin effect" region results on the free surface that dominates grid requirements. Infinitesimally thin boundary cells can be introduced using Chebyshev polynomial expansions without detriment to the numerical accuracy. This paper presents a general methodology of the pseudo-spectral approach and outlines the solution procedures used. Several instructive example applications are given: the aluminium electrolysis MHD problem, induction melting and stirring and the dynamics of magnetically levitated droplets in AC and DC fields. Comparisons to available analytical solutions and to experimental measurements will be discussed.

Support vector machines for regression and applications to software quality prediction

Software metrics are the key tool in software quality management. In this paper, we propose to use support vector machines for regression applied to software metrics to predict software quality. In experiments we compare this method with other regression techniques such as Multivariate Linear Regression, Conjunctive Rule and Locally Weighted Regression. Results on benchmark dataset MIS, using mean absolute error, and correlation coefficient as regression performance measures, indicate that support vector machines regression is a promising technique for software quality prediction. In addition, our investigation of PCA based metrics extraction shows that using the first few Principal Components (PC) we can still get relatively good performance.