Simulation modelling of spatial problems

The thesis presents a simulation modelling strategy for spatial problems which uses a data structure based on spatial relationships. Using this network based approach, two domain specific data-driven models are developed in which the movement of people is modelled as a quasi-continuous process. The development of simulation modelling technology is examined to find reasons why there should be a reluctance to use the technique. With particular reference to problems which are spatially related, the established simulation modelling techniques, together with their diagrammatic representations, are evaluated for their helpfulness at the model building stage. Using a specimen example, it is demonstrated that the commonly used approaches for digital discrete event simulation, which use a procedural paradigm, give little help with problems which involve the allocation of a resource and have spatial constraints. Two domain specific generic models are demonstrated which adopt an object-oriented approach, for which the model description, including the logical constraints, are given in the data-file. A method for modelling the movement of people at different levels of congestion as a quasi-continuous process is validated using results from reported surveys of people's movement rates and direct observations, and this is applied in both models. The first models the emergency evacuation of a building, using a graph structure to represent the spatial components. This is implemented using object-oriented code and test runs are compared with evacuation times from a building at the University of North London. The second provides an experimental tool for comparing the effect upon ward function of different layouts and was influenced by a published survey of a nurse activity analysis carried out in fourteen different wards. The nurse activity model uses two graph structures and an object class to model the nurses who move, with reference to, and informed by, the spatial graph structure. The successful application of the method in the two problem domains confirms its potential usefulness for spatial problems

Application of Risk Analysis and Simulation for Nuclear Refurbishment Projects

In this thesis, a planning methodology is proposed for nuclear refurbishment projects as a means to address project objectives, influential factors, constraints, and their interdependencies to attain a more reliable estimate of project outcomes. As part of this process, the uncertainty and impact of risk events around project outcomes are taken into account. The proposed methodology consists of two stages. The first stage addresses the impact of commonly identified risks (i.e., Type I risks) and uncertainty on the project outcomes. Also, the interdependence among shift schedule, productivity rate, calendar duration, and risk registers within each identified what-if scenario has been taken into account. The confidence in achieving each of the what-if scenarios is determined using Monte Carlo simulation and a 3-dimensional joint confidence limit model. Based on the simulation results, the deterministic values of the selected project outcomes and the mean values of the resultant distributions are driven primarily by uncertainty, and the distribution tails represent the impact of materialized risks. Also, the probability of failure for each project outcome is less than the joint probability of failure for multiple outcomes. In the second stage of the methodology, the resultant distribution tails (attained from the previous stage) are explored by primarily assessing the impact of outliers (i.e., Type II risks) on project outcomes. Although outliers are typically considered rare events with extreme impacts, the scale and complexity of megaprojects such as refurbishment of nuclear reactors leads to a more frequent occurrence of such events. The applied methodology stems from the reliability analysis approach used to partially justify soft error within integrated circuits due to the observed commonalities such as scale and complexity. A combination of probability theory, Critical Path Method, and Monte Carlo simulation is used to assess the true probability of occurrence for such events. Based on the simulation results, the outliers should be acknowledged and incorporated in the risk management plan of large-scale and complex ventures such as megaprojects. The proposed methodology is validated via Delphi and sensitivity analysis, and functional demonstration using information from an actual multi-billion dollar nuclear refurbishment project and a unique full-scale mock-up of the reactor’s fuel channels and feeders

Toward composing variable structure models and their interfaces: a case of intensional coupling definitions

In this thesis, we investigate a combination of traditional component-based and variable structure modeling. The focus is on a structural consistent specification of couplings in modular, hierarchical models with a variable structure. For this, we exploitintensional definitions, as known from logic, and introduce a novel intensional coupling definition, which allows a concise yet expressive specification of complex communication and interaction patterns in static as well as variable structure models, without the need to worryabout structural consistency.In der Arbeit untersuchen wir ein Zusammenbringen von klassischer komponenten-basierter und variabler Strukturmodellierung. Der Fokus liegt dabei auf der Spezifikation von strukturkonsistenten Kopplungen in modular-hierarchischen Modellen mit einer variablen Struktur. Dafür nutzen wir intensionale Definitionen, wie sie aus der Logik bekannt sind, und führen ein neuartiges Konzept von intensionalen Kopplungen ein, welches kompakte gleichzeitig ausdrucksstarke Spezifikationen von komplexen Kommunikations- und Interaktionsmuster in statischen und variablen Strukturmodellen erlaubt