The mathematical modelling of the environmental performance of buildings as an aid in the design process

This thesis is a theoretical study of the accuracy and usability of models that attempt to represent the environmental control system of buildings in order to improve environmental design. These models have evolved from crude representations of a building and its environment through to an accurate representation of the dynamic characteristics of the environmental stimuli on buildings. Each generation of models has had its own particular influence on built form. This thesis analyses the theory, structure and data of such models in terms of their accuracy of simulation and therefore their validity in influencing built form. The models are also analysed in terms of their compatability with the design process and hence their ability to aid designers. The conclusions are that such models are unlikely to improve environmental performance since: a the models can only be applied to a limited number of building types, b they can only be applied to a restricted number of the characteristics of a design, c they can only be employed after many major environmental decisions have been made, d the data used in models is inadequate and unrepresentative, e models do not account for occupant interaction in environmental control. It is argued that further improvements in the accuracy of simulation of environmental control will not significantly improve environmental design. This is based on the premise that strategic environmental decisions are made at the conceptual stages of design whereas models influence the detailed stages of design. It is hypothesised that if models are to improve environmental design it must be through the analysis of building typologies which provides a method of feedback between models and the conceptual stages of design. Field studies are presented to describe a method by which typologies can be analysed and a theoretical framework is described which provides a basis for further research into the implications of the morphology of buildings on environmental design.

Improving the design process for factories:modelling human performance variation

Theprocess of manufacturing system design frequently includes modeling, and usually, this means applying a technique such as discrete event simulation (DES). However, the computer tools currently available to apply this technique enable only a superficial representation of the people that operate within the systems. This is a serious limitation because the performance of people remains central to the competitiveness of many manufacturing enterprises. Therefore, this paper explores the use of probability density functions to represent the variation of worker activity times within DES models.

Human performance modelling as an aid in the process of manufacturing system design

Manufacturing system design is an ongoing activity within industry. Modelling tools based on Discrete Event Simulation are often used by practitioners during this design cycle. However, such tools do not adequately model the behaviour of 'direct' workers in manufacturing environments. There is an important need to expand the capability of modelling to include the relationships between human centred factors (demography, attitudes, beliefs, etc), their working environment (physical and organizational), and their subsequent performance in terms of productive routines. Therefore, this paper describes research that has formed a pilot modelling methodology that is an important first step in providing such a capability.

Using process-oriented holonic (PrOH) modelling to increase understanding of information systems

Methodologies for understanding business processes and their information systems (IS) are often criticized, either for being too imprecise and philosophical (a criticism often levied at softer methodologies) or too hierarchical and mechanistic (levied at harder methodologies). The process-oriented holonic modelling methodology combines aspects of softer and harder approaches to aid modellers in designing business processes and associated IS. The methodology uses holistic thinking and a construct known as the holon to build process descriptions into a set of models known as a holarchy. This paper describes the methodology through an action research case study based in a large design and manufacturing organization. The scientific contribution is a methodology for analysing business processes in environments that are characterized by high complexity, low volume and high variety where there are minimal repeated learning opportunities, such as large IS development projects. The practical deliverables from the project gave IS and business process improvements for the case study company.

Multiscale modelling of heterogeneously catalysed transesterification reaction process:an overview

Biodiesel is fast becoming one of the key transport fuels as the world endeavours to reduce its carbon footprint and find viable alternatives to oil derived fuels. Research in the field is currently focusing on more efficient ways to produce biodiesel, with the most promising avenue of research looking into the use of heterogeneous catalysis. This article presents a framework for kinetic reaction and diffusive transport modelling of the heterogeneously catalysed transesterification of triglycerides into fatty acid methyl esters (FAMEs), unveiled by a model system of tributyrin transesterification in the presence of MgO catalysts. In particular, the paper makes recommendations on multicomponent diffusion calculations such as the diffusion coefficients and molar fluxes from infinite dilution diffusion coefficients using the Wilke and Chang correlation, intrinsic reaction kinetic studies using the Eley-Rideal kinetic mechanism with methanol adsorption as the rate determining steps and multiscale reaction-diffusion process simulation between catalytic porous and bulk reactor scales. © 2013 The Royal Society of Chemistry.

Reliability modelling and verification of manufacturing processes based on process knowledge management

Reliability modelling and verification is indispensable in modern manufacturing, especially for product development risk reduction. Based on the discussion of the deficiencies of traditional reliability modelling methods for process reliability, a novel modelling method is presented herein that draws upon a knowledge network of process scenarios based on the analytic network process (ANP). An integration framework of manufacturing process reliability and product quality is presented together with a product development and reliability verification process. According to the roles of key characteristics (KCs) in manufacturing processes, KCs are organised into four clusters, that is, product KCs, material KCs, operation KCs and equipment KCs, which represent the process knowledge network of manufacturing processes. A mathematical model and algorithm is developed for calculating the reliability requirements of KCs with respect to different manufacturing process scenarios. A case study on valve-sleeve component manufacturing is provided as an application example of the new reliability modelling and verification procedure. This methodology is applied in the valve-sleeve component manufacturing processes to manage and deploy production resources.

Immunological synapse: a mathematical model of the bond formation process:mathematical modelling of the immature synapse

The cell:cell bond between an immune cell and an antigen presenting cell is a necessary event in the activation of the adaptive immune response. At the juncture between the cells, cell surface molecules on the opposing cells form non-covalent bonds and a distinct patterning is observed that is termed the immunological synapse. An important binding molecule in the synapse is the T-cell receptor (TCR), that is responsible for antigen recognition through its binding with a major-histocompatibility complex with bound peptide (pMHC). This bond leads to intracellular signalling events that culminate in the activation of the T-cell, and ultimately leads to the expression of the immune eector function. The temporal analysis of the TCR bonds during the formation of the immunological synapse presents a problem to biologists, due to the spatio-temporal scales (nanometers and picoseconds) that compare with experimental uncertainty limits. In this study, a linear stochastic model, derived from a nonlinear model of the synapse, is used to analyse the temporal dynamics of the bond attachments for the TCR. Mathematical analysis and numerical methods are employed to analyse the qualitative dynamics of the nonequilibrium membrane dynamics, with the specic aim of calculating the average persistence time for the TCR:pMHC bond. A single-threshold method, that has been previously used to successfully calculate the TCR:pMHC contact path sizes in the synapse, is applied to produce results for the average contact times of the TCR:pMHC bonds. This method is extended through the development of a two-threshold method, that produces results suggesting the average time persistence for the TCR:pMHC bond is in the order of 2-4 seconds, values that agree with experimental evidence for TCR signalling. The study reveals two distinct scaling regimes in the time persistent survival probability density prole of these bonds, one dominated by thermal uctuations and the other associated with the TCR signalling. Analysis of the thermal fluctuation regime reveals a minimal contribution to the average time persistence calculation, that has an important biological implication when comparing the probabilistic models to experimental evidence. In cases where only a few statistics can be gathered from experimental conditions, the results are unlikely to match the probabilistic predictions. The results also identify a rescaling relationship between the thermal noise and the bond length, suggesting a recalibration of the experimental conditions, to adhere to this scaling relationship, will enable biologists to identify the start of the signalling regime for previously unobserved receptor:ligand bonds. Also, the regime associated with TCR signalling exhibits a universal decay rate for the persistence probability, that is independent of the bond length.

A process-based Knowledge Management framework supported by ARIS Enterprise Modelling architecture

Knowledge and its management have been respectively accepted as a critical resource and a core business competency. Despite that literature proves the existence of a gap between the theoretical considerations of Knowledge Management (KM) and their efficient application. Such lacking, we argue, derives from the missing link between a framework of Knowledge Management and the particular methods and guidelines of its implementation. In an attempt to bridge this gap, an original, process- based holistic Knowledge Management framework is proposed, aiming to address the problem of knowledge management application and performance by utilising a set of well accepted Enterprise Modelling (EM) methods and tools.

Computational modelling of interacting phenomena in the shape casting process

Abstract not available

Modelling the mixing of lead bullion during the refining process

Abstract not available

Modelling interacting phenomena during the solidification of metals in the casting process

A variety of interacting complex phenomena takes place during the casting of metallic components. Here molten metal is poured into a mould cavity where it flows, cools, solidifies and then deforms in its solid state. As the metal cools, thermal gradients will promote thermal convection which will redistribute the heat around the component (usually from feeders or risers) towards the solidification front and mushy zone. Also, as the evolving solid regions of the cast component deform they will form gap at the cast-mould interface. This gap may change the rate of solidification in certain parts the casting, hence affecting the manner in which the cast component solidifies. Interaction between a cast component and its surrounding mould will also govern stress magnitudes in both the cast and mould -these may lead to defects such as cracks. This paper presents a multiphysics modelling approach to this complex process. Emphasis will be placed on the interacting phenomena taking place during the process and the modelling strategy used. Comparisons with plant data are also be given.

Modelling of water removal during a paper vacuum dewatering process using a Level-Set method

Water removal in paper manufacturing is an energy-intensive process. The dewatering process generally consists of four stages of which the first three stages include mechanical water removal through gravity filtration, vacuum dewatering and wet pressing. In the fourth stage, water is removed thermally, which is the most expensive stage in terms of energy use. In order to analyse water removal during a vacuum dewatering process, a numerical model was created by using a Level-Set method. Various different 2D structures of the paper model were created in MATLAB code with randomly positioned circular fibres with identical orientation. The model considers the influence of the forming fabric which supports the paper sheet during the dewatering process, by using volume forces to represent flow resistance in the momentum equation. The models were used to estimate the dry content of the porous structure for various dwell times. The relation between dry content and dwell time was compared to laboratory data for paper sheets with basis weights of 20 and 50 g/m2 exposed to vacuum levels between 20 kPa and 60 kPa. The comparison showed reasonable results for dewatering and air flow rates. The random positioning of the fibres influences the dewatering rate slightly. In order to achieve more accurate comparisons, the random orientation of the fibres needs to be considered, as well as the deformation and displacement of the fibres during the dewatering process.

Structural control of gold nanoparticles self-assemblies by layer-by-layer process

This work presents a novel way to introduce gold nanoparticles (Au NPs) in a multilayer polymer produced by the layer-by-layer (LbL) assembling technique. The technique chosen shows that, depending on the pH used, different morphological structures can be obtained from monolayer or bilayer Au NPs. The MEIS and RBS techniques allowed for the modelling of the interface polymer-NPs, as well as the understanding of the interaction of LbL system, when adjusting the pH in weak polyelectrolytes. The process reveals that the optical properties of multilayer systems could be fine-tuned by controlling the addition of metallic nanoparticles, which could also modify specific polarization responses.