Modern building design is complex and involves many different disciplines operating in a fragmented manner. Appropriate computer-based decision support (DS) tools are sought that can raise the level of integration of different activities at the conceptual stage, in order to help create better designs solutions. This project investigates opportunities that exist for using techniques based upon the Genetic Algorithm (GA) to support critical activities of conceptual building design (CBD). Collective independent studies have shown that the GA is a powerful optimisation and exploratory search technique with widespread application. The GA is essentially very simple yet it offers robustness and domain independence. The GA efficiently searches a domain to exploit highly suitable information. It maintains multiple solutions to problems simultaneously and is well suited to non-linear problems and those of a discontinuous nature found in engineering design. The literature search first examines traditional approaches to supporting conceptual design. Existing GA techniques and applications are discussed which include pioneering studies in the field of detailed structural design. Broader GA studies are also reported which have demonstrated possibilities for investigating geometrical, topological and member size variation. The tasks and goals of conceptual design are studied. A rationale is introduced, aimed at enabling the GA to be applied in a manner that provides the most effective support to the designer. Numerical experiments with floor planning are presented. These studies provide a basic foundation for a subsequent design support system (OSS) capable ofgenerating structural design concepts. A hierarchical Structured GA (SGA) created by Oasgupta et al [1] is investigated to support the generation of diverse structural design concepts. The SGA supports variation in the size, shape and structural configuration of a building and in the choice of structural frame type and floor system. The benefits and limitations of the SGA approach are discussed. The creation of a prototype DSS system, abritrarily called Designer-Pro (OPRO), is described. A detailed building design model is introduced which is required for design development and appraisal. Simplifications, design rationale and generic component modelling are mentioned. A cost-based single criteria optimisation problem (SCOP) is created in which other constraints are represented as design parameters. The thesis describes the importance of the object-oriented programming (OOP) paradigm for creating a versatile design model and the need for complementary graphical user interface (Gill) tools to provide human-computer interaction (HCI) capabilities for control and intelligent design manipulation. Techniques that increase flexibility in the generation and appraisal of concept are presented. Tools presented include a convergence plot of design solutions that supports cursor-interrogation to reveal the details of individual concepts. The graph permits study of design progression, or evolution of optimum design solutions. A visualisation tool is also presented. The DPRO system supports multiple operating modes, including single-design appraisal and enumerative search (ES). Case study examples are provided which demonstrate the applicability of the DPRO system to a range of different design scenarios. The DPRO system performs well in all tests. A parametric study demonstrates the potential of the system for DS. Limitations of the current approach and opportunities to broaden the study form part of the scope for further work. Some suggestions for further study are made, based upon newly-emerging techniques.

The design of high quality electron generators to meet specific requirements is important in the application of these devices to a variety of materials processing systems (including welding, cutting and additive manufacture), X-ray tubes for medical, scientific and industrial applications, microscopy and lithography. Designs can be analysed by field solvers, and electron trajectories plotted to provide an indication of the beam quality. Incremental improvement of designs has normally been executed by trial and error, and this can be a time consuming activity requiring expert intervention for each iteration of the design process. The unique contribution made to knowledge by this work is the application of optimisation techniques to the design of electron guns to produce beams with the required optical properties. This thesis presents a review of the design of electron guns, including a discussion of thermionic cathode material properties and their suitability for use in electron guns for processing materials, the influence of space-charge on gun design and the derivation of salient beam metrics to characterise the beam. Beam quality metrics have been developed that allow quantification of electron beam characteristics, allowing objectives to be set for the optimisation process. Additionally, a method is presented that enables real world measurements to be directly compared with modelled beams. Various optimisation methods are reviewed. A genetic algorithm was selected, which would use gun modelling and beam characterisation calculations as the objective function, as a suitable method for application to this problem. However, it was recognised that selections for the best evolutionary parameters, the population size, number of parents, the mutation rate and mutation scale, were not readily determined from published work. An investigation is presented where a range of evolutionary parameters was tested for a set of geometrical problems, which had some similarity to electron gun design but could be computed sufficiently quickly to enable an extensive survey, and the most efficient combination of parameters was identified. Detail is given of the customisation of a genetic evolutionary optimisation method for the design of electron guns. Examples are presented of electron gun design optimisation processes to meet specified beam requirements within defined geometric and electrical constraints. The results of this work show that optimum evolutionary parameter settings for the geometric problem vary with the complexity of the problem and trends have been identified. Application of these parameters to an electron gun optimisation has been successful. The derived beam parameter metrics have been applied to electron guns as an objective function. Comparisons of modelled predictions of the beam characteristics with the measured real world values have been shown to be reasonable.

Les atteintes à l’environnement causées par un usage important de pesticides remettent en cause lemodèle productif actuel en viticulture d’appellation. Un cadre d’analyse évolutionniste est mobilisépour comprendre le manque de changement de pratiques phytosanitaires dans ce secteur malgrél’augmentation des pressions réglementaire et sociétale ces dernières années. Après avoir analysé lelock-in des viticulteurs vis-à-vis de l’utilisation des pesticides, nous appréhendons les nouvellespratiques grâce au concept d’innovation environnementale. En nous basant sur une enquête et unmodèle évolutionniste, nous montrons que l’IPM, en tant qu’innovation de processus, permet deréduire de manière significative les quantités de pesticides employées le long de trajectoiresgagnant-gagnant, mais que l’absence de compétences spécifiques dans les exploitations entrave sonadoption. Nous mettons ainsi en évidence l’importance des processus d’apprentissage pour laréduction des pesticides en viticulture. En l’absence de R & D formalisée, les viticulteurs ont besoind’un accompagnement spécifique et d’organismes de conseil agricole structurés localement pourrelever le défi de produire des vins rentables et respectueux de l’environnement. Les politiquespubliques en construction peuvent donc s’appuyer sur ces résultats pour impulser le changementattendu dans un délai raisonnable. / The environmental damage caused by the intensive use of pesticides challenges the current production model in appellation wine growing. We mobilize here an evolutionary framework to understand the lack of change in vineyard phytosanitary protection despite increasing regulatory and social pressure in recent years. After analyzing grape growers’ pesticide lock-in, we consider new protection practices via the concept of environmental innovation. Our case analysis and evolutionary model allow us to show that IPM could significantly reduce pesticide use along win-win trajectories, but also that the lack of specific implementation know-how in farms hampers its adoption. We therefore highlight the importance of learning processes for pesticide reduction in grape growing. In the absence of formal R & D, growers need specialized advice and structured extension services to meet the challenge they face: producing profitable and environmentally friendly wines. Public policies can therefore be based on this result to drive the expected change in a reasonable time.

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