Maintaining design intent for aircraft manufacture

Design and manufacture of aircraft requires deep multi-disciplinary understanding of system behaviour. The intention of the designer can get lost due to the many changes occurring to the product and the inability of the methods and tools used to capture it. Systems engineering and optimisation tools underpin industrial approaches to design, but are not without issue. The challenge is to find a route from concept to manufacture which enables designers to maintain their original intent. The novelty in this work is that the parameterisation used to build the CAD model reflects the manufacturing capability, ensuring design intent is maintained from concept to manufacture.

Optimisation of Environment-friendly SCFRC mixes use in precast Concrete Industry

The concept of green concrete has been progressively introduced in concrete technology. At the same time, new generations of superplasticisers have become widely available and self-compacting concrete is being increasingly implemented. The aim of this research is to study the impact that different sustainable materials have on both fresh and hardened properties of Self-Compacting Fibre Reinforced Concrete (SCFRC) in order to implement their use in a precast concrete company. Different combinations of cement, mineral additions (active and inert), polypropylene fibres, superplasticisers, and aggregates have been considered. Fresh state performance has been assessed by means of: slump flow test, V-funnel, and J-ring. Concrete compressive strength values at different ages have been retained as representative of the material's performance in its hardened state. All these properties have been correlated with SCFRC proportioning parameters. The importance of interactions between mineral additions and between these and superplasticiser is emphasised, as well as the different consequences of using powders as cement replacement or as mineral additions.

Optimisation of Environment-friendly SCFRC mixes use in precast Concrete Industry (PDF Download Available). Available from: http://www.researchgate.net/publication/263304799_Optimisation_of_Environment-friendly_SCFRC_mixes_use_in_precast_Concrete_Industry [accessed Jun 5, 2015].

Taguchi optimisation approach for production of activated carbon from phosphoric acid impregnated palm kernel shell by microwave heating

Taguchi method was applied to investigate the optimal operating conditions in the preparation of activated carbon using palm kernel shell with quadruple control factors: irradiation time, microwave power, concentration of phosphoric acid as impregnation substance and impregnation ratio between acid and palm kernel shell. The best combination of the control factors as obtained by applying Taguchi method was microwave power of 800 W, irradiation time of 17 min, impregnation ratio of 2, and acid concentration of 85%. The noise factor (particle size of raw material) was considered in a separate outer array, which had no effect on the quality of the activated carbon as confirmed by t-test. Activated carbon prepared at optimum combination of control factors had high BET surface area of 1,473.55 m² g-1 and high porosity. The adsorption equilibrium and kinetic data can satisfactorily be described by the Langmuir isotherm and a pseudo-second-order kinetic model, respectively. The maximum adsorbing capacity suggested by the Langmuir model was 1000 mg g-1.

Aerofoil Optimisation Using CST Parameterisation in SU2

This paper describes an implementation of the popular method of Class-Shape Transformation for aerofoil design within SU2 software framework. To exploit the adjoint based methods for aerodynamic optimisation within the SU2, a formulation to obtain geometric sensitivities from the new parameterisation is introduced, enabling the calculation of gradients with respect to new design variables. To assess the accuracy and efficiency of the alternative approach, two transonic optimisation problems are investigated: an inviscid problem with multiple constraints and a viscous problems without any constraints. Results show the new parameterisation obtaining reliable optimums, with similar levels of
performance of the software native parameterisations.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Design of Scaled Bridge Prototype for Energy Harvesting Testing

Energy harvesting from ambient vibration is a promising field, especially for applications in larger infrastructures such as bridges. These structures are more frequently monitored for damage detection because of their extended life, increased traffic load and environmental deterioration. In this regard, the possibility of sourcing the power necessary for the sensors from devices embedded in the structure, thus cutting the cost due to the management of battery replacing over the lifespan of the structure, is particularly attracting. Among others, piezoelectric devices have proven to be especially effective and easy to apply since they can be bonded to existing host structure. For these devices the energy harvesting capacity is achieved directly from the variation in the strain conditions from the surface of the structure. However these systems need to undergo significant research for optimisation of their harvesting capacity and for assessing the feasibility of application to various ranges of bridge span and load. In this regard scaled bridge prototypes can be effectively used not only to assess numerical models and studies in an inexpensive and repeatable way but also to test the electronic devices under realistic field conditions. In this paper the theory of physical similitude is applied to the design of bridge beams with embedded energy harvesting systems and health monitoring sensors. It will show both how bridge beams can be scaled in such a way to apply and test energy harvesting systems and 2) how experimental data from existing bridges can be applied to prototypes in a laboratory environment. The study will be used for assessing the reliability of the system over a train bridge case study undergoing a set load cycles and induced localised damage.

Investigation of Utilizing Single Surface Depressions in Optimization of NLF Aerofoil Design

An environment has been created for the optimisation of aerofoil profiles with inclusion of small surface features. For TS wave dominated flows, the paper examines the consequences of the addition of a depression on the aerodynamic optimisation of an NLF aerofoil, and describes the geometry definition fidelity and optimisation algorithm employed in the development process. The variables that define the depression for this optimisation investigation have been fixed, however a preliminary study is presented demonstrating the sensitivity of the flow to the depression characteristics. Solutions to the optimisation problem are then presented using both gradient-based and genetic algorithm techniques, and for accurate representation of the inclusion of small surface perturbations it is concluded that a global optimisation method is required for this type of aerofoil optimisation task due to the nature of the response surface generated. When dealing with surface features, changes in the transition onset are likely to be of a non-linear nature so it is highly critical to have an optimisation algorithm that is robust, suggesting that for this framework, gradient-based methods alone are not suited.

Investigations on the Analysis and Design of Aperiodic Frequency Selective Surfaces for Space Applications

An investigation on the design of aperiodic FSS is presented. First, an accurate yet efficient method which allows the analysis of finite sized aperiodic FSS has been developed. Subsequently, an optimisation method is implemented which optimises all the FSS elements to obtain an FSS design with an aperiodic element layout. Preliminary designs of aperiodic FSS are presented and the numerical results are discussed.

An Automated Design Framework for Assembly Task Simulation

This paper presents an automated design framework for the development of individual part forming tools for a composite stiffener. The framework uses parametrically developed design geometries for both the part and its layup tool. The framework has been developed with a functioning user interface where part / tool combinations are passed to a virtual environment for utility based assessment of their features and assemblability characteristics. The work demonstrates clear benefits in process design methods with conventional design timelines reduced from hours and days to minutes and seconds. The methods developed here were able to produce a digital mock up of a component with its associated layup tool in less than 3 minutes. The virtual environment presenting the design to the designer for interactive assembly planning was generated in 20 seconds. Challenges still exist in determining the level of reality required to provide an effective learning environment in the virtual world. Full representation of physical phenomena such as gravity, part clashes and the representation of standard build functions require further work to represent real physical phenomena more accurately.

Optimisation of viscoelastic treatments using genetic algorithms

Viscoelastic treatments are one of the most efficient treatments, as far as passive damping is concerned, particularly in the case of thin and light structures. In this type of treatment, part of the strain energy generated in the viscoelastic material is dissipated to the surroundings, in the form of heat. A layer of viscoelastic material is applied to a structure in an unconstrained or constrained configuration, the latter proving to be the most efficient arrangement. This is due to the fact that the relative movement of both the host and constraining layers cause the viscoelastic material to be subjected to a relatively high strain energy. There are studies, however, that claim that the partial application of the viscoelastic material is just as efficient, in terms of economic costs or any other form of treatment application costs. The application of patches of material in specific and selected areas of the structure, thus minimising the extension of damping material, results in an equally efficient treatment. Since the damping mechanism of a viscoelastic material is based on the dissipation of part of the strain energy, the efficiency of the partial treatment can be correlated to the modal strain energy of the structure. Even though the results obtained with this approach in various studies are considered very satisfactory, an optimisation procedure is deemed necessary. In order to obtain optimum solutions, however, time consuming numerical simulations are required. The optimisation process to use the minimum amount of viscoelastic material is based on an evolutionary geometry re-design and calculation of the modal damping, making this procedure computationally costly. To avert this disadvantage, this study uses adaptive layerwise finite elements and applies Genetic Algorithms in the optimisation process.

Nutritional Evaluation and Optimisation in Neonates: a randomized, double-blind controlled trial of amino acid regimen and intravenous lipid composition in preterm parenteral nutrition

Background: Parenteral nutrition is central to the care of very immature infants. Current international recommendations favor higher amino acid intakes and fish oil–containing lipid emulsions. Objective: The aim of this trial was to compare 1) the effects of high [immediate recommended daily intake (Imm-RDI)] and low [incremental introduction of amino acids (Inc-AAs)] parenteral amino acid delivery within 24 h of birth on body composition and 2) the effect of a multicomponent lipid emulsion containing 30% soybean oil, 30% medium-chain triglycerides, 25% olive oil, and 15% fish oil (SMOF) with that of soybean oil (SO)-based lipid emulsion on intrahepatocellular lipid (IHCL) content. Design: We conducted a 2-by-2 factorial, double-blind, multicenter randomized controlled trial. Results: We randomly assigned 168 infants born at ,31 wk of gestation. We evaluated outcomes at term in 133 infants. There were no significant differences between Imm-RDI and Inc-AA groups for nonadipose mass [adjusted mean difference: 1.0 g (95% CI: 2108, 111 g; P = 0.98)] or between SMOF and SO groups for IHCL [adjusted mean SMOF:SO ratio: 1.1 (95% CI: 0.8, 1.6; P = 0.58]. SMOF does not affect IHCL content. There was a significant interaction (P = 0.05) between the 2 interventions for nonadipose mass. There were no significant interactions between group differences for either primary outcome measure after adjusting for additional confounders. Imm-RDI infants were more likely than Inc-AA infants to have blood urea nitrogen concentrations .7 mmol/L or .10 mmol/L, respectively (75% compared with 49%, P , 0.01; 49% compared with 18%, P , 0.01). Head circumference at term was smaller in the Imm-RDI group [mean difference: 20.8 cm (95% CI: 21.5, 20.1 cm; P = 0.02)]. There were no significant differences in any prespecified secondary outcomes, including adiposity, liver function tests, incidence of conjugated hyperbilirubinemia, weight, length, mortality, and brain volumes. Conclusion: Imm-RDI of parenteral amino acids does not benefit body composition or growth to term and may be harmful. This trial was registered at www.isrctn.com as ISRCTN29665319 and at eudract.ema.europa.eu as EudraCT 2009-016731-34.

Les campagnes sociales destinées aux jeunes adultes québécois sur Internet : pistes pour l'optimisation des sites Web

Avec la montée en popularité d’Internet et des médias sociaux, de plus en plus d’organismes sociaux et publics, notamment, intègrent des plateformes Web à leurs volets traditionnels. La question d’Internet demeure toutefois peu étudiée eu égard à la publicité sociale. Ce mémoire porte donc sur la question du Web en relation avec les campagnes sociales adressées aux jeunes Québécois de 18 à 25 ans, une population particulièrement réceptive aux nouvelles technologies. Plus exactement, dans cette étude, nous avons analysé trois sites Web rattachés à des campagnes sociales (La vitesse, ça coûte cher de la SAAQ, Les ITSS se propagent du MSSS et 50 000 adeptes, 5 000 toutous de la Fondation CHU Sainte-Justine) dans l’objectif de déterminer leurs forces et leurs faiblesses pour ensuite proposer des pistes pour leur optimisation. C’est à l’aide d’une analyse critique de contenu suivie d’entrevues et d’observations individuelles auprès de 19 participants que nous sommes parvenue à suggérer des pistes pour l’optimisation des sites Web de campagnes sociales destinées aux jeunes adultes québécois. Une des plus grandes difficultés en ce qui a trait à leur conception consiste à choisir les stratégies les plus appropriées pour provoquer un changement d’attitude ou de comportement, a fortiori chez ceux qui adoptent des comportements à risque (fumer, conduire en état d’ébriété, avoir des relations sexuelles non protégées); des stratégies qui, pour être plus efficaces, devraient être adaptées en fonction des caractéristiques propres aux publics cibles et aux médias de diffusion. Afin d’analyser adéquatement les campagnes sociales, nous avons fait appel aux théories de la persuasion et aux théories sur l’influence des médias jugées pertinentes dans notre contexte puisqu’elles sont propres à ce type d’étude. Ces approches combinées nous ont permis d’intégrer à l’analyse d’une campagne donnée les contextes qui l’entourent et les pratiques dans lesquelles elle s’inscrit. Cette étude nous a, entre autres, permis de démontrer qu’il existait d’importants écarts entre les attentes et les besoins des internautes et l’offre des sites Web étudiés.

Optimisation des horaires des agents et du routage des appels dans les centres d’appels

Nous étudions la gestion de centres d'appels multi-compétences, ayant plusieurs types d'appels et groupes d'agents. Un centre d'appels est un système de files d'attente très complexe, où il faut généralement utiliser un simulateur pour évaluer ses performances. Tout d'abord, nous développons un simulateur de centres d'appels basé sur la simulation d'une chaîne de Markov en temps continu (CMTC), qui est plus rapide que la simulation conventionnelle par événements discrets. À l'aide d'une méthode d'uniformisation de la CMTC, le simulateur simule la chaîne de Markov en temps discret imbriquée de la CMTC. Nous proposons des stratégies pour utiliser efficacement ce simulateur dans l'optimisation de l'affectation des agents. En particulier, nous étudions l'utilisation des variables aléatoires communes. Deuxièmement, nous optimisons les horaires des agents sur plusieurs périodes en proposant un algorithme basé sur des coupes de sous-gradients et la simulation. Ce problème est généralement trop grand pour être optimisé par la programmation en nombres entiers. Alors, nous relaxons l'intégralité des variables et nous proposons des méthodes pour arrondir les solutions. Nous présentons une recherche locale pour améliorer la solution finale. Ensuite, nous étudions l'optimisation du routage des appels aux agents. Nous proposons une nouvelle politique de routage basé sur des poids, les temps d'attente des appels, et les temps d'inoccupation des agents ou le nombre d'agents libres. Nous développons un algorithme génétique modifié pour optimiser les paramètres de routage. Au lieu d'effectuer des mutations ou des croisements, cet algorithme optimise les paramètres des lois de probabilité qui génèrent la population de solutions. Par la suite, nous développons un algorithme d'affectation des agents basé sur l'agrégation, la théorie des files d'attente et la probabilité de délai. Cet algorithme heuristique est rapide, car il n'emploie pas la simulation. La contrainte sur le niveau de service est convertie en une contrainte sur la probabilité de délai. Par après, nous proposons une variante d'un modèle de CMTC basé sur le temps d'attente du client à la tête de la file. Et finalement, nous présentons une extension d'un algorithme de coupe pour l'optimisation stochastique avec recours de l'affectation des agents dans un centre d'appels multi-compétences.