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This thesis proposes several new techniques to improve the performance of speciated particle swarms in multimodal environments. We investigate how these algorithms can become more robust and adaptive, easier to use and able to solve a wider variety of optimisation problems. We then develop a technique that uses regression to vastly improve an algorithm's convergence speed without requiring extra evaluations. Speciation techniques play an important role in particle swarms. They allow an algorithm to locate multiple optima, providing the user with a choice of solutions. Speciation also provides diversity preservation, which can be critical for dynamic optimisation. By increasing diversity and tracking multiple peaks simultaneously, speciated algorithms are better able to handle the changes inherent in dynamic environments. Speciation algorithms often require a user to specify a parameter that controls how species form. This is a major drawback since the knowledge may not be available a priori. If the parameter is incorrectly set, the algorithm's performance is likely to be highly degraded. We propose using a time-based measure to control the speciation, allowing the algorithm to define species far more adaptively, using the population's characteristics and behaviour to control membership. Two new techniques presented in this thesis, ANPSO and ESPSO, use time-based convergence measures to define species. These methods are shown to be robust while still providing highly competitive performance. Both algorithms effectively optimised all of our test functions without requiring any tuning. Speciated algorithms are ideally suited to optimising dynamic environments, however the complexity of these environments makes them far more difficult to design algorithms for. To increase an algorithm's performance it is necessary to determine in what ways it should be improved. While all performance metrics allow optimisation techniques to be compared, they cannot show how to improve an algorithm. Until now this has been done largely by trial and error. This is extremely inefficient, in the same way it is inefficient trying to improve a program's speed without profiling it first. This thesis proposes a new metric that exclusively measures convergence speed. We show that an algorithm can be profiled by correlating the performance as measured by multiple metrics. By combining these two techniques, we can obtain far better insight into how best to improve an algorithm. Using this information, we then propose a local convergence enhancement that greatly increases performance by actively estimating the location of an optimum. The enhancement uses regression to fit a surface to the peak, guiding the search by estimating the peak's true location. By incorporating this technique, the algorithm is able to use the information contained within the fitness landscape far more effectively. We show that by combining the regression with an existing speciated algorithm, we are able to vastly improve the algorithm's performance. This technique will greatly enhance the utility of PSO on problems where fitness evaluations are expensive, or that require fast reaction to change.

La modélisation de la dynamique épidémiologique des ascomycètes parasites des arbres fruitiers présente deux aspects très importants : l’évaluation de la quantité d'inoculum et de son évolution, et l’identification des évènements climatiques donnant lieu à une contamination. Le travail présenté aborde ces deux aspects au travers de deux exemples : la tavelure du pommier, et la maladie de l’œil de paon de l’olivier, parasites majeurs pour les filières concernées.L’acquisition des connaissances sur la biologie des deux maladies a été abordée uniquement sur la base de données acquises sur le terrain, ce qui est original car généralement les modèles ont été réalisés sur la base de connaissances établies en conditions contrôlées.Dans le cas de Venturia inaequalis, agent de la tavelure du pommier, la vitesse de développement journalier de l’inoculum a été établie par optimisation numérique, sur la base d’observations réalisées en Provence. Un modèle de dynamique de projection des ascospores incluant la suspension de l’évolution de l’inoculum primaire lors des périodes sèches a été réalisé puis validé sur un jeu de données indépendantes. La transposabilité du modèle a été ensuite étudiée pour une autre région (Aquitaine). Dans le cas de Fusicladium oleagineum, agent de la maladie de l’oeil de paon, les conditions de contamination ont été établies en fonction de la température et de l’hygrométrie, d’une part par la réalisation d’un abaque sur la base de points sélectionnés par dires d’expert, et d’autre part de façon automatique à l’aide d’un système par apprentissage (réseau de neurones). Un modèle, liant la température moyenne après la contamination à l’apparition des symptômes a été ensuite réalisé. / Apple scab, caused by Venturia inaequalis, and peacoq leaf spot, cause by Fusicladiumoleagineum, are key diseases respectively for apple and olive growers. These disease usuallyrequire a large number of treatments. Adequate protection need a good evaluation ofquantitative disponibility of inoculum, and estimation of infection conditions.In this thesis, these two problems were studied using only field data. This is an originalaprroach to obtain knowledge about biology of fungi : most previous works were realised byregression of laboratory data obtained under controled conditions.In the case of Venturia inaequalis, primary inoculum consists of pseudothecia present in leaflitter. Treatments agains ascospore release period is the cornerstone of the strategy againstapple scab. However, the existing forecasting models are not reliable, and are all based ondegree-day time scale, proposed in 1982.Here, using a corpus of data acquired between 1996 and 2013, including observations ofascospore release and weather data, we assessed the daily rate of development of primaryinoculum by fitting generic new time scale functions. Further improvements were then studiedto take into account elements reported in litterature about the incidence of rain or wetness.Different methods were tested and adapted for the parameterisation of models by numericaloptimisation. Some forcasting models were proposed and adapted to the area where the studywas conducted, with parameters including rain and temperature. The validity was tested, andfurther developements of the forecasting tool was then proposed.In the case of Fusicladium oleagineum, a field-operational model predicting disease outbreakswas established as a function of temperature and relative humidity. First with the help ofpoints selected by experts, Secondly automaticaly using a neural network. A model defininglatent period as a function of average temperature after contamination was then realised.

The Super Proton Synchrotron (SPS) injection system plays a fundamental role to preserve the quality of injected high-brightness beams for the Large Hadron Collider (LHC) physics program and to maintain the maximum storable intensity. The present system is the result of years of upgrades and patches of a system not conceived for such intensities and beam qualities. In this study, we first investigate the effect of emittance growth due to amplitude-dependent tune shifts for erroneously injected beams. As a next step, we propose the design of a completely new injection system for the SPS using multi-level numerical optimisation, including realistic hardware assumptions. Methods and pseudo-algorithms of how this hierarchical optimisation framework can be adapted to other situations for optimal accelerator system design are shown. In addition, we explore the benefits of a numerical optimisation framework for the current SPS injection kicker timing system to minimise residual injection oscillations for maximised delivered beam intensity. We also demonstrate how a simple neural network based upon recorded data can approximate the injection system as a surrogate model, allowing for further studies of different optimisation algorithms even without beam time.

In the context of gradient-based numerical optimisation, the adjoint method is an e cient way of computing the gradient of the cost function at a computational cost independent of the number of design parameters, which makes it a captivating option for industrial CFD applications involving costly primal solves. The method is however a ected by instabilities, some of which are inherited from the primal solver, notably if the latter does not fully converge. The present work is an attempt at curbing primal solver limitations with the goal of indirectly alleviating adjoint robustness issues. To that end, a novel discretisation scheme for the steady-state incompressible Navier- Stokes problem is proposed: Mixed Hybrid Finite Volumes (MHFV). The scheme draws inspiration from the family of Mimetic Finite Di erences and Mixed Virtual Elements strategies, rid of some limitations and numerical artefacts typical of classical Finite Volumes which may hinder convergence properties. Derivation of MHFV operators is illustrated and each scheme is validated via manufactured solutions: rst for pure anisotropic di usion problems, then convection-di usion-reaction and nally Navier-Stokes. Traditional and novel Navier-Stokes solution algorithms are also investigated, adapted to MHFV and compared in terms of performance. The attention is then turned to the discrete adjoint Navier-Stokes system, which is assembled in an automated way following the principles of Equational Di erentiation, i.e. the di erentiation of the primal discrete equations themselves rather than the algorithm used to solve them. Practical/computational aspects of the assembly are discussed, then the adjoint gradient is validated and a few solution algorithms for the MHFV adjoint Navier-Stokes are proposed and tested. Finally, two examples of full shape optimisation procedures on internal ow test cases (S-bend and U-bend) are reported.

Photonic links have been proposed to transport radio frequency (RF) signals over optical fiber. External optical modulation is commonly used in high performance RF-photonic links. The practical use of optical fiber to transport RF signals is still limited due to high RF signal loss. In order to reduce the RF signal loss, highly efficient modulators are needed. For many applications, modulators with broad bandwidths are required. However, there are applications that require only a narrow bandwidth. For these narrow-band applications, the modulation efficiency can be improved through the resonant enhancement technique at the expense of reduced bandwidth. The aim of this thesis is to investigate highly efficient Mach-Zehnder optical modulators (MZMs) on Lithium Niobate (LiNbO3) with resonant enhancement techniques for narrow-band RF-photonic applications. This work focuses in particular on analyzing the factors that affect the modulation efficiency through resonant enhancement so that the modulator electrode structure can be optimized for maximum modulation efficiency. A parameter study of the effects of the electrode characteristics on the modulation efficiency of resonantly enhanced modulators (RE-MZM) is provided. From this study, optimum design objectives are identified. Numerical optimization is employed to explore the design trade-offs so that optimal configurations can be found. A sensitivity analysis is carried out to assess the performance of optimal RE-MZMs with respect to the variations of fabrication conditions. The results of these investigations indicate that the RE-MZM with a large electrode gap is the optimal design since it provides high modulation efficiency although the inherent switching voltage is high, and is the most tolerant to the fabrication fluctuations. A highly efficient RE-MZM on X-cut LiNbO3 is practically demonstrated with the resonant enhancement factor of 5 dB when comparing to the unenhanced modulator with the same electrode structure and effective switching voltage of 2 V at 1.8 GHz. The performance of the RF-photonic link using the fabr icated RE-MZM is evaluated. Optimization of RE-MZMs for operating at millimeter-wave frequencies is also reported. Factors that limit the modulation efficiency of an RE-MZM at millimeter-wave frequencies are identified. Novel resonant structures that can overcome these limitations are proposed. Preliminary designs indicate that greatly improved modulation efficiency could be expected.

The transition from internal combustion engine to battery electric cars is accompanied by a shift on the NVH issues damaging the passenger comfort. The rolling noise generated by the wheels and tyres is in particular characterized by an increasing attention from OEMs and car manufacturers. Among the causes of the rolling noise are the vibrations generated at the wheel, which are transmitted to the vehicle interior through its structure. To limit these vibrations at their source, a new innovative concept has been proposed at Stellantis. This idea is based on the use of a specific type of vibration absorber known by the acronym MTMD (Multiple Tuned Mass Damper).First, the existing literature about vibrations absorbers and optimisation techniques has been reviewed. Then, initial simulations on a global model comprising the wheel and beam-like resonators have shown how this system can effectively reduce a resonant peak.Optimisation processes have then revealed an important attenuation of a wheel resonance, even when the peak frequency is shifted. This demonstrated how important the distribution of resonators resonance frequencies are and their damping ratios when designing a robust and efficient MTMD.Finally, local resonators have been designed and modelled by considering the constraints for an integration on a wheel. A satisfactory design for resonators able to vibrate at the wanted frequency has been found. The beam-like resonators used in the first global model have then been replaced by these real resonators, confirming the possible gain with this device in a vehicle. / Övergången från förbränningsmotorer till batterielektriska bilar åtföljs av en övergång till NVH-frågor som kan påverka passagerarnas komfort. Det rullningsljud som genereras av hjul och däck får i synnerhet ökad uppmärksamhet från OEM:er och biltillverkare.Bland orsakerna till rullningsljudet finns de vibrationer som genereras vid hjulet och som överförs till fordonets inre genom dess struktur. För att begränsa dessa vibrationer vid källan har ett nytt innovativt koncept föreslagits av Stellantis. Idén bygger på användningen av en särskild typ av vibrationsdämpare som kallas MTMD (Multiple Tuned Mass Damper).Först har den befintliga litteraturen om vibrationsdämpare och optimeringstekniker gåtts igenom. Därefter har inledande simuleringar på en global modell som omfattar hjulet och balkliknande resonatorer visat hur detta system effektivt kan minska en resonanstopp.Optimeringsprocesserna har sedan bekräftat att hjulresonansen är kraftigt dämpad, även när toppfrekvensen är förskjuten. Detta visade hur viktig fördelningen av resonansfrekvenser och dämpningsförhållanden för resonatorer är när man utformar en robust och effektiv MTMD.Slutligen har lokala resonatorer utformats och modellerats genom att beakta begränsningarna för en integrering i ett hjul. En tillfredsställande utformning av resonatorer som kan vibrera vid den önskade frekvensen har hittats. De balkliknande resonatorer som användes i den första globala modellen har sedan ersatts av dessa riktiga resonatorer, vilket bekräftar den potentiella förbättringen med denna anordning i ett fordon.