Rozprawy doktorskie: „HYBRID OPTIMIZATION MODEL”

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Sachs, Julia [Verfasser]. "Model-Based Optimization of Hybrid Energy Systems / Julia Sachs". Aachen : Shaker, 2016. http://d-nb.info/1101185112/34.

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Werner, Quentin. "Model-based optimization of electrical system in the early development stage of hybrid drivetrains". Thesis, Université de Lorraine, 2017. http://www.theses.fr/2017LORR0109.

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Cette thèse analyse les challenges auxquels sont confrontés les composants électriques pour les systèmes de traction hybrides. L’analyse de ces composants et de leurs interactions en tant qu’entité indépendante est un sujet de recherche important afin de dimensionner de manière optimale le système au lieu de combiner des composants optimaux. Les véhicules hybrides sont un domaine de recherche qui suscite un grand intérêt parce qu’il s’agit d’une solution efficace à court terme afin de préparer la transition énergétique vers les véhicules à zéro émission. Malgré les avantages de cette solution, c’est un sujet de recherche complexe car les composants électriques doivent être intégrés dans un système de propulsion conventionnel. Ainsi le but de ce travail de recherche est axé sur la détermination de méthodes appropriées pour étudier les composants électriques et les contributions apportées par cette thèse visent à répondre à la problématique suivante : déterminer le niveau suffisant de détails pour modéliser les systèmes électriques pour les systèmes de traction pour véhicules hybrides afin d’identifier le dimensionnement idéal des composants pour différents systèmes pendant la phase de développement. Afin de résoudre cette problématique, ce rapport est divisé en quatre parties au sein de six chapitres. D’abord l’état de l’art des véhicules hybrides, des composants électriques ainsi que des méthodes d’optimisation associées sont présentés (chapitre 1). Ensuite, pour chaque composant (chapitre 2 à 4), des méthodes de modélisation appropriées sont déterminées afin de les modéliser mais aussi afin d’évaluer leur intégration dans le système de propulsion. Puis, une solution pour l’étude du système globale est déterminée à partir de l’analyse de travaux précédents (chapitre 5). Finalement, une approche d’optimisation est développée et permet d’analyser différents systèmes ainsi que l’influence de différents paramètres sur le dimensionnement (chapitre 6). Grâce à l’analyse du développement actuel et des travaux précédents sur le sujet ainsi qu’au développement d’outils de simulation, cette thèse étudie et analyse les relations entre le niveau de tension et de courant, et les performances du système dans différents cas. Les résultats permettent de déterminer l’influence de ces paramètres sur les composants ainsi que l’impact de l’environnement industriel sur les résultats. En tenant compte du cadre législatif actuel, les résultats convergent globalement tous dans la même direction : une réduction du niveau de tension, respectivement une augmentation du courant, entraine une amélioration du système global par rapport aux méthodes de dimensionnent actuelles. Ces observations sont liées à l’architecture, au cycle d’évaluation et à l’environnement considérés mais les méthodes et l’approche développée ont posé les bases pour étendre les connaissances dans le domaine de l’optimisation des véhicules hybrides. En plus de l’optimisation générale, des cas particuliers sont analysés afin de montrer la modularité des méthodes et l’influence de paramètres supplémentaires (système 48V ou convertisseur Boost). Afin de conclure, cette thèse a mis en place les bases pour l’étude des composants électriques pour les véhicules hybrides. De part un environnement fluctuant et les nombreuses technologies possibles, ce sujet suscite encore un grand intérêt et les points suivants peuvent être encore étudiés de manière plus détaillée : * Application des méthodes pour d’autres systèmes de propulsion (autre architectures hybrides, véhicule à pile à combustible ou tout électrique), * Étude de nouvelles technologies comme le carbure de silicium pour l’électronique de puissance, la machine à reluctance variable ou le sulfure de lithium pour les batteries, * Analyse d’autre cycle d’évaluation ainsi que leur cadre législatif, * Mise en place de structures additionnelles pour l’électronique de puissance, * Validations supplémentaires avec d’autres composants
This work analyses the challenges faced by the electric components for traction purpose in hybrid drivetrains. It investigates the components and their interactions as an independent entity in order to refine the scope of investigation and to find the best combinations of components instead of the best components combinations. Hybrid vehicle is currently a topic of high interest because it stands for a suitable short-term solution towards zero emission vehicle. Despite its advantages, it is a challenging topic because the components need to be integrated in a conventional drivetrain architecture. Therefore, the focus of this work is set on the determination of the right methods to investigate only the electric components for traction purpose. The aim and the contributions of this work lies thereby in the resolution of the following statement: Determine the sufficient level of details in modeling electric components at the system level and develop models and tools to perform dynamic simulations of these components and their interactions in a global system analysis to identify ideal designs of various drivetrain electric components during the design process. To address these challenges, this work is divided in four main parts within six chapters. First the current status of the hybrid vehicle, the electric components and the associated optimization methods and simulation are presented (first chapter). Then for each component, the right modeling approach is defined in order to investigate the electrical, mechanical and thermal behavior of the components as well as methods to evaluate their integration in the drivetrain (second to fourth chapter). After this, a suitable method is defined to evaluate the global system and to investigate the interactions between the components based on the review of relevant previous works (chapter five). Finally, the last chapter presents the optimization approach considered in this work and the results by analyzing different system and cases (chapter six). Thanks to the analysis of the current status, previous works and the development of the simulations tools, this work investigates the relationships between the voltage, the current and the power in different cases. The results enable, under the considered assumptions of the work, to determine the influence of these parameters on the components and of the industrial environment on the optimization results. Considering the current legislative frame, all the results converge toward the same observation referred to the reference systems: a reduction of the voltage and an increase of the current leads to an improvement of the integration and the performance of the system. These observations are linked with the considered architecture, driving cycle and development environment but the developed methods and approaches have set the basis to extend the knowledge for the optimization of the electric system for traction purpose. Beside the main optimization, special cases are investigated to show the influence of additional parameters (increase of the power, 48V-system, machine technology, boost-converter…) In order to conclude, this work have set the basis for further investigations about the electric components for traction purpose in more electrified vehicle. Due to the constantly changing environment, the new technologies and the various legislative frame, this topic remains of high interest and the following challenges still need to be deeper investigated: * Application of the methods for other drivetrain architecture (series hybrid, power-split hybrid, fuel-cell vehicle, full electric vehicle), * Investigation of new technologies such as silicon-carbide for the power electronics, lithium–sulfur battery or switch reluctance machine, * Investigation of other driving cycle, legislative frame, * Integration of additional power electronics structure, * Further validation of the modeling approaches with additional components

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Bertini, Lorenzo. "Modeling and Optimization of a Fuel Cell Hybrid System". Thesis, KTH, Skolan för kemivetenskap (CHE), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-51143.

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The purpose of this project was the modeling, optimization and prediction of a hybrid system composed of a fuel cell, a dc-dc converter and a supercapacitor in series. Lab tests were performed for each device to understand their behavior, and then each one was modeled using software (Simulink). The validation of the model was done by comparing its results with measured data; finally the model was used for the optimization and the prediction of the hybrid system

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Šandera, Čeněk. "Hybridní model metaheuristických algoritmů". Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2015. http://www.nusl.cz/ntk/nusl-234259.

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The main topic of this PhD thesis is metaheuristic algorithm in wider scope. The first chapters are dedicated to a description of broader context of metaheuristics, i.e. various optimization classes, determination of their omplexity and different approaches to their solutions. The consequent discussion about metaheuristics and their typical characteristics is followed by several selected examples of metaheuristics concepts. The observed characteristics serve as a base for building general metaheuristics model which is suitable for developing brand new or hybrid algorithms. The thesis is concluded by illustration of author’s publications with discussion about their adaptation to the proposed model. On the attached CD, there is also available a program implementation of the created model.

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Thalheimer, William Cooper. "Structural analysis and optimization with a locally-Cartesian Hybrid Shell Model". Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107054.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 131-133).
The Hybrid Shell Model (HSM) is presented as an intermediate-fidelity structural model well suited for conceptual design of aerospace vehicles. Although significantly simpler and more economical than full 3D elasticity models, it can still capture full 3D geometries, large deformations, and anisotropic materials. HSM is formulated from the full 3D equilibrium and compatibility equations all projected onto local bases defined on the 2D shell manifold. General anisotropic constitutive equations are also formulated in the local 2D shell manifold bases. The resulting continuous HSM formulation is discretized in weak form with a Galerkin finite element method (FEM), with spherical interpolation used for the local basis vectors. Displacements, basis rotations, and stress resultants are the primary unknowns. A fully adjoint-consistent plane-stress HSM version (HSM2D) is developed for the purpose of model verification and demonstration of order-of-accuracy convergence. The Method of Exact Solutions (MES) is applied to the case of a uniform plate hanging under its own weight. The effectiveness of the adjoint model for structural optimization is also demonstrated for a simplified rotor blade in a centrifugal force field, featuring non-uniform forcing, non-zero Poisson ratio, large deflection, and optimization of multiple parameters. The suitability of HSM as an intermediate fidelity conceptual aircraft design tool is thus demonstrated.
by William Cooper Thalheimer.
S.M.

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Wu, Zheng. "Hybrid Multi-Objective Optimization Models for Managing Pavement Assets". Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/26092.

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Increasingly tighter budgets, changes in government role/function, declines in staff resources, and demands for increased accountability in the transportation field have brought unprecedented challenges for state transportation officials at all management levels. Systematic methodologies for effective management of a specific type of infrastructure (e.g., pavement and bridges) as well as for holistically managing all types of infrastructure assets are being developed to approach these challenges. In particular, the intrinsic characteristics of highway system make the use of multi-objective optimization techniques particularly attractive for managing highway assets. Recognizing the need for effective tradeoff tools and the limitations of state-of-practice analytical models and tools in highway asset management, the main objective of this dissertation was to develop a performance-based asset management framework that uses multi-objective optimization techniques and consists of stand-alone but logically interconnected optimization models for different management levels. Based on a critical review of popular multi-objective optimization techniques and their applications in highway asset management, a synergistic integration of complementary multi-criteria optimization techniques is recommended for the development of practical and efficient decision-supporting tools. Accordingly, the dissertation first proposes and implements a probabilistic multi-objective model for performance-based pavement preservation programming that uses the weighting sum method and chance constraints. This model can handle multiple incommensurable and conflicting objectives while considering probabilistic constraints related to the available budget over the planning horizon, but is found more suitable to problems with small number of objective functions due to its computational intensity. To enhance the above model, a hybrid model that requires less computing time and systematically captures the decision maker's preferences on multiple objectives is developed by combining the analytic hierarchy process and goal programming. This model is further extended to also capture the relative importance existent within optimization constraints to be suitable for allocations of funding across multiple districts for a decentralized state department of transportation. Finally, as a continuation of the above proposed models for the succeeding management level, a project selection model capable of incorporating qualitative factors (e.g. equity, user satisfaction) into the decision making is developed. This model combines k-means clustering, analytic hierarchy process and integer linear programming. All the models are logically interconnected in a comprehensive resource allocation framework. Their feasibility, practicality and potential benefits are illustrated through various case studies and recommendations for further developments are provided.
Ph. D.

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Meyer, Danielle L. "Energy Optimization of a Hybrid Unmanned Aerial Vehicle (UAV)". The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523493111005807.

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Yeung, King-ho, i 楊景豪. "An optimization model for a solar hybrid water heating and adsorption ice-making system". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29632432.

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Shah, Kshitij P. "Calibration and Validation of a Hybrid Vehicle Model for its Implementation inOptimization Routines for Model-Based Fuel Economy Optimization". The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1501183963696296.

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Jiang, Siyu. "A Comparison of PSO, GA and PSO-GA Hybrid Algorithms for Model-based Fuel Economy Optimization of a Hybrid-Electric Vehicle". The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu156612591067731.

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Casoli, Paolo, Luca Riccò, Federico Campanini, Antonio Lettini i Cesare Dolcin. "Hydraulic Hybrid Excavator: Layout Definition, Experimental Activity, Mathematical Model Validation and Fuel Consumption Evaluation". Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-200473.

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Energy saving and fuel consumption reduction techniques are among the principal interests for both academic institutions and industries, in particular, system optimization and hybridization. This paper presents a new hydraulic hybrid system layout for mobile machinery implemented on a middle size excavator. The hybridization procedure took advantage of a dynamic programming (DP) algorithm, which was also utilized for the hybrid components dimensioning and control strategy definition. A dedicated experimental activity on test bench was performed on the main components of the energy recovery system (ERS). The JCMAS working cycle was considered as the reference test for a fuel consumption comparison between the standard and the hybrid excavator. A fuel saving up to 8% on the JCMAS cycle, and up to 11% during the digging cycle, has been allowed by the proposed hybrid system.

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Gupta, Shobhit. "Look-Ahead Optimization of a Connected and Automated 48V Mild-Hybrid Electric Vehicle". The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1554478434629481.

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Wang, Hong. "A new model in designing neural network in optimization : a hybrid neural network approach to machine scheduling". Connect to resource, 1998. http://rave.ohiolink.edu/etdc/view.cgi?acc%5Fnum=osu1261316668.

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EZEMOBI, ETHELBERT NWABUGWU. "Battery States Monitoring and its Application in Energy Optimization of Hybrid Electric Vehicles". Doctoral thesis, Politecnico di Torino, 2022. https://hdl.handle.net/11583/2970996.

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Stewart, Calvin. "A Hybrid Constitutive Model For Creep, Fatigue, And Creep-Fatigue Damage". Doctoral diss., University of Central Florida, 2013. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/6023.

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In the combustion zone of industrial- and aero- gas turbines, thermomechanical fatigue (TMF) is the dominant damage mechanism. Thermomechanical fatigue is a coupling of independent creep, fatigue, and oxidation damage mechanisms that interact and accelerate microstructural degradation. A mixture of intergranular cracking due to creep, transgranular cracking due to fatigue, and surface embrittlement due to oxidation is often observed in gas turbine components removed from service. The current maintenance scheme for gas turbines is to remove components from service when any criteria (elongation, stress-rupture, crack length, etc.) exceed the designed maximum allowable. Experimental, theoretical, and numerical analyses are performed to determine the state of the component as it relates to each criterion (a time consuming process). While calculating these metrics individually has been successful in the past, a better approach would be to develop a unified mechanical modeling that incorporates the constitutive response, microstructural degradation, and rupture of the subject material via a damage variable used to predict the cumulative “damage state” within a component. This would allow for a priori predictions of microstructural degradation, crack propagation/arrest, and component-level lifing. In this study, a unified mechanical model for creep-fatigue (deformation, cracking, and rupture) is proposed. It is hypothesized that damage quantification techniques can be used to develop accurate creep, fatigue, and plastic/ductile cumulative- nonlinear- damage laws within the continuum damage mechanics principle. These damage laws when coupled with appropriate constitutive equations and a degrading stiffness tensor can be used to predict the mechanical state of a component. A series of monotonic, creep, fatigue, and tensile-hold creep-fatigue tests are obtained from literature for 304 stainless steel at 600°C (1112°F) in an air. Cumulative- nonlinear- creep, fatigue, and a coupled creep-fatigue damage laws are developed. The individual damage variables are incorporated as an internal state variable within a novel unified viscoplasticity constitutive model (zero yield surface) and degrading stiffness tensor. These equations are implemented as a custom material model within a custom FORTRAN one-dimensional finite element code. The radial return mapping technique is used with the updated stress vector solved by Newton-Raphson iteration. A consistent tangent stiffness matrix is derived based on the inelastic strain increment. All available experimental data is compared to finite element results to determine the ability of the unified mechanical model to predict deformation, damage evolution, crack growth, and rupture under a creep-fatigue environment.
Ph.D.
Doctorate
Mechanical and Aerospace Engineering
Engineering and Computer Science
Mechanical Engineering

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Kraus, Kimberly L. "Optimization and Utilization of Hybrid Culture Between Rat and Fly Primary Neurons: A Novel Model for Studying Neurodegenerative Diseases". Ohio University Honors Tutorial College / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ouhonors1461325756.

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Chen, Minghan. "Stochastic Modeling and Simulation of Multiscale Biochemical Systems". Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/90898.

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Numerous challenges arise in modeling and simulation as biochemical networks are discovered with increasing complexities and unknown mechanisms. With the improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for quantitative stochastic models for gene and protein networks at cellular levels that match well with the data and account for cellular noise. This dissertation studies a stochastic spatiotemporal model of the Caulobacter crescentus cell cycle. A two-dimensional model based on a Turing mechanism is investigated to illustrate the bipolar localization of the protein PopZ. However, stochastic simulations are often impeded by expensive computational cost for large and complex biochemical networks. The hybrid stochastic simulation algorithm is a combination of differential equations for traditional deterministic models and Gillespie's algorithm (SSA) for stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks with multiscale features, which contain both species populations and reaction rates with widely varying magnitude. The populations of some reactant species might be driven negative if they are involved in both deterministic and stochastic systems. This dissertation investigates the negativity problem of the hybrid method, proposes several remedies, and tests them with several models including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of empirical data must be large enough to obtain statistically valid parameter estimates. To optimize system parameters, a quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic budding yeast cell cycle model by matching multivariate probability distributions between simulated results and empirical data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental cooperative binding mechanism by a stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different objective functions are explored targeting different features of the empirical data.
Doctor of Philosophy
Modeling and simulation of biochemical networks faces numerous challenges as biochemical networks are discovered with increased complexity and unknown mechanisms. With improvement in experimental techniques, biologists are able to quantify genes and proteins and their dynamics in a single cell, which calls for quantitative stochastic models, or numerical models based on probability distributions, for gene and protein networks at cellular levels that match well with the data and account for randomness. This dissertation studies a stochastic model in space and time of a bacterium’s life cycle— Caulobacter. A two-dimensional model based on a natural pattern mechanism is investigated to illustrate the changes in space and time of a key protein population. However, stochastic simulations are often complicated by the expensive computational cost for large and sophisticated biochemical networks. The hybrid stochastic simulation algorithm is a combination of traditional deterministic models, or analytical models with a single output for a given input, and stochastic models. The hybrid method can significantly improve the efficiency of stochastic simulations for biochemical networks that contain both species populations and reaction rates with widely varying magnitude. The populations of some species may become negative in the simulation under some circumstances. This dissertation investigates negative population estimates from the hybrid method, proposes several remedies, and tests them with several cases including a realistic biological system. As a key factor that affects the quality of biological models, parameter estimation in stochastic models is challenging because the amount of observed data must be large enough to obtain valid results. To optimize system parameters, the quasi-Newton algorithm for stochastic optimization (QNSTOP) was studied and applied to a stochastic (budding) yeast life cycle model by matching different distributions between simulated results and observed data. Furthermore, to reduce model complexity, this dissertation simplifies the fundamental molecular binding mechanism by the stochastic Hill equation model with optimized system parameters. Considering that many parameter vectors generate similar system dynamics and results, this dissertation proposes a general α-β-γ rule to return an acceptable parameter region of the stochastic Hill equation based on QNSTOP. Different optimization strategies are explored targeting different features of the observed data.

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Isaksson, Daniel. "Robust portfolio optimization with Expected Shortfall". Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-187888.

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This thesis project studies robust portfolio optimization with Expected Short-fall applied to a reference portfolio consisting of Swedish linear assets with stocks and a bond index. Specifically, the classical robust optimization definition, focusing on uncertainties in parameters, is extended to also include uncertainties in log-return distribution. My contribution to the robust optimization community is to study portfolio optimization with Expected Shortfall with log-returns modeled by either elliptical distributions or by a normal copula with asymmetric marginal distributions. The robust optimization problem is solved with worst-case parameters from box and ellipsoidal un-certainty sets constructed from historical data and may be used when an investor has a more conservative view on the market than history suggests. With elliptically distributed log-returns, the optimization problem is equivalent to Markowitz mean-variance optimization, connected through the risk aversion coefficient. The results show that the optimal holding vector is almost independent of elliptical distribution used to model log-returns, while Expected Shortfall is strongly dependent on elliptical distribution with higher Expected Shortfall as a result of fatter distribution tails. To model the tails of the log-returns asymmetrically, generalized Pareto distributions are used together with a normal copula to capture multivariate dependence. In this case, the optimization problem is not equivalent to Markowitz mean-variance optimization and the advantages of using Expected Shortfall as risk measure are utilized. With the asymmetric log-return model there is a noticeable difference in optimal holding vector compared to the elliptical distributed model. Furthermore the Expected Shortfall in-creases, which follows from better modeled distribution tails. The general conclusions in this thesis project is that portfolio optimization with Expected Shortfall is an important problem being advantageous over Markowitz mean-variance optimization problem when log-returns are modeled with asymmetric distributions. The major drawback of portfolio optimization with Expected Shortfall is that it is a simulation based optimization problem introducing statistical uncertainty, and if the log-returns are drawn from a copula the simulation process involves more steps which potentially can make the program slower than drawing from an elliptical distribution. Thus, portfolio optimization with Expected Shortfall is appropriate to employ when trades are made on daily basis.
Examensarbetet behandlar robust portföljoptimering med Expected Shortfall tillämpad på en referensportfölj bestående av svenska linjära tillgångar med aktier och ett obligationsindex. Specifikt så utvidgas den klassiska definitionen av robust optimering som fokuserar på parameterosäkerhet till att även inkludera osäkerhet i log-avkastningsfördelning. Mitt bidrag till den robusta optimeringslitteraturen är att studera portföljoptimering med Expected Shortfall med log-avkastningar modellerade med antingen elliptiska fördelningar eller med en norma-copul med asymmetriska marginalfördelningar. Det robusta optimeringsproblemet löses med värsta tänkbara scenario parametrar från box och ellipsoid osäkerhetsset konstruerade från historiska data och kan användas när investeraren har en mer konservativ syn på marknaden än vad den historiska datan föreslår. Med elliptiskt fördelade log-avkastningar är optimeringsproblemet ekvivalent med Markowitz väntevärde-varians optimering, kopplade med riskaversionskoefficienten. Resultaten visar att den optimala viktvektorn är nästan oberoende av vilken elliptisk fördelning som används för att modellera log-avkastningar, medan Expected Shortfall är starkt beroende av elliptisk fördelning med högre Expected Shortfall som resultat av fetare fördelningssvansar. För att modellera svansarna till log-avkastningsfördelningen asymmetriskt används generaliserade Paretofördelningar tillsammans med en normal-copula för att fånga det multivariata beroendet. I det här fallet är optimeringsproblemet inte ekvivalent till Markowitz väntevärde-varians optimering och fördelarna med att använda Expected Shortfall som riskmått används. Med asymmetrisk log-avkastningsmodell uppstår märkbara skillnader i optimala viktvektorn jämfört med elliptiska fördelningsmodeller. Därutöver ökar Expected Shortfall, vilket följer av bättre modellerade fördelningssvansar. De generella slutsatserna i examensarbetet är att portföljoptimering med Expected Shortfall är ett viktigt problem som är fördelaktigt över Markowitz väntevärde-varians optimering när log-avkastningar är modellerade med asymmetriska fördelningar. Den största nackdelen med portföljoptimering med Expected Shortfall är att det är ett simuleringsbaserat optimeringsproblem som introducerar statistisk osäkerhet, och om log-avkastningar dras från en copula så involverar simuleringsprocessen flera steg som potentiellt kan göra programmet långsammare än att dra från en elliptisk fördelning. Därför är portföljoptimering med Expected Shortfall lämpligt att använda när handel sker på daglig basis.

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Wissmann, Paul J. "Simultaneous approach to model building and process design using experimental design application to chemical vapor deposition /". Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26543.

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Thesis (Ph.D)--Chemical Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Grover, Martha; Committee Member: Garmestani, Hamid; Committee Member: Hess, Dennis; Committee Member: McDowell, David; Committee Member: Nenes, Athanasios; Committee Member: Realff, Matthew. Part of the SMARTech Electronic Thesis and Dissertation Collection.

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Tulpule, Pinak J. "Control and optimization of energy flow in hybrid large scale systems - A microgrid for photovoltaic based PEV charging station". The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1313522717.

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Li, Zongcheng. "Conceptual design of shapes by reusing existing heterogeneous shape data through a multi-layered shape description model and for VR applications". Thesis, Paris, ENSAM, 2015. http://www.theses.fr/2015ENAM0025/document.

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Les récentes avancées en matière de systèmes d'acquisition et de modélisation ont permis la mise à disposition d'une très grande quantité de données numériques (e.g. images, vidéos, modèles 3D) dans différents domaines d'application. En particulier, la création d'Environnements Virtuels (EVs) nécessite l'exploitation de données nu-mériques pour permettre des simulations et des effets proches de la réalité. Malgré ces avancées, la conception d'EVs dédiés à certaines applications requiert encore de nombreuses et parfois laborieuses étapes de modélisation et de traitement qui impliquent plusieurs experts (e.g. experts du domaine de l'application, experts en modélisation 3D et programmeur d'environnements virtuels, designers et experts communication/marketing). En fonction de l'application visée, le nombre et le profil des experts impliqués peuvent varier. Les limitations et difficultés d'au-jourd'hui sont principalement dues au fait qu'il n'existe aucune relation forte entre les experts du domaine qui ont des besoins, les experts du numérique ainsi que les outils et les modèles qui prennent part au processus de déve-loppement de l'EV. En fait, les outils existants focalisent sur des définitions souvent très détaillées des formes et ne sont pas capables de supporter les processus de créativité et d'innovation pourtant garants du succès d'un pro-duit ou d'une application. De plus, la grande quantité de données numériques aujourd'hui accessible n'est pas réellement exploitée. Clairement, les idées innovantes viennent souvent de la combinaison d'éléments et les don-nées numériques disponibles pourraient être mieux utilisées. Aussi, l'existence de nouveaux outils permettant la réutilisation et la combinaison de ces données serait d'une grande aide lors de la phase de conception conceptuelle de formes et d'EVs. Pour répondre à ces besoins, cette thèse propose une nouvelle approche et un nouvel outil pour la conception conceptuelle d'EVs exploitant au maximum des ressources existantes, en les intégrant et en les combinant tout en conservant leurs propriétés sémantiques. C'est ainsi que le Modèle de Description Générique de Formes (MDGF) est introduit. Ce modèle permet la combinaison de données multimodales (e.g. images et maillages 3D) selon trois niveaux : Conceptuel, Intermédiaire et Données. Le niveau Conceptuel exprime quelles sont les différentes parties de la forme ainsi que la façon dont elles sont combinées. Chaque partie est définie par un Elément qui peut être soit un Composant soit un Groupe de Composants lorsque ceux-ci possèdent des carac-téristiques communes (e.g. comportement, sens). Les Eléments sont liés par des Relations définies au niveau Con-ceptuel là où les experts du domaine interagissent. Chaque Composant est ensuite décrit au niveau Données par sa Géométrie, sa Structure et ses informations Sémantiques potentiellement attachées. Dans l'approche proposée, un Composant est une partie d'image ou une partie d'un maillage triangulaire 3D. Quatre Relations sont proposées (fusion, assemblage, shaping et localisation) et décomposées en un ensemble de Contraintes qui contrôlent la po-sition relative, l'orientation et le facteur d'échelle des Composants au sein de la scène graphique. Les Contraintes sont stockées au niveau Intermédiaire et agissent sur des Entités Clés (e.g. points, des lignes) attachées à la Géo-métrie ou à la Structure des Composants. Toutes ces contraintes sont résolues en minimisant une fonction énergie basée sur des grandeurs physiques. Les concepts du MDGF ont été implémentés et intégrés au sein d'un outil de design conceptuel développé par l'auteur. Différents exemples illustrent le potentiel de l'approche appliquée à différents domaines d'application
Due to the great advances in acquisition devices and modeling tools, a huge amount of digital data (e.g. images, videos, 3D models) is becoming now available in various application domains. In particular, virtual envi-ronments make use of those digital data allowing more attractive and more effectual communication and simula-tion of real or not (yet) existing environments and objects. Despite those innovations, the design of application-oriented virtual environment still results from a long and tedious iterative modeling and modification process that involves several actors (e.g. experts of the domain, 3D modelers and VR programmers, designers or communica-tions/marketing experts). Depending of the targeted application, the number and the profiles of the involved actors may change. Today's limitations and difficulties are mainly due to the fact there exists no strong relationships between the expert of the domain with creative ideas, the digitally skilled actors, the tools and the shape models taking part to the virtual environment development process. Actually, existing tools mainly focus on the detailed geometric definition of the shapes and are not suitable to effectively support creativity and innovation, which are considered as key elements for successful products and applications. In addition, the huge amount of available digital data is not fully exploited. Clearly, those data could be used as a source of inspiration for new solutions, being innovative ideas frequently coming from the (unforeseen) combination of existing elements. Therefore, the availability of software tools allowing the re-use and combination of such digital data would be an effective support for the conceptual design phase of both single shapes and VR environments. To answer those needs, this thesis proposes a new approach and system for the conceptual design of VRs and associated digital assets by taking existing shape resources, integrating and combining them together while keeping their semantic meanings. To support this, a Generic Shape Description Model (GSDM) is introduced. This model allows the combination of multimodal data (e.g. images and 3D meshes) according to three levels: conceptual, intermediate and data levels. The conceptual level expresses what the different parts of a shape are, and how they are combined together. Each part of a shape is defined by an Element that can either be a Component or a Group of Components when they share common characteristics (e.g. behavior, meaning). Elements are linked with Relations defined at the Concep-tual level where the experts in the domain are acting and exchanging. Each Component is then further described at the data level with its associated Geometry, Structure and potentially attached Semantics. In the proposed ap-proach, a Component is a part of an image or a part of a 3D mesh. Four types of Relation are proposed (merging, assembly, shaping and location) and decomposed in a set of Constraints which control the relative position, orien-tation and scaling of the Components within the 3D viewer. Constraints are stored at the intermediate level and are acting on Key Entities (such as points, a lines, etc.) laying on the Geometry or Structure of the Components. All these constraints are finally solved while minimizing an additional physically-based energy function. At the end, most of the concepts of GSDM have been implemented and integrated into a user-oriented conceptual design tool totally developed by the author. Different examples have been created using this tool demonstrating the potential of the approach proposed in this document

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Babajide, Nathaniel Akinrinde. "The electricity crisis in Nigeria : building a new future to accommodate 20% renewable electricity generation by 2030". Thesis, University of Dundee, 2017. https://discovery.dundee.ac.uk/en/studentTheses/7c6df776-e790-4afc-8970-3877d91a2663.

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As part of efforts to curb the protracted electricity problem in Nigeria, the government enacted the National Renewable Energy and Energy Efficiency Policy (NREEEP) in 2014. Through this policy, the country plans to increase its electricity generation from renewables to 20% by 2030. This thesis investigates the economic feasibility of this lofty goal, and as well determine the best hybrid configuration for off-grid rural/remote power generation across the six geopolitical zones of Nigeria The economic feasibility results, using Long-range Energy Alternative Planning (LEAP) tool, show that the 20% renewables goal in the Nigerian power generation mix by 2030 is economically feasible but will require vast investment, appropriate supportive mechanisms, both fiscal and non-fiscal (especially for solar PV) and unalloyed commitment on the part of the government. Moreover, the techno-economic results with Hybrid Optimization Model for Electric Renewable (HOMER) reveal Small hydro/Solar PV/Diesel generator/Battery design as the most cost-effective combination for power supply in remote/rural areas of Nigeria. Findings also highlight the better performance of this system in terms of fuel consumption and GHGs emission reduction. Lastly, the study identifies factors influencing RE development, and offers strategic and policy suggestions to advance RE deployment in Nigeria.

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Buffo, Marc. "Contribution à la conception, par validation numérique et expérimentale, et l’optimisation pour l’aéronautique de contacteur hybride haute tension DC". Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0024/document.

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Le concept de l'avion plus électrique a pour but de remplacer les différents types de transmissions de puissance aéronautique par des transmissions électriques. Le réseau électrique doit donc évoluer. Ce concept a inspiré le projet AEROCOTS dont une partie est la modification du moyen de coupure en un contacteur hybridé avec un circuit électrique. Afin de mieux comprendre ce qui se passe aux bornes du contacteur et vérifier qu'il n'y a pas apparition d'arc électrique, une méthode de caractérisation est employée pour obtenir un modèle complet du contacteur paramétré. Deux circuits électriques sont étudiés et l'absence d'un arc est vérifiée. Leur principe est de réduire à zéro le courant avant l'ouverture du contacteur. Leurs fonctionnements et leurs modèles sont vérifiés expérimentalement. Le choix du second circuit est justifié par un contrôle du courant à ouvrir. Une optimisation évolutionnaire, principe de la théorie de Darwin, est réalisée pour répondre aux objectifs aéronautiques
The main goal of the more electrical aircraft is to substitute the different kind of transmission for the aeronautical power by electrical transmissions. The electric network has to evolve. This concept inspires the project AEROCOTS, which a part lies in the modification of the breaking means thanks to a hybrid contactor with an electrical circuit. To better understand what occurs between the contacts of the contactor and verified the absence of an electrical arc, a characterization method is employed to have a complete parameterized model of a contactor. Two electrical circuits are studied and the absence of an arc is verified. Their principle is to reduce to zero the current before the opening of the contactor. Their functioning and their models are experimentally verified. The choice of the second circuit is justified by a control of the opening current. An evolutionary algorithm, principle of the Darwin's theory, is realized to answer to the aeronautical objectives

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Jonsson, Holm Erik. "Predictive Energy Management of Long-Haul Hybrid Trucks : Using Quadratic Programming and Branch-and-Bound". Thesis, Linköpings universitet, Fordonssystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178224.

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This thesis presents a predictive energy management controller for long-haul hybrid trucks. In a receding horizon control framework, the vehicle speed reference, battery energy reference, and engine on/off decision are optimized over a prediction horizon. A mixed-integer quadratic program (MIQP) is formulated by performing modelling approximations and by including the binary engine on/off decision in the optimal control problem. The branch-and-bound algorithm is applied to solve this problem. Simulation results show fuel consumption reductions between 10-15%, depending on driving cycle, compared to a conventional truck. The hybrid truck without the predictive control saves significantly less. Fuel consumption is reduced by 3-8% in this case. A sensitivity analysis studies the effects on branch-and-bound iterations and fuel consumption when varying parameters related to the binary engine on/off decision. In addition, it is shown that the control strategy can maintain a safe time gap to a leading vehicle. Also, the introduction of the battery temperature state makes it possible to approximately model the dynamic battery power limitations over the prediction horizon. The main contributions of the thesis are the MIQP control problem formulation, the strategy to solve this with the branch-and-bound method, and the sensitivity analysis.

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Hägglund, Andreas, i Moa Källgren. "Impact of Engine Dynamics on Optimal Energy Management Strategies for Hybrid Electric Vehicles". Thesis, Linköpings universitet, Fordonssystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148890.

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In recent years, rules and regulations regarding fuel consumption of vehicles and the amount of emissions produced by them are becoming stricter. This has led the automotive industry to develop more advanced solutions to propel vehicles to meet the legal requirements. The Hybrid Electric Vehicle is one of the solutions that is becoming more popular in the automotive industry. It consists of an electrical driveline combined with a conventional powertrain, propelled by either a diesel or petrol engine. Two power sources create the possibility to choose when and how to use the power sources to propel the vehicle. The strategy that decides how this is done is referred to as an energy management strategy. Today most energy management strategies only try to reduce fuel consumption using models that describe the steady state behaviour of the engine. In other words, no reduction of emissions is achieved and all transient behaviour is considered negligible. In this thesis, an energy management strategy incorporating engine dynamics to reduce fuel consumption and nitrogen oxide emissions have been designed. First, the models that describe how fuel consumption and nitrogen oxide emissions behave during transient engine operation are developed. Then, an energy management strategy is developed consisting of a model predictive controller that combines the equivalent consumption minimization strategy and convex optimization. Results indicate that by considering engine dynamics in the energy management strategy, both fuel consumption and nitrogen oxide emissions can be reduced. Furthermore, it is also shown that the major reduction in fuel consumption and nitrogen oxide emissions is achieved for short prediction horizons.

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ZANELLI, ALESSANDRO. "Development of a Comprehensive 0-1D Powertrain and Vehicle Model for the Analysis of an Innovative 48 V Mild-Hybrid Diesel Passenger Car". Doctoral thesis, Politecnico di Torino, 2020. http://hdl.handle.net/11583/2842511.

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Quaratino, Marco. "Virtual Calibration of CO2 and Pollutant Emissions of a High-Performance PHEV using Model-in-the-Loop Methodology". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/22053/.

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The study analyses the calibration process of a newly developed high-performance plug-in hybrid electric passenger car powertrain. The complexity of modern powertrains and the more and more restrictive regulations regarding pollutant emissions are the primary challenges for the calibration of a vehicle’s powertrain. In addition, the managers of OEM need to know as earlier as possible if the vehicle under development will meet the target technical features (emission included). This leads to the necessity for advanced calibration methodologies, in order to keep the development of the powertrain robust, time and cost effective. The suggested solution is the virtual calibration, that allows the tuning of control functions of a powertrain before having it built. The aim of this study is to calibrate virtually the hybrid control unit functions in order to optimize the pollutant emissions and the fuel consumption. Starting from the model of the conventional vehicle, the powertrain is then hybridized and integrated with emissions and aftertreatments models. After its validation, the hybrid control unit strategies are optimized using the Model-in-the-Loop testing methodology. The calibration activities will proceed thanks to the implementation of a Hardware-in-the-Loop environment, that will allow to test and calibrate the Engine and Transmission control units effectively, besides in a time and cost saving manner.

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Fouquet, Manon. "Commande prédictive non-linéaire. Application à la production d'énergie". Thesis, CentraleSupélec, 2016. http://www.theses.fr/2016SUPL0003/document.

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Cette thèse porte sur l'optimisation et la commande prédictive des centrales de production d'énergie en utilisant des modèles physiques des installations. Les modèles sont réalisés à l'aide du langage Modelica, un langage équationnel adapté à la modélisation de systèmes multi-physiques. La modélisation de systèmes physiques dans ce langage est présentée dans une première partie, ainsi que les traitements symboliques réalisés par les compilateurs Modelica pour mettre les modèles sous une forme adaptée à l'optimisation. On présente dans une seconde partie le développement d'une méthode d'optimisation dynamique hybride pour les centrales de production d'énergie, qui fournit une trajectoire optimisée de l'installation sur un horizon long. Les trajectoires calculées incluent les trajectoires des commandes continues ainsi que les décisions d'engagement des différents équipements. L'algorithme d'optimisation combine la méthode de collocation et une méthode nommée Sum Up Rounding (SUR) pour la prise en compte des décisions d'engagement. Un algorithme de commande prédictive (MPC) est enfin introduit afin de garantir le suivi des trajectoires optimales et de prendre en compte en temps réel la présence de perturbations et les erreurs du modèle d'optimisation. L'algorithme MPC utilise des modèles linéarisés tangents générés automatiquement à partir du modèle non linéaire
This thesis deals with hybrid optimal control and Model Predictive Control (MPC) of power plants by use of physical models. Models of the facilities are developped with Modelica, an equation based language tailored for modelling multi-physics systems. Modeling of physical systems with Modelica is introduced in a first part, as well as some of the symbolic processing done by Modelica compilers that transform the original model to a form suited for optimization. Then, a method to solve optimal control problems on hybrid systems (such as power plants) is presented. This methods provides an optimal trajectory for the power plant on a long horizon. The optimal trajectory computed by the method includes the trajectories of continuous inputs as well as switching decisions for components in the plant. The optimization algorithm combines the collocation method and a method named Sum Up Rounding (SUR) for dealing with switches. Finally, a Model Predictive Controller is developped in order to follow this optimal trajectory in real time, and to cope with disturbances on the actual system and modelling errors. The proposed MPC uses tangent linear models of the plant that are derived automatically from the nonlinear model

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Ben, beldi Nesrine. "Modélisation et optimisation des systèmes complexes en conception innovante : application aux chaines de transmission hybrides". Thesis, Paris, ENSAM, 2015. http://www.theses.fr/2015ENAM0028.

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Dans un contexte industriel qui évolue rapidement et constamment, les constructeurs automobiles sont amenés à développer des produits qui soient en adéquation avec des demandes d'un marché international et qui respectent en même temps les contraintes réglementaires imposées. Les systèmes de chaine de transmission hybrides rentrent donc dans cette volonté des constructeurs à vouloir proposer des produits véhicules performants, à faible coût et respectant les contraintes d'émission de gaz polluants. A travers le travail effectué dans cette thèse, nous proposons une démarche de conception permettant de modéliser un système technique complexe à différents niveaux systémiques au cours du cycle de conception, de l'optimiser localement à partir des expertises métiers, de modéliser les connaissances collaboratives qui sont échangées entre les modèles métiers et d'optimiser l'espace de conception afin de converger vers une solution de conception optimale dans un contexte d'innovation ou nous partons de la feuille blanche.L'objectif de ce travail est de proposer une nouvelle façon d'aborder les problèmes de conception des systèmes complexes, qui s'adapte au contexte de conception innovante tout comme la conception routinière. Ceci afin de permettre aux entreprises telles que PSA Peugeot Citroën de pouvoir proposer des produits avec des technologies à forte rupture tout en réduisant leurs coûts et garantir leurs images de marque. Ce travail a été illustré et validé à travers les résultats obtenus dans le cadre du projet de conception de chaine de transmission hybride MTI effectué au département d'innovation de PSA Peugeot Citroën
In an industrial context that is continuously evolving and changing, automotive constructors find themselves obliged to develop their products by taking into account the requirements of an international market and the imposed regulations in this field. Hybrid powertrain systems fits into this constructor will to propose to customers efficient products that respects the regulation regarding gas emissions and presents a profitable low cost. Through the work done in this PhD, we propose a design approach that allow the modeling of a complex technical system in its different systemic levels during the design process, the local optimization done from professional expertise, the modeling of collaborative data exchanged between expert models and the optimization of the design space in order to converge towards an optimal design solution in innovative context.The aim of our work is to propose a new way of dealing with design problems related to complex systems that can be adapted to an innovative design context. This will allow companies such as PSA Peugeot Citroen to be able to diversify their products and integrated even the latest technology in it. This work has been illustrated and validated through the results obtained on the MTI project for the design of hybrid powertrain

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Eeles, Charles William Owen. "Parameter optimization of conceptual hydrological models". Thesis, Open University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.261674.

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Roth, Anastasia. "Développement de méthodologies génériques pour la conception optimale et durable des parcs hybrides d'énergies renouvelables". Thesis, Toulouse, INPT, 2019. http://www.theses.fr/2019INPT0036/document.

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Les enjeux planétaires du développement durable et du réchauffement climatique remettent en cause le fonctionnement de nos sociétés. La transition énergétique se traduit notamment par l’augmentation de l’utilisation des énergies renouvelables et constitue ainsi le contexte de nos travaux. Dans le cadre d’un contrat CIFRE avec l’entreprise VALOREM, nous proposons des méthodologies pour le développement et la conception d’installations renouvelables soutenables. L’approche d’Ingénierie Des Modèles mise en place nous permet de garder une démarche scientifique cohérente entre une vue très générale du contexte d’insertion des renouvelables et une vision plus technique et opérationnelle pour le développement d’installations renouvelables. Dans un premier temps, nous avons décrit de manière macroscopique le contexte d’insertion des énergies renouvelables en France, en proposant un cadre conceptuel pour le développement de projet d’aménagement du territoire. Il permet l’analyse des systèmes sociotechniques en transition grâce à une formalisation UML2 d’une part, et une méthode d’évaluation de la durabilité d’un processus d’autre part. Nous avons illustré ce cadre sur deux cas d’étude : le succès du développement de la centrale hydro-éolienne de l’île d’El Hierro dans les Canaries et l’échec du barrage de Sivens dans le Tarn en France. Par comparaison, nous montrons que l’implication des parties prenantes sur l’ensemble du processus de développement est cruciale pour le succès d’un projet. Nous avons ensuite proposé une implémentation logicielle permettant le suivi et le pilotage de projet d’aménagement du territoire en temps réel à l’aide d’outils d’intelligence artificielle. Conscient des limites opérationnelles de notre proposition, nous avons décidé de changer de point de vue pour adopter une vision plus technique sur les énergies renouvelables. La transition énergétique fait évoluer le système électrique français d’un modèle centralisé vers un modèle décentralisé, ce qui amène VALOREM à reconsidérer ses propositions techniques de production d’énergies renouvelables. Entre autre, l’entreprise tend vers l’hybridation de ses centrales et constate le besoin d’un outil de dimensionnement en phase d’avant-projet, afin d’identifier les opportunités d’activités. Nous faisons donc la proposition d’un prototype logiciel qui se veut flexible en termes de modélisation des centrales de production hybrides renouvelables et en termes de définition des objectifs et contraintes à satisfaire. Il est codé en C++ et basé sur des modèles d’optimisation linéaires. Nous illustrons son opérationnalité sur quatre cas d’étude : deux orientés marché électrique et deux en autoconsommation (l’un isolé, l’autre connecté au réseau). Les résultats des études montrent que les coûts de stockage batterie sont trop élevés pour pouvoir envisager l’installation de batteries dans les centrales hybrides renouvelables. Les systèmes en autoconsommation connectés au réseau semblent être plus prometteurs. Enfin, nous terminons par une analyse environnementale de différentes sources de production électrique afin de déterminer celles vers lesquelles la transition énergétique doit être axée. Les résultats montrent que la biomasse, l’éolien et le PV au sol sont les moyens de production les plus propres. La conclusion de la thèse propose une réflexion ascendante en complexité vers l’implication des acteurs dans les modèles de processus de développement territoriaux
Sustainable growth issues and climate change imply to shift our society organisation towards new paradigms. In the energy sector, it is illustrated by an energy transition via renewables. Within this context and the support of the company VALOREM, we propose a methodology for the sustainable development and design of renewable infrastructures. By using a Model Driven Engineering approach, we were able to adopt several viewpoints on renewable energy issues, while keeping a consistent scientific approach. First of all, from a holistic stance, we developed a conceptual framework for land settlement development process. Thanks to its modelling with UML2 and a methodology to assess the sustainability of processes, it can be used to analyse the trajectory of sociotechnical systems. The framework was tested on two case studies: the success of El Hierro hydrowind power plant implementation in Canary Islands and the failure of the Sivens dam project in the south of France. Their comparison shows that implication of stakeholders at all stages of the development process is crucial for the success of the project. We further propose to implement the conceptual framework as a software tool for the monitoring of land settlement project in real time, with the help of artificial intelligence concepts. However, this proposition was deemed not in line with Valorem’s priorities and we decided to focus on a technical instantiation of the framework for Hybride Renewable Energy Systems (HRES), which design and operation are part of VALOREM’s activity. As, the energy transition implies to change the electrical system model from a centralized to a decentralized one, there exists a need for a grassroots sizing tool for identifying new HRES opportunities. A software prototype for the grassroot optimal design of HRES was developed, offering flexibility in terms of modelling, setting constraints and defining objective functions. It is coded in C++ and based on linear programming model. We showed its relevance on four HRES case studies: two related to electricity market and two for self-supply of energy (one isolated and the other grid-connected). The results show that battery costs are too high to be profitable in HRES and that grid-connected systems seems to be a good alternative. Finally, we carried out an environmental impact assessment of several sources of electricity production to find out which are the “cleaner” ones. The results show that biomass, wind turbines and ground PV are those that should be considered for a sustainable energy transition. In the conclusion, we step back to a more complex viewpoint and develop perspectives to model human interactions within territory development process

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Morávek, Jan. "Procesy řízení v energetických systémech s alternativními zdroji energie". Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2017. http://www.nusl.cz/ntk/nusl-364616.

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The dissertation is an publication summary focused on the field of management processes in renewable energy systems, mathematical models and optimization possibilities for large and small scale photovoltaic systems. The articles were published in foreign impacted and reviewd journals and indexed proceedings of foreign and domestic conferences. The main results of the dissertation are the design, configuration and realization of the hybrid energy system with subsequent optimization. Using the data from the laboratory system, a mathematical model was compiled and subsequently validated in the Matlab/Simulink environment for a hybrid energy system with accumulation. The options for power production optimization with photovoltaic sources are based on both operational measurements (for commercial applications) and on the analysis of power flow controllers to optimize the~energy balance (for small scale applications in private buildings).

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Oesterle, Jonathan. "Holistic approach to designing hybrid assembly lines A comparative study of Multi-Objective Algorithms for the Assembly Line Balancing and Equipment Selection Problem under consideration of Product Design Alternatives Evaluation of the influence of dominance rules for the assembly line design problem under consideration of product design alternatives Hybrid Multi-objective Optimization Method for Solving Simultaneously the line Balancing, Equipment and Buffer Sizing Problems for Hybrid Assembly Systems Comparison of Multiobjective Algorithms for the Assembly Line Balancing Design Problem Efficient multi-objective optimization method for the mixed-model-line assembly line design problem Detaillierungsgrad von Simulationsmodellen Rechnergestützte Austaktung einer Mixed-Model Line. Der Weg zur optimalen Austaktung". Thesis, Troyes, 2017. http://www.theses.fr/2017TROY0012.

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Le travail présenté dans cette thèse concerne la formulation et la résolution de deux problèmes d'optimisation multi-objectifs. Ces problèmes de décision, liés à une approche holistique, ont pour but de sélectionner la meilleure configuration « produit/ligne d’assemblage » à partir d'un ensemble de design produits, et de ressources. Concernant le premier problème, un modèle de coût a été développé afin de traduire les interdépendances complexes entre la sélection d’un design produit et les caractéristiques des ressources. Une étude empirique est proposée et vise à comparer, selon plusieurs indicateurs de qualité multi-objectifs, différentes méthodes de résolution - comprenant des algorithmes génétiques, de colonies de fourmis, d’optimisation par essaims particulaires, des chauves-souris, de recherche du coucou et de pollinisation des fleurs. Plusieurs règles de dominance et une recherche locale spécifique au problème ont été appliquées aux méthodes de résolution les plus prometteuses. Concernant le second problème, qui se penche également sur le dimensionnement des stocks tampons, les méthodes de résolution sont à un modèle de simulation à événements discrets, dont la fonction première est l’évaluation des valeurs des différentes fonctions objectives. L’approche holistique associée aux deux problèmes a été validée avec deux cas industriels
The work presented in this thesis concerns the formulation and the resolution of two holistic multi-objective optimization problems associated with the selection of the best product and hybrid assembly line configuration out of a set of products, processes and resources alternatives. Regarding the first problem, a cost model was developed in order to translate the complex interdependencies between the selection of specific product designs, processes and resources characteristics. An empirical study is proposed, which aimed at comparing, according to several multi-objective quality indicators, various resolution methods – including variants of evolutionary algorithms, ant colony optimization, particle swarm optimization, bat algorithms, cuckoo search algorithms, and flower-pollination algorithms. Several dominance rules and a problem-specific local search were applied to the most promising resolution methods. Regarding the second problem, which also considers the buffer sizing, the developed algorithms were enhanced with a genetic discrete-event simulation model, whose primary function is to evaluate the value of the various objective functions. The demonstration of the associated resolution frameworks for both problems was validated through two industrial-cases

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Alam, Muhammad Mahtab. "Power-Aware adaptive techniques for wireless sensor networks". Thesis, Rennes 1, 2013. http://www.theses.fr/2013REN1S049/document.

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Les Réseaux de capteurs sans fil (WSN) sont une technologie émergente avec des applications potentielles dans divers domaines de la vie quotidienne, tels que la surveillance structurelle et environnementale, la médecine, la surveillance militaire, les explorations robotisées, etc. Les nœuds de capteurs doivent fonctionner pendant une longue période avec des batteries capacité limitée, par conséquent le facteur plus important dans les WSN est la consommation d'énergie. Dans cette thèse, nous proposons des techniques d'optimisation algorithmiques dynamiques, et adaptative pour la réduction de l'énergie. Tout d'abord, un modèle énergétique précis est présenté. Ce modèle repose sur des mesures réelles de courant consommé pour différents scénarios qui peuvent se produire lors de la communication entre les nœud. Il en est conclu que la couche MAC joue un rôle essentiel dans la réduction de l'énergie consommée. Ensuite, un protocole MAC dynamique est présenté. Il adapte de manière dynamique l’intervalle de réveil des nœuds de capteurs à partir d’une estimation du trafic. L’algorithme adaptatif modélisé de façon heuristique pour comprendre le comportement de convergence des paramètres algorithmiques. Le protocole est appliqué sur des réseaux de capteurs corporels et il surclasse les autres protocoles MAC en termes de latence ainsi que de consommation d'énergie ce qui permet donc d'augmenter la durée de vie de trois à six fois. Enfin, une technique basée sur l’optimisation adaptative de la puissance d'émission radio est appliquée sur des canaux variant dans le temps. La puissance de sortie est réglée dynamiquement au meilleur niveau de puissance selon l’état du canal, ce qui diminue la consommation d’un facteur deux
Wireless Sensor Networks (WSN) are a fast emerging technology with potential applications in various domains of daily-life, such as structural and environmental monitoring, medicine, military surveillance, robotic explorations etc. WSN devices are required to operate for a long time with limited battery capacity, therefore, the most important constraint in WSN is energy consumption. In this thesis, we propose algorithmic-level dynamic and adaptive optimization techniques for energy reduction in WSN. First, an accurate energy model is presented. This model relies on real-time power measurements of various scenarios that can occur during communication between sensor nodes. It is concluded that MAC layer plays a pivotal role for energy reduction. Then, a traffic-aware dynamic MAC protocol is presented which dynamically adapts the wake-up schedule of sensor nodes through traffic estimation. An adaptive algorithm is designed for this purpose that is heuristically modeled to understand the convergence behavior of algorithmic parameters. The proposed protocol is applied to body area networks and it outperforms other low-power MAC protocols in terms of latency as well as energy consumption and consequently increases the lifetime from three to six times. Finally, an SNR-based adaptive transmit power optimization technique is applied under time-varying channels. The output power is dynamically tuned to best power level under slow varying channel, which results in an average gain by two times

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Aslan, Murat Samil. "Tracker-aware Detection: A Theoretical And An Experimental Study". Phd thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610474/index.pdf.

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A promising line of research attempts to bridge the gap between detector and tracker by means of considering jointly optimal parameter settings for both of these subsystems. Along this fruitful path, this thesis study focuses on the problem of detection threshold optimization in a tracker-aware manner so that a feedback from the tracker to the detector is established to maximize the overall system performance. Special emphasis is given to the optimization schemes based on two non-simulation performance prediction (NSPP) methodologies for the probabilistic data association filter (PDAF), namely, the modified Riccati equation (MRE) and the hybrid conditional averaging (HYCA) algorithm. The possible improvements are presented in two domains: Non-maneuvering and maneuvering target tracking. In the first domain, a number of algorithmic and experimental evaluation gaps are identified and newly proposed methods are compared with the existing ones in a unified theoretical and experimental framework. Furthermore, for the MRE based dynamic threshold optimization problem, a closed-form solution is proposed. This solution brings a theoretical lower bound on the operating signal-to-noise ratio (SNR) concerning when the tracking system should be switched to the track before detect (TBD) mode. As the improvements of the second domain, some of the ideas used in the first domain are extended to the maneuvering target tracking case. The primary contribution is made by extending the dynamic optimization schemes applicable to the PDAF to the interacting multiple model probabilistic data association filter (IMM-PDAF). Resulting in an online feedback from the filter to the detector, this extension makes the tracking system robust against track losses under low SNR values.

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Freitas, Oliveira Rui Manuel. "Supervision, control and optimization of biotechnological processes based on hybrid models /". [S.l. : s.n.], 1998. http://deposit.ddb.de/cgi-bin/dokserv?idn=960441417.

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Ku, Jieun. "A Hybrid Optimization Scheme for Helicopters with Composite Rotor Blades". Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16268.

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Rotorcraft optimization is a challenging problem due to its conflicting requirements among many disciplines and highly coupled design variables affecting the overall design. Also, the design process for a composite rotor blade is often ambiguous because of its design space. Furthermore, analytical tools do not produce acceptable results compared with flight test when it comes to aerodynamics and aeroelasticity unless realistic models are used, which leads to excessive computer time per iteration. To comply these requirements, computationally efficient yet realistic tools for rotorcraft analysis, such as VABS and DYMORE were used as analysis tools. These tools decompose a three-dimensional problem into a two-dimensional cross-sectional and a one-dimensional beam analysis. Also, to eliminate the human interaction between iterations, a previously VABS-ANSYS macro was modified and automated. The automated tool shortened the computer time needed to generate the VABS input file for each analysis from hours to seconds. MATLAB was used as the wrapper tool to integrate VABS, DYMORE and the VABS-ANSYS macro into the methodology. This methodology uses Genetic Algorithm and gradient-based methods as optimization schemes. The baseline model is the rotor system of generic Georgia Tech Helicopter (GTH), which is a three-bladed, soft-in-plane, bearingless rotor system. The resulting methodology is a two-level optimization, global and local. Previous studies showed that when stiffnesses are used as design variables in optimization, these values act as if they are independent and produce design requirements that cannot be achieved by local-level optimization. To force design variables at the global level to stay within the feasible design space of the local level, a surrogate model was adapted into the methodology. For the surrogate model, different ``design of experiments" (DOE) methods were tested to find the most computationally efficient DOE method. The response surface method (RSM) and Kriging were tested for the optimization problem. The results show that using the surrogate model speeds up the optimization process and the Kriging model shows superior performance over RSM models. As a result, the global-level optimizer produces requirements that the local optimizer can achieve.

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Chun, So Yeon. "Hybrid is good: stochastic optimization and applied statistics for or". Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/44717.

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In the first part of this thesis, we study revenue management in resource exchange alliances. We first show that without an alliance the sellers will tend to price their products too high and sell too little, thereby foregoing potential profit, especially when capacity is large. This provides an economic motivation for interest in alliances, because the hope may be that some of the foregone profit may be captured under an alliance. We then consider a resource exchange alliance, including the effect of the alliance on competition among alliance members. We show that the foregone profit may indeed be captured under such an alliance. The problem of determining the optimal amounts of resources to exchange is formulated as a stochastic mathematical program with equilibrium constraints. We demonstrate how to determine whether there exists a unique equilibrium after resource exchange, how to compute the equilibrium, and how to compute the optimal resource exchange. In the second part of this thesis, we study the estimation of risk measures in risk management. In the financial industry, sell-side analysts periodically publish recommendations of underlying securities with target prices. However, this type of analysis does not provide risk measures associated with underlying companies. In this study, we discuss linear regression approaches to the estimation of law invariant conditional risk measures. Two estimation procedures are considered and compared; one is based on residual analysis of the standard least squares method and the other is in the spirit of the M-estimation approach used in robust statistics. In particular, Value-at-Risk and Average Value-at-Risk measures are discussed in detail. Large sample statistical inference of the estimators is derived. Furthermore, finite sample properties of the proposed estimators are investigated and compared with theoretical derivations in an extensive Monte Carlo study. Empirical results on the real data (different financial asset classes) are also provided to illustrate the performance of the estimators.

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Sattar, Abdul. "Face analysis by using hybrid single objective and hybrid multiple objective optimizations in 2. 5D active appearance model". Rennes 1, 2010. http://www.theses.fr/2010REN1S021.

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L'équipe SCEE de Supélec travaille dans le domaine de la radio logicielle et intelligente, encore appelée Radio Cognitive (CR - Cognitive Radio). Dans cette thèse, nous avons présenté une solution pour l'analyse de visage temps réel dans un équipement de radio cognitive. Dans ce cadre particulier, nous proposons des solutions d'analyse de visage, à savoir «l'estimation de la pose et des caractéristiques faciale d'un visage inconnu orienté ». Nous proposons deux systèmes d'alignement de visages. 1) Le premier exploite un AAM 2. 5D et une seule caméra. La phase d'optimisation de cet AAM est hybride: elle mixe un algorithme génétique et une descente de gradient. Notre contribution tient dans l'opérateur de descente de gradient qui travaille de concert avec l'opérateur classique de mutation : de cette manière sa présence ne pénalise pas la vitesse d'exécution du système. 2) Le second met en œuvre un AAM 2. 5D mais exploite plusieurs caméras. La recherche de la meilleure solution découle également d'une approche hybride qui mixe une optimisation multi-objectifs : le NSGA-II, avec une descente de gradient. Notre contribution tient dans la proposition d'une méthode efficace pour extraire des informations concernant la pertinence de chacune des vues, ces informations sont ensuite exploitées par la descente de gradient. Des comparaisons quantitatives et qualitatives avec d'autres approches mono et multi-objectifs montrent l'intérêt de notre méthode lorsqu'il s'agit d'évaluer la pose et les traits caractéristiques d'un visage inconnu
In this study we are interested in the pose estimation and precise localization of face features such as the eyes, the nose and the mouth of an out-of-plane rotated unknown face. Main application of this thesis work is in the Cognitive Radio equipments. We place ourselves within the framework of a low quality acquisition with camera(s) installed on Cognitive Radio equipments e. G. Mobile phone, laptop, desktop computers etc. The face pose and localization of facial features in an unconstrained environment are the major problems for CR equipment. All of its subsequent face related applications (e. G. Face recognition, face synthesis, face data compression etc. ) highly depend upon the methods used for the facial analysis system. In order to extract face features, we use the Active Appearance Models (AAM), deformable models allowing shape and texture to be jointly synthesized. We initially propose a new 2. 5D AAM, based on 3D model, which makes it possible to perform pose estimation and features localization of an oriented face. Secondly, we propose a new optimization methodology for the face search by AAM, in a single camera system, by the hybridization of deterministic and direct search method which has never been used and tested before. Our method hybridizes Gradient Descent (GD) inside the Genetic Algorithm (GA) in a unique way. Along with other operators of GA we propose gradient operator which works in conjunction with the mutation operator of GA thus it does not make the system computationally expensive. Finally for a complete facial analysis system by multiple cameras, we proposed a new concept of multi-objective AAM. In this method, facial images from multiple cameras are analyzed simultaneously by 2. 5D AAM. For the face search optimization we propose a unique way of hybridizing GD with NSGA-II (Non-dominating Search Genetic Algorithm-II). Both of our propositions are robust, real time, efficient and extract facial features even in unknown and out-of-plane rotated faces

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BOGGERO, LUCA. "Design techniques to support aircraft systems development in a collaborative MDO environment". Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2710702.

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The aircraft design is a complex multidisciplinary and collaborative process. Thousands of disciplinary experts with different design competences are involved within the whole development process. The design disciplines are often in contrast with each other, as their objectives might be not coincident, entailing compromises for the determination of the global optimal solution. Therefore, Multidisciplinary Design and Optimization (MDO) algorithms are being developed to mathematically overcome the divergences among the design disciplines. However, a MDO formulation might identify an optimal solution, but it could be not sufficient to ensure the success of a project. The success of a new project depends on two factors. The first one is relative to the aeronautical product, which has to be compliant with all the capabilities actually demanded by the stakeholders. Furthermore, a “better” airplane may be developed in accordance with customer expectations concerning better performance, lower operating costs and fewer emissions. The second important factor refers to the competitiveness among the new designed product and all the other competitors. The Time-To-Market should be reduced to introduce in the market an innovative product earlier than the other aeronautical industries. Furthermore, development costs should be decreased to maximize profits or to sell the product at a lower price. Finally, the development process must reduce all the risks due to wrong design choices. These two main motivations entail two main objectives of the current dissertation. The first main objective regards the assessment and development of design techniques for the integration of the aircraft subsystems conceptual design discipline within a collaborative and multidisciplinary development methodology. This methodology shall meet all the necessities required to design an optimal and competitive product. The second goal is relative to the employment of the proposed design methodology for the initial development of innovative solutions. As the design process is multidisciplinary, this thesis is focused on the on-board systems discipline, without neglecting the interactions among this discipline with all the other design disciplines. Thus, two kinds of subsystems are treated in the current dissertation. The former deals with hybrid-electric propulsion systems installed aboard Remotely Piloted Aerial Systems (RPASs) and general aviation airplanes. The second case study is centered on More and All Electric on-board system architectures, which are characterized by the removal of the hydraulic and/or pneumatic power generation systems in favor of an enhancement of the electrical system. The proposed design methodology is based on a Systems Engineering approach, according to which all the customer needs and required system functionalities are defined since the earliest phase of the design. The methodology is a five-step process in which several techniques are implemented for the development of a successful product. In Step 1, the design case and the requirements are defined. A Model Based Systems Engineering (MBSE) approach is adopted for the derivation and development of all the functionalities effectively required by all the involved stakeholders. All the design disciplines required in the MDO problem are then collected in Step 2. In particular, all the relations among these disciplines – in terms of inputs/outputs – are outlined, in order to facilitate their connection and the setup of the design workflow. As the present thesis is mainly focused on the on-board system design discipline, several algorithms for the preliminary sizing of conventional and innovative subsystems (included the hybrid propulsion system) are presented. In the third step, an MDO problem is outlined, determining objectives, constraints and design variables. Some design problems are analyzed in the present thesis: un-converged and converged Multidisciplinary Design Analysis (MDA), Design Of Experiments (DOE), optimization. In this regard, a new multi-objective optimization method based on the Fuzzy Logic has been developed during the doctoral research. This proposed process would define the “best” aircraft solution negotiating and relaxing some constraints and requirements characterized by a little worth from the user perspective. In Step 4, the formulation of the MDO problem is then transposed into a MDO framework. Two kinds of design frameworks are here considered. The first one is centered on the subsystems design, with the aim of preliminarily highlighting the impacts of this discipline on the entire Overall Aircraft Design (OAD) process and vice-versa. The second framework is distributed, as many disciplinary experts are involved within the design process. In this case, the level of fidelity of the several disciplinary modules is higher than the first framework, but the effort needed to setup the entire workflow is much higher. The proposed methodology ends with the investigation of the design space through the implemented framework, eventually selecting the solution of the design problem (Step 5). The capability of the proposed methodology and design techniques is demonstrated by means of four application cases. The first case study refers to the initial definition of the physical architecture of a hybrid propulsion system based on a set of needs and capabilities demanded by the customer. The second application study is focused on the preliminary sizing of a hybrid-electric propulsion system to be installed on a retrofit version of a well-known general aviation aircraft. In the third case study, the two kinds of MDO framework previously introduced are employed to design conventional, More Electric and All Electric subsystem architectures for a 90-passenger regional jet. The last case study aims at minimizing the aircraft development costs. A Design-To-Cost approach is adopted for the design of a hybrid propulsion system.

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Küttler, Sulivan. "Dimensionnement optimal de machines synchrones pour des applications de véhicules hybrides". Phd thesis, Université de Technologie de Compiègne, 2013. http://tel.archives-ouvertes.fr/tel-01023815.

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Les travaux de recherche présentés dans ce document portent sur le dimensionnement de machines synchrones pour des applications de véhicules hybrides. L'utilisation de la machine électrique au sein du véhicule hybride est caractérisée par des appels de puissance de courtes durées. Cette thèse propose donc une stratégie de dimensionnement permettant de minimiser considérablement le volume de l'actionneur par la prise en compte des limites thermiques réelles lors du cycle de conduite. La stratégie de dimensionnement est composée de deux étapes. La première étape est l'optimisation du dimensionnement de l'actionneur à partir des points de fonctionnement du cycle. Nous autorisons des niveaux d'induction dans le fer élevés et des niveaux de densité de courant dans les conducteurs dépassant les niveaux habituellement autorisés pour un fonctionnement en régime permanent thermique. Ces deux points ont un impact réel sur le volume de la machine. Cela-dit, à ce stade, la thermique de la machine n'est prise en compte qu'indirectement en fixant une densité de courant dans les conducteurs. La seconde étape permet alors de vérifier la thermique par une simulation sur cycle pour ensuite réajuster si besoin la densité de courant et reprendre la première étape d'optimisation de la machine. Des modèles adaptés au processus d'optimisation ont alors été mis en place et offrent un bon compromis entre le temps de calcul et la précision requise. Par conséquent, un modèle magnétique prenant en compte la saturation croisée dans la machine utilisant la méthode nodale a été développé ; un modèle permettant une meilleure prise en compte des pertes fer notamment dans le zone de défluxage a également été développé ainsi qu'un modèle thermique en transitoire utilisant également la méthode nodale. Le modèle thermique étant la clé de la stratégie de dimensionnement, une grande attention y a été portée. Ce modèle permet de prendre en compte la direction des flux dans les trois dimensions et fournit de bonnes estimations des températures dans la machine notamment aux endroits les plus chauds comme les encoches et les têtes de bobines. Ces résultats ont été corroborés par des essais expérimentaux réalisés dans les bancs IFPEN sur une machine spécialement instrumentée en thermocouples. Cela a permis de valider le comportement thermique en régime permanent thermique et en régime transitoire thermique. Ces modèles ont ensuite été implantés dans une modélisation multi-physique pour l'outil d'optimisation et pour l'outil de simulation. Une étude de cas a été présentée pour un véhicule hybride Kangoo où la machine doit pouvoir assurer son fonctionnement pour un cycle Artémis urbain. Les résultats de la stratégie de dimensionnement permettent alors de conclure que sur cycle, le volume extérieur des parties actives de la machine électrique peut-être réduit de 40 % par rapport à un dimensionnement établi par les règles de l'art en régime permanent. De plus, la réduction du volume de fer dans la machine induit également une réduction des pertes fer ce qui nous permet de conclure que, toujours sur cycle, son rendement moyen reste élevé.

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Yu, Shaohua. "Optimization models and methods for tour planning in smart urban logistics". Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPAST045.

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La distribution urbaine désigne les activités de distribution de marchandises desservant les zones urbaines et les banlieues. Les progrès technologiques récents dans le domaine de la distribution sans personnel, ainsi que les nouvelles réglementations limitant l’utilisation des véhicules à moteur à combustion, vont modifier de manière significative la distribution urbaine de marchandises. En outre, le nouveau modèle commercial du commerce électronique apporte également de nouvelles opportunités et de nouveaux défis à la distribution urbaine de marchandises. Cette thèse se concentre sur un nouveau système de distribution visant à fournir de meilleurs services pour la distribution logistique urbaine. Nous allons tout d’abord étudier un système de livraison urbaine robotisé basé sur un fourgon qui peut transporter plusieurs robots, ce qui rend le système de distribution plus flexible et efficace. Ensuite, nous proposons d’intégrer la technologie de recharge en route et de recharge inverse dans le système de livraison urbaine robotisée par camionnette dans les opérations logistiques, afin d’économiser le temps pendant lequel les camionnettes électriques transportent les robots pour les recharger, ce qui augmente l’efficacité des systèmes de distribution. Enfin, nous incorporons les ramassages hybrides et les opérations de livraison dans le système de distribution urbaine robotisée basés sur des fourgons pour nous adapter au nouveau modèle commercial des entreprises de commerce électronique
Urban distribution refers to the distribution activities of goods serving urban areas and suburbs. Recent technological advances in unmanned distribution field, as well as new regulations limiting the use of combustion engine vehicles, will significantly change urban goods distribution. Besides, the new ecommerce business model also brings new opportunities and challenges to urban goods distribution. This thesis focuses on a novel distribution system to provide better services for urban logistics distribution. We first study a van-based robot urban delivery system and allow a van can carry multiple robot to make the distribution system more flexible. Then we incorporate en-route charging, and reverse charging technology into the van-based robot urban delivery system in logistics operations, to effectively use the time during which electric vans are carrying robots to recharge the robots, thereby increasing distribution systems’ efficiency. Finally, we incorporate hybrid pickup and delivery operations into the van-based robot urban distribution system to adapt to the new business model of e-commerce enterprises

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Nakka, Sai Krishna Sumanth. "Co-design of Hybrid-Electric Propulsion System for Aircraft using Simultaneous Multidisciplinary Dynamic System Design Optimization". University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1602153187738909.

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Mesbahi, Tedjani. "Influence des stratégies de gestion d’une source hybride de véhicule électrique sur son dimensionnement et sa durée de vie par intégration d’un modèle multi-physique". Thesis, Ecole centrale de Lille, 2016. http://www.theses.fr/2016ECLI0004/document.

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Ce mémoire contribue à l’amélioration des performances d’une source de stockage hybride embarquée alimentant un véhicule électrique. La solution investiguée est composée de l’association de batteries Li-ion et de super condensateurs, dans le but d’obtenir, par rapport aux solutions classiques, un gain en masse et en durée de vie pour une certaine plage d’autonomie du véhicule. Notre objectif est de mettre à profit l’utilisation de nouvelles méthodes de gestion de la source hybride et de quantifier le gain obtenu. Un modèle multi-physique incluant les aspects électrique, thermique et vieillissement a été développé et intégré dans l’algorithme de gestion d’énergie afin d’évaluer la dégradation progressive des performances des éléments de stockage au cours des cycles de conduite selon la stratégie de gestion implantée. De nouvelles stratégies de gestion ayant pour objectif d’agir sur la durée de vie ont été évaluées. Leur impact sur les performances de la source en termes de masse, coût et durée de vie a pu être quantifié et montre bien que par une meilleure gestion des puissances, il est possible de mieux utiliser le stockeur hybride, ouvrant ainsi la voie à de nouvelles approches de gestion d’énergie pour ces systèmes
This thesis contributes to the improvement of hybrid embedded source performances supplies an electric vehicle. The studied solution is composed of Li-ion batteries and supercapacitors hybridization, with an aim to achieve improved performances in terms of weight and lifetime over traditional solutions. Our main goal is to take the best advantage of new energy management strategies of the hybrid embedded source and quantify obtained improvements. A multi-physic model including electric, thermal and aging behaviors is developed and integrated into the algorithm of energy management in order to evaluate the gradual degradation of storage components performances during driving cycles and implemented control strategy. New energy management strategies intended to act on the lifetime of hybrid embedded source have been evaluated. Their impact on the performances of the source in terms of weight, cost and lifetime has been quantified and clearly shows that it is possible to make better use of hybrid embedded source thanks to a good power sharing, thus opening the way to new approaches of energy management for these systems

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Cai, Xinye. "A multi-objective GP-PSO hybrid algorithm for gene regulatory network modeling". Diss., Manhattan, Kan. : Kansas State University, 2009. http://hdl.handle.net/2097/1492.

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VENDITTI, MATTIA. "Innovative models and algorithms for the optimization of layout and control strategy of complex diesel HEVs". Doctoral thesis, Politecnico di Torino, 2015. http://hdl.handle.net/11583/2617536.

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This study is focused on the design, optimization and analysis of non plug-in parallel and complex vehicles and on the evaluation of their potential to reduce fuel consumption and NOx emissions, in comparison with a reference vehicle. The simulated vehicles are equipped with compression ignition engines; two different engines were considered for the layout optimization process, and the related data were provided by GMPT-E (General Motors PowerTrain-Europe). A tool has been developed and employed to identify the optimal layout of each vehicle on the basis of the minimization of the overall powertrain costs during the whole vehicle life. These costs include the initial investment due to the production of the components as well as the operating costs related to fuel consumption and to battery depletion. The control strategy has been defined as the algorithm that selects the transmission gear and that manages the power to be provided by the engine and the electric machines of the power-train. In this framework, the transmission gear and the power management are the two control variables. Identification of the optimal control strategy is necessary in order to fully exploit the potential of the hybrid architecture to reduce fuel consumption and pollutant emissions. It is therefore carried out by the so-called optimizer in terms of a specific objective function. This function aims at maximizing the fuel economy with some constraints to the pollutant emissions and to the battery energy and life consumption, according to the application. To this end, two global optimizers, one of a deterministic nature and another of a stochastic type, have been developed, applied and compared. These methods are fundamental for the definition of the vehicle optimal control strategy. They are indeed referred to as benchmark optimizers. A zero-dimensional kinematic model of the vehicle has been developed in the Matlab environment in order to evaluate the evolution of the system variables, as a function of the vehicle velocity and of the control variables. A new mathematical technique has been developed and applied to the vehicle simulation model in order to decrease the computational time of the optimizers. First, the vehicle model equations were written in order to allow a coarse time grid to be used, then, the control variables were discretized, and the values of the system variables were evaluated and stored in a matrix, for all the possible combinations of control variables and for each time node, before the optimization process. However, since the benchmark optimizers are not suitable for on-board applications, one static optimizer and two different rule-based optimizers, which are referred to as real-time optimizers, have been also developed, compared to the benchmark tools and implemented in the vehicle control unit, in order to perform an on-board optimization. Usually this kind of optimization is based on heuristic techniques that may lack of performance in a broad range of applications. In this thesis, machine-learning techniques have been introduced to train the real-time tools. The training procedure that is applied to the rule-based optimizers consists of two parts: the input variable clustering and the rule definition. The vehicle velocity and power, as well as the battery state of charge, have been selected as the input variables. A clustering algorithm has been coded to discretize the input domain of the rule itself into a mesh, i.e., each combination of input variables is associated to an unique cluster. The rule connects every cluster to one of the discrete values of each control variable. Two different approaches have been followed in this study to develop the rule-based optimizers. A clustering algorithm has been developed for the first tool to generate the mesh that is associated to the rule, while genetic algorithms are applied to generate the action to take for each cluster of the mesh itself. In fact, the tool is referred to as Cluster Extracted Rule Optimized (CERO). Genetic algorithms have been instead applied for the second tool to generate the optimal mesh that is associated to the rule, while the most frequent action, in the set of actions that have been suggested by the benchmark optimizer in a cluster of the mesh, is correlated to that cluster. The tool is referred to as Cluster Optimized Rule Extracted (CORE). The vehicle control unit is required to receive the data about the instantaneous vehicle velocity, power and battery state of charge during the trip. These data are processed to identify the cluster they belong to, which is used to index the rule to extract the discrete values of the control variables. The control unit is therefore able to actuate the power-train components to drive the vehicle. The performance of the hybrid vehicles has been evaluated over several driving missions for different oriented optimizations and a detailed energetic analysis has been carried out in order to clearly identify the key operating modes that contribute most to the fuel consumption and NOx mission savings of the different hybrid architectures.

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47

Moumen, Chiraz. "Une méthode d'optimisation hybride pour une évaluation robuste de requêtes". Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30070/document.

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La qualité d'un plan d'exécution engendré par un optimiseur de requêtes est fortement dépendante de la qualité des estimations produites par le modèle de coûts. Malheureusement, ces estimations sont souvent imprécises. De nombreux travaux ont été menés pour améliorer la précision des estimations. Cependant, obtenir des estimations précises reste très difficile car ceci nécessite une connaissance préalable et détaillée des propriétés des données et des caractéristiques de l'environnement d'exécution. Motivé par ce problème, deux approches principales de méthodes d'optimisation ont été proposées. Une première approche s'appuie sur des valeurs singulières d'estimations pour choisir un plan d'exécution optimal. A l'exécution, des statistiques sont collectées et comparées à celles estimées. En cas d'erreur d'estimation, une ré-optimisation est déclenchée pour le reste du plan. A chaque invocation, l'optimiseur associe des valeurs spécifiques aux paramètres nécessaires aux calculs des coûts. Cette approche peut ainsi induire plusieurs ré-optimisations d'un plan, engendrant ainsi de mauvaises performances. Dans l'objectif d'éviter cela, une approche alternative considère la possibilité d'erreurs d'estimation dès la phase d'optimisation. Ceci est modélisé par l'utilisation d'un ensemble de points d'estimations pour chaque paramètre présumé incertain. L'objectif est d'anticiper la réaction à une sous-optimalité éventuelle d'un plan d'exécution. Les méthodes dans cette approche cherchent à générer des plans robustes dans le sens où ils sont capables de fournir des performances acceptables et stables pour plusieurs conditions d'exécution. Ces méthodes supposent souvent qu'il est possible de trouver un plan robuste pour l'ensemble de points d'estimations considéré. Cette hypothèse reste injustifiée, notamment lorsque cet ensemble est important. De plus, la majorité de ces méthodes maintiennent sans modification un plan d'exécution jusqu'à la terminaison. Cela peut conduire à de mauvaises performances en cas de violation de la robustesse à l'exécution. Compte tenu de ces constatations, nous proposons dans le cadre de cette thèse une méthode d'optimisation hybride qui vise deux objectifs : la production de plans d'exécution robustes, notamment lorsque l'incertitude des estimations utilisées est importante, et la correction d'une violation de la robustesse pendant l'exécution. Notre méthode s'appuie sur des intervalles d'estimations calculés autour des paramètres incertains, pour produire des plans d'exécution robustes. Ces plans sont ensuite enrichis par des opérateurs dits de contrôle et de décision. Ces opérateurs collectent des statistiques à l'exécution et vérifient la robustesse du plan en cours. Si la robustesse est violée, ces opérateurs sont capables de prendre des décisions de corrections du reste du plan sans avoir besoin de rappeler l'optimiseur. Les résultats de l'évaluation des performances de notre méthode indiquent qu'elle fournit des améliorations significatives dans la robustesse d'évaluation de requêtes
The quality of an execution plan generated by a query optimizer is highly dependent on the quality of the estimates produced by the cost model. Unfortunately, these estimates are often imprecise. A body of work has been done to improve estimate accuracy. However, obtaining accurate estimates remains very challenging since it requires a prior and detailed knowledge of the data properties and run-time characteristics. Motivated by this issue, two main optimization approaches have been proposed. A first approach relies on single-point estimates to choose an optimal execution plan. At run-time, statistics are collected and compared with estimates. If an estimation error is detected, a re-optimization is triggered for the rest of the plan. At each invocation, the optimizer uses specific values for parameters required for cost calculations. Thus, this approach can induce several plan re-optimizations, resulting in poor performance. In order to avoid this, a second approach considers the possibility of estimation errors at the optimization time. This is modelled by the use of multi-point estimates for each error-prone parameter. The aim is to anticipate the reaction to a possible plan sub-optimality. Methods in this approach seek to generate robust plans, which are able to provide good performance for several run-time conditions. These methods often assume that it is possible to find a robust plan for all expected run-time conditions. This assumption remains unjustified. Moreover, the majority of these methods maintain without modifications an execution plan until the termination. This can lead to poor performance in case of robustness violation at run-time. Based on these findings, we propose in this thesis a hybrid optimization method that aims at two objectives : the production of robust execution plans, particularly when the uncertainty in the used estimates is high, and the correction of a robustness violation during execution. This method makes use of intervals of estimates around error-prone parameters. It produces execution plans that are likely to perform reasonably well over different run-time conditions, so called robust plans. Robust plans are then augmented with what we call check-decide operators. These operators collect statistics at run-time and check the robustness of the current plan. If the robustness is violated, check-decide operators are able to make decisions for plan modifications to correct the robustness violation without a need to recall the optimizer. The results of performance studies of our method indicate that it provides significant improvements in the robustness of query processing

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48

Salameh, Farah. "Méthodes de modélisation statistique de la durée de vie des composants en génie électrique". Phd thesis, Toulouse, INPT, 2016. http://oatao.univ-toulouse.fr/16622/1/Salameh_Farah.pdf.

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La fiabilité constitue aujourd’hui un enjeu important dans le contexte du passage aux systèmes plus électriques dans des secteurs critiques tels que l’aéronautique, l’espace ou le nucléaire. Il s’agit de comprendre, de modéliser et de prédire les mécanismes de vieillissement susceptibles de conduire les composants à la défaillance et le système à la panne. L’étude des effets des contraintes opérationnelles sur la dégradation des composants est indispensable pour la prédiction de leur durée de vie. De nombreux modèles de durée de vie ont été développés dans la littérature dans le contexte du génie électrique. Cependant, ces modèles présentent des limitations car ils dépendent du matériau étudié et de ses propriétés physiques et se restreignent souvent à un ou deux facteurs de stress, sans intégrer les interactions pouvant exister entre ces facteurs. Cette thèse présente une nouvelle méthodologie pour la modélisation de la durée de vie des composants du génie électrique. Cette méthodologie est générale ; elle s’applique à différents composants sans a priori sur leurs propriétés physiques. Les modèles développés sont des modèles statistiques estimés sur la base de données expérimentales issues de tests de vieillissement accéléré où plusieurs types de stress sont considérés. Les modèles visent alors à étudier les effets des différents facteurs de stress ainsi que de leurs différentes interactions. Le nombre et la configuration des tests de vieillissement nécessaires à construire les modèles (bases d’apprentissage) sont optimisés de façon à minimiser le coût expérimental tout en maximisant la précision des modèles. Des points expérimentaux supplémentaires aléatoirement configurés sont réalisés pour valider les modèles (bases de test). Deux catégories de composants sont testées : deux types d’isolants couramment utilisés dans les machines électriques et des sources de lumière OLED. Différentes formes des modèles de durée de vie sont présentées : les modèles paramétriques, non paramétriques et les modèles hybrides. Tous les modèles développés sont évalués à l’aide de différents outils statistiques permettant, d’une part, d’étudier la pertinence des modèles et d’autre part, d’évaluer leur prédictibilité sur les points des bases de test. Les modèles paramétriques permettent de quantifier les effets des facteurs et de leurs interactions sur la durée de vie à partir d’une expression analytique prédéfinie. Un test statistique permet ensuite d’évaluer la significativité de chacun des paramètres inclus dans le modèle. Ces modèles sont caractérisés par une bonne qualité de prédiction sur leurs bases de test. La relation entre la durée de vie et les contraintes est également modélisée par les arbres de régression comme méthode alternative aux modèles paramétriques. Les arbres de régression sont des modèles non paramétriques qui permettent de classifier graphiquement les points expérimentaux en différentes zones dans lesquelles les contraintes sont hiérarchisées selon leurs effets sur la durée de vie. Ainsi, une relation simple, graphique, et directe entre la durée de vie et les contraintes est obtenue. Cependant, à la différence des modèles paramétriques continus sur le domaine expérimental étudié, les arbres de régression sont constants par morceaux, ce qui dégrade leur qualité de prédiction sur la base de test. Pour remédier à cet inconvénient, une troisième approche consiste à attribuer un modèle linéaire à chacune des zones identifiées avec les arbres de régression. Le modèle résultant, dit modèle hybride, est donc linéaire par morceaux et permet alors de raffiner les modèles paramétriques en évaluant les effets des facteurs dans chacune des zones tout en améliorant la qualité de prédiction des arbres de régression.

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49

Mickum, George S. "Development of a dedicated hybrid K-edge densitometer for pyroprocessing safeguards measurements using Monte Carlo simulation models". Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54358.

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Pyroprocessing is an electrochemical method for recovering actinides from used nuclear fuel and recycling them into fresh nuclear fuel. It is posited herein that proposed safeguards approaches on pyroprocessing for nuclear material control and accountability face several challenges due to the unproven plutonium-curium inseparability argument and the limitations of neutron counters. Thus, the Hybrid K-Edge Densitometer is currently being investigated as an assay tool for the measurement of pyroprocessing materials in order to perform effective safeguards. This work details the development of a computational model created using the Monte Carlo N-Particle code to reproduce HKED assay of samples expected from the pyroprocesses. The model incorporates detailed geometrical dimensions of the Oak Ridge National Laboratory HKED system, realistic detector pulse height spectral responses, optimum computational efficiency, and optimization capabilities. The model has been validated on experimental data representative of samples from traditional reprocessing solutions and then extended to the sample matrices and actinide concentrations of pyroprocessing. Data analysis algorithms were created in order to account for unsimulated spectral characteristics and correct inaccuracies in the simulated results. The realistic assay results obtained with the model have provided insight into the extension of the HKED technique to pyroprocessing safeguards and reduced the calibration and validation efforts in support of that design study. Application of the model has allowed for a detailed determination of the volume of the sample being actively irradiated as well as provided a basis for determining the matrix effects from the pyroprocessing salts on the HKED assay spectra.

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50

Kamrath, Matthew. "Extending standard outdoor noise propagation models to complex geometries". Thesis, Le Mans, 2017. http://www.theses.fr/2017LEMA1038/document.

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Les méthodes d'ingénierie acoustique (e.g. ISO 9613-2 ou CNOSSOS-EU) approchent efficacement les niveaux de bruit générés par les routes, les voies ferrées et les sources industrielles en milieu urbain. Cependant, ces approches d'ingénierie sont limitées à des géométries de forme simple, le plus souvent de section rectangulaire. Ce mémoire développe donc, et valide, une approche hybride permettant l'extension des méthodes d'ingénierie à des formes plus complexes, en introduisant un terme d’atténuation supplémentaire qui représente l'effet d'un objet réel comparé à un objet simple.Le calcul de cette atténuation supplémentaire nécessite des calculs de référence, permettant de quantifier la différence entre objets simple et complexe. Dans la mesure où il est trop onéreux, numériquement, '’effectuer ce calcul pour tous les chemins de propagation, l'atténuation supplémentaire est obtenue par interpolation de données stockées dans un tableau et évaluées pour un large jeu de positions de sources, de récepteurs et de fréquences. Dans notre approche, le calcul de référence utilise la méthode BEM en 2.5D, et permet ainsi de produire les niveaux de référence pour les géométries simple et complexe, tout en tabulant leur écart. Sur le principe, d'autres approches de référence pourraient être utilisées.Ce travail valide cette approche hybride pour un écran en forme de T avec un sol rigide, un sol absorbant et un cas avec bâtiments. Ces trois cas démontrent que l'approche hybride est plus précise que l'approche d’ingénierie standard dans des cas complexes
Noise engineering methods (e.g. ISO 9613-2 or CNOSSOS-EU) efficiently approximate sound levels from roads, railways, and industrial sources in cities. However, engineering methods are limited to only simple box-shaped geometries. This dissertation develops and validates a hybrid method to extend the engineering methods to more complicated geometries by introducing an extra attenuation term that represents the influence of a real object compared to a simplified object.Calculating the extra attenuation term requires reference calculations to quantify the difference between the complex and simplified objects. Since performing a reference computation for each path is too computationally expensive, the extra attenuation term is linearly interpolated from a data table containing the corrections for many source and receiver positions and frequencies. The 2.5D boundary element method produces the levels for the real complex geometry and a simplified geometry, and subtracting these levels yields the corrections in the table.This dissertation validates this hybrid method for a T-barrier with hard ground, soft ground, and buildings. All three cases demonstrate that the hybrid method is more accurate than standard engineering methods for complex cases

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