"A well-known challenge in estimating the distance of the antenna pair in time-of-arrival (ToA) based RF localization systems is the problem of obstruction of the direct path (DP) between transmitter and receiver. The absence of DP component in received channel profile creates undetected direct path (UDP) conditions. UDP condition, in turn, will cause occurrence of unexpected large ranging errors which pose serious challenge to precise indoor localization. Analysis of the behavior of the ranging error in such conditions is essential for the design of precise ToA-based indoor localization systems. This dissertation discusses two open problems in ToA-based indoor localization systems. The first contribution of this dissertation discusses the problem of modeling of dynamic behavior of ranging error. We propose a novel analytical framework for analysis of dynamic spatial variations of ranging error observed by a mobile user based on an application of Markov chain. The model relegates the behavior of ranging error into four main categories associated with four states of Markov process. Parameters of distributions of ranging error in each Markov state are extracted from empirical data collected from a measurement-calibrated ray tracing algorithm simulating a typical office environment. The analytical derivation of parameters of the Markov model employs the existing path-loss models for first detected path and total multipath received power in the same office environment. Results of simulated errors from the Markov model and actual errors from empirical data show close agreement. The second contribution of this dissertation discusses the problem of identification of UDP condition given an unknown channel profile. Existing of UDP condition in a channel profile poses serious degradation to ranging estimate process. Therefore, identification of occurrence of UDP condition is of our subsequent concern. After identification, the second step is to mitigate ranging errors in such conditions. In this dissertation we present two methodologies, based on binary hypothesis testing and an application of artificial neural network design, to identify UDP conditions and mitigate ranging error using statistics extracted from wideband frequency-domain indoor measurements conducted in typical office building. "

The objective of this thesis is to propose modeling techniques that enable the design and optimization of material systems which require descriptions via molecular simulations. These kinds of systems are quite common in materials and engineering research. The first step in performing design and optimization tasks on such systems is the development of accurate simulation models from experimental data. In the first part of this thesis, we present a novel simulation model for the hyperbranched polymerization process of difunctional A2 oligomers, and B3 monomers. Unlike the previous models developed by other groups, our model is able to simulate the evolution of the polymer structure development under a wide range of synthesis routes, and in the presence of cyclization and endcapping reactions. Furthermore, our results are in agreement with the experimental data, and add insight into the underlying kinetic mechanisms of this polymerization process. The second major step in our work is the development of reduced order process models that are suitable for design and optimization tasks, using simulation data. We illustrate our approach on a stochastic simulation model of epitaxial thin film deposition process. Compared to the widely used approach called equation-free modeling, our method requires fewer assumptions about the dynamic system. The assumptions required in equation-free modeling include a wide separation between the time scales of low and high order moments describing the system state, and the accuracy of the time derivatives of system properties computed from molecular simulation data, despite the potentially large amount of fluctuations in stochastic simulations. Unlike the recent similar studies, our study also includes the analysis of prediction error which is important to evaluate the predictions of the reduced order model, compared to the high dimensional molecular simulations. Hence, we address two major issues in this thesis: development of simulation models from molecular experimental data, and derivation of reduced order models from molecular simulation data. These two aspects of modeling are both necessary to design and optimize processing conditions of materials for which continuum level descriptions are not available or accurate enough.

This thesis documents the studies conducted in deriving a mathematical model representing the dynamics of a maneuvering ship to be implemented as part of an interactive real-time simulation system, as well as the details and results of the implementation process itself. Different effects on the dynamics of ship motions are discussed separately, meaning that the effects are considered to be applied to the system one at a time and they are included in the model simply by the principle of superposition. The model is intended to include the hydrodynamic interactions between the ship hull and the ocean via added mass (added inertia), damping and restoring force concepts. In addition to these effects, which are derived considering no incident waves are present on the ocean, the environmental disturbances, such as wind, wave and ocean current are also taken into account for proposing a mathematical model governing the dynamics of the ship. Since the ultimate product of this thesis work is a running computer code that can be integrated into an available simulation software, the algorithm development and code implementation processes are also covered. Improvements made on the implementation to achieve &ldquo / better&rdquo / real-time performance are evaluated comparatively in reference to original runs conducted before the application of improvement under consideration. A new method to the computation of the wave model that allows faster calculation in real-time is presented. A modular programming approach is followed in the overall algorithm development process in order to make the integration of new program components into the software, such as a new hull or propulsion model or a different integrator type possible, easily and quickly.

The focus of interest in this study is the RHex robot, which is a hexapod robot that is capable of locomotion over rugged, fractured terrain through statically and dynamically stable gaits while stability of locomotion is preserved. RHex is primarily a research platform that is based on over five years of previous research. The purpose of the study is to build a virtual prototype of RHex robot in order to simulate different behavior without manufacturing expensive prototypes. The virtual prototype is modeled in MSC ADAMS software which is a very useful program to simulate flexible multibody dynamical systems. The flexible half circular legs are modeled in a finite element program (MSC NASTRAN) and are embedded in the main model. Finally a closed loop control mechanism is built in MATLAB to be able to simulate real autonomous RHex robot. The interaction of MATLAB and MSC ADAMS softwares is studied.

Dynamic complexity occurs in every social structure. Film industry, as a type of creative industries, constitutes a dynamic environment where uncertainty is at high levels. This complexity of the environment renders the more traditional operations research models somewhat ineffective, and thus, requires a dynamic analysis. In this study, a model showing the dynamics of film exhibition is given. The interactions within and between the theatrical and the DVD sales channels are implemented by the model. Later on, the possible effects of piracy to the model are discussed, using the inferences obtained by the created model. The model is examined with scenario and sensitivity analysis. All the modeling studies are done with a commercial dynamic systems modeling software. The model also can be extended for the whole film industry, or for some other creative industries like the publishing industry.

Cooperative control enables combinations of sensor data from multiple autonomous underwater vehicles (AUVs) so that multiple AUVs can perform smarter behaviors than a single AUV. In addition, in some situations, a human-driven underwater vehicle (HUV) and a group of AUVs need to collaborate and preform formation behaviors. However, the collective dynamics of a fleet of heterogeneous underwater vehicles are more complex than the non-trivial single vehicle dynamics, resulting in challenges in analyzing the formation behaviors of a fleet of heterogeneous underwater vehicles. The research addressed in this dissertation investigates the collective dynamics and control of a fleet of heterogeneous underwater vehicles, including multi-AUV systems and systems comprised of an HUV and a group of AUVs (human-AUV systems). This investigation requires a mathematical motion model of an underwater vehicle. This dissertation presents a review of a six-degree-of-freedom (6DOF) motion model of a single AUV and proposes a method of identifying all parameters in the model based on computational fluid dynamics (CFD) calculations. Using the method, we build a 6DOF model of the EcoMapper and validate the model by field experiments. Based upon a generic 6DOF AUV model, we study the collective dynamics of a multi-AUV system and develop a method of decomposing the collective dynamics. After the collective dynamics decomposition, we propose a method of achieving orientation control for each AUV and formation control for the multi-AUV system. We extend the results and propose a cooperative control for a human-AUV system so that an HUV and a group of AUVs will form a desired formation while moving along a desired trajectory as a team. For the post-mission stage, we present a method of analyzing AUV survey data and apply this method to AUV measurement data collected from our field experiments carried out in Grand Isle, Louisiana in 2011, where AUVs were used to survey a lagoon, acquire bathymetric data, and measure the concentration of reminiscent crude oil in the water of the lagoon after the BP Deepwater Horizon oil spill in the Gulf of Mexico in 2010.

Recently, the environmental impact of aircraft and rising fuel prices have become an increasing concern in the aviation industry. To address these problems, organizations such as NASA have set demanding goals for reducing aircraft emissions, fuel burn, and noise. In an effort to reach the goals, a movement toward more-electric aircraft and electric propulsion has emerged. With this movement, the number of critical electrical loads on an aircraft is increasing causing power system reliability to be a point of concern. Currently, power system reliability is maintained through the use of back-up power supplies such as batteries and ram-air-turbines (RATs). However, the increasing power requirements for critical loads will quickly outgrow the capacity of the emergency devices. Therefore, reliability needs to be addressed when designing the primary power distribution system. Power system reliability is a function of component reliability and redundancy. Component reliability is often not determined until detailed component design has occurred; however, the amount of redundancy in the system is often set during the system architecting phase. In order to meet the capacity and reliability requirements of future power distribution systems, a method for redundancy allocation during the system architecting phase is needed. This thesis presents an aircraft power system design methodology that is based upon the engineering decision process. The methodology provides a redundancy allocation strategy and quantitative trade-off environment to compare architecture and technology combinations based upon system capacity, weight, and reliability criteria. The methodology is demonstrated by architecting the power distribution system of an aircraft using turboelectric propulsion. The first step in the process is determining the design criteria which includes a 40 MW capacity requirement, a 20 MW capacity requirement for the an engine-out scenario, and a maximum catastrophic failure rate of one failure per billion flight hours. The next step is determining gaps between the performance of current power distribution systems and the requirements of the turboelectric system. A baseline architecture is analyzed by sizing the system using the turboelectric system power requirements and by calculating reliability using a stochastic flow network. To overcome the deficiencies discovered, new technologies and architectures are considered. Global optimization methods are used to find technology and architecture combinations that meet the system objectives and requirements. Lastly, a dynamic modeling environment is constructed to study the performance and stability of the candidate architectures. The combination of the optimization process and dynamic modeling facilitates the selection of a power system architecture that meets the system requirements and objectives.

This thesis is motivated by practical problems encountered in handling live products in the poultry processing industry, where live birds are manually transferred by human labors. As the task of handling live products is often unpleasant and hazardous, it is an ideal candidate for automation. To reduce the number of configurations and live birds to be tested, this thesis focuses on developing analytical models based on the Lagrange method to predict the effect of mechanical inversion on the shackled bird. Unlike prior research which focused on the effect of different inversion paths on the joint force/torque of a free-falling shackled bird, this thesis research examines the effect of kinematic constraints (designed to support the bird body) on the shackled bird. Unlike free-falling, the imposed kinematic constraints enable the shackled bird to rotate about its center of mass, and thus minimize wing flapping. In this thesis, birds are geometrically approximated as ellipsoids while the lower extremity is modeled as a pair of multi-joint serial manipulators. With the constraint equations formulated into a set of differential algebraic equations, the equations of motion as well as Lagrange multipliers characterizing kinematical constraints are numerically solved for the bird motion, specifically the position, velocity, and orientation and hence the forces and torques of the joints. The dynamic models are verified by comparing simulation results against those obtained using a finite element method. The outcomes of this thesis will provide some intuitive insights essential to design optimization of a live-bird transfer system.

Les Réseaux de Chaleur (RdC) connaissent un nouvel essor en France qui s’explique par leur capacité à valoriser, à un prix raisonnable, des énergies bas carbone dans les domaines du chauffage et de l’eau chaude sanitaire aujourd’hui fortement émetteurs de CO2. L’amélioration du contrôle de ces systèmes complexes est un enjeu clé pour accroître leur compétitivité et favoriser leur développement. Cette thèse s’intéresse à la gestion par commande optimale des RdC. Pour cette application, nous avons développé et évalué un algorithme qui, à partir d’une prévision de la demande, optimise l’utilisation des différents moyens de production ainsi que la température de départ et la pression différentielle. Par rapport aux systèmes existants, les originalités de notre solution sont de tirer pleinement partie des capacités de stockage thermique dans le réseau et de déterminer le meilleur compromis entre coûts liés au pompage et pertes thermiques. Cette thèse débute par un travail de modélisation dynamique réalisé à l’échelle composant. En nous appuyant sur une démarche de validation expérimentale, nous avons systématiquement recherché le meilleur compromis entre précision et efficacité numérique (Chapitre 1). Le cas d’étude, décrit dans le Chapitre 2, est un RdC virtuel à l’échelle d’un quartier, représentatif du cas Grenoble. Pour le développement du système de gestion avancée, nous présentons ensuite une version linéarisée du modèle de réseau de distribution que nous intégrons à un optimiseur en suivant le formalisme de la programmation linéaire mixte. L’algorithme de gestion proposé est ensuite décrit (Chapitre 3). Il associe un modèle dynamique non-linéaire et l’optimiseur précité. L’objet du quatrième chapitre est l’évaluation des performances de notre algorithme par la simulation et la comparaison à des méthodes de contrôle existantes. Enfin, un dernier chapitre étudie la robustesse de l’algorithme en condition de commande réelle, c’est-à-dire en tenant compte de différentes sources d’incertitude. / District Heating (DH) are currently fast-growing in France. This situation is explained by their ability to exploit and disseminate massively, at a reasonable price, energy sources with low CO2 contents in the sectors of space heating and domestic hot water production, nowadays strongly emitters of greenhouse gases. Improving the control of these complex energy systems is a key issue for increasing their competitiveness and promote their development.This thesis focuses on the optimal control of DH systems. For this application, we have developed and tested an algorithm that optimizes, given a load prediction, the use of the production means, the supply temperature and the differential pressure. Compared to existing methods, the original features of the developed solution are to fully exploit the thermal storage capacity of the network and to determine the best compromise between costs for pumping and heat losses.This thesis begins with a work on dynamic modeling carried out at the component scale. Based on an experimental validation approach, we systematically sought the best compromise between accuracy and computational efficiency (Chapter 1). The case study, described in Chapter 2, is a virtual DH at the district scale, representing the Grenoble case. For the development of the advanced control system, we then present a linearized version of the distribution network model that we integrate into an optimizer relying on Mixed Linear Programming. The proposed control algorithm is described in Chapter 3. It combines a nonlinear dynamic model and the aforementioned optimizer. The topic of the fourth chapter is the evaluation of the performance of our algorithm by simulation and comparison with existing methods of control. A final chapter examines the robustness of the algorithm in real control conditions considering various sources of uncertainty.

Dans les années récentes, des politiques visant à promouvoir l’efficacité énergétique ont été instaurées en réponse aux obligations réglementaires européennes et internationales. Le stockage d’énergie thermique s’est révélé être une technologie qui permet une amélioration de l’efficacité énergétique, en particulier celle des installations techniques pour le conditionnement d’air, le chauffage et l’eau chaude sanitaire pour le bâtiment. Parmi les différents types existants, le stockage thermique par chaleur sensible est le plus ancien et le plus répandu sur le marché. Or, l’intégration du ballon de stockage dans les installations énergétiques s’avère délicate tant dans la phase de conception que de l’exploitation de ces installations. Par ailleurs, il convient d’évaluer – pour les systèmes et équipements techniques du bâtiment – leurs consommations énergétiques annuelles (ou saisonnières). Pour répondre à l’ensemble de ces exigences, le recours à la modélisation et simulation dynamique des composants et systèmes énergétiques devient indispensable. Le travail de la présente thèse présente une approche de modélisation et de simulation dynamique d’un ballon de stockage d’eau par chaleur sensible qui répond aux contraintes particulières suivantes : assurer une modélisation fine à partir de la résolution des équations de Navier-Stokes d’un composant – le ballon de stockage – dans lesquels les mécanismes de transfert et d’écoulement sont complexes et réaliser une modélisation dynamique d’un système thermique associant des divers composants techniques d’un circuit et ceci avec des temps de calcul raisonnables, compatibles avec les pratiques courantes des bureaux d’étude spécialisés en conception d’installations . Le travail réalisé associe donc une analyse fine du comportement dynamique du ballon grâce au développement d’un modèle CFD, la détermination d’un modèle réduit à partir de ce modèle – qui permet la construction d’un champ dynamique de température – et enfin une modélisation sous Modelica adaptée à la simulation d’un système énergétique complexe. Dans les différentes phases de cette étude, les résultats issus de la simulation sont alors confrontés aux résultats déduits de divers travaux expérimentaux. La validation de la démarche suite à cette confrontation calculs/expériences permet d’envisager l’application des outils présentés à des projets techniques notamment au projet « PV cooling » de climatisation des bâtiments avec une ressource solaire photovoltaïque, projet réalisé en parallèle de ce projet de thèse et porté par les acteurs industriels qui soutiennent cette recherche. / In recent years, policies to promote energy efficiency have been introduced in response to European and International regulatory obligations. Thermal Energy Storage has proven to be a technology that improves energy efficiency, particularly for the air conditioning, heating and domestic hot water utilities in buildings. Among the existing types, sensible heat storage is the oldest and most widespread on the market. The integration of the storage tank into energy installations may be tricky in both the design and operation phases of these installations. Moreover, the annual (or seasonal) energy consumption of the building's technical systems and equipment should be evaluated. To meet all these requirements, dynamic modeling and simulation of energy components and systems becomes essential. The work of this thesis presents a dynamic modeling and simulation approach of a sensible heat water storage tank which respond to the following particular constraints: To ensure a fine modeling based on the resolution of the Navier-Stokes equations of a component – the storage tank – in which the flow and transfer mechanisms are complex, and to carry out a dynamic modeling and simulation, with reasonable computational time, of a thermal energy system associating various technical components of a circuit and compatible with the usual practices of the specialized system design offices. Thus, the carried out work combines a detailed analysis of the dynamic behavior of the storage tank through the development of a CFD model, the development of a reduced model from the previous CFD model that allows the construction of temperature dynamic fields and finally a Modelica modeling adapted to the simulation of a complex energy system. In the different phases of this study, the results from the simulation are compared to the results deduced from various experimental works. The validation of the approach following this comparison between calculations and experimental results makes it possible to consider the application, of the presented tools, in technical projects and in particular the project “PV cooling” for buildings air conditioning with a photovoltaic solar resource, a project that is carried out in parallel with this thesis by the industrial players supporting this research.