В первом разделе работы рассмотрены факторы, определяющие климатические условия в помещении и методика расчета теплопотерь. Также приведено описание современных способов регулирования температуры в помещении и рассмотрены два реализованных алгоритма для управления температурным режимом в помещении, основанные на математическом анализе и на базе нечеткой логике. Во втором разделе рассматривается тепловая модель здания для традиционной системы регулирования температуры, реализованная в Matlab-Simulink. По рассмотренной модели проведен сравнительный анализ использования различного вида регуляторов и его выбор для реализации интеллектуальной системы управления температурным режимом. В третьем разделе описана реализация алгоритма для предикции температуры на базе нейронных сетей. А также представлено описание реализации аппаратной и программной части интеллектуальной системы. / In the first section of the dissertation, the factors that determine the climatic conditions in the room and the method for calculating heat loss are considered. It also provides a description of modern methods of room temperature control and considers two implemented algorithms for controlling the temperature regime in a room, based on mathematical analysis and on the basis of fuzzy logic. The second section examines a building thermal model for a traditional temperature control system implemented in Matlab-Simulink. Based on the considered model, a comparative analysis of the use of various types of controllers and its choice for the implementation of an intelligent temperature control system is carried out. The third section describes the implementation of an algorithm for predicting temperature based on neural networks. It also provides a description of the implementation of the hardware and software of the intelligent system.

As smart homes become increasingly common and concerns over Internet of Things (IoT) security grow, this study delves into the vulnerabilities of smart thermostats. These devices offer convenience but also comes with increased risk of cyber attacks. This study evaluates the susceptibility of the Shelly Thermostatic Radiator Valve (TRV) and the Meross Smart Thermostat to potential threats across various attack vectors – encompassing firmware, network, radio, and cloud – through penetration testing guided by the PatrIoT methodology. Findings reveal four unknown vulnerabilities in the Meross Smart Thermostat and two in the Shelly TRV. These vulnerabilities consist of insecure firmware updates, lack of network encryption, exploitable radio communication, and cloud-related gaps. Recommendations aiming at mitigating the found vulnerabilities include implementing secure Wi-Fi access points for both models during setup, and ensuring strong encryption for the Meross Smart Thermostat’s radio communication. The study contributes to an increased awareness of potential security risks associated with these devices, though the extent of vulnerabilities across all smart thermostat models cannot be definitively concluded. / I takt med att smarta hem blir allt vanligare och med växande medvetenhet om säkerhet för Internet of Things (IoT), undersöker denna studie potentiella sårbarheter hos smarta termostater. Dessa enheter förenklar användares vardag, men ger också upphov till nya cyberhot. Denna studie granskar Shelly TRV och Meross Smart Thermostat för potentiella hot inom attackvektorerna firmware, nätverk, radio och moln, genom penetreringstestning som vägleds av PatrIoT-metodiken. Resultatet är fyra upptäckta sårbarheter i Meross-modellen och två i Shelly Thermostatic Radiator Valve (TRV) inklusive osäkra firmware-uppdateringar, brist på nätverkskryptering, utnyttjbar radiokommunikation och molnrelaterade problem. Rekommendationer med syfte att mitigera de upptäckta sårbarheterna inkluderar att implementera säkra Wi-Fi-åtkomstpunkter för båda modellerna under installationen och att säkerställa stark kryptering för Meross Smart Thermostat:s radiokommunikationen. Studien bidrar till en ökad medvetenhet om potentiella säkerhetsrisker som är förknippade med dessa enheter, även om det inte kan fastställas hur vanligt det är med sårbarheter i smarta termostater

<p dir="ltr">In U.S. residential buildings, space heating makes up about 43% of total energy use, with natural gas fulfilling 45% of this demand. As climate change concerns escalate, moving away from fossil fuel heating systems to more sustainable options are essential, especially in cold climates where heating needs are significant. Air-source heat pumps are a promising alternative, but their capacity and efficiency decrease as outdoor temperatures drop, impacting comfort due to lower supply temperatures (e.g., 32°C/90°F). This can lead to potential discomfort, as such temperatures feel cooler than skin temperature. Additionally, defrosting cycles pull heat from indoor spaces to clear outdoor coils. Conversely, gas furnaces provide steady heat at higher temperatures (over 49°C/120°F) without defrosting issues. Research shows that discomfort prompts occupants to raise thermostat setpoints and increase energy use.This study aims to investigate the influence of operational characteristics of various comfort delivery systems in cold weather on occupants' thermostat adjustment behaviors, identify the limitations of current heat pump systems, and develop a novel wall-embedded micro heat pump (WEMHP) radiant heating system that enhances comfort and reduces energy consumption, supporting the electrification of residential buildings. To achieve this goal, the research focuses on the following specific objectives: 1) develop a controlled laboratory testbed to emulate different thermal comfort delivery systems, including convective air and radiant systems; 2) investigate occupant setpoint preferences and thermostat adjustment behaviors under different operational modes using a residential community testbed; 3) study occupant thermostat adjustment behaviors for different types of heat pump systems through laboratory experiments; 4) develop and evaluate a novel wall-embedded micro heat pump for radiant heating in buildings; 5) design and test a prototype of the wall-embedded micro heat pump as a proof-of-concept demonstration.</p><p dir="ltr">This study first introduces the Human Building Interaction Laboratory (HBIL), a new facility with a modular design that includes reconfigurable thermally active panels for walls, floors, and ceilings. Each panel’s surface temperature can be independently controlled via a hot and cold water hydronic system, allowing the simulation of various climate zones, building conditions, and different heating/cooling systems. This setup facilitates research on localized comfort delivery, occupant comfort control, active building materials, and more.</p><p dir="ltr">Subsequently, a residential community test-bed was established within a newly built residential community in Indianapolis. A study was conducted in 30 homes to collect data on occupants' thermostat adjustments under two different operation modes: 1) a baseline mode featuring a heat pump paired with an auxiliary heater controlled by default thermostat heuristic rules, and 2) a comparison mode where the auxiliary heater was activated to provide the majority of heating. The findings showed that 8 out of 13 units preferred lower setpoints in the comparison mode, where higher supply air temperatures were utilized. Four distinct setpoint-increasing behaviors were identified, contributing to the observed setpoint differences between the two modes. Notably, two of these behaviors were closely linked to the operational characteristics of heat pumps in cold weather, specifically cases of insufficient and sufficient HP capacity.</p><p dir="ltr">To further explore the differences in setpoint preferences and the motivations behind setpoint adjustments, two scenarios were designed, and 32 experiments with human test-subjects were conducted in a controlled laboratory (Human Building Interaction Laboratory). The first case, with a single-stage heat pump and auxiliary heater, replicated the operational characteristics observed in the field study. The second case, using a variable-speed heat pump with enhanced comfort features, aimed to investigate participants' comfort preferences and provide insights for future heat pump design improvements. According to the thermal comfort survey results, 19 out of 32 participants increased their setpoints in the single-stage heat pump case, even though the heat pump had sufficient capacity to warm the indoor space. Cold air movement and indoor temperature fluctuations due to the heat pump cycling on/off were the main reasons participants reported increasing their setpoints in this case. In contrast, participants felt more comfortable with the variable-speed heat pump in the laboratory study, attributing their comfort to stable indoor temperatures and the absence of cold air movement.</p><p dir="ltr">Finally, a novel wall-embedded micro heat pump (WEMHP) was developed as a new distributed comfort delivery approach with several distinct advantages compared to alternatives: (1) A WEMHP eliminates the need for a secondary water loop and does not require separate indoor and outdoor units. Instead, a WEMHP unit operating in heating mode directly absorbs heat through an embedded heat exchanger (evaporator) at the outside wall surface and then conditions the indoor space using an embedded heat exchanger (condenser) at the indoor surface. (2) This packaged solution eliminates the need for extensive HVAC installation and on-site refrigerant charging. (3) The interior surface temperature of the exterior wall section empowered by the micro heat pump is independently controlled, allowing for distributed space conditioning and delivery of radiant heating to meet diverse occupant needs in different zones. The system performance was studied thoroughly based on energy simulation and experimental comfort study. Moreover, a prototype WEMHP was designed, assembled, and tested in a laboratory environment as a proof-of-concept demonstration. The test results demonstrated that the heating capacity under condition H1 reached around 190 W at a compressor speed of 4000 RPM with a COP of 1.67. Additionally, the system exhibited a fast thermal response, with a time constant τ₆₃ (the time it takes for the surface temperature to reach 63% of the difference between its final and initial values) of less than 0.5 hours and a τ₉₅of approximately 1.5 hours.</p>

<p dir="ltr">Supervisory predictive control of residential building heating, ventilation, and air conditioning (HVAC) systems could protect electrical infrastructure, enhance occupants’ thermal comfort, reduce energy costs, and minimize emissions. However, there are few experimental demonstrations, with most of the work focusing on simulation studies. To convince stakeholders of the benefits of supervisory predictive controls for residential HVAC systems, it is important to demonstrate practical systems in real buildings. Practical demonstrations also further our understanding of the field performance of these systems. This thesis presents the first comprehensive review of supervisory predictive control experiments in residential buildings, drawing critical insights on the estimated energy savings, the types of equipment controlled, the objectives and problem formulations considered, and other practical considerations. To address limitations in the existing body of experimental work, a series of field demonstrations were performed in a real house with student occupants near the Purdue campus in West Lafayette, Indiana, U.S.A.</p><p dir="ltr">The first field demonstration involved supervisory predictive control of an air-to-air heat pump with backup electric resistance heat. This was the first experiment to consider this equipment configuration, which is common in North America. A simple data-driven method is presented for learning a model of the temperature dynamics of a detached residential building. Using this model, the control system adjusts indoor temperature set points based on weather forecasts, occupancy conditions, and data-driven models of the heating equipment. Field tests from January to March of 2023 included outdoor temperatures as low as −15 ℃. During these tests, the control system reduced total heating energy costs by 19% on average (95% confidence interval: 13–24%) and energy used for backup heat by 38%. The control system also reduced the frequency of using high-stage (19 kW) backup heat by 83%. Concurrent surveys of residents showed that the control system maintained satisfactory thermal comfort. These real-world results could strengthen the case for deploying predictive home heating control, bringing the technology one step closer to reducing emissions, utility bills, and power grid impacts at scale.</p><p dir="ltr">The second field demonstration advanced the state of the art of predictive residential cooling control, wherein past experimental demonstrations relied on “sensible” models of building thermal dynamics and neglected humidity effects. In this thesis, a model-free machine learning method is introduced to predict the indoor wet-bulb temperature and the sensible heat ratio in a “latent” model formulation, with the aim to increase the accuracy of the real electrical power prediction. The latent and sensible formulations are tested in two separate model predictive controller (MPC) schemes in an on-off fashion. One MPCscheme aims to reduce energy costs while enhancing comfort. The other is a power-limiting controller that aims to keep the power of the HVAC equipment below 2.5 kW between 4 PM and 8 PM. The two MPC schemes and the two load models are assessed through 38 days of testing. It is found that across both economic MPC and power-limiting MPC, the energy savings across the latent and sensible formulations are similar. Through a normalized Cooling Degrees Days analysis, the energy savings to the baseline controller in the house are found to be 16 to 32% for economic MPC (95% confidence interval) and -5 to 10% for power-limiting MPC, with 7 to 21% savings across both controllers (14% mean). For power limiting, the latent formulation reduced the total duration of constraint violation by 88% and the sensible formulation by 40%, with respect to the non-MPC baseline. Additionally, the latent formulation reduced the peak power demand by 13% relative to the baseline, a behavior not observed in the sensible formulation.</p><p dir="ltr">The third field experiment investigated the problem of protecting home electrical infrastructure in the context of electrification retrofits. Installing electric appliances or vehicle charging in a residential building can sharply increase the electric current draws. In older housing, high current draws can jeopardize circuit breaker panels or electrical service (the wires that connect a building to the distribution grid). Upgrading electrical panels or service often entails long delays and high costs, and thus it poses a significant barrier to electrification. This thesis develops and field tests a novel control system that avoids the need for electrical upgrades by maintaining an electrified home’s total current draw within the safe limits of its existing panel and service. In the proposed control architecture, a high-level controller plans device set-points over a rolling prediction horizon, while a low-level controller monitors real-time conditions and ramps down devices if necessary. The control system was tested for 31 consecutive winter days with outdoor temperatures as low as -20 ℃. The control system maintained the whole-home current within the safe limits of electrical panels and service rated at 100 A, a common rating for older houses in North America, by adjusting only the temperature set-points of the heat pump and water heater. Simulations suggest that the same 100 A limit could accommodate a second electric vehicle (EV) with Level II (11.5 kW) charging. The proposed control system could allow older homes to safely electrify without upgrading electrical panels or service, saving a typical household on the order of $2,000 to $10,000. </p><p dir="ltr">These three field experiments demonstrate that low-cost predictive control systems can serve multiple objectives, improving the efficiency of heat pumps and water heaters while maintaining comfort and protecting electrical infrastructure. Future work will be directed toward improving the scalability of these proposed controllers through the incorporation of data-driven methodologies such as data-enabled predictive control, as well as understanding the application of these algorithms with different systems, including batteries, on-site solar photovoltaics, and electrical vehicle charging.</p>

Les propriétés magnétiques des matériaux sont fortement connectées à leur structure cristallographique. Nous proposons un modèle atomique de la dynamique d'aimantation capable de rendre compte de cette magnétoélasticité. Bien que ce travail s'inscrive dans une thématique générale de l'étude des matériaux magnétiques en température, nous la particularisons à un seul élément, le Cobalt. Dans ce modèle effectif, les atomes sont décrits par 3 vecteurs classiques qui sont position, impulsion et spin. Ils interagissent entre eux via un potentiel magnéto-mécanique ad hoc. On s'intéresse tout d'abord à la dynamique de spin atomique. Cette méthode permet d'aborder simplement l'écriture des équations d'évolution d'un système atomique de spins dans lequel la position et l'impulsion des atomes sont gelées. Il est toutefois possible de définir une température de spin permettant de développer naturellement une connexion avec un bain thermique. Montrant les limites d'une approche stochastique, nous développons une nouvelle formulation déterministe du contrôle de la température d'un système à spins.Dans un second temps, nous développons et analysons les intégrateurs géométriques nécessaires au couplage temporel de la dynamique moléculaire avec cette dynamique de spin atomique. La liaison des spins avec le réseau est assurée par un potentiel magnétique dépendant des positions des atomes. La nouveauté de ce potentiel réside dans la manière de paramétrer l'anisotropie magnétique qui est la manifestation d'un couplage spin-orbite. L'écriture d'un modèle de paires étendu de l'anisotropie permet de restituer les constantes de magnétostriction expérimentales du hcp-Co. En considérant un système canonique, où pression et température sont contrôlées, nous avons mis en évidence la transition de retournement de spin si particulière au Co vers 695K.Nous finissons par l'étude des retournements d'aimantation super-paramagnétiques de nanoplots de Co permettant de comparer ce couplage spin-réseau aux mesures récentes. / The magnetic properties of materials are strongly connected to their crystallographic structure. An atomistic model of the magnetization dynamics is developed which takes into account magneto-elasticity. Although this study is valid for all magnetic materials under temperatures, this study focuses only on Cobalt. In our effective model, atoms are described by three classical vectors as position, momentum and spin, which interact via an ad hoc magneto-mechanical potential.The atomistic spin dynamics is first considered. This method allows us to write the evolution equations of an atomic system of spins in which positions and impulsions are first frozen. However, a spin temperature is introduced to develop a natural connection with a thermal bath. Showing the limits of the stochastic approach, a genuine deterministic approach is followed to control the canonical temperature in this spin system.In a second step, several geometrical integrators are developed and analyzed to couple together both the molecular dynamics and atomic spin dynamics schemes. The connection between the spins and the lattice is provided by the atomic positions dependence of the magnetic potential. The novelty of this potential lies in the parameterization of the magnetic anisotropy which originates in the spin-orbit coupling. Using a dedicated pair model of anisotropy, the magnetostrictive constants of hcp-Co are restored. In a canonical system where pressure and temperature are controlled simultaneously, the transition of rotational magnetization of Co is found.Finally the magnetization reversals of super-paramagnetic Co nanodots is studied to quantify the impact of spin-lattice coupling respectively to recent measurements.

This bachelor's thesis deals with problematics of technological procedures and techniques for modification of microelectrodes with nanostructures. Furthermore, it describes a device needed for automated production of nanosensors, their properties and communication with computer. These devices communicate through RS-232 and USB interfaces.

Thermostated time evolutions are on a firm ground and widely used in classical molecular dynamics (MD) simulations. Hamilton´s equations of motion are supplemented by time-dependent pseudofriction terms that convert the microcanonical isoenergetic time evolution into a canonical isothermal time evolution, thus permitting the calculation of canonical ensemble averages by time averaging. However, similar methods for quantum MD schemes are still lacking. Given the rich dynamical behavior of ultracold trapped quantum gases depending on the value of the s-wave scattering length, it is timely to investigate how classical thermostating methods can be combined with powerful approximate quantum dynamics schemes to deal with interacting quantum systems at finite temperature. In this work, the popular method of Nose and Hoover to create canonically distributed positions and momenta in classical MD simulations is generalized to a genuine quantum system of infinite dimensionality. We show that for the quantum harmonic oscillator, the equations of motion in terms of coherent states may be modified in a Nose-Hoover manner to mimic the coupling of the system to a thermal bath and create a quantum canonical ensemble. The method is developed initially for a single particle and then generalized to the case of an arbitrary number of identical quantum particles, involving entangled distribution functions. The resulting isothermal equations of motion for bosons and fermions contain additional terms leading to Bose-attraction and Pauli-blocking, respectively. Questions of ergodicity are discussed for different coupling schemes. In the many-particle case, the superiority of the Nose-Hoover technique to a Langevin approach is demonstrated. In addition, the work contains an investigation of the Grilli-Tosatti thermostating method applied to the harmonic oscillator, and calculations for quantum wavefunctions moving with a time-invariant shape in a harmonic potential.

No description available.

Ce travail de thèse a pour objet l'étude de modèles markoviens qui résultent de la prise en compte d'incertitudes dans des systèmes possédant une dynamique hybride : entrées bruitées, dynamique mal connue, ou évènements aléatoires par exemple. De tels modèles, parfois qualifiés de Systèmes Hybrides Stochastiques (SHS), sont utilisés principalement en automatique et en recherche opérationnelle.<br /><br />Nous introduisons dans la première partie du mémoire la notion de processus diffusif par morceaux, qui fournit un cadre théorique général qui unifie les différentes classes de modèles "hybrides" connues dans la littérature. Différents aspects de ces modèles sont alors envisagés, depuis leur construction mathématique (traitée grâce au théorème de renaissance pour les processus de Markov) jusqu'à l'étude de leur générateur étendu, en passant par le phénomène de Zénon.<br /><br />La deuxième partie du mémoire s'intéresse plus particulièrement à la question de la "propagation de l'incertitude", c'est-à-dire à la manière dont évolue la loi marginale de l'état au cours du temps. L'équation de Fokker-Planck-Kolmogorov (FPK) usuelle est généralisée à diverses classes de processus diffusifs par morceaux, en particulier grâce aux notions d'intensité moyenne de sauts et de courant de probabilité. Ces résultats sont illustrés par deux exemples de modèles multidimensionnels, pour lesquels une résolution numérique de l'équation de FPK généralisée a été effectuée grâce à une discrétisation en volumes finis. La comparaison avec des méthodes de type Monte-Carlo est également discutée à partir de ces deux exemples.

Theme of diploma thesis is the heating of the indoor swimming pool. The thesis is departed to three parts. In the first part, there is a theoretical solution indoor climate of swimming pool. In the second part, there is a calculation solution of the project. Project solves heating of the indoor swimming pool. The last part is an experimental part. Theme of the experiment is measurement of temperature and relative humidity of the swimming pool.