The main objective of this thesis is to develop a physical design tool that is capable of being used by microarchitects to evaluate the impact of their design decisions on the physical design aspects of future microprocessor development. For deep submicron technology wire delay will scale increasingly badly compared to gate delay and so will become a major bottleneck to performance improvement. Three dimensional integrated circuits (3D ICs) offer a new method of dealing with non-linear wire latency by allowing shorter interconnects that act within their linear region. Thermal considerations in 3D ICs will be more important than traditional designs however, so this problem must also be addressed. This thesis presents a microarchitectural floorplanning tool that will help computer architects to attack the wire delay problem early in the design stages of higher performance microprocessors by including consideration of design for 3D ICs. Consideration of the new problems that occur due to the move to 3D and inherent difficulties with deep submicron design is included. Experiments demonstrate that this tool can generate microprocessor floorplans that include many objectives and continue to enhance performance into the next generation of high performance design.

Neonatal necrotizing enterocolitis (NEC) is one of the most severe digestive tract emergencies in neonates, involving bowel edema, hemorrhage, and necrosis, and can lead to serious complications including death. Since it is difficult to diagnose early, the morbidity and mortality rates are high due to severe complications in later stages of NEC and thus early detection is key to the treatment of NEC. In this thesis, a novel automatic image acquisition and analysis system combining a color and depth (RGB-D) sensor with an infrared (IR) camera is proposed for NEC diagnosis. A design for sensors configuration and a data acquisition process are introduced. A calibration method between the three cameras is described which aims to ensure frames synchronization and observation consistency among the color, depth, and IR images. Subsequently, complete segmentation procedures based on the original color, depth, and IR information are proposed to automatically separate the human body from the background, remove other interfering items, identify feature points on the human body joints, distinguish the human torso and limbs, and extract the abdominal region of interest. Finally, first-order statistical analysis is performed on thermal data collected over the entire extracted abdominal region to compare differences in thermal data distribution between different patient groups. Experimental validation in a real clinical environment is reported and shows encouraging results.

No description available.

Au cours des dernières années, l’essor spectaculaire des microsystèmes (ou MEMS), qui touche tous les domaines industriels, est à l’origine de nombreux et nouveaux progrès technologiques. Néanmoins, dans ce contexte prometteur de large envergure, la fiabilité des MEMS s’avère être la problématique à améliorer pour franchir la phase d’industrialisation à grande échelle. C’est dans le cadre de cette thématique de fiabilité des microsystèmes, que s’inscrit ce travail.La température étant un paramètre majeur entrant dans de nombreux mécanismes d’endommagement des MEMS, notre étude présente la conception et la réalisation d’un banc de thermographie infrarouge de haute résolution (2 µm), associé à la mise en œuvre d’une méthodologie d’analyse et de traitement des mesures infrarouges.Ce dispositif innovant permet un diagnostic in-situ, sans contact et rapide des défaillances des MEMS par mesures locales et quantitatives des pertes thermiques associées. Cet outil constitue une avancée importante pour détecter, mesurer et comprendre les mécanismes d’endommagement des MEMS. Il nous permet de reconstituer des images thermiques de tout type de microsystème en cours de fonctionnement ou soumis à des tests de vieillissement accéléré, et ceci afin de réaliser une analyse fine et rapide de leur fiabilité.Ce travail apporte de nouveaux résultats en ce qui concerne la détection des mécanismes de défaillance de différents types de MEMS-RF et tout particulièrement des MEMS-RF avec contact électrique. / Over the last few years, considerable effort has gone into the study of the failure mechanisms and reliability of MicroElectroMechanical Systems (MEMS). MEMS performance and reliability are affected by many parameters, such as the complex physical interactions between thermo-mechanical deformation, current flow, high power actuation and contact heating. In particular, temperature is a key issue for the design of a low loss and reliable MEMS. In order to improve device reliability it is essential to understand the thermal behaviours of RF-MEMS under standard or harsh current conditions. In this work, we present a new approach to investigate the failure mechanism of MEMS. An original set-up has been developed to localise and measure the heat loss of MEMS during actuation. Thermal characterization has been performed using infrared thermography to investigate the thermal sensitivity of MEMS. A brand new infrared bench was developed for temperature distribution measurement. An infrared camera, operating in the 1,5 - 5 µm bandwidth, was coupled to a new specific optic to reach an enhanced spatial resolution better than 2 µm/pixel. This work presents several results obtained on different advanced RF-MEMS including RF-MEMS switches where failure mechanism had been diagnosed.

Integrating the electrical and thermal community buildings' energy systems can play an important role in harvesting wasted energy resources and reduction of carbon emissions from buildings and electricity generation sectors. It also increases demand management flexibility by minimizing the curtailed electricity on the grid through electrified heating without increasing the electricity peak demand. The current work examines Integrated Community Energy and Harvesting systems (ICE-Harvest), a new generation of distributed energy resources systems (DERs). They prioritize the harvesting of community waste energy resources—for example, heat rejected from cooling processes and distributed peak electricity fossil-fuel-fired generators, as well as energy from curtailed clean grid electricity resources—to help in satisfying the heating demands of commercial and residential buildings. As such, ICE-Harvest systems provide a solution that can minimize greenhouse gas emissions from high-energy-consumption buildings in cold-climate regions such as North America and Northern Europe. In the current research, a thermal energy sharing model was developed to provide a dynamic characterization of the potential benefits of integrating and harvesting energy within a community of any number of buildings. The proposed model estimates the amount of rejected heat from cooling and refrigeration systems that can be simultaneously collected and used to heat other nearby buildings connected with a low temperature microthermal network (MTN). It also determines the proper timing and quantity of electricity used by the heat pumps in low-temperature MTNs as well as the reduction of both GHG emissions and the energy required from the EMC relative to conventional stand-alone systems. For an energy-balanced community cluster, the model showed that, over the course of a year, the energy harvesting would reduce this node’s GHG emissions by 74% and cover approximately 82% of the heating requirements compared to the BAU system. The results also revealed that the diversity in thermal demand between the connected buildings increases the harvesting potential. This research develops two clustering methods for the ICE-Harvest system. The proposed methods are clustering around anchor building and density-based (DB) clustering with post-processing by adding the closest anchor building to each cluster that focuses on the diversity of the buildings in each cluster. The energy sharing model is used to examine these techniques in comparison with the density-based clustering technique, the commonly used technique in the literature on a large database of 14000 high energy consumption buildings collected in Ontario, Canada. The results of this case study reveal that DB clustering with post-processing resulted in the largest emission reduction per unit piping network length of 360 t CO2eq /km/year. In addition, this research identified seven different cluster categories based on the total and simultaneous cooling-to-heating ratios of each cluster. The ICE harvest system integrates the thermal and electrical networks to add more flexibility to the electricity grid and schedule the electrification of heating (EoH). Current research provides a reduced model for the ICE-Harvest system to study its impact for over 1100 clusters of different categories on a provincial scale on the GHG emission and electricity demand from the grid. The use of ICE-Harvest systems at this scale can displace the energy required from the gas-fired heating resources by 11 TWh, accounting for over 70% of the clusters’ total heating requirements. This results in a 1.9 Mt CO2eq reduction in total GHG emissions, which represents around 60% of the clusters’ emissions. Operating conditions of the thermal network (TN) in the integrated community energy systems affect the ability to harvest waste energy and the reduction of GHG emissions as well as the electricity peak demand and consumption. In the current research, modeling of different thermal distribution network operating scenarios was performed for the different community energy profile clusters. These operation scenarios include low-temperature (fourth generation), ultra-low (fifth generation), a binary range-controlled temperature modulating thermal network operating between Low and Ultra-low temperatures (ICE-Harvest), and a new proposed scenario wherein a continuous range-controlled temperature modulating micro-thermal network. The continuous range-controlled temperature scenario shows the most benefits with the large implementation on the identified clusters. It adds more flexibility to balance the electricity grid as well as results in large GHG emission savings while controlling the increase in site electricity peak demand. The load profile of the cluster affects the selection of the most beneficial energy integrated system. This research shows that, for most of the heating-dominated clusters, it is better to employ the continuous range-controlled temperature TN with peak control and CHP on sites to serve the high heating demands along with short term and seasonal thermal storage. For the majority of balanced and /or cooling-dominated clusters, it is better to implement more carbon-free resources to the electricity grid or on-site that produce electricity but are not associated with heat such as wind, hydro, and solar PV panels. Parametric studies were performed in this research including changing the CHP size, the CHP utilization efficiency, and the grid gas-fired generators usage conditions to show their impact on the GHG emissions reduction from the clustered buildings. The analysis was implemented on a fleet of 1139 sites in Ontario and the results showed that the CHP size and operating hours have a measurable impact on GHG emission saving. The system can reach up to 58% and 66.5% emission savings of the total sites’ emissions with 93% and 39% operating hours respectively following the Ontario grid natural gas peaking power plants for the years of 2016 and 2017 with larger CHP sizes. The largest share of GHG emission saving in 2016 is by the CHP (61%) as opposed to 30% in 2017. The reduced models introduced in this research for the thermal energy sharing, the ICE-harvest system operation and sizing, and the MTN operation aid the investigation of the impact of the large implementation of the ICE-Harvest systems on the GHG emissions and electricity grid. / Thesis / Doctor of Philosophy (PhD)

The thesis focuses on the gas flow profile optimization of a non-conventional injector in a hot-wall MOCVD system. The injector’s gas flow profile is simulated with CFD and demonstrates awell-behaved laminar flow with a parabolic profile. To ensure the theory is in coherence with the reality, a qualitative study with five thermocouples in a test graphite piece of the was performed. First the thesis will take you through an introduction of the semiconductor field to arrive in a problem formulation. Then you will read about the principles of MOCVD systems, fluid dynamics principles and thermocouple theory. The experiment’s way of approach is thendescribed through all steps from blue print to results. A discussion about the result and the conclusion will be read before the proposals of future work based on the thesis work. The laminar flow is confirmed according to the resulting data and the limitations of the system is set to two different cases depending on background temperature. At 1000 °C a laminar flow is strongly indicated to be obtained at position 3A, closest to the growth area, within the gas flow range of 25 SLM regardless of background pressure, except for 700 mBar indicating turbulent flow for 15 SLM an up. At 20 and 200 mBar the laminar flow limit is suggested by data to be even higher and reaching a value of 35 SLM. At 450 °C the data indicate a laminar flow up to 20 SLM at position 3A regardless of background pressure condition, except for 700 mBar where the data indicate a laminar flow at 35 and 40 SLM. 50 mBar strongly indicates a laminar flow profile up to a gas flow of 35 SLM. With a background pressure of 20 mBar, the data suggests a laminar flow profile up to at least 25 SLM. At 100 mBar the data indicates a laminar flow within the range of 30 SLM.

Master’s thesis, „Optimization of hanger design in petrochemical industry heaters”, describes a procedure and means, leading to better hanger design in various cases. The thesis describes several problems which are necessary to be solved in hanger design. Technical expertise is executed on hangers of various designs. The procedure of optimization is shown on one chosen hanger design.