Dynamic thermal performance of building components and application to the experimental and theoretical analysis of a ventilated façade

The general aim of this work is to contribute to the energy performance assessment of ventilated façades by the simultaneous use of experimental data and numerical simulations. A significant amount of experimental work was done on different types of ventilated façades with natural ventilation. The measurements were taken on a test building. The external walls of this tower are rainscreen ventilated façades. Ventilation grills are located at the top and at the bottom of the tower. In this work the modelling of the test building using a dynamic thermal simulation program (ESP-r) is presented and the main results discussed. In order to investigate the best summer thermal performance of rainscreen ventilated skin façade a study for different setups of rainscreen walls was made. In particular, influences of ventilation grills, air cavity thickness, skin colour, skin material, orientation of façade were investigated. It is shown that some types of rainscreen ventilated façade typologies are capable of lowering the cooling energy demand of a few percent points.

I dati metereologici per applicazioni energetiche e ambientali

Many energetic and environmental evaluations need appropriate meteorological data, as input to analysis and prevision softwares. In Italy there aren't adeguate meteorological data because, in many cases, they are incomplete, incorrect and also very expensive for a long-term analysis (that needs multi-year data sets). A possible solution to this problem is the use of a Typical Meteorological Year (TRY), generated for specific applications. Nowadays the TRYs have been created, using statistical criteria, just for the analysis of solar energy systems and for predicting the thermal performance of buildings, applying it also to the study of photovoltaic plants (PV), though not specifically created for this type of application. The present research has defined the methodology for the creation of TRYs for different applications. In particular TRYs for environmental and wind plant analysis have been created. This is the innovative aspect of this research, never explored before. In additions, the methodology of the generation for the PV TRYs has been improved. The results are very good and the TRYs generated for these applications are adeguate to characterize the climatic condition of the place over a long period and can be used for energetic and environmental studies.

Electrothermal characterization and nonlinear modelling of GaN transistors for telecommunication circuit design

This thesis starts showing the main characteristics and application fields of the AlGaN/GaN HEMT technology, focusing on reliability aspects essentially due to the presence of low frequency dispersive phenomena which limit in several ways the microwave performance of this kind of devices. Based on an equivalent voltage approach, a new low frequency device model is presented where the dynamic nonlinearity of the trapping effect is taken into account for the first time allowing considerable improvements in the prediction of very important quantities for the design of power amplifier such as power added efficiency, dissipated power and internal device temperature. An innovative and low-cost measurement setup for the characterization of the device under low-frequency large-amplitude sinusoidal excitation is also presented. This setup allows the identification of the new low frequency model through suitable procedures explained in detail. In this thesis a new non-invasive empirical method for compact electrothermal modeling and thermal resistance extraction is also described. The new contribution of the proposed approach concerns the non linear dependence of the channel temperature on the dissipated power. This is very important for GaN devices since they are capable of operating at relatively high temperatures with high power densities and the dependence of the thermal resistance on the temperature is quite relevant. Finally a novel method for the device thermal simulation is investigated: based on the analytical solution of the tree-dimensional heat equation, a Visual Basic program has been developed to estimate, in real time, the temperature distribution on the hottest surface of planar multilayer structures. The developed solver is particularly useful for peak temperature estimation at the design stage when critical decisions about circuit design and packaging have to be made. It facilitates the layout optimization and reliability improvement, allowing the correct choice of the device geometry and configuration to achieve the best possible thermal performance.

Experimental and Numerical Analysis of Gas Forced Convection through Microtubes and Micro Heat Exchangers

The last decade has witnessed very fast development in microfabrication technologies. The increasing industrial applications of microfluidic systems call for more intensive and systematic knowledge on this newly emerging field. Especially for gaseous flow and heat transfer at microscale, the applicability of conventional theories developed at macro scale is not yet completely validated; this is mainly due to scarce experimental data available in literature for gas flows. The objective of this thesis is to investigate these unclear elements by analyzing forced convection for gaseous flows through microtubes and micro heat exchangers. Experimental tests have been performed with microtubes having various inner diameters, namely 750 m, 510 m and 170 m, over a wide range of Reynolds number covering the laminar region, the transitional zone and also the onset region of the turbulent regime. The results show that conventional theory is able to predict the flow friction factor when flow compressibility does not appear and the effect of fluid temperature-dependent properties is insignificant. A double-layered microchannel heat exchanger has been designed in order to study experimentally the efficiency of a gas-to-gas micro heat exchanger. This microdevice contains 133 parallel microchannels machined into polished PEEK plates for both the hot side and the cold side. The microchannels are 200 µm high, 200 µm wide and 39.8 mm long. The design of the micro device has been made in order to be able to test different materials as partition foil with flexible thickness. Experimental tests have been carried out for five different partition foils, with various mass flow rates and flow configurations. The experimental results indicate that the thermal performance of the countercurrent and cross flow micro heat exchanger can be strongly influenced by axial conduction in the partition foil separating the hot gas flow and cold gas flow.

Experimental and Numerical Analysis of Gas Flows in Microchannels and Micro Heat Exchanger

Due to increased interest in miniaturization, great attention has been given in the recent decade to the micro heat exchanging systems. Literature survey suggests that there is still a limited understanding of gas flows in micro heat exchanging systems. The aim of the current thesis is to further the understanding of fluid flow and heat transfer phenomenon inside such geometries when a compressible working fluid is utilized. A combined experimental and numerical approach has been utilized in order to overcome the lack of employable sensors for micro dimensional channels. After conducting a detailed comparison between various data reduction methodologies employed in the literature, the best suited methodology for gas microflow experimentalists is proposed. A transitional turbulence model is extensively validated against the experimental results of the microtubes and microchannels under adiabatic wall conditions. Heat transfer analysis of single microtubes showed that when the compressible working fluid is used, Nusselt number results are in partial disagreement with the conventional theory at highly turbulent flow regime for microtubes having a hydraulic diameter less than 250 microns. Experimental and numerical analysis on a prototype double layer microchannel heat exchanger showed that compressibility is detrimental to the thermal performance. It has been found that compressibility effects for micro heat exchangers are significant when the average Mach number at the outlet of the microchannel is greater than 0.1 compared to the adiabatic limit of 0.3. Lastly, to avoid a staggering amount of the computational power needed to simulate the micro heat exchanging systems with hundreds of microchannels, a reduced order model based on the porous medium has been developed that considers the compressibility of the gas inside microchannels. The validation of the proposed model against experimental results of average thermal effectiveness and the pressure loss showed an excellent match between the two.

High power density electrical machines with hairpin windings

Nowadays, electrical machines are seeing an ever-increasing development and extensive research is currently being dedicated to the improvement of their efficiency and torque/power density. Compared to conventional random windings, hairpin winding inherently features lower DC resistance, higher fill factor, better thermal performance, improved reliability, and an automated manufacturing process. However, several challenges need to be addressed, including electromagnetic, thermal, and manufacturing aspects. Of these, the high ohmic losses at high-frequency operations due to skin and proximity effects are the most severe, resulting in low efficiency or high-temperature values. In this work, the hairpin winding challenges were highlighted at high-frequency operations and at showing the limits of applicability of these standard approaches. Afterward, a multi-objective design optimization is proposed aiming to enhance the exploitation of the hairpin technology in electrical machines. Efficiency and volume power density are considered as main design objectives. Subsequently, a changing paradigm is made for the design of electric motors equipped with hairpin windings, where it is proven that a temperature-oriented approach would be beneficial when designing this type of pre-formed winding. Furthermore, the effect of the rotor topology on AC losses is also considered. After providing design recommendations and FE electromagnetic and thermal evaluations, experimental tests are also performed for validation purposes on a motorette wound with pre-formed conductors. The results show that operating the machine at higher temperatures could be beneficial to efficiency, particularly in high-frequency operations where AC losses are higher at low operating temperatures. The last part of the thesis focuses on comparing the main electromagnetic performance metrics for a conventional hairpin winding, wound onto a benchmark stator with a semi-closed slot opening design, and a continuous hairpin winding, in which the slot opening is open. Lastly, the adoption of semi-magnetic slot wedges is investigated to improve the overall performance of the motor.

Monitoring and Prediction of Thermal Emergencies in High Performance Computing Systems

Modern scientific discoveries are driven by an unsatisfiable demand for computational resources. High-Performance Computing (HPC) systems are an aggregation of computing power to deliver considerably higher performance than one typical desktop computer can provide, to solve large problems in science, engineering, or business. An HPC room in the datacenter is a complex controlled environment that hosts thousands of computing nodes that consume electrical power in the range of megawatts, which gets completely transformed into heat. Although a datacenter contains sophisticated cooling systems, our studies indicate quantitative evidence of thermal bottlenecks in real-life production workload, showing the presence of significant spatial and temporal thermal and power heterogeneity. Therefore minor thermal issues/anomalies can potentially start a chain of events that leads to an unbalance between the amount of heat generated by the computing nodes and the heat removed by the cooling system originating thermal hazards. Although thermal anomalies are rare events, anomaly detection/prediction in time is vital to avoid IT and facility equipment damage and outage of the datacenter, with severe societal and business losses. For this reason, automated approaches to detect thermal anomalies in datacenters have considerable potential. This thesis analyzed and characterized the power and thermal characteristics of a Tier0 datacenter (CINECA) during production and under abnormal thermal conditions. Then, a Deep Learning (DL)-powered thermal hazard prediction framework is proposed. The proposed models are validated against real thermal hazard events reported for the studied HPC cluster while in production. This thesis is the first empirical study of thermal anomaly detection and prediction techniques of a real large-scale HPC system to the best of my knowledge. For this thesis, I used a large-scale dataset, monitoring data of tens of thousands of sensors for around 24 months with a data collection rate of around 20 seconds.

Model predictive control in thermal management of multiprocessor systems-on-chip

MultiProcessor Systems-on-Chip (MPSoC) are the core of nowadays and next generation computing platforms. Their relevance in the global market continuously increase, occupying an important role both in everydaylife products (e.g. smartphones, tablets, laptops, cars) and in strategical market sectors as aviation, defense, robotics, medicine. Despite of the incredible performance improvements in the recent years processors manufacturers have had to deal with issues, commonly called “Walls”, that have hindered the processors development. After the famous “Power Wall”, that limited the maximum frequency of a single core and marked the birth of the modern multiprocessors system-on-chip, the “Thermal Wall” and the “Utilization Wall” are the actual key limiter for performance improvements. The former concerns the damaging effects of the high temperature on the chip caused by the large power densities dissipation, whereas the second refers to the impossibility of fully exploiting the computing power of the processor due to the limitations on power and temperature budgets. In this thesis we faced these challenges by developing efficient and reliable solutions able to maximize performance while limiting the maximum temperature below a fixed critical threshold and saving energy. This has been possible by exploiting the Model Predictive Controller (MPC) paradigm that solves an optimization problem subject to constraints in order to find the optimal control decisions for the future interval. A fully-distributedMPC-based thermal controller with a far lower complexity respect to a centralized one has been developed. The control feasibility and interesting properties for the simplification of the control design has been proved by studying a partial differential equation thermal model. Finally, the controller has been efficiently included in more complex control schemes able to minimize energy consumption and deal with mixed-criticalities tasks

Mathematical Optimization Applied to Thermal and Electrical Energy Systems

This Thesis aims at building and discussing mathematical models applications focused on Energy problems, both on the thermal and electrical side. The objective is to show how mathematical programming techniques developed within Operational Research can give useful answers in the Energy Sector, how they can provide tools to support decision making processes of Companies operating in the Energy production and distribution and how they can be successfully used to make simulations and sensitivity analyses to better understand the state of the art and convenience of a particular technology by comparing it with the available alternatives. The first part discusses the fundamental mathematical background followed by a comprehensive literature review about mathematical modelling in the Energy Sector. The second part presents mathematical models for the District Heating strategic network design and incremental network design. The objective is the selection of an optimal set of new users to be connected to an existing thermal network, maximizing revenues, minimizing infrastructure and operational costs and taking into account the main technical requirements of the real world application. Results on real and randomly generated benchmark networks are discussed with particular attention to instances characterized by big networks dimensions. The third part is devoted to the development of linear programming models for optimal battery operation in off-grid solar power schemes, with consideration of battery degradation. The key contribution of this work is the inclusion of battery degradation costs in the optimisation models. As available data on relating degradation costs to the nature of charge/discharge cycles are limited, we concentrate on investigating the sensitivity of operational patterns to the degradation cost structure. The objective is to investigate the combination of battery costs and performance at which such systems become economic. We also investigate how the system design should change when battery degradation is taken into account.

Miglioramento delle performance termiche e energetiche degli edifici rurali: valutazione del retrofit di locali per la conservazione del vino su casi studio

Il presente studio si colloca all’interno di una ricerca più ampia volta alla definizione di criteri progettuali finalizzati all’ottimizzazione delle prestazioni energetiche delle cantine di aziende vitivinicole, di dimensioni produttive medio - piccole. Nello specifico la ricerca riguarda la riqualificazione di fabbricati rurali esistenti di modeste dimensioni, da convertire a magazzini per la conservazione del vino in bottiglia. Lo studio si pone come obiettivo la definizione di criteri di analisi per la valutazione di interventi di retrofit di tali fabbricati, volto sia al miglioramento delle prestazioni energetiche dell’involucro edilizio, sia alla riduzione del fabbisogno energetico legato al funzionamento di eventuali impianti di controllo termico. La ricerca è stata condotta mediante l’utilizzo del software di simulazione termica Energy Plus, per ottenere i valori simulati di temperatura interna relativi ai diversi scenari migliorativi ipotizzati, e mediante la successiva definizione di indicatori che esplicitino l’influenza delle principali variabili progettuali sull’andamento delle temperature interne dei locali di conservazione e sul fabbisogno energetico del fabbricato necessario a garantire l’intervallo di temperatura di comfort del vino. Tra tutti gli interventi possibili per il miglioramento della prestazione energetica degli edifici, quelli analizzati in questo studio prevedono l’aggiunta di un isolamento a cappotto delle pareti esterne, l’isolamento della copertura e l’aggiunta di una struttura ombreggiante vegetale esterna. I risultati ottenuti danno una prima indicazione sugli interventi più efficaci in termini di miglioramento energetico e mettono in luce l’utilità del criterio proposto nell’evidenziare le criticità degli interventi migliorativi ipotizzati. Il metodo definito nella presente ricerca risulta quindi un valido strumento di valutazione a supporto della progettazione degli interventi di retrofit dei fabbricati rurali da convertire a magazzini per la conservazione del vino.

Study of new Catalysts for the Selective Oxidation of n-Butane to Maleic Anhydride: The Role of Catalysts Thermal Treatment

Maleic anhydride (MA) is a very versatile molecule, indeed, with three functional groups (two carbonyl groups and one double bond C=C) it is an excellent joining and cross-linking material. It is obtained via selective oxidation of n-butane, using vanadyl pyrophosphate as a catalyst. The catalytic system has been largely studied over the years and it is normally used in the industrial production of MA, but the main open problem is to completely control its preparation. This thesis reports the effect of different preparation parameters employed during the calcination procedure for the transformation of precursor into the active catalyst. The thermal treatment is already known to be favoured in the presence of water, hence the first study was on the role of different amount of water co-fed with air, leading to obtain catalysts with an higher crystallinity. This is not the only parameter to control: the molar ratio of oxygen has also an important role, to obtain an active and selective catalyst. Some tests decreasing the “oxidizing power” of the mixture were carried out and it was observed a progressive development of VPP phase instead of oxidized V/P/O systems. Established the role of water and oxygen, the optimal conditions have been found when a mixture composed of air, water and nitrogen was used for the calcination, in the molar ratio of 30:10:60% respectively. Also at the lower temperature tested, i.e. 400°C, the catalyst presents the higher conversion of n-butane and MA yield compared to all other samples. The important conclusion we have reached is that not higher amount of water is necessary to obtain the most performing catalyst, thus leading to economic savings. Performing the same experiments on two different precursors, give catalysts with different activity but the mixture previously descripted is always the one that leads to the best performance.

Growth performance, gut health, and metabolism of broilers under thermoneutral and heat stress conditions: multidisciplinary studies on the effects of nutritional strategies and genotype

This PhD project aimed to (i) investigate the effects of three nutritional strategies (supplementation of a synbiotic, a muramidase, or arginine) on growth performance, gut health, and metabolism of broilers fed without antibiotics under thermoneutral and heat stress conditions and to (ii) explore the impacts of heat stress on hypothalamic regulation of feed intake in three broiler lines from diverse stages of genetic selection and in the red jungle fowl, the ancestor of domestic chickens. Synbiotic improved feed efficiency and footpad health, increased Firmicutes and reduced Bacteroidetes in the ceca of birds kept in thermoneutral conditions, while did not mitigate the impacts of heat stress on growth performance. Under optimal thermal conditions, muramidase increased final body weight and reduced cumulative feed intake and feed conversion ratio in a dose-dependent way. The highest dose reduced the risk of footpad lesions, cecal alpha diversity, the Firmicutes to Bacteroidetes ratio, and butyrate producers, increased Bacteroidaceae and Lactobacillaceae, plasmatic levels of bioenergetic metabolites, and reduced the levels of pro-oxidant metabolites. The same dose, however, failed to reduce the effects of heat stress on growth performance. Arginine supplementation improved growth rate, final body weight, and feed efficiency, increased plasmatic levels of arginine and creatine and hepatic levels of creatine and essential amino acids, reduced alpha diversity, Firmicutes, and Proteobacteria (especially Escherichia coli), and increased Bacteroidetes and Lactobacillus salivarius in the ceca of thermoneutral birds. No arginine-mediated attenuation of heat stress was found. Heat stress altered protein metabolism and caused the accumulation of antioxidant and protective molecules in oxidative stress-sensitive tissues. Arginine supplementation, however, may have partially counterbalanced the effects of heat stress on energy homeostasis. Stable gene expression of (an)orexigenic neuropeptides was found in the four chicken populations studied, but responses to hypoxia and heat stress appeared to be related to feed intake regulation.

Novel methods of state estimation and parameter identification for high-performance motorcycles

This research activity aims at providing a reliable estimation of particular state variables or parameters concerning the dynamics and performance optimization of a MotoGP-class motorcycle, integrating the classical model-based approach with new methodologies involving artificial intelligence. The first topic of the research focuses on the estimation of the thermal behavior of the MotoGP carbon braking system. Numerical tools are developed to assess the instantaneous surface temperature distribution in the motorcycle's front brake discs. Within this application other important brake parameters are identified using Kalman filters, such as the disc convection coefficient and the power distribution in the disc-pads contact region. Subsequently, a physical model of the brake is built to estimate the instantaneous braking torque. However, the results obtained with this approach are highly limited by the knowledge of the friction coefficient (μ) between the disc rotor and the pads. Since the value of μ is a highly nonlinear function of many variables (namely temperature, pressure and angular velocity of the disc), an analytical model for the friction coefficient estimation appears impractical to establish. To overcome this challenge, an innovative hybrid solution is implemented, combining the benefit of artificial intelligence (AI) with classical model-based approach. Indeed, the disc temperature estimated through the thermal model previously implemented is processed by a machine learning algorithm that outputs the actual value of the friction coefficient thus improving the braking torque computation performed by the physical model of the brake. Finally, the last topic of this research activity regards the development of an AI algorithm to estimate the current sideslip angle of the motorcycle's front tire. While a single-track motorcycle kinematic model and IMU accelerometer signals theoretically enable sideslip calculation, the presence of accelerometer noise leads to a significant drift over time. To address this issue, a long short-term memory (LSTM) network is implemented.