Os efeitos nucleares em processos de produ¸c˜ao de quarkonium no Relativistic Heavy Ion Collider (RHIC) e no Large Hadron Collider (LHC)

Neste trabalho de disserta¸c˜ao, investigamos os efeitos nucleares em processos de produ¸c˜ao de quarkonium no Relativistic Heavy Ion Collider (RHIC) e no Large Hadron Collider (LHC). Para tanto, consideramos o Modelo de Evapora¸c˜ao de Cor (CEM), baseado em processos partˆonicos calculados mediante a QCD perturbativa e em intera¸c˜oes n˜ao perturbativas via troca de gl´uons suaves para a forma¸c˜ao do quarkonium. Supress˜ao de quarkonium ´e um dos sinais de forma¸c˜ao do assim chamado Plasma de Quarks e Gl´uons (QGP) em colis˜oes ultrarelativ´ısticas de ´ıons pesados. No entanto, a supress˜ao n˜ao ´e somente causada em colis˜oes n´ucleo-n´ucleo (AA) devido `a forma¸c˜ao do QGP. De fato, a supress˜ao de quarkonium tamb´em foi observada em colis˜oes pr´oton-n´ucleo (pA). A fim de separar os efeitos da mat´eria quente (devidos ao QGP) e fria (efeitos n˜ao devidos ao QGP), pode-se olhar primeiro para colis˜oes pA, onde somente efeitos de mat´eria fria desempenham um papel fundamental, e depois aplicar esses efeitos em colis˜oes AA, uma vez que parte da supress˜ao ´e devido a efeitos de mat´eria fria. No regime de altas energias, a produ¸c˜ao do quarkonium ´e fortemente dependente da distribui¸c˜ao de gl´uons nuclear, o que viabiliza uma oportunidade ´unica de estudar o comportamento de pequeno x dos gl´uons dentro do n´ucleo e, consequentemente, restringir os efeitos nucleares. Estudamos os processos nucleares utilizando distintas parametriza¸c˜oes para as distribui¸c˜oes partˆonicas nucleares. Calculamos a raz˜ao nuclear para processos pA e AA em fun¸c˜ao da vari´avel rapidez para a produ¸c˜ao de quarkonium, o que permite estimar os efeitos nucleares. Al´em disso, apresentamos uma compara¸c˜ao com os dados do RHIC para a produ¸c˜ao do m´eson J/Ψ em colis˜oes pA, demonstrando que a an´alise deste observ´avel ´e uma quest˜ao em aberto na literatura. Adicionalmente, estimamos a produ¸c˜ao de quarks pesados e quarkonium na etapa inicial e durante a fase termal de uma colis˜ao ultrarelativ´ıstica de ´ıons pesados. O objetivo deste estudo ´e estimar as distintas contribui¸c˜oes para a produ¸c˜ao e de alguns efeitos do meio nuclear.

Experimental and analytical investigation of refrigerant and lubricant migration

The off-cycle refrigerant mass migration has a direct influence on the on-cycle performance since compressor energy is necessary to redistribute the refrigerant mass. No studies, as of today, are available in the open literature which experimentally measured the lubricant migration within a refrigeration system during cycling or stop/start transients. Therefore, experimental procedures measuring the refrigerant and lubricant migration through the major components of a refrigeration system during stop/start transients were developed and implemented. Results identifying the underlying physics are presented. The refrigerant and lubricant migration of an R134a automotive A/C system-utilizing a fixed orifice tube, minichannel condenser, plate and fin evaporator, U-tube type accumulator and fixed displacement compressor-was measured across five sections divided by ball valves. Using the Quick-Closing Valve Technique (QCVT) combined with the Remove and Weigh Technique (RWT) using liquid nitrogen as the condensing agent resulted in a measurement uncertainty of 0.4 percent regarding the total refrigerant mass in the system. The determination of the lubricant mass distribution was achieved by employing three different techniques-Remove and Weigh, Mix and Sample, and Flushing. To employ the Mix and Sample Technique a device-called the Mix and Sample Device-was built. A method to separate the refrigerant and lubricant was developed with an accuracy-after separation-of 0.04 grams of refrigerant left in the lubricant. When applying the three techniques, the total amount of lubricant mass in the system was determined to within two percent. The combination of measurement results-infrared photography and high speed and real time videography-provide unprecedented insight into the mechanisms of refrigerant and lubricant migration during stop-start operation. During the compressor stop period, the primary refrigerant mass migration is caused by, and follows, the diminishing pressure difference across the expansion device. The secondary refrigerant migration is caused by a pressure gradient as a result of thermal nonequilibrium within the system and causes only vapor phase refrigerant migration. Lubricant migration is proportional to the refrigerant mass during the primary refrigerant mass migration. During the secondary refrigerant mass migration lubricant is not migrating. The start-up refrigerant mass migration is caused by an imbalance of the refrigerant mass flow rates across the compressor and expansion device. The higher compressor refrigerant mass flow rate was a result of the entrainment of foam into the U-tube of the accumulator. The lubricant mass migration during the start-up was not proportional to the refrigerant mass migration. The presence of water condensate on the evaporator affected the refrigerant mass migration during the compressor stop period. Caused by an evaporative cooling effect the evaporator held 56 percent of the total refrigerant mass in the system after three minutes of compressor stop time-compared to 25 percent when no water condensate was present on the evaporator coil. Foam entrainment led to a faster lubricant and refrigerant mass migration out of the accumulator than liquid entrainment through the hole at the bottom of the U-tube. The latter was observed for when water condensate was present on the evaporator coil because-as a result of the higher amount of refrigerant mass in the evaporator before start-up-the entrainment of foam into the U-tube of the accumulator ceased before the steady state refrigerant mass distribution was reached.

A numerical model for prediction of oil, trajectory due to extraction activity in the north coasts of the Persian Gulf

This thesis considers a three- dimensional numerical model based on 3-D Navier— Stokes and continuity equations involving various wind speeds (North west), water surface levels, horizontal shier stresses, eddy viscosity, densities of oil and gas condensate- water mixture flows. The model is used to simulate the prediction of the surface movement of oil and gas condensate slicks from spill accident in the north coasts of Persian Gulf.

Non-invasive monitoring of changes in exhaled markers of airway inflammation in Thoroughbred racehorses

Exhaled breath (EB) and exhaled breath condensate (EBC) contain numerous volatile gases and a wide-array of non-volatile compounds, several of which have been investigated as markers of lower airway inflammation in human and veterinary medicine and have been used to diagnose and monitor diseases associated with pulmonary inflammation. The identification of reliable biomarkers within EB and EBC is an active research focus with the common goal of establishing non-invasive and repeatable assessment of respiratory health and disease in mammals. The application of EB and EBC analysis holds considerable appeal in the investigation of respiratory disease in Thoroughbred racehorses, as inflammatory airway disease (IAD) is a common cause for poor performance in this population of animals. This study documented that EB and EBC samples can be safely collected from Thoroughbred racehorses in their own environment, without adverse effect or interference with the horse’s training regimen. The use of off-line collection and analysis of exhaled gases via chemiluminescence is suitable for the measurement of exhaled carbon monoxide, but is not appropriate for analyzing exhaled nitric oxide in horses. Significant changes in the concentration of exhaled CO and the pH of EBC occurred in response to strenuous exercise and when exercising in different environmental temperatures. Exhaled CO was associated with tracheal mucus score (and the number of neutrophils in the mucus) and EBC pH was significantly different in horses with evidence of neutrophilic IAD compared to horses without IAD. Numerous physiological and environmental variables were identified as confounding factors in the assessment of both exhaled CO and EBC pH, with respiratory rate prior to EB collection, and during EBC collection, consistently identified as an explanatory variable influencing the concentration of exhaled biomarkers. Further studies in EB and EBC analysis in horses need to focus on objectively accounting for key respiratory dynamics during sample collection.

A geometric study of liquid retention in open-cell metal foams

Open-cell metal foams show promise as an emerging novel material for heat exchanger applications. The high surface-area-to-volume ratio suggests increased compactness and decrease in weight of heat exchanger designs. However, the metal foam structure appears conducive to condensate retention, which would degenerate heat transfer performance. This research investigates the condensate retention behavior of aluminum open-cell metal foams through the use of static dip tests and geometrical classification via X-ray Micro-Computed Tomography. Aluminum open-cell metal foam samples of 5, 10, 20, and 40 pores per inch (PPI), all having a void fraction greater than 90%, were included in this investigation. In order to model the condensate retention behavior of metal foams, a clearer understanding of the geometry was required. After exploring the ideal geometries presented in the open literature, X-ray Micro-Computed Tomography was employed to classify the actual geometry of the metal foam samples. The images obtained were analyzed using specialized software from which geometric information including strut length and pore shapes were extracted. The results discerned a high variability in ligament length, as well as features supporting the ideal geometry known as the Weaire-Phelan unit cell. The static dip tests consisted of submerging the metal foam samples in a liquid, then allowing gravity-induced drainage until steady-state was reached and the liquid remaining in the metal foam sample was measured. Three different liquids, water, ethylene glycol, and 91% isopropyl alcohol, were employed. The behaviors of untreated samples were compared to samples subjected to a Beomite surface treatment process, and no significant differences in retention behavior were discovered. The dip test results revealed two distinct regions of condensate retention, each holding approximately half of the total liquid retained by the sample. As expected, condensate retention increased as the pores sizes decreased. A model based on surface tension was developed to predict the condensate retention in the metal foam samples and verified using a regular mesh. Applying the model to both the ideal and actual metal foam geometries showed good agreement with the dip test results in this study.

Entropy production in the early-cosmology pionic phase

We point out that in the early universe, for temperatures in the approximate interval 150-80 MeV (after the quark-gluon plasma), pions carried a large share of the entropy and supported the largest inhomogeneities. Its thermal conductivity (previously calculated) allows the characterization of entropy production due to equilibration (damping) of thermal fluctuations. Simple model distributions of thermal fluctuations are considered and the associated entropy production evaluated.

Unpolarized transverse momentum dependent parton distribution and fragmentation functions at next-to-next-to-leading order

The transverse momentum dependent parton distribution/fragmentation functions (TMDs) are essential in the factorization of a number of processes like Drell-Yan scattering, vector boson production, semi-inclusive deep inelastic scattering, etc. We provide a comprehensive study of unpolarized TMDs at next-to-next-to-leading order, which includes an explicit calculation of these TMDs and an extraction of their matching coefficients onto their integrated analogues, for all flavor combinations. The obtained matching coefficients are important for any kind of phenomenology involving TMDs. In the present study each individual TMD is calculated without any reference to a specific process. We recover the known results for parton distribution functions and provide new results for the fragmentation functions. The results for the gluon transverse momentum dependent fragmentation functions are presented for the first time at one and two loops. We also discuss the structure of singularities of TMD operators and TMD matrix elements, crossing relations between TMD parton distribution functions and TMD fragmentation functions, and renormalization group equations. In addition, we consider the behavior of the matching coefficients at threshold and make a conjecture on their structure to all orders in perturbation theory.

Pirólise termoquímica de pós da fibra de coco seco em um reator de cilindro rotativo para produção de bio-óleo

This master thesis aims at developing a new methodology for thermochemical degradation of dry coconut fiber (dp = 0.25mm) using laboratory rotating cylinder reactor with the goal of producing bio-oil. The biomass was characterized by infrared spectroscopy with Fourier transform FTIR, thermogravimetric analysis TG, with evaluation of activation energy the in non-isothermal regime with heating rates of 5 and 10 °C/min, differential themogravimetric analysis DTG, sweeping electron microscopy SEM, higher heating value - HHV, immediate analysis such as evaluated all the amounts of its main constituents, i.e., lignin, cellulose and hemicelluloses. In the process, it was evaluated: reaction temperature (450, 500 and 550oC), carrier gas flow rate (50 and 100 cm³/min) and spin speed (20 and 25 Hz) to condensate the bio-oil. The feed rate of biomass (540 g/h), the rotation of the rotating cylinder (33.7 rpm) and reaction time (30 33 min) were constant. The phases obtained from the process of pyrolysis of dry coconut fiber were bio-oil, char and the gas phase non-condensed. A macroscopic mass balance was applied based on the weight of each phase to evaluate their yield. The highest yield of 20% was obtained from the following conditions: temperature of 500oC, inert gas flow of 100 cm³/min and spin speed of 20 Hz. In that condition, the yield in char was 24.3%, non-condensable gas phase was 37.6% and losses of approximately 22.6%. The following physicochemical properties: density, viscosity, pH, higher heating value, char content, FTIR and CHN analysis were evaluated. The sample obtained in the best operational condition was subjected to a qualitative chromatographic analysis aiming to know the constituents of the produced bio-oil, which were: phenol followed by sirigol, acetovanilona and vinyl guaiacol. The solid phase (char) was characterized through an immediate analysis (evaluation of moisture, volatiles, ashes and fixed carbon), higher heating value and FTIR. The non-condensing gas phase presented as main constituents CO2, CO and H2. The results were compared to the ones mentioned by the literature.

Quarkonia and heavy-light mesons in a covariant quark model

Preliminary calculations using the Covariant Spectator Theory (CST) employed a scalar linear confining interaction and an additional constant vector potential to compute the mesonic mass spectra. In this work we generalize the confining interaction to include more general structures, in particular a vector and also a pseudoscalar part, as suggested by a recent study. A one-gluon-exchange kernel is also implemented to describe the short-range part of the interaction. We solve the simplest CST approxima- tion to the complete Bethe-Salpeter equation, the one-channel spectator equation, using a numerical technique that eliminates all singularities from the kernel. The parameters of the model are determined through a fit to the experimental pseudoscalar meson spectra, with a good agreement for both quarkonia and heavy-light states.

Development of a thermochemical/biological process to convert waste biomass into new resources

The increasing attention to environmental issues of recent times encourages us to find new methods for the production of energy from renewable sources, and to improve existing ones, increasing their energy yield. Most of the waste and agricultural residues, with a high content of lignin and non-hydrolysable polymers, cannot be effectively transformed into biofuels with existing technology. The purpose of the study was to develop a new thermochemical/ biological process (named Py-AD) for the valorization of scarcely biodegradable substances. A complete continuous prototype was design built and run for 1 year. This consists into a slow pyrolysis system coupled with two sequential digesters and showed to produce a clean pyrobiogas (a biogas with significant amount of C2-C3 hydrocarbons and residual CO/H2), biochar and bio-oil. Py-AD yielded 31.7% w/w biochar 32.5% w/w oil and 24.8% w/w pyrobiogas. The oil condensate obtained was fractionated in its aqueous and organic fraction (87% and 13% respectively). Subsequently, the anaerobic digestion of aqueous fraction was tested in a UASB reactor, for 180 days, in increasing organic loading rate (OLR). The maximum convertible concentration without undergoing instability phenomena and with complete degradation of pyrogenic chemicals was 1.25 gCOD L digester-1 d-1. The final yield of biomethane was equal to 40% of the theoretical yield and with a noticeable additional production equal to 20% of volatile fatty acids. The final results confirm that anaerobic digestion can be used as a useful tool for cleaning of slow pyrolysis products (both gas and condensable fraction) and the obtaining of relatively clean pyrobiogas that could be directly used in internal combustion engine.

Structural health monitoring of storage tanks

In this thesis, Ph.D candidate presents a compact sensor node (SN) designed for long-term and real-time acoustic emission (AE) monitoring of above ground storage tanks (ASTs). Each SN exploits up to three inexpensive low-frequency sensors based on piezoelectric diaphragms for effective leakage detection, and it is capable by means of built-in Digital Signal Processing functionalities to process the acquired time waveforms extracting the AE features usually required by testing protocols. Alternatively, capability to plug three high frequency AE sensors to a SN for corrosion simulated phenomena detection is envisaged and demonstrated. Another innovative aspect that the Ph.D candidate presents in this work is an alternative mathematical model of corrosion location on the bottom of the AST. This approach implies considering the three-dimensional localization model versus the two-dimensional commonly used according to the literature. This approach is aimed at significant optimization in the number of sensors in relation to the standard approach for solving localization problems as well as to allow filtering the false AE events related to the condensate droplets from AST ceiling. The technological implementation of this concept required the solution of a number of technical problems, such as the precise time of arrival (ToA) signal estimation, vertical localization of the AE source and multilaration solution that were discussed in detail in this work. To validate the developed prototype, several experimental campaigns were organized that included the simulation of target phenomena both in laboratory conditions and on a real water storage tank. The presented test results demonstrate the successful application of the developed AE system both for simulated leaks and for corrosion processes on the tank bottom. Mathematical and technological algorithms for localization and characterization of AE signals implemented during the development of the prototype are also confirmed by the test results.

Application of Deep Learning techniques in the search for BSM Higgs bosons in the $\mu\mu$ final state in CMS

The Standard Model (SM) of particle physics predicts the existence of a Higgs field responsible for the generation of particles' mass. However, some aspects of this theory remain unsolved, supposing the presence of new physics Beyond the Standard Model (BSM) with the production of new particles at a higher energy scale compared to the current experimental limits. The search for additional Higgs bosons is, in fact, predicted by theoretical extensions of the SM including the Minimal Supersymmetry Standard Model (MSSM). In the MSSM, the Higgs sector consists of two Higgs doublets, resulting in five physical Higgs particles: two charged bosons $H^{\pm}$, two neutral scalars $h$ and $H$, and one pseudoscalar $A$. The work presented in this thesis is dedicated to the search of neutral non-Standard Model Higgs bosons decaying to two muons in the model independent MSSM scenario. Proton-proton collision data recorded by the CMS experiment at the CERN LHC at a center-of-mass energy of 13 TeV are used, corresponding to an integrated luminosity of $35.9\ \text{fb}^{-1}$. Such search is sensitive to neutral Higgs bosons produced either via gluon fusion process or in association with a $\text{b}\bar{\text{b}}$ quark pair. The extensive usage of Machine and Deep Learning techniques is a fundamental element in the discrimination between signal and background simulated events. A new network structure called parameterised Neural Network (pNN) has been implemented, replacing a whole set of single neural networks trained at a specific mass hypothesis value with a single neural network able to generalise well and interpolate in the entire mass range considered. The results of the pNN signal/background discrimination are used to set a model independent 95\% confidence level expected upper limit on the production cross section times branching ratio, for a generic $\phi$ boson decaying into a muon pair in the 130 to 1000 GeV range.

Study of charm hadronisation in pp collisions at $\sqrt{s}$ = 13 TeV with the ALICE experiment

In high-energy hadron collisions, the production at parton level of heavy-flavour quarks (charm and bottom) is described by perturbative Quantum Chromo-dynamics (pQCD) calculations, given the hard scale set by the quark masses. However, in hadron-hadron collisions, the predictions of the heavy-flavour hadrons eventually produced entail the knowledge of the parton distribution functions, as well as an accurate description of the hadronisation process. The latter is taken into account via the fragmentation functions measured at e$^+$e$^-$ colliders or in ep collisions, but several observations in LHC Run 1 and Run 2 data challenged this picture. In this dissertation, I studied the charm hadronisation in proton-proton collision at $\sqrt{s}$ = 13 TeV with the ALICE experiment at the LHC, making use of a large statistic data sample collected during LHC Run 2. The production of heavy-flavour in this collision system will be discussed, also describing various hadronisation models implemented in commonly used event generators, which try to reproduce experimental data, taking into account the unexpected results at LHC regarding the enhanced production of charmed baryons. The role of multiple parton interaction (MPI) will also be presented and how it affects the total charm production as a function of multiplicity. The ALICE apparatus will be described before moving to the experimental results, which are related to the measurement of relative production rates of the charm hadrons $\Sigma_c^{0,++}$ and $\Lambda_c^+$, which allow us to study the hadronisation mechanisms of charm quarks and to give constraints to different hadronisation models. Furthermore, the analysis of D mesons ($D^{0}$, $D^{+}$ and $D^{*+}$) as a function of charged-particle multiplicity and spherocity will be shown, investigating the role of multi-parton interactions. This research is relevant per se and for the mission of the ALICE experiment at the LHC, which is devoted to the study of Quark-Gluon Plasma.

The interplay of multiplicity and effective energy for (multi) strange hadron production in pp collisions at the LHC

The enhanced production of strange hadrons in heavy-ion collisions relative to that in minimum-bias pp collisions is historically considered one of the first signatures of the formation of a deconfined quark-gluon plasma. At the LHC, the ALICE experiment observed that the ratio of strange to non-strange hadron yields increases with the charged-particle multiplicity at midrapidity, starting from pp collisions and evolving smoothly across interaction systems and energies, ultimately reaching Pb-Pb collisions. The understanding of the origin of this effect in small systems remains an open question. This thesis presents a comprehensive study of the production of $K^{0}_{S}$, $\Lambda$ ($\bar{\Lambda}$) and $\Xi^{-}$ ($\bar{\Xi}^{+}$) strange hadrons in pp collisions at $\sqrt{s}$ = 13 TeV collected in LHC Run 2 with ALICE. A novel approach is exploited, introducing, for the first time, the concept of effective energy in the study of strangeness production in hadronic collisions at the LHC. In this work, the ALICE Zero Degree Calorimeters are used to measure the energy carried by forward emitted baryons in pp collisions, which reduces the effective energy available for particle production with respect to the nominal centre-of-mass energy. The results presented in this thesis provide new insights into the interplay, for strangeness production, between the initial stages of the collision and the produced final hadronic state. Finally, the first Run 3 results on the production of $\Omega^{\pm}$ ($\bar{\Omega}^{+}$) multi-strange baryons are presented, measured in pp collisions at $\sqrt{s}$ = 13.6 TeV and 900 GeV, the highest and lowest collision energies reached so far at the LHC. This thesis also presents the development and validation of the ALICE Time-Of-Flight (TOF) data quality monitoring system for LHC Run 3. This work was fundamental to assess the performance of the TOF detector during the commissioning phase, in the Long Shutdown 2, and during the data taking period.

Machine learning techniques for heavy-flavour baryon production measurements at the LHC

Il quark-gluon plasma (QGP) è uno stato della materia previsto dalla cromodinamica quantistica. L’esperimento ALICE a LHC ha tra i suoi obbiettivi principali lo studio della materia fortemente interagente e le proprietà del QGP attraverso collisioni di ioni pesanti ultra-relativistici. Per un’esaustiva comprensione di tali proprietà, le stesse misure effettuate su sistemi collidenti più piccoli (collisioni protone-protone e protone-ione) sono necessarie come riferimento. Le recenti analisi dei dati raccolti ad ALICE hanno mostrato che la nostra comprensione dei meccanismi di adronizzazione di quark pesanti non è completa, perchè i dati ottenuti in collisioni pp e p-Pb non sono riproducibili utilizzando modelli basati sui risultati ottenuti con collisioni e+e− ed ep. Per questo motivo, nuovi modelli teorici e fenomenologici, in grado di riprodurre le misure sperimentali, sono stati proposti. Gli errori associati a queste nuove misure sperimentali al momento non permettono di verificare in maniera chiara la veridicità dei diversi modelli proposti. Nei prossimi anni sarà quindi fondamentale aumentare la precisione di tali misure sperimentali; d’altra parte, stimare il numero delle diverse specie di particelle prodotte in una collisione può essere estremamente complicato. In questa tesi, il numero di barioni Lc prodotti in un campione di dati è stato ottenuto utilizzando delle tecniche di machine learning, in grado di apprendere pattern e imparare a distinguere candidate di segnale da quelle di fondo. Si sono inoltre confrontate tre diverse implementazioni di un algoritmo di Boosted Decision Trees (BDT) e si è utilizzata quella più performante per ricostruire il barione Lc in collisioni pp raccolte dall’esperimento ALICE.