Holographic Tools for Probing the Dynamics of Strongly Coupled Field Theories

Thesis (Ph.D.)--University of Washington, 2016-08

Outer crust of a cold non-accreting magnetar

The outer-crust structure and composition of a cold, non-accreting magnetar are studied. We model the outer crust to be made of fully equilibrated matter where ionized nuclei form a Coulomb crystal embedded in an electron gas. The main effects of the strong magnetic field are those of quantizing the electron motion in Landau levels and of modifying the nuclear single-particle levels producing, on average, an increased binding of nucleons in nuclei present in the Coulomb lattice. The effect of a homogeneous and constant magnetic field on nuclear masses has been predicted by using a covariant density functional in which induced currents and axial deformation due to the presence of a magnetic field that breaks time-reversal symmetry have been included self-consistently in the nucleon and meson equations of motion. Although not yet observed, for Ba 1016 G both effects contribute to produce different compositions - odd-mass nuclei are frequently predicted - and to increase the neutron-drip pressure as compared to a typical neutron star. Specifically, in such a regime, the magnetic-field effects on nuclei favor the appearance of heavier nuclei at low pressures. As B increases, such heavier nuclei are also preferred up to larger pressures. For the most extreme magnetic field considered, B=1018 G, and for the models studied, almost the whole outer crust is made of 4092Zr52.

Fiber Bragg Gratings Strain Sensors for Railway Applications

Fiber optical sensors have played an important role in applications for monitoring the health of civil infrastructures, such as bridges, oil rigs, and railroads. Due to the reduction in cost of fiber-optic components and systems, fiber optical sensors have been studied extensively for their higher sensitivity, precision and immunity to electrical interference compared to their electrical counterparts. A fiber Bragg grating (FBG) strain sensor has been employed for this study to detect and distinguish normal and lateral loads on rail tracks. A theoretical analysis of the relationship between strain and displacement under vertical and horizontal strains on an aluminum beam has been performed, and the results are in excellent agreement with the measured strain data. Then a single FBG sensor system with erbium-doped fiber amplifier broadband source has been carried out. Force and temperature applied on the system have resulted in changes of 0.05 nm per 50 με and 0.094 nm per 10 oC at the center wavelength of the FBG. Furthermore, a low cost fiber-optic sensor system with a distributed feedback (DFB) laser as the light source has been implemented. We show that it has superior noise and sensitivity performances compared to strain gauge sensors. The design has been extended to accommodate multiple sensors with negligible cross talk. When two cascaded sensors on a rail track section are tested, strain readings of the sensor 20 inches away from the position of applied force decay to one seventh of the data of the sensor at the applied force location. The two FBG sensor systems can detect 1 ton of vertical load with a square wave pattern and 0.1 ton of lateral loads (3 tons and 0.5 ton, respectively, for strain gauges). Moreover, a single FBG sensor has been found capable of detecting and distinguishing lateral and normal strains applied at different frequencies. FBG sensors are promising alternatives to electrical sensors for their high sensitivity,ease of installation, and immunity to electromagnetic interferences.

Areal rainfall estimation using moving cars - computer experiments including hydrological modeling

The need for high temporal and spatial resolution precipitation data for hydrological analyses has been discussed in several studies. Although rain gauges provide valuable information, a very dense rain gauge network is costly. As a result, several new ideas have been emerged to help estimating areal rainfall with higher temporal and spatial resolution. Rabiei et al. (2013) observed that moving cars, called RainCars (RCs), can potentially be a new source of data for measuring rainfall amounts. The optical sensors used in that study are designed for operating the windscreen wipers and showed promising results for rainfall measurement purposes. Their measurement accuracy has been quantified in laboratory experiments. Considering explicitly those errors, the main objective of this study is to investigate the benefit of using RCs for estimating areal rainfall. For that, computer experiments are carried out, where radar rainfall is considered as the reference and the other sources of data, i.e. RCs and rain gauges, are extracted from radar data. Comparing the quality of areal rainfall estimation by RCs with rain gauges and reference data helps to investigate the benefit of the RCs. The value of this additional source of data is not only assessed for areal rainfall estimation performance, but also for use in hydrological modeling. The results show that the RCs considering measurement errors derived from laboratory experiments provide useful additional information for areal rainfall estimation as well as for hydrological modeling. Even assuming higher uncertainties for RCs as obtained from the laboratory up to a certain level is observed practical.

A space-time hybrid hourly rainfall model for derived flood frequency analysis

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters.

Sensor inteligente para medição de cargas mecânicas

A medição precisa da força é necessária para muitas aplicações, nomeadamente, para a determinação da resistência mecânica dos materiais, controlo de qualidade durante a produção, pesagem e segurança de pessoas. Dada a grande necessidade de medição de forças, têm-se desenvolvido, ao longo do tempo, várias técnicas e instrumentos para esse fim. Entre os vários instrumentos utilizados, destacam-se os sensores de força, também designadas por células de carga, pela sua simplicidade, precisão e versatilidade. O exemplo mais comum é baseado em extensómetros elétricos do tipo resistivo, que aliados a uma estrutura formam uma célula de carga. Este tipo de sensores possui sensibilidades baixas e em repouso, presença de offset diferente de zero, o que torna complexo o seu condicionamento de sinal. Este trabalho apresenta uma solução para o condicionamento e aquisição de dados para células de carga que, tanto quanto foi investigado, é inovador. Este dispositivo permite efetuar o condicionamento de sinal, digitalização e comunicação numa estrutura atómica. A ideia vai de encontro ao paradigma dos sensores inteligentes onde um único dispositivo eletrónico, associado a uma célula de carga, executa um conjunto de operações de processamento de sinal e transmissão de dados. Em particular permite a criação de uma rede ad-hoc utilizando o protocolo de comunicação IIC. O sistema é destinado a ser introduzido numa plataforma de carga, desenvolvida na Escola Superior de Tecnologia e Gestão de Bragança, local destinado à sua implementação. Devido à sua estratégia de conceção para a leitura de forças em três eixos, contém quatro células de carga, com duas saídas cada, totalizando oito saídas. O hardware para condicionamento de sinal já existente é analógico, e necessita de uma placa de dimensões consideráveis por cada saída. Do ponto de vista funcional, apresenta vários problemas, nomeadamente o ajuste de ganho e offset ser feito manualmente, tornando-se essencial um circuito com melhor desempenho no que respeita a lidar com um array de sensores deste tipo.

Mensuração de perdas de sedimentos por escoamento superficial em encostas, com uso de parcelas de erosão, em diferentes usos e coberturas do solo no Bioma Cerrado : Bacia Hidrográfica do Ribeirão do Gama/DF

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, 2015.

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

Examination of the Effect of Time Delay on Fragmentation

The main objective of blasting is to produce optimum fragmentation for downstream processing. Fragmentation is usually considered optimum when the average fragment size is minimum and the fragmentation distribution as uniform as possible. One of the parameters affecting blasting fragmentation is believed to be time delay between holes of the same row. Although one can find a significant number of studies in the literature, which examine the relationship between time delay and fragmentation, their results have been often controversial. The purpose of this work is to increase the level of understanding of how time delay between holes of the same row affects fragmentation. Two series of experiments were conducted for this purpose. The first series involved tests on small scale grout and granite blocks to determine the moment of burden detachment. The instrumentation used for these experiments consisted mainly of strain gauges and piezoelectric sensors. Some experiments were also recorded with a high speed camera. It was concluded that the time of detachment for this specific setup is between 300 and 600 μs. The second series of experiments involved blasting of a 2 meter high granite bench and its purpose was the determination of the hole-to-hole delay that provides optimum fragmentation. The fragmentation results were assessed with image analysis software. Moreover, vibration was measured close to the blast and the experiments were recorded with high speed cameras. The results suggest that fragmentation was optimum when delays between 4 and 6 ms were used for this specific setup. Also, it was found that the moment at which gases first appear to be venting from the face was consistently around 6 ms after detonation.

Novel efficient technologies in Europe for axle bearing condition monitoring – the MAXBE project

Axle bearing damage with possible catastrophic failures can cause severe disruptions or even dangerous derailments, potentially causing loss of human life and leading to significant costs for railway infrastructure managers and rolling stock operators. Consequently the axle bearing damage process has safety and economic implications on the exploitation of railways systems. Therefore it has been the object of intense attention by railway authorities as proved by the selection of this topic by the European Commission in calls for research proposals. The MAXBE Project (http://www.maxbeproject.eu/), an EU-funded project, appears in this context and its main goal is to develop and to demonstrate innovative and efficient technologies which can be used for the onboard and wayside condition monitoring of axle bearings. The MAXBE (interoperable monitoring, diagnosis and maintenance strategies for axle bearings) project focuses on detecting axle bearing failure modes at an early stage by combining new and existing monitoring techniques and on characterizing the axle bearing degradation process. The consortium for the MAXBE project comprises 18 partners from 8 member states, representing operators, railway administrations, axle bearing manufactures, key players in the railway community and experts in the field of monitoring, maintenance and rolling stock. The University of Porto is coordinating this research project that kicked-off in November 2012 and it is completed on October 2015. Both on-board and wayside systems are explored in the project since there is a need for defining the requirement for the onboard equipment and the range of working temperatures of the axle bearing for the wayside systems. The developed monitoring systems consider strain gauges, high frequency accelerometers, temperature sensors and acoustic emission. To get a robust technology to support the decision making of the responsible stakeholders synchronized measurements from onboard and wayside monitoring systems are integrated into a platform. Also extensive laboratory tests were performed to correlate the in situ measurements to the status of the axle bearing life. With the MAXBE project concept it will be possible: to contribute to detect at an early stage axle bearing failures; to create conditions for the operational and technical integration of axle bearing monitoring and maintenance in different European railway networks; to contribute to the standardization of the requirements for the axle bearing monitoring, diagnosis and maintenance. Demonstration of the developed condition monitoring systems was performed in Portugal in the Northern Railway Line with freight and passenger traffic with a maximum speed of 220 km/h, in Belgium in a tram line and in the UK. Still within the project, a tool for optimal maintenance scheduling and a smart diagnostic tool were developed. This paper presents a synthesis of the most relevant results attained in the project. The successful of the project and the developed solutions have positive impact on the reliability, availability, maintainability and safety of rolling stock and infrastructure with main focus on the axle bearing health.

Throughfall and soil properties in shaded and unshaded coffee plantations and a secondary forest: a case study from Southern Colombia

In Colombia coffee production is facing risks due to an increase in the variability and amount of rainfall, which may alter hydrological cycles and negatively influence yield quality and quantity. Shade trees in coffee plantations, however, are known to produce ecological benefits, such as intercepting rainfall and lowering its velocity, resulting in a reduced net-rainfall and higher water infiltration. In this case study, we measured throughfall and soil hydrological properties in four land use systems in Cauca, Colombia, that differed in stand structural parameters: shaded coffee, unshaded coffee, secondary forest and pasture. We found that throughfall was rather influenced by stand structural characteristics than by rainfall intensity. Lower throughfall was recorded in the shaded coffee compared to the other systems when rain gauges were placed at a distance of 1.0 m to the shade tree. The variability of throughfall was high in the shaded coffee, which was due to different canopy characteristics and irregular arrangements of shade tree species. Shaded coffee and secondary forest resembled each other in soil structural parameters, with an increase in saturated hydraulic conductivity and microporosity, whereas bulk density and macroporosity decreased, compared to the unshaded coffee and pasture. In this context tree-covered systems indicate a stronger resilience towards changing rainfall patterns, especially in mountainous areas where coffee is cultivated.

Heavy-Light Mesons in Minkowski Space

Following up on earlier work on the $q\bar{q}$-bound-state problem using a covariant, chiral-symmetric formalism based upon the Covariant Spectator Theory, we study the heavy–light case for both pseudoscalar and vector mesons. Derived directly in Minkowski space, our approach approximates the full Bethe–Salpeter-equation, taking into account, effectively, the contributions of both ladder and crossed ladder diagrams in the kernel. Results for several mass spectra using a relativistic covariant generalization of a Cornell plus a constant potential to model the interquark interaction are given and discussed.

Bond behaviour and kb factor in GFRP rebars casted in concrete

A proper bond between reinforcement and concrete is key for an appropriate composite action of both materials in reinforced concrete structures. However, to-date limited studies exist on bond of fiber reinforced polymer (FRP) bars in concrete members under flexure. In this paper, the bond strength developed by FRP and steel rebars is evaluated and compared, by testing reinforced concrete beams under three point bending load. The investigation included several beams that were 183 cm long × 15 cm wide × 36 cm deep: many of them were reinforced with sand coated GFRP rebars, while steel was used to reinforce the remaining ones. For each of the reinforcing systems, various different embedded lengths were tested. The beams were tested under a 3-point-bending setup and they were monitored using several measuring devices: LVDTS, potentiometers and strain gauges. Preliminary results show that the GFRP rebars have lower bond capacity than the ones made of steel. Moreover, it was inferred that the embedded lengths suggested by actual code provisions for GFRP rebars are too conservative.

Assessment of sea-level variability for the Emilia-Romagna coastal area in the framework of the Mediterranean Sea

Sea–level change is one of the ocean characteristics closely connected to climate change. Understanding its variation is essential since a large portion of the world’s population is located in low–lying locations. Two main techniques are employed to measure sea level: satellite altimetry and tide gauges. Satellite altimetry monitors sea–level relative to a geocentric reference, is unaffected by crustal processes and covers nearly the entire surface of the oceans since 1993. Conversely, tide gauges measure sea level at specific coastal locations and relative to a local ground benchmark, therefore are impacted by vertical land movements. In this study, the linear and non–linear geocentric and relative sea–level trends along the Emilia–Romagna coast (Northern Italy) have been analyzed over different periods. In order to assess the local sea–level variability, data from satellite altimetry and tide gauges have been compared over a common time interval (1993–2019), hence disentangling the contribute of vertical land movements. Non–linearity has been also evaluated at the broader scale of the Mediterranean Sea, in order to depict the main variability in geocentric sea–level trends from regional to sub–basin scale. Furthermore, the anthropogenic and natural influence at the river basin scale has been addressed, in order to shed light on the factors inducing the drastic reduction of riverine sediment supply to the Emilia–Romagna coast over the period 1920–2020. The findings of this analysis indicate that the sediment delivery reduction to the coast by rivers has been driven by several anthropogenic processes, acting on various spatiotemporal scales. Moreover, the local absolute sea–level trend is far from linear and appear "contaminated" by the presence of natural oscillations that act at the multi–decadal, quasi–decadal and inter–annual scale, mainly driven by both large–scale climatic modes and variations in local oceanography.

SPHERA, a new Italian convection-permitting regional reanalysis: improving heavy-rainfall representation and describing hail-prone environments

Extreme weather events related to deep convection are high-impact critical phenomena whose reliable numerical simulation is still challenging. High-resolution (convection-permitting) modeling setups allow to switch off physical parameterizations accountable for substantial errors in convection representation. A new convection-permitting reanalysis over Italy (SPHERA) has been produced at ARPAE to enhance the representation and understanding of extreme weather situations. SPHERA is obtained through a dynamical downscaling of the global reanalysis ERA5 using the non-hydrostatic model COSMO at 2.2 km grid spacing over 1995-2020. This thesis aims to verify the expectations placed on SPHERA by analyzing two weather phenomena that are particularly challenging to simulate: heavy rainfall and hail. A quantitative statistical analysis over Italy during 2003-2017 for daily and hourly precipitation is presented to compare the performance of SPHERA with its driver ERA5 considering the national network of rain gauges as reference. Furthermore, two extreme precipitation events are deeply investigated. SPHERA shows a quantitative added skill over ERA5 for moderate to severe and rapid accumulations in terms of adherence to the observations, higher detailing of the spatial fields, and more precise temporal matching. These results prompted the use of SPHERA for the investigation of hailstorms, for which the combination of multiple information is crucial to reduce the substantial uncertainties permeating their understanding. A proxy for hail is developed by combining hail-favoring environmental numerical predictors with observations of ESWD hail reports and satellite overshooting top detections. The procedure is applied to the extended summer season (April-October) of 2016-2018 over the whole SPHERA spatial domain. The results indicate maximum hail likelihood over pre-Alpine regions and the northern Adriatic sea around 15 UTC in June-July, in agreement with recent European hail climatologies. The method demonstrates enhanced performance in case of severe hail occurrences and the ability to separate between ambient signatures depending on hail severity.