976 resultados para system emission limit


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Compensation of the detrimental impacts of nonlinearity on long-haul wavelength division multiplexed system performance is discussed, and the difference between transmitter, receiver and in-line compensation analyzed. We demonstrate that ideal compensation of nonlinear noise could result in an increase in the signal-to-noise ratio (measured in dB) of 50%, and that reaches may be more than doubled for higher order modulation formats. The influence of parametric noise amplification is discussed in detail, showing how increased numbers of optical phase conjugators may further increase the received signal-tonoise ratio. Finally the impact of practical real world system imperfections, such as polarization mode dispersion, are outlined.

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The optical-structural characteristics of the direct optical band-gap semiconducting series of surfactant template-mediated laminar (CdS)x(CdCl2)y(CnH2n+4N)z nanocomposites are reported. X-ray diffraction measurements of the nanocomposites exhibited interlaminar distances in the range 2.9-3.6 nm with observations of eighth order {0 0 l} diffraction planes indicative of a high degree of laminarity and crystallographic order. Diffuse reflectance measurements have determined that the profile of their emission spectrum is that of a direct band-gap with absorption edges in the range 2.11-2.40 eV, depending on the CdS mole fraction in the nanocomposite. Photoluminescence (PL) excitation and time-resolved PL spectroscopies give an estimate of the maximum relative absorbance of the nanocomposites at ∼420 nm while the minimum was observed at ∼560 nm. The main emission was observed at ∼700 nm with emission from doubly ionized sulphur vacancies observed at ∼615 nm at room temperature. The CdS-containing nanocomposite is thus a surfactant-mediated modular system with variable band-gap energy emission.

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Limit-periodic (LP) structures exhibit a type of nonperiodic order yet to be found in a natural material. A recent result in tiling theory, however, has shown that LP order can spontaneously emerge in a two-dimensional (2D) lattice model with nearest-and next-nearest-neighbor interactions. In this dissertation, we explore the question of what types of interactions can lead to a LP state and address the issue of whether the formation of a LP structure in experiments is possible. We study emergence of LP order in three-dimensional (3D) tiling models and bring the subject into the physical realm by investigating systems with realistic Hamiltonians and low energy LP states. Finally, we present studies of the vibrational modes of a simple LP ball and spring model whose results indicate that LP materials would exhibit novel physical properties.

A 2D lattice model defined on a triangular lattice with nearest- and next-nearest-neighbor interactions based on the Taylor-Socolar (TS) monotile is known to have a LP ground state. The system reaches that state during a slow quench through an infinite sequence of phase transitions. Surprisingly, even when the strength of the next-nearest-neighbor interactions is zero, in which case there is a large degenerate class of both crystalline and LP ground states, a slow quench yields the LP state. The first study in this dissertation introduces 3D models closely related to the 2D models that exhibit LP phases. The particular 3D models were designed such that next-nearest-neighbor interactions of the TS type are implemented using only nearest-neighbor interactions. For one of the 3D models, we show that the phase transitions are first order, with equilibrium structures that can be more complex than in the 2D case.

In the second study, we investigate systems with physical Hamiltonians based on one of the 2D tiling models with the goal of stimulating attempts to create a LP structure in experiments. We explore physically realizable particle designs while being mindful of particular features that may make the assembly of a LP structure in an experimental system difficult. Through Monte Carlo (MC) simulations, we have found that one particle design in particular is a promising template for a physical particle; a 2D system of identical disks with embedded dipoles is observed to undergo the series of phase transitions which leads to the LP state.

LP structures are well ordered but nonperiodic, and hence have nontrivial vibrational modes. In the third section of this dissertation, we study a ball and spring model with a LP pattern of spring stiffnesses and identify a set of extended modes with arbitrarily low participation ratios, a situation that appears to be unique to LP systems. The balls that oscillate with large amplitude in these modes live on periodic nets with arbitrarily large lattice constants. By studying periodic approximants to the LP structure, we present numerical evidence for the existence of such modes, and we give a heuristic explanation of their structure.

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Carbon Capture and Storage (CCS) technologies provide a means to significantly reduce carbon emissions from the existing fleet of fossil-fired plants, and hence can facilitate a gradual transition from conventional to more sustainable sources of electric power. This is especially relevant for coal plants that have a CO2 emission rate that is roughly two times higher than that of natural gas plants. Of the different kinds of CCS technology available, post-combustion amine based CCS is the best developed and hence more suitable for retrofitting an existing coal plant. The high costs from operating CCS could be reduced by enabling flexible operation through amine storage or allowing partial capture of CO2 during high electricity prices. This flexibility is also found to improve the power plant’s ramp capability, enabling it to offset the intermittency of renewable power sources. This thesis proposes a solution to problems associated with two promising technologies for decarbonizing the electric power system: the high costs of the energy penalty of CCS, and the intermittency and non-dispatchability of wind power. It explores the economic and technical feasibility of a hybrid system consisting of a coal plant retrofitted with a post-combustion-amine based CCS system equipped with the option to perform partial capture or amine storage, and a co-located wind farm. A techno-economic assessment of the performance of the hybrid system is carried out both from the perspective of the stakeholders (utility owners, investors, etc.) as well as that of the power system operator.

In order to perform the assessment from the perspective of the facility owners (e.g., electric power utilities, independent power producers), an optimal design and operating strategy of the hybrid system is determined for both the amine storage and partial capture configurations. A linear optimization model is developed to determine the optimal component sizes for the hybrid system and capture rates while meeting constraints on annual average emission targets of CO2, and variability of the combined power output. Results indicate that there are economic benefits of flexible operation relative to conventional CCS, and demonstrate that the hybrid system could operate as an energy storage system: providing an effective pathway for wind power integration as well as a mechanism to mute the variability of intermittent wind power.

In order to assess the performance of the hybrid system from the perspective of the system operator, a modified Unit Commitment/ Economic Dispatch model is built to consider and represent the techno-economic aspects of operation of the hybrid system within a power grid. The hybrid system is found to be effective in helping the power system meet an average CO2 emissions limit equivalent to the CO2 emission rate of a state-of-the-art natural gas plant, and to reduce power system operation costs and number of instances and magnitude of energy and reserve scarcity.

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This work is an investigation into collimator designs for a deuterium-deuterium (DD) neutron generator for an inexpensive and compact neutron imaging system that can be implemented in a hospital. The envisioned application is for a spectroscopic imaging technique called neutron stimulated emission computed tomography (NSECT).

Previous NSECT studies have been performed using a Van-de-Graaff accelerator at the Triangle Universities Nuclear Laboratory (TUNL) in Duke University. This facility has provided invaluable research into the development of NSECT. To transition the current imaging method into a clinically feasible system, there is a need for a high-intensity fast neutron source that can produce collimated beams. The DD neutron generator from Adelphi Technologies Inc. is being explored as a possible candidate to provide the uncollimated neutrons. This DD generator is a compact source that produces 2.5 MeV fast neutrons with intensities of 1012 n/s (4π). The neutron energy is sufficient to excite most isotopes of interest in the body with the exception of carbon and oxygen. However, a special collimator is needed to collimate the 4π neutron emission into a narrow beam. This work describes the development and evaluation of a series of collimator designs to collimate the DD generator for narrow beams suitable for NSECT imaging.

A neutron collimator made of high-density polyethylene (HDPE) and lead was modeled and simulated using the GEANT4 toolkit. The collimator was designed as a 52 x 52 x 52 cm3 HDPE block coupled with 1 cm lead shielding. Non-tapering (cylindrical) and tapering (conical) opening designs were modeled into the collimator to permit passage of neutrons. The shape, size, and geometry of the aperture were varied to assess the effects on the collimated neutron beam. Parameters varied were: inlet diameter (1-5 cm), outlet diameter (1-5 cm), aperture diameter (0.5-1.5 cm), and aperture placement (13-39 cm). For each combination of collimator parameters, the spatial and energy distributions of neutrons and gammas were tracked and analyzed to determine three performance parameters: neutron beam-width, primary neutron flux, and the output quality. To evaluate these parameters, the simulated neutron beams are then regenerated for a NSECT breast scan. Scan involved a realistic breast lesion implanted into an anthropomorphic female phantom.

This work indicates potential for collimating and shielding a DD neutron generator for use in a clinical NSECT system. The proposed collimator designs produced a well-collimated neutron beam that can be used for NSECT breast imaging. The aperture diameter showed a strong correlation to the beam-width, where the collimated neutron beam-width was about 10% larger than the physical aperture diameter. In addition, a collimator opening consisting of a tapering inlet and cylindrical outlet allowed greater neutron throughput when compared to a simple cylindrical opening. The tapering inlet design can allow additional neutron throughput when the neck is placed farther from the source. On the other hand, the tapering designs also decrease output quality (i.e. increase in stray neutrons outside the primary collimated beam). All collimators are cataloged in measures of beam-width, neutron flux, and output quality. For a particular NSECT application, an optimal choice should be based on the collimator specifications listed in this work.

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Over 150 million cubic meter of sand-sized sediment has disappeared from the central region of the San Francisco Bay Coastal System during the last half century. This enormous loss may reflect numerous anthropogenic influences, such as watershed damming, bay-fill development, aggregate mining, and dredging. The reduction in Bay sediment also appears to be linked to a reduction in sediment supply and recent widespread erosion of adjacent beaches, wetlands, and submarine environments. A unique, multi-faceted provenance study was performed to definitively establish the primary sources, sinks, and transport pathways of beach sized-sand in the region, thereby identifying the activities and processes that directly limit supply to the outer coast. This integrative program is based on comprehensive surficial sediment sampling of the San Francisco Bay Coastal System, including the seabed, Bay floor, area beaches, adjacent rock units, and major drainages. Analyses of sample morphometrics and biological composition (e.g., Foraminifera) were then integrated with a suite of tracers including 87Sr/86Sr and 143Nd/144Nd isotopes, rare earth elements, semi-quantitative X-ray diffraction mineralogy, and heavy minerals, and with process-based numerical modeling, in situ current measurements, and bedform asymmetry to robustly determine the provenance of beach-sized sand in the region.

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Herschel Island in the southern Beaufort Sea is a push moraine at the northwestern-most limit of the Laurentide Ice Sheet. Stable water isotope (d18O, dD) and hydrochemical studies were applied to two tabular massive ground ice bodies to unravel their genetic origin. Buried glacier ice or basal regelation ice was encountered beneath an ice-rich diamicton with strong glaciotectonic deformation structures. The massive ice isotopic composition was highly depleted in heavy isotopes (mean d18O: -33 per mil; mean dD: -258 per mil), suggesting full-glacial conditions during ice formation. Other massive ice of unknown origin with a very large d18O range (from -39 to -21 per mil) was found adjacent to large, striated boulders. A clear freezing slope was present with progressive depletion in heavy isotopes towards the centre of the ice body. Fractionation must have taken place during closed-system freezing, possibly of a glacial meltwater pond. Both massive ground ice bodies exhibited a mixed ion composition suggestive of terrestrial waters with a marine influence. Hydrochemical signatures resemble the Herschel Island sediments that are derived from nearshore marine deposits upthrust by the Laurentide ice. A prolonged contact between water feeding the ice bodies and the surrounding sediment is therefore inferred.

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Future power systems are expected to integrate large-scale stochastic and intermittent generation and load due to reduced use of fossil fuel resources, including renewable energy sources (RES) and electric vehicles (EV). Inclusion of such resources poses challenges for the dynamic stability of synchronous transmission and distribution networks, not least in terms of generation where system inertia may not be wholly governed by large-scale generation but displaced by small-scale and localised generation. Energy storage systems (ESS) can limit the impact of dispersed and distributed generation by offering supporting reserve while accommodating large-scale EV connection; the latter (load) also participating in storage provision. In this paper, a local energy storage system (LESS) is proposed. The structure, requirement and optimal sizing of the LESS are discussed. Three operating modes are detailed, including: 1) storage pack management; 2) normal operation; and 3) contingency operation. The proposed LESS scheme is evaluated using simulation studies based on data obtained from the Northern Ireland regional and residential network.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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To maintain the pace of development set by Moore's law, production processes in semiconductor manufacturing are becoming more and more complex. The development of efficient and interpretable anomaly detection systems is fundamental to keeping production costs low. As the dimension of process monitoring data can become extremely high anomaly detection systems are impacted by the curse of dimensionality, hence dimensionality reduction plays an important role. Classical dimensionality reduction approaches, such as Principal Component Analysis, generally involve transformations that seek to maximize the explained variance. In datasets with several clusters of correlated variables the contributions of isolated variables to explained variance may be insignificant, with the result that they may not be included in the reduced data representation. It is then not possible to detect an anomaly if it is only reflected in such isolated variables. In this paper we present a new dimensionality reduction technique that takes account of such isolated variables and demonstrate how it can be used to build an interpretable and robust anomaly detection system for Optical Emission Spectroscopy data.

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The work presented in my thesis addresses the two cornerstones of modern astronomy: Observation and Instrumentation. Part I deals with the observation of two nearby active galaxies, the Seyfert 2 galaxy NGC 1433 and the Seyfert 1 galaxy NGC 1566, both at a distance of $\sim10$ Mpc, which are part of the Nuclei of Galaxies (NUGA) sample. It is well established that every galaxy harbors a super massive black hole (SMBH) at its center. Furthermore, there seems to be a fundamental correlation between the stellar bulge and SMBH masses. Simulations show that massive feedback, e.g., powerful outflows, in Quasi Stellar Objects (QSOs) has an impact on the mutual growth of bulge and SMBH. Nearby galaxies follow this relation but accrete mass at much lower rates. This gives rise to the following questions: Which mechanisms allow feeding of nearby Active Galactic Nuclei (AGN)? Is this feeding triggered by events, e.g., star formation, nuclear spirals, outflows, on $\sim500$ pc scales around the AGN? Does feedback on these scales play a role in quenching the feeding process? Does it have an effect on the star formation close to the nucleus? To answer these questions I have carried out observations with the Spectrograph for INtegral Field Observation in the Near Infrared (SINFONI) at the Very Large Telescope (VLT) situated on Cerro Paranal in Chile. I have reduced and analyzed the recorded data, which contain spatial and spectral information in the H-band ($1.45 \mic-1.85 \mic$) and K-band ($1.95 \mic-2.45 \mic$) on the central $10\arcsec\times10\arcsec$ of the observed galaxies. Additionally, Atacama Large Millimeter/Sub-millimeter Array (ALMA) data at $350$ GHz ($\sim0.87$ mm) as well as optical high resolution Hubble Space Telescope (HST) images are used for the analysis. For NGC 1433 I deduce from comparison of the distributions of gas, dust, and intensity of highly ionized emission lines that the galaxy center lies $\sim70$ pc north-northwest of the prior estimate. A velocity gradient is observed at the new center, which I interpret as a bipolar outflow, a circum nuclear disk, or a combination of both. At least one dust and gas arm leads from a $r\sim200$ pc ring towards the nucleus and might feed the SMBH. Two bright warm H$_2$ gas spots are detected that indicate hidden star formation or a spiral arm-arm interaction. From the stellar velocity dispersion (SVD) I estimate a SMBH mass of $\sim1.74\times10^7$ \msol. For NGC 1566 I observe a nuclear gas disk of $\sim150$ pc in radius with a spiral structure. I estimate the total mass of this disk to be $\sim5.4\times10^7$ \msol. What mechanisms excite the gas in the disk is not clear. Neither can the existence of outflows be proven nor is star formation detected over the whole disk. On one side of the spiral structure I detect a star forming region with an estimated star formation rate of $\sim2.6\times10^{-3}$ \msol\ yr$^{-1}$. From broad Br$\gamma$ emission and SVD I estimate a mean SMBH mass of $\sim5.3\times10^6$ \msol\ with an Eddington ratio of $\sim2\times10^{-3}$. Part II deals with the final tests of the Fringe and Flexure Tracker (FFTS) for LBT INterferometric Camera and the NIR/Visible Adaptive iNterferometer for Astronomy (LINC-NIRVANA) at the Large Binocular Telescope (LBT) in Arizona, USA, which I conducted. The FFTS is the subsystem that combines the two separate beams of the LBT and enables near-infrared interferometry with a significantly large field of view. The FFTS has a cryogenic system and an ambient temperature system which are separated by the baffle system. I redesigned this baffle to guarantee the functionality of the system after the final tests in the Cologne cryostat. The redesign did not affect any scientific performance of LINC-NIRVANA. I show in the final cooldown tests that the baffle fulfills the temperature requirement and stays $<110$ K whereas the moving stages in the ambient system stay $>273$ K, which was not given for the old baffle design. Additionally, I test the tilting flexure of the whole FFTS and show that accurate positioning of the detector and the tracking during observation can be guaranteed.

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Dans ce projet de recherche, le dépôt des couches minces de carbone amorphe (généralement connu sous le nom de DLC pour Diamond-Like Carbon en anglais) par un procédé de dépôt chimique en phase vapeur assisté par plasma (ou PECVD pour Plasma Enhanced Chemical Vapor deposition en anglais) a été étudié en utilisant la Spectroscopie d’Émission Optique (OES) et l’analyse partielle par régression des moindres carrés (PLSR). L’objectif de ce mémoire est d’établir un modèle statistique pour prévoir les propriétés des revêtements DLC selon les paramètres du procédé de déposition ou selon les données acquises par OES. Deux séries d’analyse PLSR ont été réalisées. La première examine la corrélation entre les paramètres du procédé et les caractéristiques du plasma pour obtenir une meilleure compréhension du processus de dépôt. La deuxième série montre le potentiel de la technique d’OES comme outil de surveillance du procédé et de prédiction des propriétés de la couche déposée. Les résultats montrent que la prédiction des propriétés des revêtements DLC qui était possible jusqu’à maintenant en se basant sur les paramètres du procédé (la pression, la puissance, et le mode du plasma), serait envisageable désormais grâce aux informations obtenues par OES du plasma (particulièrement les indices qui sont reliées aux concentrations des espèces dans le plasma). En effet, les données obtenues par OES peuvent être utilisées pour surveiller directement le processus de dépôt plutôt que faire une étude complète de l’effet des paramètres du processus, ceux-ci étant strictement reliés au réacteur plasma et étant variables d’un laboratoire à l’autre. La perspective de l’application d’un modèle PLSR intégrant les données de l’OES est aussi démontrée dans cette recherche afin d’élaborer et surveiller un dépôt avec une structure graduelle.

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