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Impact of flare destruction efficiencies on ozone concentrations: a case study for Houston, TexasAlfadhli, Fahad Mohammed 25 October 2010 (has links)
Industrial flaring can result in atmospheric emissions that have significant impact on regional air quality. This study investigates the impact on one-hour average ozone concentrations due to industrial flaring, using the region around Houston, Texas as a case study. Specifically, this study examined the impact on ozone formation of different flare destruction efficiencies. There are some concerns about whether flare destruction efficiency is reduced from design conditions (98 to 99% destruction) at low flare flow rates. Some studies have reported very low flares destruction efficiencies under low flow, so it is possible that ozone precursor emissions may be underestimated by an order of magnitude or more at low flow conditions. In this thesis, 100 different destruction efficiency scenarios have been constructed where destruction efficiency depends on the ratio of flare flow rate to the maximum flow rate (turndown ratio). The scenarios differ in the assumed destruction efficiency at near zero flow and the turndown ratio at which destruction efficiency returns to the design value. These destruction scenarios are applied to hourly mass flow data for twenty-five flares in Houston, Texas. The scenarios have very different impacts on air quality. The air quality implications of these results for possible modifications to flare operation are explored. / text
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Particle kinematics in solar flares: observations and theoryBattaglia, Marina January 2008 (has links)
Zugl.: Zürich, Techn. Hochsch., Diss., 2008
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Flare for orchestra based on poetry by Mary OliverSharp, Justin Edward 08 October 2010 (has links)
“Flare for orchestra based on poetry by Mary Oliver” is a three-movement work based on the poem “Flare,” by Mary Oliver. In “Flare,” the emotional and expressive content of the poetry is captured in the programmatic narrative of the music. Oliver’s poem also influences structural elements of the music. Another important feature of the music is the use of a dialectic approach to the many contrasting aspects of the poetry. The goal of “Flare” is to infuse numerous elements of the poetry into the music programmatically and structurally to create a shared creative experience of both the music and poetry. / text
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Flare stars in the solar vicinity a search for young stars /König, Brigitte. Unknown Date (has links) (PDF)
University, Diss., 2003--München.
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Magnetic activity in late-type starsHussain, Gaitee January 1999 (has links)
High resolution spectroscopic techniques are used to investigate the magnetic topology of the young, rapidly rotating star, AB Dor. Doppler images of AB Dor are produced using the Li I 6708 Å line and compared to images produced using Ca I and Fe i lines. A Li abundance of 2.9±0.3 dex is measured using LTE profile synthesis. By evaluating the effects of enhanced spot Li abundances we find that starspots are unlikely to lead to an overestimation of the photospheric Li abundance. While the Li I 6708 Å line is strengthened in the presence of starspots, the extent to which the Li I line equivalent width displays rotational modulation is diluted. A Zeeman Doppler imaging code, which maps the surface magnetic flux distributions on rapid rotators, has been developed and tested in this thesis. Reliability tests indicate that this technique is robust with respect to small errors in line and stellar parameters. Spectropolarimetric observations of AB Dor from three years are presented here. The technique of least squares deconvolution, combines the signal from over 1500 lines, enhancing the S/N of the observed dataset. Brightness and magnetic maps of AB Dor are reconstructed using the deconvolved profiles and show excellent agreement with maps produced using independently developed codes by J.-F. Donati. This points to the consistency of Doppler imaging techniques. Magnetic field maps show the presence of strong radial and azimuthal fields at almost all latitudes. This non-solar like distribution of magnetic flux may indicate the presence of a distributed dynamo component operating in the convection zones of rapid rotators. By tracing the positions of absorption transients in Ha, we find prominence complexes at almost all longitudes. Footpoint locations remain difficult to ascertain. Prominences are ejected over much shorter timescales than the timescale over which differential rotation should act further observations with closer time sampling are necessary to investigate the coronal topology further.
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Spectral emission from high temperature plasmasGreer, Caroline J. January 1996 (has links)
No description available.
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Developing an effective gas flaring regulation for the Nigerian upstream oil and gas industry : lessons from Norway and the United KingdomOtiotio, Dennis January 2017 (has links)
No description available.
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Spectroscopic Studies of the Dynamic Solar Chromosphere: Spicules and Flares / 太陽彩層のダイナミクスについての分光学的研究:スピキュールとフレアTei, Akiko 23 March 2020 (has links)
京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第22253号 / 理博第4567号 / 新制||理||1656(附属図書館) / 京都大学大学院理学研究科物理学・宇宙物理学専攻 / (主査)教授 柴田 一成, 准教授 浅井 歩, 教授 一本 潔 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DFAM
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Observations and radiative hydrodynamic simulations of solar and stellar flares /Allred, Joel C., January 2005 (has links)
Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 101-105).
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Automated Prediction of Solar Flares Using SDO Data. The Development of An Automated Computer System for Predicting Solar Flares Based on SDO Satellite Data Using HMI Images Analysis, Visualisation, and Deep Learning TechnologiesAbed, Ali K. January 2021 (has links)
Nowadays, space weather has become an international issue to the world's countries
because of its catastrophic effect on space-borne and ground-based systems, and
industries, impacting our lives. One of the main solar activities that is considered as a
major driver of space weather is solar flares. Solar flares can be defined as an enormous
eruption in the sun's atmosphere. This phenomenon happens when magnetic energy stored
in twisted magnetic fields, usually near sunspots, is suddenly released. Yet, their
occurrence is not fully understood. These flares can affect the Earth by the release of
massive quantities of charged particles and electromagnetic radiation. Investigating the
associations between solar flares and sunspot groups is helpful in comprehending the
possible cause and effect relationships among solar flares and sunspot features. 01 This
thesis proposes a new approach developed by integrating advances in image processing,
machine learning, and deep learning with advances in solar physics to extract valuable
knowledge from historical solar data related to sunspot regions and flares.
This dissertation aims to achieve the following:
1) We developed a new prediction algorithm based on the Automated Solar Activity
Prediction system (ASAP) system. The proposed algorithm updates the ASAP system
by extending the training process and optimizing the learning rules to the optimize
performance better. Two neural networks are used in the proposed approach. The first
neural network is used to predict whether a specific sunspot class at a particular time
is likely to produce a significant flare or not. The second neural network is used to
predict the type of this flare, X or M-class.
2) We proposed a new system called the ASAP_Deep system built on top of the ASAP
system introduced in [6] but improves the system with an updated deep learning-based
prediction capability. In addition, we successfully apply Convolutional Neural
Network (CNN) to the sunspot group image without any pr-eprocessing or feature
extraction. Moreover, our system results are considerably better, especially for the
false alarm ratio (FAR); this reduces the losses resulting from the protection measures
applied by companies. In addition, the proposed system achieves a relatively high
score of True Skill Statistic (TSS) and Heidke Skill Score (HSS).
3) We presented a novel system that used the Deep Belief Networks (DBNs) to predict
the solar flares occurrence. The input data are SDO/HMI Intensitygram and
Magnetogram images. The model outputs are "Flare or No-Flare" of significant flare
occurrence (M and X-class flares). In addition, we created a dataset from the sunspots
groups extracted from SDO HMI Intensitygram images. We compared the results
obtained from the complete suggested system with those of three previous flare forecast models using several statistical metrics.
In our view, these developed methods and results represent an excellent initial
step toward enhancing the accuracy of flare forecasting, enhance our understanding of flare occurrence, and develop efficient flare prediction systems. The systems, implementation, results, and future work are explained in this dissertation.
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