Numerical simulations of microphysical processes in pyro-convective clouds

Hochreichende Konvektion über Waldbränden ist eine der intensivsten Formen von atmosphärischer Konvektion. Die extreme Wolkendynamik mit hohen vertikalen Windgeschwindigkeiten (bis 20 m/s) bereits an der Wolkenbasis, hohen Wasserdampfübersättigungen (bis 1%) und die durch das Feuer hohen Anzahlkonzentration von Aerosolpartikeln (bis 100000 cm^-3) bilden einen besonderen Rahmen für Aerosol-Wolken Wechselwirkungen.Ein entscheidender Schritt in der mikrophysikalischen Entwicklung einer konvektiven Wolke ist die Aktivierung von Aerosolpartikeln zu Wolkentropfen. Dieser Aktivierungsprozess bestimmt die anfängliche Anzahl und Größe der Wolkentropfen und kann daher die Entwicklung einer konvektiven Wolke und deren Niederschlagsbildung beeinflussen. Die wichtigsten Faktoren, welche die anfängliche Anzahl und Größe der Wolkentropfen bestimmen, sind die Größe und Hygroskopizität der an der Wolkenbasis verfügbaren Aerosolpartikel sowie die vertikale Windgeschwindigkeit. Um den Einfluss dieser Faktoren unter pyro-konvektiven Bedingungen zu untersuchen, wurden numerische Simulationen mit Hilfe eines Wolkenpaketmodells mit detaillierter spektraler Beschreibung der Wolkenmikrophysik durchgeführt. Diese Ergebnisse können in drei unterschiedliche Bereiche abhängig vom Verhältnis zwischen vertikaler Windgeschwindigkeit und Aerosolanzahlkonzentration (w/NCN) eingeteilt werden: (1) ein durch die Aerosolkonzentration limitierter Bereich (hohes w/NCN), (2) ein durch die vertikale Windgeschwindigkeit limitierter Bereich (niedriges w/NCN) und (3) ein Übergangsbereich (mittleres w/NCN). Die Ergebnisse zeigen, dass die Variabilität der anfänglichen Anzahlkonzentration der Wolkentropfen in (pyro-) konvektiven Wolken hauptsächlich durch die Variabilität der vertikalen Windgeschwindigkeit und der Aerosolkonzentration bestimmt wird. rnUm die mikrophysikalischen Prozesse innerhalb der rauchigen Aufwindregion einer pyrokonvektiven Wolke mit einer detaillierten spektralen Mikrophysik zu untersuchen, wurde das Paketmodel entlang einer Trajektorie innerhalb der Aufwindregion initialisiert. Diese Trajektore wurde durch dreidimensionale Simulationen eines pyro-konvektiven Ereignisses durch das Model ATHAM berechnet. Es zeigt sich, dass die Anzahlkonzentration der Wolkentropfen mit steigender Aerosolkonzentration ansteigt. Auf der anderen Seite verringert sich die Größe der Wolkentropfen mit steigender Aerosolkonzentration. Die Reduzierung der Verbreiterung des Tropfenspektrums stimmt mit den Ergebnissen aus Messungen überein und unterstützt das Konzept der Unterdrückung von Niederschlag in stark verschmutzen Wolken.Mit Hilfe des Models ATHAM wurden die dynamischen und mikrophysikalischen Prozesse von pyro-konvektiven Wolken, aufbauend auf einer realistischen Parametrisierung der Aktivierung von Aerosolpartikeln durch die Ergebnisse der Aktivierungsstudie, mit zwei- und dreidimensionalen Simulationen untersucht. Ein modernes zweimomenten mikrophysikalisches Schema wurde in ATHAM implementiert, um den Einfluss der Anzahlkonzentration von Aerosolpartikeln auf die Entwicklung von idealisierten pyro-konvektiven Wolken in US Standardamtosphären für die mittleren Breiten und den Tropen zu untersuchen. Die Ergebnisse zeigen, dass die Anzahlkonzentration der Aerosolpartikel die Bildung von Regen beeinflusst. Für geringe Aerosolkonzentrationen findet die rasche Regenbildung hauptsächlich durch warme mikrophysikalische Prozesse statt. Für höhere Aerosolkonzentrationen ist die Eisphase wichtiger für die Bildung von Regen. Dies führt zu einem verspäteten Einsetzen von Niederschlag für verunreinigtere Atmosphären. Außerdem wird gezeigt, dass die Zusammensetzung der Eisnukleationspartikel (IN) einen starken Einfluss auf die dynamische und mikrophysikalische Struktur solcher Wolken hat. Bei sehr effizienten IN bildet sich Regen früher. Die Untersuchung zum Einfluss des atmosphärischen Hintergrundprofils zeigt eine geringe Auswirkung der Meteorologie auf die Sensitivität der pyro-konvektiven Wolken auf diernAerosolkonzentration. Zum Abschluss wird gezeigt, dass die durch das Feuer emittierte Hitze einen deutlichen Einfluss auf die Entwicklung und die Wolkenobergrenze von pyro-konvektive Wolken hat. Zusammenfassend kann gesagt werden, dass in dieser Dissertation die Mikrophysik von pyrokonvektiven Wolken mit Hilfe von idealisierten Simulation eines Wolkenpaketmodell mit detaillierte spektraler Mikrophysik und eines 3D Modells mit einem zweimomenten Schema im Detail untersucht wurde. Es wird gezeigt, dass die extremen Bedingungen im Bezug auf die vertikale Windgeschwindigkeiten und Aerosolkonzentrationen einen deutlichen Einfluss auf die Entwicklung von pyro-konvektiven Wolken haben.

Analisi dello spettro di massa invariante j/psi pi+ pi- in collisioni p-p a sqrt(s) = 8 tev con il rivelatore cms

In questo lavoro di tesi è stato studiato lo spettro di massa invariante del sistema J/psi pi+ pi-, m(J/psi pi+ pi-), in collisioni protone-protone a LHC, con energia nel centro di massa sqrt(s)) pari a 8 TeV, alla ricerca di nuovi stati adronici. Lo studio è stato effettuato su un campione di dati raccolti da CMS in tutto il 2012, corrispondente ad una luminosità integrata di 18.6 fb-1. Lo spettro di massa invariante m(J/psi pi+ pi-), è stato ricostruito selezionando gli eventi J/psi->mu+ mu- associati a due tracce cariche di segno opposto, assunte essere pioni, provenienti da uno stesso vertice di interazione. Nonostante l'alta statistica a disposizione e l'ampia regione di massa invariante tra 3.6 e 6.0 GeV/c^2 osservata, sono state individuate solo risonanze già note: la risonanza psi(2S) del charmonio, lo stato X(3872) ed una struttura più complessa nella regione attorno a 5 GeV/c^2, che è caratteristica della massa dei mesoni contenenti il quark beauty (mesoni B). Al fine di identificare la natura di tale struttura, è stato necessario ottenere un campione di eventi arricchito in adroni B. È stata effettuata una selezione basata sull'elevata lunghezza di decadimento, che riflette la caratteristica degli adroni B di avere una vita media relativamente lunga (ordine dei picosecondi) rispetto ad altri adroni. Dal campione così ripulito, è stato possibile distinguere tre sottostrutture nello spettro di massa invariante in esame: una a 5.36 GeV/c^2, identificata come i decadimenti B^0_s-> J/psi pi+ pi-, un'altra a 5.28 GeV/c^2 come i candidati B^0-> J/psi pi+ pi- e un'ultima allargata tra 5.1 e 5.2 GeV/c^2 data da effetti di riflessione degli scambi tra pioni e kaoni. Quest'ultima struttura è stata identificata come totalmente costituita di una combinazione di eventi B^0-> J/psi K+ pi- e B^0_s-> J/psi K+ K-.

Aerosol-cloud interactions studied with a chemistry-climate model

This study aims at a comprehensive understanding of the effects of aerosol-cloud interactions and their effects on cloud properties and climate using the chemistry-climate model EMAC. In this study, CCN activation is regarded as the dominant driver in aerosol-cloud feedback loops in warm clouds. The CCN activation is calculated prognostically using two different cloud droplet nucleation parameterizations, the STN and HYB CDN schemes. Both CDN schemes account for size and chemistry effects on the droplet formation based on the same aerosol properties. The calculation of the solute effect (hygroscopicity) is the main difference between the CDN schemes. The kappa-method is for the first time incorporated into Abdul-Razzak and Ghan activation scheme (ARG) to calculate hygroscopicity and critical supersaturation of aerosols (HYB), and the performance of the modied scheme is compared with the osmotic coefficient model (STN), which is the standard in the ARG scheme. Reference simulations (REF) with the prescribed cloud droplet number concentration have also been carried out in order to understand the effects of aerosol-cloud feedbacks. In addition, since the calculated cloud coverage is an important determinant of cloud radiative effects and is influencing the nucleation process two cloud cover parameterizations (i.e., a relative humidity threshold; RH-CLC and a statistical cloud cover scheme; ST-CLC) have been examined together with the CDN schemes, and their effects on the simulated cloud properties and relevant climate parameters have been investigated. The distinct cloud droplet spectra show strong sensitivity to aerosol composition effects on cloud droplet formation in all particle sizes, especially for the Aitken mode. As Aitken particles are the major component of the total aerosol number concentration and CCN, and are most sensitive to aerosol chemical composition effect (solute effect) on droplet formation, the activation of Aitken particles strongly contribute to total cloud droplet formation and thereby providing different cloud droplet spectra. These different spectra influence cloud structure, cloud properties, and climate, and show regionally varying sensitivity to meteorological and geographical condition as well as the spatiotemporal aerosol properties (i.e., particle size, number, and composition). The changes responding to different CDN schemes are more pronounced at lower altitudes than higher altitudes. Among regions, the subarctic regions show the strongest changes, as the lower surface temperature amplifies the effects of the activated aerosols; in contrast, the Sahara desert, where is an extremely dry area, is less influenced by changes in CCN number concentration. The aerosol-cloud coupling effects have been examined by comparing the prognostic CDN simulations (STN, HYB) with the reference simulation (REF). Most pronounced effects are found in the cloud droplet number concentration, cloud water distribution, and cloud radiative effect. The aerosol-cloud coupling generally increases cloud droplet number concentration; this decreases the efficiency of the formation of weak stratiform precipitation, and increases the cloud water loading. These large-scale changes lead to larger cloud cover and longer cloud lifetime, and contribute to high optical thickness and strong cloud cooling effects. This cools the Earth's surface, increases atmospheric stability, and reduces convective activity. These changes corresponding to aerosol-cloud feedbacks are also differently simulated depending on the cloud cover scheme. The ST-CLC scheme is more sensitive to aerosol-cloud coupling, since this scheme uses a tighter linkage of local dynamics and cloud water distributions in cloud formation process than the RH-CLC scheme. For the calculated total cloud cover, the RH-CLC scheme simulates relatively similar pattern to observations than the ST-CLC scheme does, but the overall properties (e.g., total cloud cover, cloud water content) in the RH simulations are overestimated, particularly over ocean. This is mainly originated from the difference in simulated skewness in each scheme: the RH simulations calculate negatively skewed distributions of cloud cover and relevant cloud water, which is similar to that of the observations, while the ST simulations yield positively skewed distributions resulting in lower mean values than the RH-CLC scheme does. The underestimation of total cloud cover over ocean, particularly over the intertropical convergence zone (ITCZ) relates to systematic defficiency of the prognostic calculation of skewness in the current set-ups of the ST-CLC scheme.rnOverall, the current EMAC model set-ups perform better over continents for all combinations of the cloud droplet nucleation and cloud cover schemes. To consider aerosol-cloud feedbacks, the HYB scheme is a better method for predicting cloud and climate parameters for both cloud cover schemes than the STN scheme. The RH-CLC scheme offers a better simulation of total cloud cover and the relevant parameters with the HYB scheme and single-moment microphysics (REF) than the ST-CLC does, but is not very sensitive to aerosol-cloud interactions.

Ricerca di una risonanza ad alta massa nello stato finale mu+mu- a sqrt(s)=13 TeV con il rivelatore CMS

Il Modello Standard descrive la fenomenologia delle interazioni fondamentali con estrema precisione; tuttavia è incompleto e deve esistere nuova fisica oltre tale modello. Al momento non si è in grado di prevedere come e a che scala di energia tale fisica si manifesti. Un’eventuale risonanza nello stato finale μ + μ − a masse elevate costituirebbe un segnale di nuova fisica. Un fenomeno di questo tipo viene catalogato come produzione della particella Z' , la quale non rappresenterebbe necessariamente un nuovo bosone vettore sequenziale alla Z_0 . Questa tesi si colloca nell’ambito della ricerca della Z' nei processi di interazione protone-protone a LHC in termini di una generica risonanza che decade in coppie di muoni di carica opposta. I limiti attualmente fissati stabiliscono che non vi siano segnali di nuove risonanze per il Modello Sequenziale (SSM) al di sotto dei 2960 GeV. In questo lavoro di tesi si effettua un’analisi per un’eventuale Z ', fino a 5 TeV di massa. A Maggio 2015, LHC ha raggiunto un’energia nel centro di massa di 13 TeV aumentando di un fattore 10 o più il potere di scoperta per oggetti con massa superiore a 1 TeV. In questo scenario, favorevole all’osservazione di fenomeni rari, si inserisce la mia ricerca.

Using Clouds to Scale Grid Resources: An Economic Model

Infrastructure as a Service clouds are a flexible and fast way to obtain (virtual) resources as demand varies. Grids, on the other hand, are middleware platforms able to combine resources from different administrative domains for task execution. Clouds can be used by grids as providers of devices such as virtual machines, so they only use the resources they need. But this requires grids to be able to decide when to allocate and release those resources. Here we introduce and analyze by simulations an economic mechanism (a) to set resource prices and (b) resolve when to scale resources depending on the users’ demand. This system has a strong emphasis on fairness, so no user hinders the execution of other users’ tasks by getting too many resources. Our simulator is based on the well-known GridSim software for grid simulation, which we expand to simulate infrastructure clouds. The results show how the proposed system can successfully adapt the amount of allocated resources to the demand, while at the same time ensuring that resources are fairly shared among users.

Leveraging heterogeneity for energy minimization in data centers

Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

Enhancing regression models for complex systems using evolutionary techniques for feature engineering

This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.

Advanced computing for systems biology

Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

Metadata and Geospatial Data Processing on the Base of XML and Grid

The software architecture and development consideration for open metadata extraction and processing framework are outlined. Special attention is paid to the aspects of reliability and fault tolerance. Grid infrastructure is shown as useful backend for general-purpose task.

Services on Application Level in Grid for Scientific Calculations

AMS Subj. Classification: 00-02, (General)

Grid and Simulation of Digital Communication Systems

The purpose of this paper is to turn researchers' attention to the use of grid computing for simulating digital communications and its large potential for decreasing significantly the duration of the experiments and for improving the statistical representativeness and reliability of the obtained results.

Fast Information Retrieval in the Open Grid Service Architecture

This is an extended version of an article presented at the Second International Conference on Software, Services and Semantic Technologies, Sofia, Bulgaria, 11–12 September 2010.

Cloud базирана система за събиране, съхраняване и анализ на логови съобщения

Доклад, поместен в сборника на Националната конференция "Образованието в информационното общество", Пловдив, май, 2012 г.

Interoperable resource brokering with policy-based provisioning and job allocation

The increasing needs for computational power in areas such as weather simulation, genomics or Internet applications have led to sharing of geographically distributed and heterogeneous resources from commercial data centers and scientific institutions. Research in the areas of utility, grid and cloud computing, together with improvements in network and hardware virtualization has resulted in methods to locate and use resources to rapidly provision virtual environments in a flexible manner, while lowering costs for consumers and providers. ^ However, there is still a lack of methodologies to enable efficient and seamless sharing of resources among institutions. In this work, we concentrate in the problem of executing parallel scientific applications across distributed resources belonging to separate organizations. Our approach can be divided in three main points. First, we define and implement an interoperable grid protocol to distribute job workloads among partners with different middleware and execution resources. Second, we research and implement different policies for virtual resource provisioning and job-to-resource allocation, taking advantage of their cooperation to improve execution cost and performance. Third, we explore the consequences of on-demand provisioning and allocation in the problem of site-selection for the execution of parallel workloads, and propose new strategies to reduce job slowdown and overall cost.^

Infrastrutture basate su Edge Computing per Supporto a Servizi Mobili in Ambienti Ostili

Questa tesi è incentrata sulla revisione del classico modello di infrastruttura Cloud. Le motivazioni sono da ricercare nelle condizioni operative reali della maggior parte dei dispositivi connessi alla rete attualmente. Si parla di ambiente ostile riferendosi a network popolate da molti dispositivi dalle limitate caratteristiche tecniche e spesso collegati con canali radio, molto più instabili delle connessioni cablate. Allo scenario va ad aggiungersi la necessità crescente di mobilità che limita ulteriormente i vantaggi derivanti dall'utilizzo dell’infrastruttura Cloud originale. La trattazione propone il modello Edge come estensione del Cloud. Esso ne amplia il ventaglio di utilizzo, favorendo aree di applicazione che stanno acquisendo maggiore influenza negli ultimi periodi e che richiedono una revisione delle vecchie infrastrutture Cloud, dettata dalle caratteristiche stringenti che necessitano per un'operatività soddisfacente.