Дисертації з теми "Particle cloud modeling"

Les accélérateurs de particules reposent sur des simulations de haute précision pour optimiser la dynamique du faisceau. Ces simulations sont coûteuses en ressources de calcul, rendant leur analyse en temps réel difficilement réalisable. Cette thèse propose de surmonter cette limitation en explorant le potentiel de l'apprentissage automatique pour développer des modèles de substitution des simulations d'accélérateurs de particules. Ce travail se concentre sur ThomX, une source Compton compacte, et introduit deux modèles de substitution : LinacNet et Implicit Neural ODE (INODE). Ces modèles sont entraînés sur une base de données développée dans le cadre de cette thèse, couvrant une grande variété de conditions opérationnelles afin d'assurer leur robustesse et leur capacité de généralisation. LinacNet offre une représentation complète du nuage de particules en prédisant les coordonnées de toutes les macro-particules du faisceau plutôt que de se limiter à ses observables. Cette modélisation détaillée, couplée à une approche séquentielle prenant en compte la dynamique cumulative des particules tout au long de l'accélérateur, garantit la cohérence des prédictions et améliore l'interprétabilité du modèle. INODE, basé sur le cadre des Neural Ordinary Differential Equations (NODE), vise à apprendre les dynamiques implicites régissant les systèmes de particules sans avoir à résoudre explicitement les équations différentielles pendant l'entraînement. Contrairement aux méthodes basées sur NODE, qui peinent à gérer les discontinuités, INODE est conçu théoriquement pour les traiter plus efficacement. Ensemble, LinacNet et INODE servent de modèles de substitution pour ThomX, démontrant leur capacité à approximer la dynamique des particules. Ce travail pose les bases pour développer et améliorer la fiabilité des modèles basés sur l'apprentissage automatique en physique des accélérateurs
Particle accelerators rely on high-precision simulations to optimize beam dynamics. These simulations are computationally expensive, making real-time analysis impractical. This thesis seeks to address this limitation by exploring the potential of machine learning to develop surrogate models for particle accelerator simulations. The focus is on ThomX, a compact Compton source, where two surrogate models are introduced: LinacNet and Implicit Neural ODE (INODE). These models are trained on a comprehensive database developed in this thesis that captures a wide range of operating conditions to ensure robustness and generalizability. LinacNet provides a comprehensive representation of the particle cloud by predicting all coordinates of the macro-particles, rather than focusing solely on beam observables. This detailed modeling, coupled with a sequential approach that accounts for cumulative particle dynamics throughout the accelerator, ensures consistency and enhances model interpretability. INODE, based on the Neural Ordinary Differential Equation (NODE) framework, seeks to learn the implicit governing dynamics of particle systems without the need for explicit ODE solving during training. Unlike traditional NODEs, which struggle with discontinuities, INODE is theoretically designed to handle them more effectively. Together, LinacNet and INODE serve as surrogate models for ThomX, demonstrating their ability to approximate particle dynamics. This work lays the groundwork for developing and improving the reliability of machine learning-based models in accelerator physics

Cette thèse de doctorat est dédiée au développement de modèles physiques pour l’étude des systèmes d’aspersion de gouttelettes d’eau en milieu réactif d’hydrogène-air pré-mélangée dans les centrales nucléaires. Des modèles d’ordre réduit sont développés pour décrire l’évaporation des gouttelettes d’eau dans la flamme, la dispersion des nuages de particules après le passage des ondes de choc et l’évolution de l’échelle caractéristiques de turbulence avec la présence d’un jet d’eau. Une nouvelle méthodologie est proposée pour évaluer les effets de l’évaporation par l’aspersion sur la propagation de la flamme d’hydrogène turbulente à l’intérieur d’un volume fermé et un modèle simple est développé pour la quantification de la décélération de la vitesse laminaire avec l’évaporation des gouttelettes à l’intérieur de la flamme. Également, un modèle analytique est proposé pour la prédiction de la dispersion de nuage de particule après le passage d’une onde de choc en s’appuyant sur le one-way formalisme avec une extension afin de prédire l’apparition d’un pic de densité du nombre de particules en utilisant le two-way formalisme. En ce qui concerne la modulation de la turbulence induite par les particules, un modèle simple est utilisé pour l’estimation des échelles intégrales de la turbulence induites par l’injection de nuage des particules. Ces modèles numériques développés peuvent être couplés pour être mis en œuvre dans les simulations numériques à grande échelle de l’effet du système d’aspersion sur les explosions accidentelles d’hydrogène dans les centrales nucléaires
This PhD dissertation is dedicated to develop simple models to investigate the effect of water spray system on the premixed hydrogen-air combustion in the nuclear power plants. Specific simple models are developed to describe the water droplet evaporation in the flame, particle cloud dispersion after the shock wave passage, and turbulence length scale evolution with the presence of a water spray. A methodology is proposed to evaluate the spray evaporation effects on the propagation of the turbulent hydrogen flame inside a closed volume and a simple model is developed for the quantification of the laminar velocity deceleration with the droplets evaporation inside the flame. An analytical model is proposed for the prediction of particle cloud dispersion after the shock passage in the one-way formalism and another analytical model is dedicated to describe the spray-shock interaction mechanism and predict the appearance of a particle number density peak using the two-way formalism. A review of the important criteria and physical modelings related to the particle-induced turbulence modulation is given and a mechanistic model is used for the estimation of the turbulent integral length scales induced by the injection of particle clouds. These developed numerical models can be coupled to implement in the large-scale numerical simulations of the spray system effects on the accidental hydrogen explosions in the nuclear power plants

Atmospheric particles represent a component of air pollution that has been identified as a major contributor to adverse health effects and mortality. Aerosols also interact with solar radiation and clouds perturbing the atmosphere and generating responses in a wide range of scales, such as changes to severe weather and climate. Thus, being able to accurately predict aerosols and its effects on atmospheric properties is of upmost importance. This thesis presents a collection of studies with the global objective to advance in science and operations the use of WRF-Chem, a regional model able to provide weather and atmospheric chemistry predictions and simultaneously representing aerosol effects on climate. Different strategies are used to obtain accurate predictions, including finding an adequate model configuration for each application (e.g., grid resolution, parameterizations choices, processes modeled), using accurate forcing elements (e.g., weather and chemical boundary conditions, emissions), and developing and applying data assimilation techniques for different observational sources. Several environments and scales are simulated, including complex terrain at a city scale, meso-scale over the southeast US for severe weather applications, and regional simulations over the three subtropical persistent stratocumulus decks (off shore California and southeast Pacific and Atlantic) and over North America. Model performance is evaluated against a large spectrum of observations, including field experiments and ground based and satellite measurements. Overall, very positive results were obtained with the WRF-Chem system once it had been configured properly and the inputs chosen. Also, data assimilation of aerosol and cloud satellite observations contributed to improve model performance even further. The model is proven to be an excellent tool for forecasting applications, both for local and long range transported pollution. Also, advances are made to better understand aerosol effects on climate and its uncertainties. Aerosols are found to generate important perturbations, ranging from changes in cloud properties over extensive regions, up to playing a role in increasing the likelihood of tornado occurrence and intensity. Future directions are outline to keep advancing in better predictions of aerosols and its feedbacks.

The process of cloud glaciation strongly alters the properties of mixed-phase clouds. Between 0C to about -37C, cloud liquid droplets can either exist in the liquid phase in metastable state known as supercooling, or they can be composed of solid ice crystals. For a liquid droplet to freeze at these temperatures, the action of an external agent, known as ice-nucleating particle (INP) is needed. The atmospheric distribution of ice-nucleating particles was simulated in past studies as a function of the aerosol concentration, however, new experimental information about the ice- nucleating ability of different aerosol species and several new atmospheric measurements of INP are now available to be used in models. In this thesis, I use this new information to develop a global atmospheric model of the distribution of ice-nucleating particles to assess the relative importance of mineral dust, marine organic aerosols and black carbon for contributing to atmospheric concentrations of INPs. The model is evaluated against several datasets of INP concentrations measured in the atmosphere to test its realism and locate regions of the world where additional currently missing sources of INP could be important. The results show that feldspar aerosols dominate the atmospheric INP concentration for most parts of the globe, whereas marine organic aerosols are more relevant in the remote Southern Ocean. Black carbon particles, in contrast, seem not to play a substantial role when new estimates of its ice-nucleating ability are used. With the information obtained by this model, I explore whether the representation of ice-nucleating particles in climate models plays a role in the Southern Ocean radiative bias. This bias is related to modelled clouds reflecting too-little solar radiation, causing large errors in sea-surface temperatures and atmospheric circulations. I combine cloud-resolving simulations over regions of 1000 km with the new estimates of the INP concentration in remote regions to show that the simulated clouds reflect much more solar radiation than predicted by a global climate model, agreeing much better with satellite observations in both magnitude and frequency. Overall, these results will improve our understanding of the role, distribution and importance of ice-nucleating particles in the atmosphere and provide the scientific community new points of view to understand model biases.

When visualising a natural phenomena, such as a gas cloud, the constant movement and turbulens can pose a complex problem. With the use of a stochastic particle dispersion model a gas cloud is simulated and stored in a datafile. This thesis report describes some possible methods on how to structure and render such a datafile in an effective and realistic manner. This is achieved by using interpolation, the octree data structure and volume rendering. The end product will be used in a larger project at FOI, with the goal to facilitate the training of personal. Three different rendering methods are implemented and compared against each other. The best one will build the foundation for the FOI project. The end result of this report shows that the methods could be used with satisfying results but more development is needed.

The atmospheres of exoplanets are being characterised in increasing detail by observational facilities and will be examined with even greater clarity with upcoming space based missions such as the James Webb Space Telescope (JWST) and the Wide Field InfraRed Survey Telescope (WFIRST). A major component of exoplanet atmospheres is the presence of cloud particles which produce characteristic observational signatures in transit spectra and influence the geometric albedo of exoplanets. Despite a decade of observational evidence, the formation, dynamics and radiative-transport of exoplanet atmospheric cloud particles remains an open question in the exoplanet community. In this thesis, we investigate the kinetic chemistry of cloud formation in hot Jupiter exoplanets, their effect on the atmospheric dynamics and observable properties. We use a static 1D cloud formation code to investigate the cloud formation properties of the hot Jupiter HD 189733b. We couple a time-dependent kinetic cloud formation to a 3D radiative-hydrodynamic simulation of the atmosphere of HD 189733b and investigate the dynamical properties of cloud particles in the atmosphere. We develop a 3D multiple-scattering Monte Carlo radiative-transfer code to post-process the results of the cloudy HD 189733b RHD simulation and compare the results to observational results. We find that the cloud structures of the hot Jupiter HD 189733b are likely to be highly inhomogeneous, with differences in cloud particle sizes, number density and composition with longitude, latitude and depth. Cloud structures are most divergent between the dayside and nightside faces of the planet due to the instability of silicate materials on the hotter dayside. We find that the HD 189733b simulation in post-processing is consistent with geometric albedo observations of the planet. Due to the scattering properties of the cloud particles we predict that HD 189733b will be brighter in the upcoming space missions CHaracterising ExOPlanet Satellite (CHEOPS) bandpass compared to the Transiting Exoplanet Space Survey (TESS) bandpass.

L’un des enjeux principaux dans l’appréhension de l’évolution du climat planétaire réside dans la compréhension du rôle des processus de formation de la glace ainsi que leur rôle dans la formation et l’évolution des nuages troposphériques. Un cold stage nouvellement construit permet l’observation simultanée de jusqu’à 200 gouttes monodispersées de suspensions contenant des particules de K–feldspath, connues comme étant des particules glaçogènes très actives. Les propriétés glaçogènes des particules résiduelles de chaque goutte sont ensuite comparées pour les différents modes de glaciation et le lien entre noyau glaçogène en immersion et en déposition est étudié. Les premiers résultats ont montré que les mêmes sites actifs étaient impliqué dans la glaciation par immersion et par déposition. Les implications atmosphériques des résultats expérimentaux sont discutés à l’aide de Descam (Flossmann et al., 1985), un modèle 1.5–d à microphysique détaillée dans une étude de cas visant à rendre compte du rôle des différents mécanismes de glaciation dans l’évolution dynamique du nuage convective CCOPE (Dye et al., 1986). Quatre types d’aérosol minéraux (K–feldspath, kaolinite, illite et quartz) sont utilisés pour la glaciation en immersion, par contact et par déposition, à l’aide de paramétrisations sur la densité de sites glaçogènes actifs. Des études de sensibilité, où les différents types d’aérosols et modes de glaciation sont considérés séparément et en compétition, permettent de rendre compte de leurs importances relatives. La glaciation en immersion sur les particules de K–feldspath s’est révélée comme ayant le plus d’impact sur l’évolution dynamique et sur les précipications pour un nuage convectif
One of the main challenges in understanding the evolution of Earth's climate resides in the understanding the ice formation processes and their role in the formation of tropospheric clouds as well as their evolution. A newly built humidity-controlled cold stage allows the simultaneous observation of up to 200 monodispersed droplets of suspensions containing K-feldspar particles, known to be very active ice nucleating particles. The ice nucleation efficiencies of the individual residual particles were compared for the different freezing modes and the relationship between immersion ice nuclei and deposition ice nuclei were investigated. The results showed that the same ice active sites are responsible for nucleation of ice in immersion and deposition modes.The atmospheric implications of the experimental results are discussed, using Descam (Flossmann et al., 1985), a 1.5-d bin-resolved microphysics model in a case study aiming to assess the role of the different ice nucleation pathways in the dynamical evolution of the CCOPE convective cloud (Dye et al., 1986). Four mineral aerosol types (K-feldspar, kaolinite, illite and quartz) were considered for immersion and contact freezing and deposition nucleation, with explicit Ice Nucleation Active Site density parameterizations.In sensitivity studies, the different aerosol types and nucleation modes were treated seperately and in competition to assess their relative importance. Immersion freezing on K-feldspar was found to have the most pronounced impact on the dynamical evolution and precipitation for a convective cloud

The ubiquitous abundance of organic compounds in natural and anthorpogenically influenced eco-systems has put these compounds into the focus of atmospheric research. Organic compounds have an impact on air quality, climate, and human health. Moreover, they affect particle growth, secondary organic aerosol (SOA) formation, and the global radiation budget by altering particle properties. To investigate the multiphase chemistry of organic compounds and interactions with the aqueous phase in the troposphere, modelling can provide a useful tool. The oxidation of larger organic molecules to the final product CO2 can involve a huge number of intermediate compounds and tens of thousands of reactions. Therefore, the creation of explicit mechanisms relies on automated mechanism construction. Estimation methods for the prediction of the kinetic data needed to describe the degradation of these intermediates are inevitable due to the infeasibility of an experimental determination of all necessary data. Current aqueous phase descriptions of organic chemistry lag behind the gas phase descriptions in atmospheric chemical mechanisms despite its importance for the multiphase chemistry of organic compounds. In this dissertation, the gas phase mechanism Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) has been advanced by a protocol for the description of the oxidation of organic compounds in the aqueous phase. Therefore, a database with kinetic data of 465 aqueous phase hydroxyl radical and 129 aqueous phase nitrate radical reactions with organic compounds has been compiled and evaluated. The database was used to evaluate currently available estimation methods for the prediction of aqueous phase kinetic data of reactions of organic compounds. Among the investigated methods were correlations of gas and aqueous kinetic data, kinetic data of homologous series of various compound classes, reactivity comparisons of inorganic radical oxidants, Evans-Polanyi-type correlations, and structure-activity relationships (SARs). Evans-Polanyi-type correlations have been improved for the purpose of automated mechanism self-generation of mechanisms with large organic molecules. A protocol has been designed based on SARs for hydroxyl radical reactions and the improved Evans-Polanyi-type correlations for nitrate radical reactions with organic compounds. The protocol was assessed in a series of critical sensitivity studies, where uncertainties of critical parameters were investigated. The advanced multiphase generator GECKO-A was used to generate mechanisms, which were applied in box model studies and validated against two sets of aerosol chamber experiments. Experiments differed by the initial compounds used (hexane and trimethylbenzene) and the experimental conditions (UV-C lights off/on and additional in-situ hydroxyl radical source no/yes). Reasonable to good agreement of the modelled and experimental results was achieved in these studies. Finally, GECKO-A was used to create two new CAPRAM version, where, for the first time, branchingratios for different reaction pathways were introduced and the chemistry of compounds with up to four carbon atoms has been extended. The most detailed mechanism comprises 4174 compounds and 7145 processes. Detailed investigations were performed under real tropospheric conditions in urban and remote continental environments. Model results showed significant improvements, especially in regard to the formation of organic aerosol mass. Detailed investigations of concentration-time profiles and chemical fluxes refined the current knowledge of the multiphase processing of organic compounds in the troposphere, but also pointed at current limitations of the generator protocol, the mechanisms created, and current understanding of aqueous phase processes of organic compounds
Das zahlreiche Vorkommen organischer Verbindungen in natürlichen und anthropogen beeinflussten Ökosystemen hat diese Verbindungen in den Fokus der Atmosphärenforschung gerückt. Organische Verbindungen beeinträchtigen die Luftqualität, die menschliche Gesundheit und das Klima. Weiterhin werden Partikelwachstum und -eigenschaften, sekundäre organische Partikelbildung und dadurch der globale Strahlungshaushalt durch sie beeinflusst. Um die troposphärische Multiphasenchemie organischer Verbindungen und Wechselwirkungen mit der Flüssigphase zu untersuchen, sind Modellstudien hilfreich. Die Oxidation großer organischer Moleküle führt zu einer Vielzahl an Zwischenprodukten. Der Abbau erfolgt in unzähligen Reaktionen bis hin zum Endprodukt CO2. Bei der Entwicklung expliziter Mechanismen muss deshalb für diese Verbindungen auf computergestützte, automatisierte Methoden zurückgegriffen werden. Abschätzungsmethoden für die Vorhersage kinetischer Daten zur Beschreibung des Abbaus der Zwischenprodukte sind unabdingbar, da eine experimentelle Bestimmung aller benötigten Daten nicht realisierbar ist. Die derzeitige Beschreibung der Flüssigphasenchemie unterliegt deutlich den Beschreibungen der Gasphase in atmosphärischen Chemiemechanismen trotz deren Relevanz für die Multiphasenchemie. In dieser Arbeit wurde der Gasphasenmechanismusgenerator GECKO-A (“Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere”) um ein Protokoll zur Oxidation organischer Verbindungen in der Flüssigphase erweitert. Dazu wurde eine Datenbank mit kinetischen Daten von 465 Hydroxylradikal- und 129 Nitratradikalreaktionen mit organischen Verbindungen angelegt und evaluiert. Mit Hilfe der Datenbank wurden derzeitige Abschätzungsmethoden für die Vorhersage kinetischer Daten von Flüssigphasenreaktionen organischer Verbindungen evaluiert. Die untersuchten Methoden beinhalteten Korrelationen kinetischer Daten aus Gas- und Flüssigphase, homologer Reihen verschiedener Stoffklassen, Reaktivitätsvergleiche, Evans-Polanyi-Korrelationen und Struktur-Reaktivitätsbeziehungen. Für die Mechanismusgenerierung großer organischer Moleküle wurden die Evans-Polanyi-Korrelationen in dieser Arbeit weiterentwickelt. Es wurde ein Protokol für die Mechanismusgenerierung entwickelt, das auf Struktur-Reaktivitätsbeziehungen bei Reaktionen von organischen Verbindungen mit OH-Radikalen und auf den erweiterten Evans-Polanyi-Korrelationen bei NO3-Radikalreaktionen beruht. Das Protokoll wurde umfangreich in einer Reihe von Sensitivitätsstudien getestet, um Unsicherheiten kritischer Parameter abzuschätzen. Der erweiterte Multiphasengenerator GECKO-A wurde dazu verwendet, neue Mechanismen zu generieren, die in Boxmodellstudien gegen Aerosolkammerexperimente evaluiert wurden. Die Experimentreihen unterschieden sich sowohl in der betrachteten Ausgangssubstanz (Hexan und Trimethylbenzen) und dem Experimentaufbau (ohne oder mit UV-C-Photolyse und ohne oder mit zusätzlicher partikulärer Hydroxylradikalquelle). Bei den Experimenten konnte eine zufriedenstellende bis gute Übereinstimmung der experimentellen und Modellergebnisse erreicht werden. Weiterhin wurde GECKO-A verwendet, um zwei neue CAPRAM-Versionen mit bis zu 4174 Verbindungen und 7145 Prozessen zu generieren. Erstmals wurden Verzweigungsverhältnisse in CAPRAM eingeführt. Außerdem wurde die Chemie organischer Verbindungen mit bis zu vier Kohlenstoffatomen erweitert. Umfangreiche Untersuchungen unter realistischen troposphärischen Bedingungen in urbanen und ländlichen Gebieten haben deutliche Verbesserungen der erweiterten Mechanismen besonders in Bezug auf Massenzuwachs des organischen Aerosolanteils gezeigt. Das Verständnis der organischen Multiphasenchemie konnte durch detaillierte Untersuchungen zu den Konzentrations-Zeit-Profilen und chemischen Flüssen vertieft werden, aber auch gegenwärtige Limitierungen des Generators, der erzeugten Mechanismen und unseres Verständnisses für Flüssigphasenprozesse organischer Verbindungen aufgezeigt werden

Various physical mechanisms that affect radiowave propagation at millimetre wavelengths are considered. Current modelling weaknesses are highlighted and new improved models or more appropriate modelling approaches are suggested. Interference and resonance phenomena in the scattering of spherical ice and water particles are reviewed. The long standing problem of the numerous resonances observed in the scattering diagrams of dielectric spheres is answered. The spatial structure and the physical characteristics of non-precipitable ice and water clouds are reviewed. Extinction and back scattering calculations for a wide variety of cloud models over the entire millimetre frequency spectrum are given. Multiple scattering and the effects of super-large drops in clouds are also dealt with. The potential of a spaceborne instrument in deducing information about the vertical structure of various cloud types is examined. Attenuation and reflectivity profiles resulting from various cloud types are calculated for a nadir pointing fixed beam millimetre wave radar operating at 94 GHz. The physics and application of the equation of radiative transfer to millimetre wave propagation in the earth's atmosphere are given and also is the solution of this equation for a typical millimetre wave remote sensing application. The theory of gaseous absorption at millimetre wavelengths is presented and an improved modelling approach is proposed for the calculation of the absorption and dispersion spectra of atmospheric gases. The effects of trace gases on communication systems operating at high altitudes are for the first time reported. Finally the use of the 60 GHz oxygen absorption band for top-side air traffic control/navigation and broadband transmission purposes is studied.

Les particules d'aérosol sont une composante essentielle de l'atmosphère, et cette importance s'amplifie lors d'une éventuelle libération dans l'atmosphère de matières radioactives sous forme particulaire. En effet, pour améliorer la connaissance autour de la contamination des sols consécutive à une émission de particules, il est important d'étudier le rabattement des particules par la pluie sous le nuage. Dans ce but, des expériences sont menées à l'échelle microphysique (expérience BERGAME) pour quantifier l'efficacité des gouttes de pluie à collecter les particules. Ceci permet au final d'améliorer la modélisation du lessivage des aérosols atmosphériques par la pluie à méso-échelle. Le modèle utilisé est DESCAM qui décrit de manière détaillée les distributions granulométriques en masse et en nombre des particules pour chaque type d'aérosol et des hydrométéores et calcule leur évolution due aux processus microphysiques nuageux. L'expérience BERGAME a été dimensionnée et construite pour mesurer l'efficacité de collecte car les mesures de ce paramètre se sont avérées en désaccord avec les modèles classiques de la littérature pour les gouttes de pluie d'un diamètre supérieur au millimètre. Un montage optique a été imaginé pour tenter de comprendre quels mécanismes de collecte sont négligés dans les modèles standards. Un nouveau modèle d'efficacité de collecte pour les gouttes d'un diamètre de 2 mm est alors proposé prenant en compte pour les grosses gouttes une recirculation turbulente dans le sillage de la goutte capable d'augmenter de façon importante la capture des petites particules. Les nouvelles efficacités de collecte ainsi mesurées et paramétrées sont ajoutées au modèle de nuage DESCAM. Des modifications significatives sur la modélisation du lessivage par DESCAM sont observées, ouvrant ainsi la voie à une amélioration de la modélisation de la contamination des sols par les modèles de dispersion atmosphérique.

Les particules atmosphériques sont un sujet d’importance dans plusieurs couches de la société. Leur présence dans l’atmosphère est aussi bien une problématique météorologique et climatique qu’un enjeu de santé publique, notamment de par l’accroissement des maladies cardiovasculaires. En particulier, les particules radioactives émises dans l’atmosphère à la suite d’un accident nucléaire peuvent polluer les écosystèmes durant plusieurs années. Le récent accident du Centre Nucléaire de Production d’Électricité de Fukushima Daiichi en 2011 nous rappelle que, même aujourd’hui, le risque zéro n’existe pas. À la suite d’une émission dans l’atmosphère, les particules nanométriques diffusent et s’agglomèrent alors que les particules de plusieurs micromètres sédimentent. Les tailles intermédiaires vont, quant à elles, pouvoir être transportées à l’échelle globale dont le mécanisme principal de rabattement au sol provient des interactions avec les nuages et les précipitations. Afin d’améliorer la connaissance de la contamination des sols consécutive à de tels accidents, la compréhension de la capture des aérosols par les nuages est alors essentielle. Dans ce but, un modèle microphysique est implémenté dans ce travail, considérant les mécanismes microphysiques qui interviennent dans la capture des aérosols par des gouttes de nuage, notamment les forces électrostatiques dès lors que les radionucléides ont pour propriété de fortement se charger. Des mesures en laboratoire sont alors réalisées à l’aide de In-CASE (In-Cloud Aerosols Scavenging Experiment), expérience conçue dans ce travail, afin de comparer le modèle développé aux observations, et ce, toujours à une échelle microphysique où les paramètres d’influence régissant la capture au sein du nuage sont contrôlés. Par ailleurs, des systèmes de charge des particules et des gouttes sont conçus pour soigneusement maîtriser les charges électriques, tandis que l’humidité relative est précisément pilotée. Les nouvelles connaissances de la capture des particules par des gouttes de nuage qui en découlent, concernant entre autres les effets électrostatiques, sont ensuite incorporées au modèle de nuage convectif DESCAM (Detailed SCAvenging Model). Ce modèle à microphysique détaillée décrit un nuage de sa formation jusqu’aux précipitations, permettant d’étudier l’impact des nouvelles données sur le rabattement des particules à méso-échelle. De plus, des modifications sont apportées à DESCAM pour élargir l’étude aux nuages stratiformes qui constituent en France, la majorité des précipitations. À terme, cette étude ouvre la voie à l’amélioration de la modélisation du rabattement atmosphérique des particules, et notamment à la contamination des sols dans les modèles de crise de l’Institut de Radioprotection et de Sûreté Nucléaire
Atmospheric particles are a key topic in many social issues. Their presence in this atmosphere is a meteorological and climatic subject, as well as a public health concern since these particles are correlated with the increase of cardiovascular diseases. Specially, radioactive particles emitted as a result of a nuclear accident can jeopardise ecosystems for decades. The recent accident at the Fukushima Daiichi’s nuclear power plant in 2011 reminds us that the risk, even extremely unlikely, exists.After a release of nuclear material in the atmosphere, nanometric particles diffuse and coagulate, while micrometric particles settle due to gravity. Nevertheless, the intermediate size particles can be transported at a global scale when the main mechanism involved in their scavenging comes from the interaction with clouds and their precipitations. To enhance the ground contamination knowledge after such accidental releases, the understanding of the particle in-cloud collection is thus essential. For this purpose, a microphysical model is implemented in this work, including the whole microphysical mechanisms acting on the particle collection by cloud droplets like the electrostatic forces since radionuclides are well-known to become significantly charged. Laboratory measurements are then conducted through In-CASE (In-Cloud Aerosols Scavenging Experiment), a novel experiment built in this work, to get comparisons between modelling and observations, once again at a microphysical scale where every parameter influencing the particle in-cloud collection is controlled. Furthermore, two systems to electrically charge particles and droplets are constructed to set the electric charges carefully while the relative humidity level is also regulated. These new research results related to the particle collection by cloud droplets following the electrostatic forces, among others effects, are thus incorporated into the convective cloud model DESCAM (Detailed SCAvenging Model). This detailed microphysical model describes a cloud from its formation to the precipitations, allowing the study at a meso-scale of the impact of the new data on the particle scavenging. Moreover, some changes are made in DESCAM to expand the study to stratiform clouds since the major part of the French precipitations come from the stratiform ones. Finally, this work paves the way for the enhancement of the atmospheric particle scavenging modelling, including the ground contamination in the crisis model used by the French Institute in Radiological Protection and Nuclear Safety

In the atmosphere cloud droplets form and grow on aerosol particles - tiny solid or liquid particles suspended in the air. When trapped inside water drops aerosol particles are affected by the processes happening in clouds such as collisions between water drops or aqueous phase chemical reactions inside water drops. It can be said that clouds and aerosol particles coexist, continuously changing each others properties. This dissertation studies the interactions between aerosol particles and water drops in warm (i.e. ice free) boundary layer clouds. The main focus is on the collisions between water drops and the aqueous phase oxidation of sulfur to sulfate occurring inside cloud droplets and the impact of those processes on the size distribution of aerosol particles.The study is carried out using numerical simulations employing a Lagrangian representation of cloud microphysics and aqueous phase chemical reactions. The Lagrangian methods, also called particle tracking or particle based, allow to represent cloud microphysical and chemical processes as if from a point of view of an aerosol particle or a water drop. They are computationally expensive but allow to resolve numerically the changes to both aerosol particle and water drop size distribution.This study uses the Lagrangian microphysics scheme developed at the Faculty of Physics at the University of Warsaw. For the purpose of this study the Lagrangian scheme was extended to cover also the aqueous phase processes in cloud droplets. The list of chemical processes includes the dissolving of trace gases into water drops their dissociation and the oxidation reaction of sulfur to sulfate by ozone and hydrogen peroxide.Six trace gases are included in the scheme: sulfur dioxide, ozone, hydrogen peroxide, carbon dioxide, ammonia and nitric acid. The scientific software created during this study is available for further use as a part of an open source library of schemes. Parts of this dissertation may serve as the first documentation of the design, performance and the user interface of the created Lagrangian microphysics and aqueous phase chemistry scheme.The dissertation contains a short theoretical introduction to the microphysical and chemical processes occurring in warm clouds. It presents the details of the Lagrangian representation of microphysics in a numerical scheme.The new module of the Lagrangian scheme responsible for aqueous phase chemical reactions is described and tested in an adiabatic parcel model framework. Next, the created Lagrangian microphysics and aqueous phase chemistry scheme is used in a 2-dimensional kinematic setup representing a vertical slice through a boundary layer topped with a stratocumulus deck. The discussion focuses on the impact of collisions between water drops and the in-cloud oxidation of sulfur to sulfate on the size distribution on aerosol particles. The sensitivity of the obtained results to different microphysical and chemical conditions is also investigated.
Kropelki chmurowe tworzą się na cząstkach aerozolu czyli drobinach zanieczyszczeń w fazie stałej lub ciekłej zawieszonych w powietrzu. Cząstki aerozolu znajdujące się w kropelkach chmurowych są poddane działaniom procesów chmurowych takich jak zderzenia między kropelkami wody lub reakcje chemiczne zachodzące w kropelkach wody. Chmury i cząstki aerozolu wzajemnie ze sobą oddziałują i wzajemnie wpływają na swoje własności. Przedstawiona rozprawa doktorska bada interakcje pomiędzy drobinami aerozolu atmosferycznego i kropelkami wody w płytkich chmurach warstwy granicznej (t.j. w chmurach bez lodu). Przedstawione wyniki skupiają się na zderzeniach miedzy kropelkami wody i reakcji utlenienia dwutlenku siarki do kwasu siarkowego VI zachodzącej w kropelkach chmurowych oraz ich wpływie na widmo rozmiarów drobin aerozolu.Badania przedstawione w rozprawie doktorskiej są prowadzone przy użyciu symulacji numerycznych wykorzystujących lagranżowski sposób opisu mikrofizyki chmur i reakcji chemicznych w kropelkach chmurowych. Metody te są kosztowne numerycznie, ale pozwalają na dokładną reprezentację w modelu numerycznym ewolucji widma rozmiarów zarówno kropel wody jak i cząstek aerozolu.W trakcie przeprowadzonych badań użyty został lagranżowski schemat mikrofizyczny tworzony na Wydziale Fizyki Uniwersytetu Warszawskiego. Na potrzeby przeprowadzonych badań schemat ten został rozszerzony o opis procesów chemicznych zachodzących w kropelkach chmurowych. Do schematu dodany został opis rozpuszczania gazów śladowych w kropelkach chmurowych, dysocjacji rozpuszczonych związków na jony i reakcji utlenienia rozpuszczonego dwutlenku siarki do kwasu siarkowego przez ozon i nadtlenek wodoru. Do schematu zostało dodanych sześć gazów śladowych: dwutlenek siarki, ozon, nadtlenek wodoru, dwutlenek węgla, amoniak i kwas azotowy. Stworzone oprogramowanie jest dostępne jako część otwartej biblioteki schematów numerycznych. Część przedstawionej rozprawy doktorskiej może służyć jako opis struktury i sposobu działania stworzonego oprogramowania oraz dokumentacja interfejsu użytkownika.Rozprawa doktorska zawiera krótki wstęp przedstawiający teoretyczne podstawy opisu procesów mikrofizycznych i chemicznych zachodzących w płytkich chmurach warstwy granicznej. Następnie zaprezentowany jest opis zasady działania mikrofizycznego schematu lagranżowskiego. W rozprawie opisany jest również nowy moduł odpowiedzialny za reakcje chemiczne zachodzące w kropelkach chmurowych. Poprawność stworzonego opisu reakcji chemicznych w kropelkach jest przetestowana przy użyciu adiabatycznego modelu cząstki. W ostatniej części rozprawy lagranżowski opis mikrofizyki i reakcji chemicznych w chmurach jest zastosowany w 2-wymiarowym modelu reprezentującym przekrój przez warstwę graniczną przykrytą chmurą stratocumulus. Dyskusja wyników skupia się na przedstawieniu wpływu zderzeń między kropelkami oraz reakcji chemicznych zachodzących w kropelkach chmurowych na widmo rozmiarów drobin aerozolu. Dyskutowane są również symulacje testujące czułość otrzymanych wyników na początkowe warunki mikrofizyczne i chemiczne panujące w modelu.

The analysis and modelling of small-scale turbulence in the atmosphere play a significant role in improving our understanding of cloud processes, thereby contributing to the development of better parameterization of climate models. Advancement in our understanding of turbulence can be fueled from a more in-depth study of small-scale turbulence, which is the subject of this thesis. Within this thesis, small scales are understood as turbulent structures affected by viscosity as well as scales from the highwavenumber part of the inertial range which are of O(0.1m−1m) typically neglected in numerical simulations of atmospheric turbulence. This work is divided into two parts. In the first part, various approaches to estimate the turbulence kinetic energy (TKE) dissipation rate , from one-dimensional (1D) intersections that resemble experimental series, are tested using direct numerical simulation (DNS) of the stratocumulus cloudtop mixing layer and free convective boundary layer. Results of these estimates are compared with “true” DNS values of in buoyant and inhomogeneous atmospheric flows. This research focuses on recently proposed methods of the TKE dissipation-rate retrievals based on signal’s zero crossings and on recovering the missing part of the spectrum. The methods are tested on fully resolved turbulence fields and compared to standard retrievals from power spectra and structure functions. Anisotropy of turbulence due to buoyancy is shown to influence retrievals based on the vertical velocity component. TKE dissipation-rate estimates from the number of crossings correspond well to spectral estimates. As far as the recovery of the missing part of the spectrum is concerned, different models for the dissipation spectra was investigated, and the best one is chosen for further study. Results were improved when the Taylors’ microscale was used in the iterative method, instead of the Liepmann scale based on the number of signal’s zero crossings. This also allowed for the characterization of external intermittency by the Taylor-to-Liepmann scale ratio. It was shown that the new methods of TKE dissipation-rate retrieval from 1D series provide a valuable complement to standard approaches. The second part of this study addresses the reconstruction of sub-grid scales in large eddy simulation (LES) of turbulent flows in stratocumulus cloud-top. The approach is based on the fractality assumption of the turbulent velocity field. The fractal model reconstructs sub-grid velocity fields from known filtered values on LES grid, using fractal interpolation, proposed by Scotti and Meneveau [Physica D 127, 198–232 1999]. The characteristics of the reconstructed signal depend on the stretching parameter d, which is related to the fractal dimension of the signal. In many previous studies, the stretching parameter values were assumed to be constant in space and time. To improve the fractal interpolation approach, the stretching parameter variability is accounted for. The local stretching parameter is calculated from DNS data with an algorithm proposed by Mazel and Hayes [IEEE Trans. Signal Process 40(7), 1724–1734, 1992], and its probability density function (PDF) is determined. It is found that the PDFs of d have a universal form when the velocity field is filtered to wave-numbers within the inertial range. The inertial-range PDFs of d in DNS and LES of stratocumulus cloud-top and experimental airborne data from physics of stratocumulus top (POST) research campaign were compared in order to investigate its Reynolds number (Re) dependence. Next, fractal reconstruction of the subgrid velocity is performed and energy spectra and statistics of velocity increments are compared with DNS data. It is assumed that the stretching parameter d is a random variable with the prescribed PDF. Moreover, the autocorrelation of d in time is examined. It was discovered that d decorrelates with the characteristic timescale of the order of the Kolmogorov’s time scale and hence can be chosen randomly after each time step in LES. This follows from the fact that the time steps used in LES are typically considerably larger than Kolmogorov’s timescale. The implemented fractal model gives good agreement with the DNS and physics of stratocumulus cloud (POST) airborne data in terms of their spectra and PDFs of velocity increments. The error in mass conservation is smaller compared to the use of constant values of d. In conclusion, possible applications of the fractal model were addressed. A priori LES test shows that the fractal model can reconstruct the resolved stresses and residual kinetic energy. Also, based on the preliminary test, the fractal model can improve LES velocity fields used in the Lagrangian tracking of droplets for the simulation of cloud microphysics. Both parts of the thesis are based on the assumptions of scale self-similarity of Kolmogorov and local isotropy, which may not be satisfied in real atmospheric conditions. Since the standard methods for TKE dissipation rate retrieval are derived from these assumptions, the level of discrepancy is investigated by comparing the actual value of from DNS with estimates from these methods. Also, in the case of the modelling of small (subgrid) scales, the improved fractal model relies on scale-similarity. Range of scales, in which this assumption is sufficiently satisfied (i.e. inertial range scales) is reconstructed. Statistical tools from the Kolmogorov’s similarity hypotheses are used to assess the performance of the improved fractal model.