The use of hazardous toxic substances is very common in the industrial sector. The substances are often stored in tanks in storage compartments or transported between industrial premises. In case of an accident involving these substances, severe harm can affect both population and the environment. This leaves a demand for an accurate prediction of the substance concentration distribution to mitigate the risks as much as possible and in advance create suitable safety measures. Toxic gases and vapors are often denser than air making it affected by negative buoyancy forces. This will make the gas descend and spread horizontally when reaching the ground. Swedish Defence Research Agency (FOI) carries today a model called LillPello for simulating the dispersion of gases, yet it does not account for the specific case of a dense gas. Therefore, this thesis aims to implement the necessary effects needed to accurately simulate the dispersion of a dense gas. These effects were implemented in Fortran 90 by solving five conservation equations for energy, momentum (vertical and horizontal) and mass. The model was compared against experimental data of a leak of ammonia (NH3). By analyzing the result of the simulations in this thesis, we can conclude that the overall result is satisfactory. We can notice a small concentration underestimation at all measurement points and the model produced a concentration power law coefficient which lands inside the expected range. Two out of the three statistical quantities Geometric Mean (MG), Geometric Variance (VG) and Factor of 2 (FA2) produced values within the ranges of acceptable values. The drawback of the model as it is implemented today is its efficiency, so the main priority for the future of this thesis is to improve this. The model should also be analyzed on more experiments to further validate its accuracy. / Användandet av giftiga ämnen är vanligt inom den industriella sektorn. Ämnena är oftast lagrade i behållare positionerade i lagringsutrymmen eller så transporteras ämnena mellan industrilokaler. I samband med en olycka innehållande dessa substanser kan stora skador drabba både befolkning och miljön. Detta leder till ett behov av att noggrant kunna förutspå koncentrationsfördelningen för att minska riskerna, samt i förväg kunna skapa lämpliga säkerhetsåtgärder. Giftiga gaser och ångor är oftast tyngre än luft vilket gör att gasen blir påverkad av negativ bärkraft. Detta gör att gasen sjunker och sprids horisontalt när den når marken. Totalförsvarets Forskningsinstitut (FOI) besitter idag en modell kallad LillPello som simulerar spridning av gaser, men den hanterar inte det specifika fallet av en tunggas. Därför siktar detta projekt på att, in i LillPello, implementera de nödvändiga effekterna som behövs för att korrekt kunna simulera spridningen av en tunggas. Dessa effekter är implementerad i Fortran 90 genom att lösa fem konserveringsekvationer för energi, momentum (vertikal och horisontell) samt massa. Modellen jämfördes mot data från ett fältexperiment där ammoniak (NH3) släpptes ut. Genom att analysera resultatet från simuleringar kan vi dra slutsatsen att det övergripande resultatet är tillfredsställande. Vi kan notera en underskattning för alla koncentrationsmätningar i simuleringarna och modellen producerade en potenslagsexponent vars värde hamnade innanför den accepterade gränsen. Två utav de tre beräknade statistiska kvantiteterna: Geometriskt medelvärde (MG), Geometrisk varians (VG) och Faktor av 2 (FA2) producerade värden inom de acceptabla gränserna. Största nackdelen med modellen är dess effektivitet och därför är största prioritet för det fortsatta arbetet inom detta projekt att effektivisera implementeringen. Modellen ska även bli vidare analyserad mot fler experiment för att validera dess noggrannhet.

A percepção crescente da sociedade em relação aos perigos inerentes às instalações industriais que manipulam grandes inventários de substâncias perigosas faz com que a ferramenta análise quantitativa de risco ganhe importância na complexa discussão sobre a viabilidade destes empreendimentos, no intuito de promover a ocupação adequada do solo na área urbana e prevenir a ocorrência do chamado acidente maior. Contudo, para se chegar à expressão de risco de uma determinada instalação industrial deve-se aplicar um conjunto de técnicas e de modelos matemáticos, entre os quais estão os modelos de dispersão atmosférica, usados para se estimar a área afetada na vizinhança da mesma por liberações acidentais que levam à formação de nuvens de substâncias químicas na atmosfera. Em decorrência da complexidade inerente ao próprio processo de dispersão atmosférica, especialmente no que tange aos denominados gases densos, existe uma diversidade de modelos que podem ser aplicados no escopo da análise de risco, o que leva a seus usuários, naturalmente, ao questionamento sobre a suscetibilidade dos resultados finais ao tipo de modelagem adotada. Neste sentido, este trabalho estuda o processo de dispersão atmosférica de nuvens densas formadas em liberações acidentais, identificando as principais possibilidades de modelagem deste processo e, ao final, apresenta um estudo de caso demonstrando que diferentes modelagens desta dispersão, comumente empregadas em análise de risco de instalações industriais, podem produzir variações na estimativa do risco de uma mesma instalação e, portanto, influenciar as decisões baseadas em risco. / The concern of the society about the risks posed by activities that deal with hazardous substances has increased in an environment strongly industrialized and with high population density in view of the inherent potential hazards of them as well as the impact of recent accidental episodes, even though their benefits provided. In this context the quantitative risk analysis is presented as an essential tool to assess the risk of these activities and compose a complex discussion about its feasibility. Some of these accident scenarios may involve the formation of a hazardous product cloud and its subsequent air dispersion in the off-site region when an accidental released take place and one should apply the so-called atmospheric dispersion models for estimating the consequences of the releases. Due to the complexity involved in this atmospheric dispersion process, there is a wide variety of mathematical models that can be applied for estimating the offsite consequences of the accidental releases leading, naturally, to one wonder whether the final risk expression of a facility is susceptible to these differences. Often in the world of industrial use of hazardous materials, toxic or flammable there is a possibility that these accidental releases produce clouds that are denser than air, a situation that demands even more attention in terms of risk aspects involved. Then, this dissertation studies the process of atmospheric dispersion of heavier-than-air clouds produced after an accidental release, identifying the main ways of modelling the process and presents a case study comparing different dispersion models that demonstrates that the final expression of risk of a typical installation can be different when it is used different dispersion model in the process.

A percepção crescente da sociedade em relação aos perigos inerentes às instalações industriais que manipulam grandes inventários de substâncias perigosas faz com que a ferramenta análise quantitativa de risco ganhe importância na complexa discussão sobre a viabilidade destes empreendimentos, no intuito de promover a ocupação adequada do solo na área urbana e prevenir a ocorrência do chamado acidente maior. Contudo, para se chegar à expressão de risco de uma determinada instalação industrial deve-se aplicar um conjunto de técnicas e de modelos matemáticos, entre os quais estão os modelos de dispersão atmosférica, usados para se estimar a área afetada na vizinhança da mesma por liberações acidentais que levam à formação de nuvens de substâncias químicas na atmosfera. Em decorrência da complexidade inerente ao próprio processo de dispersão atmosférica, especialmente no que tange aos denominados gases densos, existe uma diversidade de modelos que podem ser aplicados no escopo da análise de risco, o que leva a seus usuários, naturalmente, ao questionamento sobre a suscetibilidade dos resultados finais ao tipo de modelagem adotada. Neste sentido, este trabalho estuda o processo de dispersão atmosférica de nuvens densas formadas em liberações acidentais, identificando as principais possibilidades de modelagem deste processo e, ao final, apresenta um estudo de caso demonstrando que diferentes modelagens desta dispersão, comumente empregadas em análise de risco de instalações industriais, podem produzir variações na estimativa do risco de uma mesma instalação e, portanto, influenciar as decisões baseadas em risco. / The concern of the society about the risks posed by activities that deal with hazardous substances has increased in an environment strongly industrialized and with high population density in view of the inherent potential hazards of them as well as the impact of recent accidental episodes, even though their benefits provided. In this context the quantitative risk analysis is presented as an essential tool to assess the risk of these activities and compose a complex discussion about its feasibility. Some of these accident scenarios may involve the formation of a hazardous product cloud and its subsequent air dispersion in the off-site region when an accidental released take place and one should apply the so-called atmospheric dispersion models for estimating the consequences of the releases. Due to the complexity involved in this atmospheric dispersion process, there is a wide variety of mathematical models that can be applied for estimating the offsite consequences of the accidental releases leading, naturally, to one wonder whether the final risk expression of a facility is susceptible to these differences. Often in the world of industrial use of hazardous materials, toxic or flammable there is a possibility that these accidental releases produce clouds that are denser than air, a situation that demands even more attention in terms of risk aspects involved. Then, this dissertation studies the process of atmospheric dispersion of heavier-than-air clouds produced after an accidental release, identifying the main ways of modelling the process and presents a case study comparing different dispersion models that demonstrates that the final expression of risk of a typical installation can be different when it is used different dispersion model in the process.

La modélisation inverse de la dispersion atmosphérique consiste à reconstruire les caractéristiques d’une source (quantité de polluants rejetée, position) à partir de mesures de concentration dans l’air, en utilisant un modèle direct de dispersion et un algorithme d’inversion. Nous avons utilisé dans cette étude deux modèles directs de dispersion atmosphérique SIRANE (Soulhac, 2000; Soulhac et al., 2011) et SIRANERISK (Cierco et Soulhac, 2009a; Lamaison et al., 2011a, 2011b). Il s’agit de deux modèles opérationnels de « réseau des rues », basés sur le calcul du bilan de masse à différents niveaux du réseau. Leur concept permet de décrire correctement les différents phénomènes physiques de dispersion et de transport de la pollution atmosphérique dans des réseaux urbains complexes. L’étude de validation de ces deux modèles directs de dispersion a été effectuée après avoir évalué la fiabilité des paramétrages adoptés pour simuler les échanges verticaux entre la canopée et l'atmosphère, les transferts aux intersections de rues et la canalisation de l’écoulement à l’intérieur du réseau de rues. Pour cela, nous avons utilisé des mesures en soufflerie effectuées dans plusieurs configurations académiques. Nous avons développé au cours de cette thèse un système de modélisation inverse de dispersion atmosphérique (nommé ReWind) qui consiste à déterminer les caractéristiques d’une source de polluant (débit, position) à partir des concentrations mesurées, en résolvant numériquement le système matriciel linéaire qui relie le vecteur des débits au vecteur des concentrations. La fiabilité des résultats et l’optimisation des temps de calcul d’inversion sont assurées par le couplage de plusieurs méthodes mathématiques de résolution et d’optimisation, bien adaptées pour traiter le cas des problèmes mal posés. L’étude de sensibilité de cet algorithme d’inversion à certains paramètres d’entrée (comme les conditions météorologiques, les positions des récepteurs,…) a été effectuée en utilisant des observations synthétiques (fictives) fournies par le modèle direct de dispersion atmosphérique. La spécificité des travaux entrepris dans le cadre de ce travail a consisté à appliquer ReWind dans des configurations complexes de quartier urbain, et à utiliser toute la variabilité turbulente des mesures expérimentales obtenues en soufflerie pour qualifier ses performances à reconstruire les paramètres sources dans des conditions représentatives de situations de crise en milieu urbain ou industriel. L’application de l’approche inverse en utilisant des signaux instantanés de concentration mesurés en soufflerie plutôt que des valeurs moyennes, a montré que le modèle ReWind fournit des résultats d’inversion qui sont globalement satisfaisants et particulièrement encourageants en termes de reproduction de la quantité de masse totale de polluant rejetée dans l’atmosphère. Cependant, l’algorithme présente quelques difficultés pour estimer à la fois le débit et la position de la source dans certains cas. En effet, les résultats de l’inversion sont assez influencés par le critère de recherche (d’optimisation), le nombre de récepteurs impactés par le panache, la qualité des observations et la fiabilité du modèle direct de dispersion atmosphérique. / The aim of this study is to develop an inverse atmospheric dispersion model for crisis management in urban areas and industrial sites. The inverse modes allows for the reconstruction of the characteristics of a pollutant source (emission rate, position) from concentration measurements, by combining a direct dispersion model and an inversion algorithm, and assuming as known both site topography and meteorological conditions. The direct models used in these study, named SIRANE and SIRANERISK, are both operational "street network" models. These are based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections and vertical exchange between a street canyon and the overlying atmosphere. The first part of this study is devoted to a detailed validation of these direct models in order to test the parameterisations implemented in them. This is achieved by comparing their outputs with wind tunnel experiments of the dispersion of steady and unsteady pollutant releases in idealised urban geometries. In the second part we use these models and experiments to test the performances of an inversion algorithm, named REWind. The specificity of this work is twofold. The first concerns the application of the inversion algorithm - using as input data instantaneous concentration signals registered at fixed receptors and not only time-averaged or ensemble averaged concentrations. - in urban like geometries, using an operational urban dispersion model as direct model. The application of the inverse approach by using instantaneous concentration signals rather than the averaged concentrations showed that the ReWind model generally provides reliable estimates of the total pollutant mass discharged at the source. However, the algorithm has some difficulties in estimating both emission rate and position of the source. We also show that the performances of the inversion algorithm are significantly influenced by the cost function used to the optimization, the number of receptors and the parameterizations adopted in the direct atmospheric dispersion model.