Geometrical automata for two phase flow simulation

Herrero, Víctor; Guido-Lavalle, G.; Clausse, Alejandro

doi:10.1016/0029-5493(95)01162-5

Cited by 5 publications

(7 citation statements)

References 6 publications

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“…Bubbly flow [Herrero96] is encountered in many industrial applications, such as distillation columns, nuclear and chemical reactors, oil piping, among others. Wherever two unmiscible fluids are forced to flow together, one of them tend to concentrate in bubbles, the other fluid acting as a continuous carrying environment.…”

Section: Bubbly Flow Simulationmentioning

confidence: 99%

Accomplishing adaptability in simulation frameworks: the Bubble approach

Pace

Triilnik²,

Campo³

et al.

25th Annual International Computer Software and Applications Conference. COMPSAC 2001

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Enforcing framework adaptability is one of the key points in the process of building an object-oriented application framework. When it comes to simulation, some adaptation mechanisms to configure components on-the-fly are usually required in order to produce good software artifacts and alleviate development effort. The paper reports an experience using a simulation multi-agent framework, initially conceived to be used in fluid flow problems. The framework architecture demonstrated during its evolution a great potential regarding to flexibility and modularity, tackling a wide range of other problems ranging from a network protocol simulation to a soccer simulation.The contribution of the work is that it provides an adaptable framework architecture with a particular combination of building mechanisms such as agents, uniform decomposition, competing tasks, events and implicit invocation, to represent complex simulations in a flexible manner. In addition, it describes three application examples using the framework, showing both practical experience about framework evolution and derived research ideas in the targeted area.The work is organized into five sections. The first section gives background information about adaptability in object oriented systems and multi-agent systems. Then, the description of our framework Bubble is presented. The following section reports three application examples based on the framework and lessons learned in this evolution process. Then, some tradeoffs and perspectives about Bubble are discussed after that. And finally, we draw the conclusions of the work. BACKGROUND INFORMATIONThis section explains what we mean by adaptability in object oriented systems (closely related with the architecture of our framework), and presents basic concepts about multiagent systems and agent-based simulations, in order to situate the rest of the work.

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Section: Bubbly Flow Simulationmentioning

confidence: 99%

Accomplishing adaptability in simulation frameworks: the Bubble approach

Pace

Triilnik²,

Campo³

et al.

25th Annual International Computer Software and Applications Conference. COMPSAC 2001

View full text Add to dashboard Cite

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“…Despite the power and success of agent-based methods to predict complex patterns in -114 -fields as diverse as social sciences [e.g., Macy and Willer, 2002], economy [e.g., Parker et al, 2003], and ecology [e.g., Grimm et al, 2006], its use in multi-phase fluid dynamics has not proliferated. So far, only Herrero et al [1996] proposed a simple two-phase model that allows capturing some properties of bubble columns. However, bubbles were treated as two-dimensional disks, and bubble expansion during ascent through the column was not considered, such that the validation of the model by comparison with actual experiments is quite controversial.…”

Section: Agent-based Model Of a Bubble Columnmentioning

confidence: 99%

“…However, bubbles were treated as two-dimensional disks, and bubble expansion during ascent through the column was not considered, such that the validation of the model by comparison with actual experiments is quite controversial. The model from Herrero et al [1996] seems to have gone unnoticed until Marcel et al [2011] used the same ideas to simulate boiling processes in square-section channels. Other agent-based models have been proposed, but they are restricted to the simulation of Taylor bubbles in pure slug flow [e.g., Barnea and Taitel, 1993;Mayor et al, 2008].…”

Section: Agent-based Model Of a Bubble Columnmentioning

confidence: 99%

“…In particular, breakup is considered to occur if the Weber dimensionless number associated to a bubble overcomes a critical value which depends on the bubble deformation and flow pattern [Hinze, 1955]. Given the complex and ultimately random nature of bubble breakup, here we follow the same approach as -123 - Herrero et al [1996] and assume that a bubble splits in two daughter bubbles when the following condition is met:…”

Section: Breakupmentioning

confidence: 99%

“…Because of bubble displacement, gas expansion, breakup, and coalescence, spherical bubbles could partially or completely exit from the space delimited by the walls of the conduit. When this occurs, bubbles are reintroduced in the domain by moving them in radial direction (relative to the cylinder) and attaching them to the walls of the conduit [Herrero et al, 1996]. On the other hand, bubble bursting is imposed when a bubble comes into contact with the liquid surface (i.e., magma head).…”

Section: Confinement In the Domain And Bubble Burstingmentioning

confidence: 99%

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On the dynamics of persistently degassing volcanoes from new physics-based approaches

Girona¹

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Persistently degassing volcanoes are the most active sub-aerial volcanoes around the world. Their activity consists of passive degassing periods interspersed by eruptions every few months or years. I present three new physics-based studies that unravel the underlying dynamics of these volcanoes. First, I calculate the pressure changes induced by the gas release during quiescence. A key finding is that magma reservoirs can depressurize several MPa within the inter-eruptive timescales, which suggests that passive degassing can induce unrest episodes and eruptions. Second, I develop a method to monitor the high-frequency water vapor emissions using light scattering theory and analysis of digital images. I show that degassing of Erebus and Mayon volcanoes emerges as a fractal phenomenon. Third, I simulate the bubble dynamics of volcanic conduits to investigate the processes leading to phreatic eruptions. I found that they can be preceded by amplitude and frequency shifts in the gas emission time series. These studies give new insights on the dynamics of persistently degassing volcanoes, and help to improve the monitoring and interpretation of degassing time series. Table 1. Mean inter-eruptive time of persistently degassing volcanoes. Volcano* Mean inter-eruptive time since 1900(months) Number of intereruptive times Oshima 25 27 Bromo 45 24 Aso 12 46 Slamet 32 20 Poás 18 24 Telica 29 23 Merapi 30 17 Langila 11 18 Kilauea 18 28 Manam 18 13 White island 17 12 Láscar 18 14 Llaima 29 16 Tangkubanparahu 94 11 Asama 21 36 San Cristóbal 13 13 Etna 8 35 Fuego 41 16 Ulawun 21 22-6-Improving eruption forecasting requires unveiling the volcanic processes occurring during quiescent degassing and unrest episodes, for which monitoring of the amount, composition, and style of the gas emissions is fundamental [e.g., Symonds et al., 1994; Aiuppa et al., 2007]. Tracking the gas emissions can be performed nowadays in real-time by using remote-sensing techniques. For example, SO 2 fluxes can be routinely measured in real-time from remote distances by using ultraviolet cameras [e.g., Tamburello et al., 2013], or by determining the absorption of the ultraviolet radiation by the gas plume with instruments like DOAS (differential optical absorption spectrometers) [e.g., Oppenheimer and Kyle, 2008]. The ratios between SO 2 and other gases can be also measured by using systems like OP-FTIR (open-path Fourier transform infrared spectrometry) or Multi-GAS, even though their use is limited to easily accessible volcanoes where the instruments can be placed at the proximities of the crater vent [e.g., Burton et al., 2000; Shinohara, 2005]. The application of these real-time remote-sensing techniques reveals for example that persistently degassing volcanoes emit several thousand tonnes of gas per day, mainly H 2 O (~ 50-90 wt%), CO 2 (~ 20-50 wt%) and SO 2

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