Dynamics of lava flow: Thickness growth characteristics of steady two‐dimensional flow

Park, Seung; Iversen, J. D.

doi:10.1029/gl011i007p00641

Cited by 52 publications

(22 citation statements)

References 7 publications

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“…Several workers have used this solution to build thermal models for lava flows (e.g., Danes 1972;Park and Iverson 1984;Pieri and Baloga 1986). Figure 8 plots cooling curves for various slab thicknesses.…”

Section: Simple Radiative Cooling Modelmentioning

confidence: 99%

The initial cooling of pahoehoe flow lobes

Keszthelyi

Denlinger

1996

Bulletin of Volcanology

159

139

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In this paper we describe a new thermal model for the initial cooling of pahoehoe lava flows. The accurate modeling of this initial cooling is important for understanding the formation of the distinctive surface textures on pahoehoe lava flows as well as being the first step in modeling such key pahoehoe emplacement processes as lava flow inflation and lava tube formation. This model is constructed from the physical phenomena observed to control the initial cooling of pahoehoe flows and is not an empirical fit to field data. We find that the only significant processes are (a) heat loss by thermal radiation, (b) heat loss by atmospheric convection, (c) heat transport within the flow by conduction with temperature and porosity-dependent thermal properties, and (d) the release of latent heat during crystallization. The numerical model is better able to reproduce field measurements made in Hawai'i between 1989 and 1993 than other published thermal models. By adjusting one parameter at a time, the effect of each of the input parameters on the cooling rate was determined. We show that: (a) the surfaces of porous flows cool more quickly than the surfaces of dense flows, (b) the surface cooling is very sensitive to the efficiency of atmospheric convective cooling, and (c) changes in the glass forming tendency of the lava may have observable petrographic and thermal signatures. These model results provide a quantitative explanation for the recently observed relationship between the surface cooling rate of pahoehoe lobes and the porosity of those lobes (Jones 1992(Jones , 1993. The predicted sensitivity of cooling to atmospheric convection suggests a simple field experiment for verification, and the model provides a tool to begin studies of the dynamic crystallization of real lavas. Future versions of the model can also be made applicable to extraterrestrial, submarine, silicic, and pyroclastic flows.

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Section: Simple Radiative Cooling Modelmentioning

confidence: 99%

The initial cooling of pahoehoe flow lobes

Keszthelyi

Denlinger

1996

Bulletin of Volcanology

159

139

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“…where T ∈ Q T is the current lava temperature, while k 1 and k 2 are parameters depending on lava rheological properties [6]. The values of k 1 and k 2 are simply obtained by solving the system of equations:…”

Section: Lava Flows Computationmentioning

confidence: 99%

“…Thus, according to (6), the temperature T avg computed in (5) is updated through the following relation:…”

Section: Lava Flows Computationmentioning

confidence: 99%

“…In the first phase, which accounts for the energy exchange directly related to the mass exchange, the cell temperature T avg is obtained as weighted average of residual lava inside the cell and lava inflows from neighboring ones: The final step updates the temperature given by (5) considering thermal energy loss due to lava surface irradiation, which can be expressed by the StefanBoltzmann equation. In particular, starting from a temperature T t a good approximation of the temperature T t+Δt is given by [6]:…”

Section: Lava Flows Computationmentioning

confidence: 99%

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Modelling Macroscopic Phenomena with Cellular Automata and Parallel Genetic Algorithms: An Application to Lava Flows

Avolio

D'Ambrosio

Gregorio

et al. 2007

Computational Science – ICCS 2007

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Abstract. Forecasting through simulations the shape of lava invasions in a real topography represents a challenging problem, especially considering that the phenomenon usually evolves for a long time (e.g. from a few to hundreds of days) and on very large areas. In the latest years, Cellular Automata (CA) have been well recognized as a valid computational approach in lava flow modelling. In this paper we present some significant developments of SCIARA, a family of deterministic CA models of lava flows which are optimized for a specific scenario through the use of a parallel genetic algorithm. Following a calibration-validation approach, the model outcomes are compared with three real events of lava effusion.

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“…where T∈Q T is the lava temperature, while k 1 and k 2 are parameters depending on lava rheological properties (Park and Iversen 1984). The values for k 1 and k 2 are simply obtained by solving the equations system:…”

Section: Lava Flows Computationmentioning

confidence: 99%

Evolutionary Computation And Modeling Of Natural Phenomena: An Application To Lava Flows

Spataro¹,

D'Ambrosio²,

Gregorio³

et al. 2007

ECMS 2007 Proceedings Edited By: I. Zelinka, Z. Oplatkova, A. Orsoni

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A Parallel Master-Slave Genetic Algorithm has been applied to evolve a two dimensional Cellular Automata model for lava flow simulation. A new quantitative measure for the evaluation of the simulations result with respect to the real event has been defined and employed as fitness function. It compares both the areal extension and the temporal duration of the simulated event with respect the real one. The 2001 Etnean Nicolosi (Italy) case study has been considered for model calibration, while the validation has been performed by considering further cases of study, which differ both in duration and emission rate. Results have confirmed both the goodness of the simulation model and of the calibration algorithm. Eventually a possible application related to Civil Defence purposes is briefly described and proposed as a future development.

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Dynamics of lava flow: Thickness growth characteristics of steady two‐dimensional flow

Cited by 52 publications

References 7 publications

The initial cooling of pahoehoe flow lobes

The initial cooling of pahoehoe flow lobes

Modelling Macroscopic Phenomena with Cellular Automata and Parallel Genetic Algorithms: An Application to Lava Flows

Evolutionary Computation And Modeling Of Natural Phenomena: An Application To Lava Flows

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