scholarly journals Effects of the crater on eruption column dynamics

2010 ◽  
Vol 115 (B7) ◽  
Author(s):  
Takehiro Koyaguchi ◽  
Yujiro J. Suzuki ◽  
Tomofumi Kozono
Keyword(s):  
Eruption Column ◽  
Column Dynamics

Chapter 4 Eruption column physics

1998 ◽  
Vol 4 ◽  
pp. 91-138 ◽  
Author(s):  
G VALENTINE
Keyword(s):  
Eruption Column

The volcanological significance of deep-sea ash layers associated with ignimbrites

1980 ◽  
Vol 117 (5) ◽  
pp. 425-436 ◽  
Author(s):  
R. S. J. Sparks ◽  
T. C. Huang
Keyword(s):  
Deep Sea ◽  
Eastern Mediterranean ◽  
Eruption Column ◽  
Size Distributions ◽  
Ash Fall ◽  
Column Collapse ◽  
Median Diameter ◽  
Grain Size Distributions ◽  
Bimodal Grain Size ◽  
Fall Deposits

SummaryMany volcanic ash layers preserved in deep-sea sediments are the products of large magnitude ignimbrite eruptions. The characteristics of such co-ignimbrite ash-fall deposits are illustrated by two layers from the Eastern Mediterranean: the Minoan ash, Santorini, and the Campanian ash, Italy. These layers are divisible into a coarse lower unit and a fine upper unit in proximal cores. Both layers also show striking bimodal grain size distributions in more distal cores. The coarser mode decreases in median diameter with distance from source whereas the finer mode shows no lateral variation. These features are interpreted in terms of a model for ignimbrite formation by eruption column collapse. Comparable volumes of ignimbrite and associated air-fall ejecta are produced.

Ensemble-based data assimilation of volcanic aerosols using FALL3D+PDAF

2021 ◽  
Author(s):  
Leonardo Mingari ◽  
Andrew Prata ◽  
Federica Pardini
Keyword(s):  
Data Assimilation ◽  
Information Transfer ◽  
High Performance ◽  
Volcanic Ash ◽  
Numerical Models ◽  
Volcanic Eruptions ◽  
Column Height ◽  
Eruption Column ◽  
Operational Environment ◽  
Assimilation System

<p>Modelling atmospheric dispersion and deposition of volcanic ash is becoming increasingly valuable for understanding the potential impacts of explosive volcanic eruptions on infrastructures, air quality and aviation. The generation of high-resolution forecasts depends on the accuracy and reliability of the input data for models. Uncertainties in key parameters such as eruption column height injection, physical properties of particles or meteorological fields, represent a major source of error in forecasting airborne volcanic ash. The availability of nearly real time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context. Data assimilation (DA) is one of the most effective ways to reduce the error associated with the forecasts through the incorporation of available observations into numerical models. Here we present a new implementation of an ensemble-based data assimilation system based on the coupling between the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The implementation is based on the last version release of FALL3D (versions 8.x) tailored to the extreme-scale computing requirements, which has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE). The proposed methodology can be efficiently implemented in an operational environment by exploiting high-performance computing (HPC) resources. The FALL3D+PDAF system can be run in parallel and supports online-coupled DA, which allows an efficient information transfer through parallel communication. Satellite-retrieved data from recent volcanic eruptions were considered as input observations for the assimilation system.</p>

Supercritical Adsorption

2005 ◽  
Author(s):  
Eldred H. Chimowitz
Keyword(s):  
Stationary Phase ◽  
Critical Point ◽  
Dynamic Models ◽  
Molecular Diffusion ◽  
Plug Flow ◽  
Fluid Phase ◽  
Commercial Application ◽  
Critical Systems ◽  
Mobile Phases ◽  
Column Dynamics

In this chapter, we discuss adsorption phenomena in supercritical systems, a situation that occurs in many application areas in chemical-process and materials engineering. An example of a commercial application in this area, which has achieved wide acceptance as a tool in analytical chemistry, is supercritical fluid chromatography (SFC). Not only is SFC a powerful technique for chemical analysis, but it also is a useful method for measuring transportive and thermodynamic properties in the near-critical systems. In the next section, we analyze adsorption-column dynamics using simple dynamic models, and describe how data from a chromatographic column can be used to estimate various thermodynamic and transport properties.We then proceed to discuss the effects of proximity to the critical point on adsorption behavior in these systems. The closer the system is to its critical point, the more interesting is its behavior. For very dilute solute systems, like those considered here, the energy balance is often ignored to a first approximation; this leads to a simple set of mass-balance equations defining transport for each species. These equations can be developed to various levels of complexity, depending upon the treatment of the adsorbent (stationary phase). The conceptual view of these phases can span a wide range of possibilities ranging from completely nonporous solids (fused structures) to porous materials with complicated ill-defined pore structures. Given these considerations, it is customary to make the following assumptions in the development of a simple model of adsorber-bed dynamics: . . .1. The stationary and mobile phases are continuous in the direction of the flow, with the fluid phase possessing a flat velocity profile (“plug” flow).. . . . . . 2. The porosity of the stationary phase is considered constant irrespective of pressure and temperature conditions (i.e., it is incompressible). . . . . . .3. The column is considered to be radially homogeneous, leading to a set of equations with one spatially independent variable, representing distance along the column axis. . . . . . . 4. The dispersion term in the model equation represents the combined effects of molecular diffusion and dispersion due to convective stirring in the bed. These effects are combined into an effective phenomenological dispersion coefficient, considered to be constant throughout the column. . . .

scholarly journals Coastal hypoxia and eutrophication as key controls on benthic release and water column dynamics of iron and manganese

2020 ◽  
Author(s):  
Wytze K. Lenstra ◽  
Martijn Hermans ◽  
Marie J.M. Séguret ◽  
Rob Witbaard ◽  
Silke Severmann ◽  
...  
Keyword(s):  
Water Column ◽  
Column Dynamics ◽  
Iron And Manganese
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