Dissipationless mergers of elliptical galaxies and the evolution of the fundamental plane

We carry out numerical simulations of dissipationless major mergers of elliptical galaxies using initial galaxy models that consist of a dark matter haloes and a stellar bulge with properties consistent with the observed fundamental plane. By varying the density profile of the dark matter haloes [standard Navarro, Frenk & White (NFW) profile versus adiabatically contracted NFW profile], the global stellar to dark matter mass ratio and the orbit of the merging galaxies, we are able to assess the impact of each of these factors on the structure of the merger remnant. Our results indicate that the properties of the remnant bulge depend primarily on the angular momentum and energy of the orbit; for a cosmologically motivated orbit, the effective radius and velocity dispersion of the remnant bulge remain approximately on the fundamental plane. This indicates that the observed properties of elliptical galaxies are consistent with significant growth via late dissipationless mergers. We also find that the dark matter fraction within the effective radius of our remnants increases after the merger, consistent with the hypothesis that the tilt of the fundamental plane from the virial theorem is due to a varying dark matter fraction as a function of galaxy mass.     

Recovery of thermohaline circulation under CO2 stabilization and overshoot scenarios

In this study we examine the behavior of the thermohaline circulation, as simulated by the Community Climate System Model version 3 (CCSM3), for several centuries following CO₂ stabilization for the SRES B1 and A1B scenarios and for an “overshoot” scenario in which CO₂ levels temporarily reach the same level as in the A1B scenario before declining to an ultimate stabilization level that is identical to the B1 case. While we find no evidence for irreversible changes of the thermohaline circulation in the overshoot experiment, the interplay of the different timescales of the temperature response of the surface and interior ocean does lead to a number of differences in the long-term response of the ocean between it and the B1 stabilization scenario where the same GHG levels are approached by different paths. The stronger initial warming and its slow penetration into the deeper ocean, followed by a transient surface cooling in the overshoot scenario leads to lower static stability, deeper mixing, and a more rapid recovery of the thermohaline circulation than in the B1 stabilization scenario. While the overshoot scenario recovers surface conditions (e.g. SST, sea ice extent) very similar to the B1 scenario shortly after reaching the same GHG levels, the additional accumulation of heat in the interior ocean during the period of higher forcing causes the global mean ocean temperature and steric sea level to remain higher than in the B1 stabilization scenario for at least another several centuries.     

Sustainable shellfish aquaculture in Saldanha Bay,South Africa

The carrying capacity for bivalve shellfish culture in Saldanha Bay, South Africa, was analysed through the application of the well-tested EcoWin ecological model, in order to simulate key ecosystem variables. The model was set up using: (i) oceanographic and water-quality data collected from Saldanha Bay, and (ii) culture-practice information provided by local shellfish farmers. EcoWin successfully reproduced key ecological processes, simulating an annual mean phytoplankton biomass of 7.5 µg Chl a l^–1 and an annual harvested shellfish biomass of about 3 000 tonnes (t) y^–1, in good agreement with reported yield. The maximum annual carrying capacity of Small Bay was estimated as 20 000 t live weight (LW) of oysters Crassostrea gigas, or alternatively 5 100 t LW of mussels Mytilus galloprovincialis, and for Big Bay as 100 000 t LW of oysters. Two production scenarios were investigated for Small Bay: a production of 4 000 t LW y^–1 of mussels, and the most profitable scenario for oysters of 19 700 t LW y^–1. The main conclusions of this work are: (i) in 2015–2016, both Small Bay and Big Bay were below their maximum production capacity; (ii) the current production of shellfish potentially removes 85% of the human nitrogen inputs; (iii) a maximum-production scenario in both Big Bay and Small Bay would result in phytoplankton depletion in the farmed area; (iv) increasing the production intensity in Big Bay would probably impact the existing cultures in Small Bay; and (v) the production in Small Bay could be increased, resulting in higher income for farmers.     

Beneath the surface: Characteristics of oceanic ecosystems under weak mixing conditions – A theoretical investigation

This study considers an important biome in aquatic environments, the subsurface ecosystem that evolves under low mixing conditions, from a theoretical point of view. Employing a conceptual model that involves phytoplankton, a limiting nutrient and sinking detritus, we use a set of key characteristics (thickness, depth, biomass amplitude/productivity) to qualitatively and quantitatively describe subsurface biomass maximum layers (SBMLs) of phytoplankton. These SBMLs are defined by the existence of two community compensation depths in the water column, which confine the layer of net community production; their depth coincides with the upper nutricline. Analysing the results of a large ensemble of simulations with a one-dimensional numerical model, we explore the parameter dependencies to obtain fundamental steady-state relationships that connect primary production, mortality and grazing, remineralization, vertical diffusion and detrital sinking. As a main result, we find that we can distinguish between factors that determine the vertically integrated primary production and others that affect only depth and shape (thickness and biomass amplitude) of this subsurface production layer. A simple relationship is derived analytically, which can be used to estimate the steady-state primary productivity in the subsurface oligotrophic ocean. The fundamental nature of the results provides further insight into the dynamics of these “hidden” ecosystems and their role in marine nutrient cycling.     

A virtual voyage through 3D structures generated by chaotic mixing of magmas and numerical simulations: a new approach for understanding spatial and temporal complexity of magma dynamics

In this contribution, we present a virtual voyage through 3D structures generated by chaotic mixing of magmas and numerical simulations with the aim to highlight the power of 3D representations in the understanding of this geological phenomenon. In particular, samples of mixed juveniles from Salina island (Southern Italy) are reconstructed in 3D by serial lapping and digital montage and numerical simulations are performed by using a 3D chaotic dynamical system. Natural and simulated magma mixing structures are visualized by using several multimedia tools including animations and “virtual reality” models. It is shown that magma interaction processes can generate large spatial and temporal compositional heterogeneities in magmatic systems. The same topological structures are observed in both 3D reconstructed rock samples and chaotic numerical simulations, indicating that the mixing of magmas is governed by chaotic dynamics. The use of 3D multimedia models gives the opportunity to penetrate into magma mixing structures and to understand their significance in the context of magma dynamics. Such an approach is very powerful since multimedia tools can strongly capture the attention of the reader bringing him/her into an interactive and memorable geological experience. Electronic supplementary material  enclosed:     

Probabilistic modeling of seismically triggered landslides using Monte Carlo simulations

The 2004 Chuetsu earthquakes of Niigata (Japan) triggered numerous landslides, and the most widespread types of landslides were highly disrupted, relatively shallow slides and soil (debris) flows. This paper presented a method to evaluate slope instability using Newmark displacement on a pixel-by-pixel basis in a given area. The proposed method was able to integrate Newmark displacement modeling and Monte Carlo simulations within geographical information systems. In the modeling, an empirical attenuation relationship was utilized to calculate Arias intensity over this study area, and the variability of geotechnical parameters was taken into account to calculate coseismic landslide displacement. Before deriving the displacement from related inputs, the Monte Carlo simulations ran 1,500 times and generated 1,500 displacement values for each grid cell, and then means and standard deviations of displacement were calculated and probabilistic distributions can be obtained. Finally, given 10 cm as a threshold value of displacement, estimated probabilities of displacement exceeding 10 cm were shown as a map of seismic landslide hazards. The resulting hazard map was classified into four categories from very low to high level.     

Efficient generation of conditional simulations by chebyshev matrix polynomial approximations to the symmetric square root of the covariance matrix

Consider the problem of generating a realization y₁ of a Gaussian random field on a dense grid of points ₁ conditioned on field observations y₂ collected on a sparse grid of points ₂. An approach to this is to generate first an unconditional realization y over the grid =_{1 2}, and then to produce y₁ by conditioning y on the data y₂. As standard methods for generating y, such as the turning bands, spectral or Cholesky approaches can have various limitations, it has been proposed by M. W. Davis to generate realizations from a matrix polynomial approximations to the square root of the covariance matrix. In this paper we describe how to generate a direct approximation to the conditional realization y₁, on ₁ using a variant of Davis' approach based on approximation by Chebyshev polynomials. The resulting algorithm is simple to implement, numerically stable, and bounds on the approximation error are readily available. Furthermore we show that the conditional realization y₁ can be generated directly with a lower order polynomial than the unconditional realization y, and that further reductions can be achieved by exploiting a nugget effect if one is present. A pseudocode version of the algorithm is provided that can be implemented using the fast Fourier transform if the field is stationary and the grid ₁ is rectangular. Finally, numerical illustrations are given of the algorithm's performance in generating various 2-D realizations of conditional processes on large sampling grids.     

Large eddy simulation of hydrocyclone—prediction of air-core diameter and shape

Hydrocyclones are widely used in the mining and chemical industries. An attempt has been made in this study, to develop a CFD (computational fluid dynamics) model, which is capable of predicting the flow patterns inside the hydrocyclone, including accurate prediction of flow split as well as the size of the air-core. The flow velocities and air-core diameters are predicted by DRSM (differential Reynolds stress model) and LES (large eddy simulations) models were compared to experimental results. The predicted water splits and air-core diameter with LES and RSM turbulence models along with VOF (volume of fluid) model for the air phase, through the outlets for various inlet pressures were also analyzed. The LES turbulence model led to an improved turbulence field prediction and thereby to more accurate prediction of pressure and velocity fields. This improvement was distinctive for the axial profile of pressure, indicating that air-core development is principally a transport effect rather than a pressure effect.     

Computer simulation studies of Crystallization under confinement conditions

Crystallization under confinement conditions is a very important process in geochemistry and geophysics. Computer simulations of fluids in nanometer scale pore spaces can provide a unique microscopic insight into the structure, dynamics and forces arising from the crystallization process. We discuss in this paper molecular dynamics computer simulations of crystallization in pores of nanometer dimensions. The crystallization pressure due to the freezing of a model of Argon in a nanopore is computed using molecular dynamics simulations. We also investigate the influence of pore geometry in determining the dynamics of confined fluids, as well as mass separation in binary mixtures. It turns out that the pore geometry reveals itself as an important variable, leading to 1) new mechanisms for fast diffusion in confined spaces, and 2) accumulation of solute in specific regions inside the pore.     

From stable dipolar towards reversing numerical dynamos

We are using a three-dimensional convection-driven numerical dynamo model without hyperdiffusivity to study the characteristic structure and time variability of the magnetic field in dependence of the Rayleigh number (Ra) for values up to 40 times supercritical. We also compare a variety of ways to drive the convection and basically find two dynamo regimes. At low Ra, the magnetic field at the surface of the model is dominated by the non-reversing axial dipole component. At high Ra, the dipole part becomes small in comparison to higher multipole components. At transitional values of Ra, the dynamo vacillates between the dipole-dominated and the multipolar regime, which includes excursions and reversals of the dipole axis. We discuss, in particular, one model of chemically driven convection, where for a suitable value of Ra, the mean dipole moment and the temporal evolution of the magnetic field resemble the known properties of the Earth’s field from paleomagnetic data.