Protostellar Outflow Evolution in Turbulent Environments

The link between turbulence in star formatting environments and protostellar jets remains controversial. To explore issues of turbulence and fossil cavities driven by young stellar outflows we present a series of numerical simulations tracking the evolution of transient protostellar jets driven into a turbulent medium. Our simulations show both the effect of turbulence on outflow structures and, conversely, the effect of outflows on the ambient turbulence. We demonstrate how turbulence will lead to strong modifications in jet morphology. More importantly, we demonstrate that individual transient outflows have the capacity to re-energize decaying turbulence. Our simulations support a scenario in which the directed energy/momentum associated with cavities is randomized as the cavities are disrupted by dynamical instabilities seeded by the ambient turbulence. Consideration of the energy power spectra of the simulations reveals that the disruption of the cavities powers an energy cascade consistent with Burgers'-type turbulence and produces a driving scale-length associated with the cavity propagation length. We conclude that fossil cavities interacting either with a turbulent medium or with other cavities have the capacity to sustain or create turbulent flows in star forming environments. In the last section we contrast our work and its conclusions with previous studies which claim that jets can not be the source of turbulence.Comment: 24 pages, submitted to the Astrophysical Journa

Streams Going Notts: The tidal debris finder comparison project

While various codes exist to systematically and robustly find haloes and subhaloes in cosmological simulations (Knebe et al., 2011, Onions et al., 2012), this is the first work to introduce and rigorously test codes that find tidal debris (streams and other unbound substructure) in fully cosmological simulations of structure formation. We use one tracking and three non-tracking codes to identify substructure (bound and unbound) in a Milky Way type simulation from the Aquarius suite (Springel et al., 2008) and post-process their output with a common pipeline to determine the properties of these substructures in a uniform way. By using output from a fully cosmological simulation, we also take a step beyond previous studies of tidal debris that have used simple toy models. We find that both tracking and non-tracking codes agree well on the identification of subhaloes and more importantly, the {\em unbound tidal features} associated with them. The distributions of basic properties of the total substructure distribution (mass, velocity dispersion, position) are recovered with a scatter of $\sim20$. Using the tracking code as our reference, we show that the non-tracking codes identify complex tidal debris with purities of $\sim40$. Analysing the results of the substructure finders, we find that the general distribution of {\em substructures} differ significantly from the distribution of bound {\em subhaloes}. Most importantly, both bound and unbound {\em substructures} together constitute $\sim18$ of the host halo mass, which is a factor of $\sim2$ higher than the fraction in self-bound {\em subhaloes}. However, this result is restricted by the remaining challenge to cleanly define when an unbound structure has become part of the host halo. Nevertheless, the more general substructure distribution provides a more complete picture of a halo's accretion history.Comment: 19 pages, 12 figures, accepted for publication in MNRA

Optimal reconstruction of concentrations, gradients and reaction rates from particle distributions

Random walk particle tracking methodologies to simulate solute transport of conservative species constitute an attractive alternative for their computational efficiency and absence of numerical dispersion. Yet, problems stemming from the reconstruction of concentrations from particle distributions have typically prevented its use in reactive transport problems. The numerical problem mainly arises from the need to first reconstruct the concentrations of species/components from a discrete number of particles, which is an error prone process, and then computing a spatial functional of the concentrations and/or its derivatives (either spatial or temporal). Errors are then propagated, so that common strategies to reconstruct this functional require an unfeasible amount of particles when dealing with nonlinear reactive transport problems. In this context, this article presents a methodology to directly reconstruct this functional based on kernel density estimators. The methodology mitigates the error propagation in the evaluation of the functional by avoiding the prior estimation of the actual concentrations of species. The multivariate kernel associated with the corresponding functional depends on the size of the support volume, which defines the area over which a given particle can influence the functional. The shape of the kernel functions and the size of the support volume determines the degree of smoothing, which is optimized to obtain the best unbiased predictor of the functional using an iterative plug-in support volume selector. We applied the methodology to directly reconstruct the reaction rates of a precipitation/dissolution problem involving the mixing of two different waters carrying two aqueous species in chemical equilibrium and moving through a randomly heterogeneous porous mediu

A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors

Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research

The Galaxy Angular Correlation Functions and Power Spectrum from the Two Micron All Sky Survey

We calculate the angular correlation function of galaxies in the Two Micron All Sky Survey. We minimize the possible contamination by stars, dust, seeing and sky brightness by studying their cross correlation with galaxy density, and limiting the galaxy sample accordingly. We measure the correlation function at scales between 1-18 arcdegs using a half million galaxies. We find a best fit power law to the correlation function has a slope of 0.76 and an amplitude of 0.11. However, there are statistically significant oscillations around this power law. The largest oscillation occurs at about 0.8 degrees, corresponding to 2.8 h^{-1} Mpc at the median redshift of our survey, as expected in halo occupation distribution descriptions of galaxy clustering. We invert the angular correlation function using Singular Value Decomposition to measure the three-dimensional power spectrum and find that it too is in good agreement with previous measurements. A dip seen in the power spectrum at small wavenumber k is statistically consistent with CDM-type power spectra. A fit of CDM-type power spectra to k < 0.2 h Mpc^{-1} give constraints of \Gamma_{eff}=0.116 and \sigma_8=0.96. This suggest a K_s-band linear bias of 1.1+/-0.2. This \Gamma_{eff} is different from the WMAP CMB derived value. On small scales the power-law shape of our power spectrum is shallower than that derived for the SDSS. These facts together imply a biasing of these different galaxies that might be nonlinear, that might be either waveband or luminosity dependent, and that might have a nonlocal origin.Comment: 14 pages, 20 figures, to be published in ApJ January 20th, revision included two new figures, version with high resolution figures can be found here http::ww

Modelling the effect of spray breakup, coalescence and evaporation on vehicle surface contamination dynamics

Vehicle surface contamination is an important design consideration as it affects drivers' vision and the performance of on board camera and sensor systems. Previous work has shown that eddy resolving methods are able to accurately capture the flow field and particle transport, leading to good agreement for vehicle soiling with experiments. What is less clear is whether the secondary break-up, coalescence and evaporation of liquid particles play an important role in spray dynamics. The work reported here attempts to answer this and also give an idea of the computational cost associated with these extra physics models. A quarter scale generic SUV model is used as a test case in which the continuous phase is solved using the Spalart-Allmaras IDDES model. The dispersed phase is computed concurrently with the continuous phase using the Lagrangian approach. The TAB secondary break-up and the stochastic O'Rourke coalescence models are used. The spray's rate of evaporation is calculated based on the relative humidity encountered on a typical October day in Britain. The secondary break-up model is found to be redundant, possibly due to the properties of spray. The coalescence model predicts high coalescence of particles close to the source and improves agreement with experiment, although at a high computational cost. Including evaporation removes small particles from the simulation and reduces overall contamination. When used along the coalescence model, evaporation is found to be negligible as it does not influence large particles to the same extent as it affects small particles. This suggests that droplet physics models need to be considered together as they can have a strong effect on each other as well as vehicle soiling. Here, we show that coalescence can be accounted for by using the time-averaged spray, obtained outside the region of high coalescence. This gives a very good agreement with experiment

Migration and generation of contaminants from launch through recovery: LDEF case history

It is possible to recreate the contamination history of the Long Duration Exposure Facility (LDEF) through an analysis of its contaminants and selective samples that were collected from surfaces with better documented exposure histories. This data was then used to compare estimates based on monitoring methods that were selected for the purpose of tracking LDEF's exposure to contaminants. The LDEF experienced much more contamination than would have been assumed based on the monitors. Work is still in progress but much of what was learned so far is already being used in the selection of materials and in the design of systems for space. Now experiments are being prepared for flight to resolve questions created by the discoveries on the LDEF. A summary of what was learned about LDEF contaminants over the first year since recovery and deintegration is presented. Over 35 specific conclusions in 5 contamination related categories are listed